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Bedside optical imaging of occipital resting-state functional connectivity in neonates
Abstract
Resting-state networks derived from temporal correlations of spontaneous hemodynamic fluctuations have been extensively used to elucidate the functional organization of the brain in adults and infants. We have previously developed functional connectivity diffuse optical tomography methods in adults, and we now apply these techniques to study functional connectivity in newborn infants at the bedside. We present functional connectivity maps in the occipital cortices obtained from healthy term-born infants and premature infants, including one infant with an occipital stroke. Our results suggest that functional connectivity diffuse optical tomography has potential as a valuable clinical tool for the early detection of functional deficits and for providing prognostic information on future development.
... Using high-density diffuse optical tomography (HD-DOT) with numerous sources and detectors, 16,42,43 abnormal amplitudes of LFOs and FC maps of cerebral oxygenation in occipital cortices were obtained from premature infants. 16 Although these diffuse optical systems show promise for detecting brain LFOs, there remain several limitations. NIRS/DCS systems suffer from limited numbers of discrete light sources and Mohtasebi et al.: Detection of low-frequency oscillations in neonatal piglets with speckle contrast. ...
... HD-DOT systems in particular have received much attention with regards to improved spatial resolution and brain signal differentiation. 16,43,46 Nonetheless, extending the field of view (FOV) with fiberbased HD-DOT contact measurement systems to gain a more complete view of the brain is hampered by complications with optical fiber coupling to heads and cap design, especially for the heads of small and fragile newborn infants. 16,43,46 Recently developed speckle contrast diffuse correlation tomography (scDCT) (US Patent No. 9/861,319, 2018 47 ) technology provides a noninvasive, fully noncontact, low-cost, and portable tool for high-density 3D imaging of blood flow distributions in deep tissue volumes (up to ∼10 mm). ...
... 16,43,46 Nonetheless, extending the field of view (FOV) with fiberbased HD-DOT contact measurement systems to gain a more complete view of the brain is hampered by complications with optical fiber coupling to heads and cap design, especially for the heads of small and fragile newborn infants. 16,43,46 Recently developed speckle contrast diffuse correlation tomography (scDCT) (US Patent No. 9/861,319, 2018 47 ) technology provides a noninvasive, fully noncontact, low-cost, and portable tool for high-density 3D imaging of blood flow distributions in deep tissue volumes (up to ∼10 mm). [48][49][50] Importantly, this device remedies many previous limitations while offering direct CBF imaging for potential LFO assessments. ...
... Studies of intrinsic brain networks have been reported using other neuroimaging modalities in addition to fMRI, EEG, and MEG. Among them, intracranial electrophysiological recordings [182,58,183,184], PET [185,186], and fNIRS [177,60,187] have all been reported (see Fig. 1), with similar computation methods to identify ICNs, as in fMRI, EEG, and MEG data. Moreover, each modality has its own advantages and drawbacks. ...
... fNIRS is a neuroimaging modality that measures concentration changes of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) in the vasculature of cortical tissues using near infrared light [189,190]. fNIRS has been effectively employed to characterize resting-state brain networks for adults [60,[191][192][193][194][195][196] and infants [197,187,198,199]. It has also been used to assess abnormal brain networks in patients with brain disorders [47,200]. ...
... Furthermore, fNIRS usually has higher temporal sampling rates (∼10 Hz) than fMRI (∼1 Hz) [190,60,189], which provides benefits of rejecting non-neuronal related hemodynamic changes, such as, due to respirations and heartbeat. In addition, fNIRS is more economically efficient and portable, and can be used for populations, such as patients with implants and infants, who are not suitable to be inside MRI scanners, as well as in challenged environments, such as brain monitoring at bed-sites [187]. Furthermore, due to its relatively high sampling rate, frequency-specific functional connectivity in the human brain has been revealed with fNIRS [194]. ...
Brains of human, as well as of other species, are all known to be organized into distinct neural networks, which have been found to serve as the basis for various brain functions and behaviors. More importantly, changes in brain networks are widely reported to be associated with almost all neurological and psychiatric disorders. Till now, numerous studies have been conducted to develop novel neuroimaging instruments and computational algorithms for both characterizing brain networks and investigating their behaviors in various populations of participants and patients. In this chapter, we discuss the state-of-the-art of these technologies in studying human brain networks and their applications to address fundamental questions in both basic and clinical neurosciences. We start our discussions on brain network mapping using individual neuroimaging modalities, i.e., functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), electroencephalography, electrocorticography (ECoG), positron emission tomography (PET), and functional near-infrared spectroscopy (fNIRS). We then continue with arguments on the value of multimodal neuroimaging technologies in studying human brain networks, which could achieve a “greater than the sum of its parts” knowledge about human brain networks due to complementary information provided by individual neuroimaging modalities. We discuss in particular on approaches deriving and characterizing intrinsic brain networks and their clinical applications, which are among the most significant findings about human brain networks in the past two decades. At the end, we further present our prospects on future works to address challenges in studying human brain networks, which could pave the way for the broad applications of brain networks in clinical and other real-world applications.
... Most previous functional connectivity studies with fNIRS identified resting state networks at the single-subject level by means of a seed-based correlation analysis, which measures the temporal synchronization between time-series across multiple channels (White et al., 2009;Mesquita et al., 2010;Zhang Y.J. et al., 2010;Fuchino et al., 2013;Novi et al., 2016). Alternatively, independent component analysis (ICA) has also been used to define maximally spatially or temporally independent components from individual datasets (Zhang H. et al., 2010;Zhang H. et al., 2011;White et al., 2012;Ferradal et al., 2015), which represent subject-specific independent patterns of functional connectivity. ...
... Similarly, the accuracy and robustness of ICA method is determined by the number of sample points available for the estimation, which are considerably larger in group-level analysis as compared to an analysis at the single-subject level. The ultimate consequence of these limitations is that most previous fNIRS RSFC studies have evaluated group differences at the single channel level (e.g., Fuchino et al., 2013;Bulgarelli et al., 2019), using qualitative comparisons (e.g., Homae et al., 2010;White et al., 2012), or performing statistical analysis on specific connectivity indexes only (e.g., Homae et al., 2010;Imai et al., 2014;Watanabe et al., 2017). ...
... Most previous optical imaging studies assessing RSFC reported only positive correlations, or presented both positive and negative correlations in the results but only discussed the former (Zhang H. et al., 2010;White et al., 2012). This has been in part due to the limited field of view of the fNIRS setups employed in these studies, but also due to the lack of a straightforward interpretation of the observed anticorrelated activity in the literature (Murphy and Fox, 2017). ...
Language acquisition is mediated by maturational and experiential mechanisms. It is a remarkably complex process, yet infants show incredible language learning capacities. In a bilingual context this process is even more challenging, since bilingual infants benefit from less day-to-day experience with each language. In addition, they need to perform specific computations such as separating their languages or storing the information of two linguistic inputs. Learning two languages, however, does not negatively affect language acquisition: bilingual infants follow a similar pace to their monolingual peers when main developmental milestones are considered. It has been suggested that bilingualism might elicit cognitive adaptations that allow infants to cope with the increased complexity of their linguistic environment. Distinctive attention allocation skills or an increased perceptual sensitivity are examples of the proposed adaptations. Whether bilingual infants’ success is also supported by modulations in the underlying functional systems in charge of these linguistic processes is the question this thesis aims to unravel. This question is addressed using a functional brain imaging technique especially suitable for infant populations: functional near-infrared spectroscopy (fNIRS). This neuroimaging technique offers the potential to study neural activity non- invasively based on cerebral hemodynamics. Because fNIRS is a relatively novel technique to measure infants functional brain activity, the thesis also contains a major methodological component. Particular focus is dedicated to data quality assessment and signal processing.
A series of fNIRS experiments are presented to investigate whether bilingualism might be one factor eliciting experience-induced neural adaptations in 4-month-old infants. First, the brain’s functional organization is examined through resting-state functional connectivity. This approach represents a viable strategy to link brain function and cognition, and it offers the potential to simultaneously examine various functional systems. Likewise, functional network activity can be modulated by different prenatal and postnatal conditions. Studying functional connectivity with fNIRS arises some methodological challenges that are inherent to this imaging technique. In particular, whether the fNIRS data preprocessing pipeline should include a step to deal with signal autocorrelation. The second study of this thesis addresses the influence of this step for functional connectivity analyses from a theoretical and empirical point of view. A third study investigates functional differences that might emerge during spoken language processing. Monolingual and bilingual infants’ brain responses to speech stimuli are measured to examine the brain areas in support of this cognitive process. The results of these experiments are presented.
Investigating the impact of bilingual exposure on how the brain works, prior to infants even beginning to babble, has remarkable theoretical implications for the field of language acquisition, which had long suspected that brain reorganization for linguistic exposure may begin in-utero, but certainly in the first months of life. This thesis also provides several methodological advancements confirming the suitability of fNIRS imaging for accurately and reliably assessing brain function in developmental populations. The importance of the theoretical and methodological implications of the findings of this thesis are discussed, as is the relevance of transparent and replicable research methodologies for future works in developmental cognitive neuroscience.
... The seed correlation [20] analysis and the independent component analysis (ICA) [33,34] are the main resting-state functional connectivity analyses. ...
... The number of independent components depends on the size of analyzed data. Between 10 and 20 independent components were used to analyze data acquired by a high-density diffuse optical tomography device [33]. Since our field of view was smaller and as only the sensorimotor function was exposed, we have chosen a smaller number of independent sources: K = 5. ...
... This would also allow to establish a comparison between optical resting-state maps and fMRI pre-operative maps. As opposed to fMRI and fNIRS resting-state analyses [17,33], the spatial patterns expressed in the ICA method cannot be sorted by comparing the patterns in the images to neuroanatomy atlas. This issue will be addressed in a future study by comparing optical and fMRI resting-state maps. ...
RGB optical imaging is a marker-free, contactless, and non-invasive technique that is able to monitor hemodynamic brain response following neuronal activation using task-based and resting-state procedures. Magnetic resonance imaging (fMRI) and functional near infra-red spectroscopy (fNIRS) resting-state procedures cannot be used intraoperatively but RGB imaging provides an ideal solution to identify resting-state networks during a neurosurgical operation. We applied resting-state methodologies to intraoperative RGB imaging and evaluated their ability to identify resting-state networks. We adapted two resting-state methodologies from fMRI for the identification of resting-state networks using intraoperative RGB imaging. Measurements were performed in 3 patients who underwent resection of lesions adjacent to motor sites. The resting-state networks were compared to the identifications provided by RGB task-based imaging and electrical brain stimulation. Intraoperative RGB resting-state networks corresponded to RGB task-based imaging (DICE:0.55±0.29). Resting state procedures showed a strong correspondence between them (DICE:0.66±0.11) and with electrical brain stimulation. RGB imaging is a relevant technique for intraoperative resting-state networks identification. Intraoperative resting-state imaging has several advantages compared to functional task-based analyses: data acquisition is shorter, less complex, and less demanding for the patients, especially for those unable to perform the tasks.
... Studies of intrinsic brain networks have been reported using other neuroimaging modalities in addition to fMRI, EEG, and MEG. Among them, intracranial electrophysiological recordings [182,58,183,184], PET [185,186], and fNIRS [177,60,187] have all been reported (see Fig. 1), with similar computation methods to identify ICNs, as in fMRI, EEG, and MEG data. Moreover, each modality has its own advantages and drawbacks. ...
... fNIRS is a neuroimaging modality that measures concentration changes of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) in the vasculature of cortical tissues using near infrared light [189,190]. fNIRS has been effectively employed to characterize resting-state brain networks for adults [60,[191][192][193][194][195][196] and infants [197,187,198,199]. It has also been used to assess abnormal brain networks in patients with brain disorders [47,200]. ...
... Furthermore, fNIRS usually has higher temporal sampling rates (∼10 Hz) than fMRI (∼1 Hz) [190,60,189], which provides benefits of rejecting non-neuronal related hemodynamic changes, such as, due to respirations and heartbeat. In addition, fNIRS is more economically efficient and portable, and can be used for populations, such as patients with implants and infants, who are not suitable to be inside MRI scanners, as well as in challenged environments, such as brain monitoring at bed-sites [187]. Furthermore, due to its relatively high sampling rate, frequency-specific functional connectivity in the human brain has been revealed with fNIRS [194]. ...
In this chapter, we present the physical and physiological basics behind EEG and MEG signal generation and propagation. We first start by presenting the biophysical principles that explain how the coordinated movements of ions inside and outside neuronal cells result in macroscale phenomena at the scalp, such as electric potentials recorded by EEG and magnetic fields sensed by MEG. These physical principles enforce EEG and MEG signals to have specific spatial and temporal features, which can be used to study brain’s response to internal and external stimuli. We continue our exploration by developing a mathematical framework within which EEG and MEG signals can be computed if the distribution of underlying brain sources is known, a process called forward problem. We further continue to discuss methods that attempt the reverse, i.e., solving for underlying brain sources given scalp measurements such as EEG and MEG, a process called source imaging. We will provide various examples of how electrophysiological source imaging techniques can help study the brain during its normal and pathological states. We will also briefly discuss how combining electrophysiological signals from EEG with hemodynamic signals from functional magnetic resonance imaging (fMRI) helps improve the spatiotemporal resolution of estimates of the underlying brain sources, which is critical for studying spatiotemporal processes within the brain. The goal of this chapter is to provide proper physical and physiological intuition and biophysical principles that explain EEG/MEG signal generation, its propagation from sources in the brain to EEG/MEG sensors, and how this process can be inverted using signal processing and machine learning techniques and algorithms.
... While most of these studies utilize functional connectivity MRI (fcMRI) to identify RSNs (Fransson et al., 2007;Doria et al., 2010;Smyser et al., 2010;Damaraju et al., 2014), functional near-infrared spectroscopy (fNIRS) has emerged as a promising modality due to its practical advantages, which include portability, low-cost, and silent operation. fNIRS studies investigating resting-state functional connectivity in infants have demonstrated: (1) evidence of primary sensory RSNs such as the visual (White et al., 2012) and auditory RSNs in term neonates (Ferradal et al., 2016), (2) increasing interhemispheric connectivity between homotopic regions in the first 6 months of life (Homae et al., 2010), and (3) altered functional connectivity patterns in preterm born neonates at term age Naoi et al., 2013). ...
... The longest motion-free segments from within each fNIRS sleep segment were extracted for the functional connectivity analyses. Previously reported infant RSN fNIRS studies used a minimum duration of 2 min of data (White et al., 2012;Bulgarelli et al., 2019Bulgarelli et al., , 2020, therefore the longest motion-free segment of at least 2 min duration was selected for AS and QS. The mean duration of fNIRS data segments was 215 s (AS = 170 ± 102 s; QS = 258 ± 146 s). ...
... However, by term equivalent age, these RSNs demonstrated lower correlation, limited spatial distribution, and reduced thalamocortical connectivity as compared to term-born controls. Using diffuse optical tomography (DOT), White et al. (2012) reported interhemispheric connectivity in the occipital cortex reflecting visual RSNs in healthy term infants. On the other hand, in a RS fNIRS study, Homae et al. (2010) showed a reduced interhemispheric connectivity in their healthy term cohort, which was only observed across all brain regions at a later stage from 3 months of age, although these effects might be caused by contamination of the optical signal from physiological artifacts in the superficial layers of the head. ...
The spontaneous cerebral activity that gives rise to resting-state networks (RSNs) has been extensively studied in infants in recent years. However, the influence of sleep state on the presence of observable RSNs has yet to be formally investigated in the infant population, despite evidence that sleep modulates resting-state functional connectivity in adults. This effect could be extremely important, as most infant neuroimaging studies rely on the neonate to remain asleep throughout data acquisition. In this study, we combine functional near-infrared spectroscopy with electroencephalography to simultaneously monitor sleep state and investigate RSNs in a cohort of healthy term born neonates. During active sleep (AS) and quiet sleep (QS) our newborn neonates show functional connectivity patterns spatially consistent with previously reported RSN structures. Our three independent functional connectivity analyses revealed stronger interhemispheric connectivity during AS than during QS. In turn, within hemisphere short-range functional connectivity seems to be enhanced during QS. These findings underline the importance of sleep state monitoring in the investigation of RSNs.
... The strong electromagnetic fields required for fMRI are unsafe for participants with implanted active electronic devices (e.g., pacemakers, deep brain stimulators, and cochlear implants). The wearable, portable nature of optical technologies opens the door to bedside and minimally constrained imaging of functional brain health, [25][26][27][28] in settings more ecologically natural than MRI. 24,[29][30][31][32][33] Given these strengths, fNIRS technologies are uniquely suited to studies involving infants and toddlers, 25,[34][35][36][37][38][39] and they are ideal for use in clinical settings in which standards of clinical care lead to complex or untenable logistics for moving the patient to an MRI machine (e.g., if the patient is on a ventilator). ...
... Indeed, advances in image quality obtained with HD-DOT, including a spatial resolution approaching that of fMRI, 25,46 have been demonstrated in recovered maps of brain function using both task-based 25,33,[45][46][47][48][49][50][51][52][53][54][55][56][57][58][59] and resting state functional connectivity techniques. 25,26,46,60 In this review, to contextualize challenges in HD-DOT system design, we will briefly describe the physical mechanisms underlying fNIRS measurements, and the theory underlying modeling of light propagation in tissue. We will then focus on optical-electronic instrumentation and cap design utilized in HD-DOT systems. ...
... A combination of foam and elastic pieces can help maintain a force perpendicular to the head surface to hold the optodes directly coupled against the scalp while allowing for moderate translation normal to the head such that the imaging cap can conform to local variations in head shape [ Fig. 6(f) used in cap design Fig. 7(b)]. 26,46 Alternatively, a spring loaded fiber tip can couple fibers to the scalp. 59 Furthermore, rigid outer structures aid in fiber management and suspend the weight of the fibers. ...
This review describes the unique opportunities and challenges for noninvasive optical mapping of human brain function. Diffuse optical methods offer safe, portable, and radiation free alternatives to traditional technologies like positron emission tomography or functional magnetic resonance imaging (fMRI). Recent developments in high-density diffuse optical tomography (HD-DOT) have demonstrated capabilities for mapping human cortical brain function over an extended field of view with image quality approaching that of fMRI. In this review, we cover fundamental principles of the diffusion of near infrared light in biological tissue. We discuss the challenges involved in the HD-DOT system design and implementation that must be overcome to acquire the signal-to-noise necessary to measure and locate brain function at the depth of the cortex. We discuss strategies for validation of the sensitivity, specificity, and reliability of HD-DOT acquired maps of cortical brain function. We then provide a brief overview of some clinical applications of HD-DOT. Though diffuse optical measurements of neurophysiology have existed for several decades, tremendous opportunity remains to advance optical imaging of brain function to address a crucial niche in basic and clinical neuroscience: that of bedside and minimally constrained high fidelity imaging of brain function.
... 9 It provides information on the relative concentration changes of oxyhemoglobin (HbO 2 ) and deoxyhemoglobin (HHb), yielding total hemoglobin (HbT) when summed. DOT measures regional changes in cerebral hemodynamics associated with cortical functional activation, 10 including resting-state networks, 11 visual activation, 12 and speech development. 13 It can also detect hemodynamic changes associated with cerebral pathology. ...
... Hz), 29 and Mayer waves (~0.1 Hz). 30 White et al. obtained CW-DOT data from the visual cortex of one infant with unilateral occipital stroke and demonstrated disrupted interhemispheric correlation of [HbO 2 ] signals at frequencies below respiration. 11 To our knowledge, we are the first group to apply LFO analysis to whole-head CW-DOT data from stroke-affected infants. We hypothesized that a detectable difference in LFO content would exist between the stroke-affected and healthy hemispheres of infants with perinatal stroke. ...
... This was based on results suggesting interhemispheric difference in spectral power that have been published from a single stroke-affected infant scanned at 10 weeks of life. 11 A possible explanation for the lack of spectral power results could be that stroke-affected infants were scanned early, prior to bulk tissue necrosis, thereby making any underlying spectral power change undetectable. Li et al. studied spontaneous left prefrontal cerebral oscillations among adults at risk for atherosclerotic stroke with single-channel NIR spectroscopy. ...
Background:
Perinatal stroke is a potentially debilitating injury, often under-diagnosed in the neonatal period. We conducted a pilot study investigating the role of the portable, non-invasive brain monitoring technique, diffuse optical tomography (DOT), as an early detection tool for infants with perinatal stroke.
Methods:
Four stroke-affected infants were scanned with a DOT system within the first 3 days of life and compared to four healthy control subjects. Spectral power, correlation, and phase lag between interhemispheric low frequency (0.0055-0.3 Hz) hemoglobin signals were assessed. Optical data analyses were conducted with and without magnetic resonance imaging (MRI)-guided stroke localization to assess the efficacy of DOT when used without stroke anatomical information.
Results:
Interhemispheric correlations of both oxyhemoglobin and deoxyhemoglobin concentration were significantly reduced in the stroke-affected group within the very low (0.0055-0.0095 Hz) and resting state (0.01-0.08 Hz) frequencies (p < 0.003). There were no interhemispheric differences for spectral power. These results were observed even without MRI stroke localization.
Conclusion:
This suggests that DOT and correlation-based analyses in the low-frequency range can potentially aid the early detection of perinatal stroke, prior to MRI acquisition. Additional methodological advances are required to increase the sensitivity and specificity of this technique.
... The cortical functions including cortical plasticity, functional connectivity or cerebral autoregulation that could be reflected based on oxygenation levels are directly related to motor and cognitive recovery after stroke. We reviewed 10 papers (38)(39)(40)(41)(42)(43)(44)(45)(46)(47) reporting cortical function recovery ( Table 2). ...
... A frequency-specific disruption in resting-state connectivity has been observed in cerebral infarction cases. fNIRS could also used in neonates as a bedside monitoring tool to early detect neurological deficiency and provide prognostic information (47). These evidence supported NIRS as a promising method for evaluating functional recovery (42). ...
... NIRS, a non-invasive neuroimaging technique with the advantages of low price, simplicity, portability and small devices, has a wide range of utility (48). The existing clinical literature suggests NIRS plays an important role in monitoring motor recovery, including upper limb (24)(25)(26)(27)(28), lower limb recovery (29)(30)(31)(32)(33)(34), balance control (35,36), motor learning (37), cortical function recovery (38)(39)(40)(41)(42)(43)(44)(45)(46)(47), cerebral hemodynamic changes (48)(49)(50)(51)(52)(53)(54)(55)(56)(57)(58)(59)(60)(61), cerebral oxygenation (62)(63)(64)(65)(66)(67)(68)(69)(70)(71)(72)(73), therapy (15,16), and other applications (20-22, 67, 74-83). In particular, its ambulatory real-time measurement without the fixation of position provides great value in tasks requiring constant movement, for example, gait control. ...
Background: Survivors of stroke often experience significant disability and impaired quality of life. The recovery of motor or cognitive function requires long periods. Neuroimaging could measure changes in the brain and monitor recovery process in order to offer timely treatment and assess the effects of therapy. A non-invasive neuroimaging technique near-infrared spectroscopy (NIRS) with its ambulatory, portable, low-cost nature without fixation of subjects has attracted extensive attention.
Methods: We conducted a comprehensive literature review in order to review the use of NIRS in stroke or post-stroke patients in July 2018. NCBI Pubmed database, EMBASE database, Cochrane Library and ScienceDirect database were searched.
Results: Overall, we reviewed 66 papers. NIRS has a wide range of application, including in monitoring upper limb, lower limb recovery, motor learning, cortical function recovery, cerebral hemodynamic changes, cerebral oxygenation, as well as in therapeutic method, clinical researches, and evaluation of the risk for stroke.
Conclusions: This study provides a preliminary evidence of the application of NIRS in stroke patients as a monitoring, therapeutic, and research tool. Further studies could give more emphasize on the combination of NIRS with other techniques and its utility in the prevention of stroke.
... The emergence and advancement of functional modalities and analysis techniques have allowed studies of early functional cerebral development. Major neuroimaging modalities include: functional magnetic resonance imaging (fMRI) [24], electroencephalography (EEG) [25,26], magnetoencephalography (MEG) [27], positron emission tomography (PET) [28], functional near-infrared spectroscopy (fNIRS) [29], diffuse optical tomography (DOT) [30], and functional ultrasound (fUS) imaging. ...
... ). In addition to the stimulus-evoked responses [149], using sufficient number of channels, fNIRS provides a new tool to assess cerebral FC [30,150,151]. Similar to EEG and MEG, fNIRS does not generate any audio noise and thus, unlike fMRI, there is no cortical activation related to the acoustic noise. This is an important advantage in resting state studies, particularly for the investigation of FC in a developing brain [152,153]. ...
... Several studies have established high-density DOT imaging of neonatal brain function at the bedside, in the normal newborn nursery or complex neonatal intensive care unit [30,177,178]. ...
Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants’ brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants’ brain.
... However, based on existing studies [15,16], functional brain networks obtained from HbR, HbO, and BOLD signals seem to exhibit high-level spatial similarities. There are more studies that have reported a highlevel spatial similarity of brain networks obtained using HbR and HbO under both task and resting conditions [15,16,[41][42][43][44][45]. While it is plausible that similar networked brain activations resulting from different contrast signals are indeed genuine, it may also be possible that observed similarity in these networks is due to the methodological limitations in probing fast dynamics of functional brain networks. ...
... To test the first hypothesis, we firstly replicated, using ICA, that HbO and HbR RSNs had similar topological features (Fig. 2). Such topological similarities have been previously reported in fNIRS literature using the correlation/ICA-based approaches [15,42,45] and our results added more evidence to the opinion that time-averaged brain-wide patterns might represent more anatomic parcellations rather than dynamic "distinct modes" of brain activity [51]. On the other hand, more differences were observed on the spatial and dynamic properties between the HbO and HbR CAPs. ...
Objective. Human resting-state networks (RSNs) estimated from oxygenated (HbO) and deoxygenated hemoglobin (HbR) data exhibit strong similarities, while task-based studies show different dynamics in HbR and HbO responses. Such a discrepancy might be explained due to time-averaged estimations of RSNs. Our study investigated differences between HbO and HbR on time-resolved brain-wide coactivation patterns (CAPs). Approach. Diffuse optical tomography was reconstructed from resting-state whole-head functional near-infrared spectroscopy data of HbR and HbO in individual healthy participants. Timeaveraged RSNs were obtained using the group-level independent component analysis. Time-resolved CAPs were estimated using a clustering approach on the time courses of all obtained RSNs. Characteristics of the RSNs and CAPs from HbR and HbO were compared. Main results. Spatial patterns of HbR and HbO RSNs exhibited significant similarities. Meanwhile, HbR CAPs revealed much more organized spatial and dynamic characteristics than HbO CAPs. The entire set of HbR CAPs suggests a superstructure resulted from brain-wide neuronal dynamics, which is less evident in the set of HbO CAPs. These differences between HbO and HbR CAPs were consistently replicated in individual session data. Conclusion. Our results suggest that human resting brain-wide neuronal activations are preserved better in time-resolved brainwide patterns, i.e., CAPs, from HbR than those from HbO, while such a difference is lost between time-averaged HbR and HbO RSNs. Significance. Our results reveal, for the first time, HbR concentration fluctuations are more directly coupled with resting dynamics of brain-wide neuronal activations in human brains.
... [12][13][14] In addition, the amount of low frequency signal has been used in fMRI and optical neuroimaging as a proxy for the amount of local neuronal activity. [15][16][17] . ...
... 18 Despite these caveats, ALFF has been used as a biomarker for localized neuronal activity in psychiatric illness, 15,30-31 white matter injury, 32 and stroke. 17,33 At least one prior study has examined LFP after cardiac arrest; van den Brule et al. 18 used TCD to assess CBF in adult cardiac arrest patients in the intensive care unit 6-72 h after cardiac arrest. Interestingly, the direction of the effect that we observed in predicting outcomes was the opposite of their study. ...
Aim
Cardiac arrest often results in severe neurologic injury. Improving care for these patients is difficult as few noninvasive biomarkers exist that allow physicians to monitor neurologic health. The amount of low-frequency power (LFP, 0.01-0.1 Hz) in cerebral haemodynamics has been used in functional magnetic resonance imaging as a marker of neuronal activity. Our hypothesis was that increased LFP in cerebral blood flow (CBF) would be correlated with improvements in invasive measures of neurologic health.
Methods
We adapted the use of LFP for to monitoring of CBF with diffuse correlation spectroscopy. We asked whether LFP (or other optical biomarkers) correlated with invasive microdialysis biomarkers (lactate-pyruvate ratio – LPR – and glycerol concentration) of neuronal injury in the 4 hours after return of spontaneous circulation in a swine model of paediatric cardiac arrest (Sus scrofa domestica, 8-11 kg, 51% female). Associations were tested using a mixed linear effects model.
Results
We found that higher LFP was associated with higher LPR and higher glycerol concentration. No other biomarkers were associated with LPR; cerebral haemoglobin concentration, oxygen extraction fraction, and one EEG metric were associated with glycerol concentration.
Conclusion
Contrary to expectations, higher LFP in CBF was correlated with worse invasive biomarkers. Higher LFP may represent higher neurologic activity, or disruptions in neurovascular coupling. Either effect may be harmful in the acute period after cardiac arrest. Thus, these results suggest our methodology holds promise for development of new, clinically relevant biomarkers than can guide resuscitation and post-resuscitation care.
Institutional protocol number: 19-001327
... When attempting to describe RSFC at the group level and to quantitatively compare RSFC patterns across experimental groups, traditional fNIRS-RSFC data analysis methods such as seed-based correlation analysis, [34][35][36][37] independent component analysis (ICA), 38,39 or clustering methods 18,40 present some limitations. For example, group-level functional connectivity studies based on ICA have often been computed by averaging subject-specific independent components (ICs) that match a priori spatial configurations (e.g., bilateral and covering sensorimotor regions) or exhibit high similarity across subjects. ...
... Most previous optical imaging studies assessing RSFC reported only positive correlations or presented both positive and negative correlations in the results but only discussed the former. 38,39 This has been mostly due to the lack of a straightforward interpretation of the observed anticorrelated activity in the literature. 90 ...
Significance: Early monolingual versus bilingual experience induces adaptations in the development of linguistic and cognitive processes, and it modulates functional activation patterns during the first months of life. Resting-state functional connectivity (RSFC) is a convenient approach to study the functional organization of the infant brain. RSFC can be measured in infants during natural sleep, and it allows to simultaneously investigate various functional systems. Adaptations have been observed in RSFC due to a lifelong bilingual experience. Investigating whether bilingualism-induced adaptations in RSFC begin to emerge early in development has important implications for our understanding of how the infant brain’s organization can be shaped by early environmental factors.
Aims: We attempt to describe RSFC using functional near-infrared spectroscopy (fNIRS) and to examine whether it adapts to early monolingual versus bilingual environments. We also present an fNIRS data preprocessing and analysis pipeline that can be used to reliably characterize RSFC in development and to reduce false positives and flawed results interpretations.
Methods: We measured spontaneous hemodynamic brain activity in a large cohort (N=99) of 4-month-old monolingual and bilingual infants using fNIRS. We implemented group-level approaches based on independent component analysis to examine RSFC, while providing proper control for physiological confounds and multiple comparisons.
Results: At the group level, we describe the functional organization of the 4-month-old infant brain in large-scale cortical networks. Unbiased group-level comparisons revealed no differences in RSFC between monolingual and bilingual infants at this age.
Conclusions: High-quality fNIRS data provide a means to reliably describe RSFC patterns in the infant brain. The proposed group-level RSFC analyses allow to assess differences in RSFC across experimental conditions. An effect of early bilingual experience in RSFC was not observed, suggesting that adaptations might only emerge during explicit linguistic tasks, or at a later point in development.
... These values exceed those of most previous wearable devices, [29][30][31][32]42,43 and this large number of source and detector locations provide a larger channel count than the HD-DOT devices used in previous neonatal studies. 62,63 The phantom we demonstrate here provides switchable, repeatable, and localized changes in absorption coefficient in the NIR range, and by exploiting MRI data and 3D printing, the construction process ensures anatomically realistic dimensions. The use of removable rod targets makes the manufacturing process significantly more straightforward than previous designs that permanently embedded the targets 48 and allows for the targets to be replaced as required. ...
... This compares favorably to the HD-DOT devices used in previous neonatal studies. 62,63 The system generates 1728 logical DOT channels per wavelength and produced 717 viable DOT channels per wavelength when applied to our novel dynamic phantom. This high-density imaging array yielded depth-resolved three-dimensional images with good spatial precision (a 3D Euclidean localization error of between 3 and 6 mm at 735 nm) and (based on the FWHM of the image perturbations at 735 nm) a lateral image resolution of approximately 10 to 12 mm at the depth of the newborn cortex. ...
Significance: Neonates are a highly vulnerable population. The risk of brain injury is greater during the first days and weeks after birth than at any other time of life. Functional neuroimaging that can be performed longitudinally and at the cot-side has the potential to improve our understanding of the evolution of multiple forms of neurological injury over the perinatal period. However, existing technologies make it very difficult to perform repeated and/or long-duration functional neuroimaging experiments at the cot-side. Aim: We aimed to create a modular, high-density diffuse optical tomography (HD-DOT) technology specifically for neonatal applications that is ultra-lightweight, low profile and provides high mechanical flexibility. We then sought to validate this technology using an anatomically accurate dynamic phantom. Approach: An advanced 10-layer rigid-flexible printed circuit board technology was adopted as the basis for the DOT modules, which allows for a compact module design that also provides the flexibility needed to conform to the curved infant scalp. Two module layouts were implemented: dual-hexagon and triple-hexagon. Using in-built board-to-board connectors, the system can be configured to provide a vast range of possible layouts. Using epoxy resin, thermochromic dyes, and MRI-derived 3D-printed moulds, we constructed an electrically switchable, anatomically accurate dynamic phantom. This phantom was used to quantify the imaging performance of our flexible, modular HD-DOT system. Results: Using one particular module configuration designed to cover the infant sensorimotor system, the device provided 36 source and 48 detector positions, and over 700 viable DOT channels per wavelength, ranging from 10 to
∼
45
mm
over an area of approximately
60
cm
2
. The total weight of this system is only 70 g. The signal changes from the dynamic phantom, while slow, closely simulated real hemodynamic response functions. Using difference images obtained from the phantom, the measured 3D localization error provided by the system at the depth of the cortex was in the of range 3 to 6 mm, and the lateral image resolution at the depth of the neonatal cortex is estimated to be as good as 10 to 12 mm. Conclusions: The HD-DOT system described is ultra-low weight, low profile, can conform to the infant scalp, and provides excellent imaging performance. It is expected that this device will make functional neuroimaging of the neonatal brain at the cot-side significantly more practical and effective.
... However, most systems lack the combination of spatial resolution and wide field-of-view (FOV) to image spatially distributed brain functions and discriminate the brain signal from overlaying scalp and skull. A few high-density tomographic systems use numerous discrete sources and detectors coupled with fiber bundles to a head cap (Hebden et al 2002, White et al 2012, Ferradal et al 2016. However, adjusting and maintaining a stable optical coupling of numerous fibers to a small fragile neonatal head (i.e. a contact measurement) is labor-intensive and poses great challenges to head cap design with safety concern. ...
... However, expanding the FOV to cover a significant portion of the head introduces great challenges in expensive high-channel-count instrumentation, difficult fiber-optic-scalp contact coupling, and complex data quality management. Particularly, adjusting and maintaining a stable optical coupling of numerous rigid and fragile optical fibers to a small neonatal head is labor-intensive and poses significant challenges on head cap design (Hebden et al 2002, White et al 2012, Ferradal et al 2016. These challenges are particularly difficult to overcome when adopting these contact measurement systems to small and fragile heads of preterm infants for continuous and longitudinal monitoring. ...
Extremely preterm infants' hemodynamic instability places them at high risk of brain injury. Currently there is no reliable bedside method to continuously monitor cerebral hemodynamics in the neonatal intensive care unit (NICU). This paper reports a feasibility study to adapt and test an innovative speckle contrast diffuse correlation tomography (scDCT) device for noncontact, high-density, 3D imaging of cerebral blood flow (CBF) in preterm infants. The scDCT scans a focused point near-infrared illumination to multiple source positions for deep tissue penetration, and controls an electron multiplying charge-coupled-device camera with thousands of pixels to achieve a high-density sampling. The optimized scDCT for use in preterm infants was first evaluated against an established diffuse correlation spectroscopy in an infant-head-simulating phantom with known properties. The observed significant correlation between the two measurements verified the capability of scDCT for transcranial brain imaging. The insignificant influence of transparent incubator wall on scDCT measurements was then confirmed by comparing adult forearm blood flow responses to artery cuff occlusions measured inside and outside the incubator. Finally, the scDCT device was moved to the NICU to image CBF variations in two preterm infants. Infant #1 with no major organ deficits showed little CBF fluctuation over the first 3 weeks of life. Infant #2 showed a significant CBF increase after the 2-hour pharmacotherapy for patent ductus arteriosus closure. While these CBF variations meet physiological expectations, the fact that no significant changes are noted with peripheral monitoring of blood oxygen saturation suggests necessity of direct cerebral monitoring. This feasibility study with timely technology development is an important and necessary step towards larger clinical studies with more subjects to further validate it for continuous monitoring and instant management of cerebral pathologies and interventions in the NICU.
... The correlation matrix is then thresholded into a binary matrix that describes the topological organization of the functional networks ( Figure 2C). Of note, there are other approaches used to get brain connectivity networks, such as clustering (Homae et al., 2010;Blanco et al., 2018) and independent component analysis (White et al., 2012;Ferradal et al., 2016;ICA). ...
... For example, 10-years-old children with cerebral palsy exhibited increased functional connectivity between sensorimotor centers, which was back to normal immediately after physical therapy but then relapsed after 6 months ( Figure 8A; Cao et al., 2015). White et al. (2012) examined the functional connectivity pattern in an infant with unilateral occipital stroke and found that the functional connectivity in the visual cortex was unilateral and nonsymmetrical ( Figure 8B). For healthy infants, the connectivity displayed a strong and bilaterally symmetrical pattern in the occipital network. ...
Early brain development from infancy through childhood is closely related to the development of cognition and behavior in later life. Human brain connectome is a novel framework for describing topological organization of the developing brain. Resting-state functional near-infrared spectroscopy (fNIRS), with a natural scanning environment, low cost, and high portability, is considered as an emerging imaging technique and has shown valuable potential in exploring brain network architecture and its changes during the development. Here, we review the recent advances involving typical and atypical development of the brain connectome from neonates to children using resting-state fNIRS imaging. This review highlights that the combination of brain connectome and resting-state fNIRS imaging offers a promising framework for understanding human brain development.
... Considering the advantages and limitations of both model-based and data-driven methods, seedand ICA-based methods provide complementary information from each other, 17,18 as many related works have shown results of both methods for analysis. [19][20][21] However, the conventional seed-based method shows degraded performance compared to the ICA-based in terms of the sensitivity a and specificity b due to its limited capability in noise and artifact reduction from the fNIR spectroscopy data. 16 This performance gap reduces reliability of analysis results using the seed-based method. ...
... 17,18 Accordingly, many related works show results of both the seed-and ICA-based methods for various aspects of analysis. [19][20][21] However, the conventional seed-based method shows degraded performance compared to the ICA-based in terms of the sensitivity and specificity. 16 This performance gap reduces reliability of analysis results using the seed-based method relative to ICAbased method. ...
Functional connectivity derived from resting-state functional near infrared spectroscopy has gained attention of recent scholars because of its capability in providing valuable insight into intrinsic networks and various neurological disorders in a human brain. Several progressive methodologies in detecting resting-state functional connectivity patterns in functional near infrared spectroscopy, such as seed-based correlation analysis and independent component analysis as the most widely used methods, were adopted in previous studies. Although these two methods provide complementary information each other, the conventional seed-based method shows degraded performance compared to the independent component analysis-based scheme in terms of the sensitivity and specificity. In this study, artificial neural network and convolutional neural network were utilized in order to overcome the performance degradation of the conventional seed-based method. First of all, the results of artificial neural network- and convolutional neural network-based method illustrated the superior performance in terms of specificity and sensitivity compared to both conventional approaches. Second, artificial neural network, convolutional neural network, and independent component analysis methods showed more robustness compared to seed-based method. Moreover, resting-state functional connectivity patterns derived from artificial neural network- and convolutional neural network-based methods in sensorimotor and motor areas were consistent with the previous findings. The main contribution of the present work is to emphasize that artificial neural network as well as convolutional neural network can be exploited for a high-performance seed-based method to estimate the temporal relation among brain networks during resting state.
... This allows the assignment of optical and physiological properties to voxels within a tissue sample. By using a high density of sources and detectors, a recent DOT study has demonstrated functional neuroimaging of the superficial cortex with images of a diagnostic quality similar to those of fMRI [72]. ...
Diffuse correlation spectroscopy (DCS) is a non-invasive optical modality which can be used to measure cerebral blood flow (CBF) in real-time. It has important potential applications in clinical monitoring, as well as in neuroscience and the development of a non-invasive brain-computer interface. However, a trade-off exists between the signal-to-noise ratio (SNR) and imaging depth, and thus CBF sensitivity, of this technique. Additionally, as DCS is a diffuse optical technique, it is limited by a lack of inherent depth discrimination within the illuminated region of each source-detector pair, and the CBF signal is therefore also prone to contamination by the extracerebral tissues which the light traverses. Placing a particular emphasis on scalability, affordability, and robustness to ambient light, in this work I demonstrate a novel approach which fuses the fields of digital holography and DCS: holographic Fourier domain DCS (FD-DCS). The mathematical formalism of FD-DCS is derived and validated, followed by the construction and validation (for both in vitro and in vivo experiments) of a holographic FD-DCS instrument. By undertaking a systematic SNR performance assessment and developing a novel multispeckle denoising algorithm, I demonstrate the highest SNR gain reported in the DCS literature to date, achieved using scalable and low-cost camera-based detection. With a view to generating a forward model for holographic FD-DCS, in this thesis I propose a novel framework to simulate statistically accurate time-integrated dynamic speckle patterns in biomedical optics. The solution that I propose to this previously unsolved problem is based on the Karhunen-Loève expansion of the electric field, and I validate this technique against novel expressions for speckle contrast for different forms of homogeneous field. I also show that this method can readily be extended to cases with spatially varying sample properties, and that it can also be used to model optical and acoustic parameters.
... As this population has a high rate of subsequent developmental disabilities, often posing limitations to MRI scan tolerance, it is critical to continue to refine and apply improved methods for stringent motion correction 62 and shorter scan acquisition time 63 to provide longitudinal measurements as patients mature beyond infancy. Such potential limitations also highlight the importance of leveraging multimodal techniques (e.g., dMRI, rs-fMRI, EEG, high density-diffuse optical tomography [HD-DOT 64,65 ]) in infancy and beyond, offering complementary knowledge and future avenues for investigation that may accommodate unique patient needs. ...
Preterm infants with intraventricular hemorrhage (IVH) are known to have some of the worst neurodevelopmental outcomes in all of neonatal medicine, with a growing body of evidence relating these outcomes to underlying disruptions in brain structure and function. This review begins by summarizing state-of-the-art neuroimaging techniques delineating structural and functional connectivity (diffusion and resting state functional MRI) and their application in infants with IVH, including unique technical challenges and emerging methods. We then review studies of altered structural and functional connectivity in this high-risk population, highlighting the role of IVH severity and location. We subsequently detail investigations linking structural and functional findings in infancy to later outcomes in early childhood. We conclude with future directions including methodologic considerations for prospective and potentially interventional studies designed to mitigate disruptions to underlying structural and functional connections and improve neurodevelopmental outcomes in this high-risk population.
... In comparison with fMRI, fNIRS provides complementary features of cost-effectiveness, portability, high temporal resolution, and compatibility with implanted medical devices or brain stimulation devices. Thus, increasing efforts are dedicated to exploring the use of fNIRS in populations not suitable for or with contraindications to fMRI, such as infants (Homae et al., 2010;Molavi et al., 2013;Watanabe et al., 2017;White et al., 2012) or patients with cochlear implants (Bortfeld, 2019;Saliba et al., 2016). ...
Background
Functional near-infrared spectroscopy (fNIRS) has been increasingly employed to monitor cerebral hemodynamics in normal and diseased conditions. However, fNIRS suffers from its susceptibility to superficial activity and systemic physiological noise. The objective of the study was to establish a noise reduction method for fNIRS in a whole-head montage.
New Method
We have developed an automated denoising method for whole-head fNIRS. A high-density montage consisting of 109 long-separation channels and 8 short-separation channels was used for recording. Auxiliary sensors were also used to measure motion, respiration and pulse simultaneously. The method incorporates principal component analysis and general linear model to identify and remove a globally uniform superficial component. Our denoising method was evaluated in experimental data acquired from a group of healthy human subjects during a visually cued motor task and further compared with a minimal preprocessing method and three established denoising methods in the literature. Quantitative metrics of contrast-to-noise ratio, within-subject standard deviation and adjusted coefficient of determination were evaluated.
Results
After denoising, whole-head topography of fNIRS revealed focal activations concurrently in the primary motor and visual areas.
Comparison with Existing Methods
Analysis showed that our method improves upon the four established preprocessing methods in the literature.
Conclusions
An automatic, effective and robust preprocessing pipeline was established for removing physiological noise in whole-head fNIRS recordings. Our method can enable fNIRS as a reliable tool in monitoring large-scale, network-level brain activities for clinical uses.
... Near-infrared spectroscopy (NIRS) and diffuse optical tomography (DOT) have already demonstrated some promise in the diagnosis of PAIS [10,11,12,13,14]. These modalities rely on low power light sources that shine non-ionising NIR light through the patient's tissue, typically to reveal changes in blood volume and Commercial wearable continuous wave NIRS systems have already appeared in the market, and miniaturized time domain systems are currently under development [15,16]. ...
Conditions such as hypoxic-ischaemic encephalopathy (HIE) and perinatal arterial ischaemic stroke (PAIS) are causes of lifelong neurodisability in a few hundred infants born in the UK each year. Early diagnosis and treatment are key, but no effective bedside detection and monitoring technology is available. Non-invasive, near-infrared techniques have been explored for several decades, but progress has been inhibited by the lack of a portable technology, and intensity measurements, which are strongly sensitive to uncertain and variable coupling of light sources and detector to the scalp. A technique known as time domain diffuse optical tomography (TD-DOT) uses measurements of photon flight times between sources and detectors placed on the scalp. Mean flight time is largely insensitive to the coupling and variation in mean flight time can reveal spatial variation in blood volume and oxygenation in regions of brain sampled by the measurements. While the cost, size and high power consumption of such technology have hitherto prevented development of a portable imaging system, recent advances in silicon technology are enabling portable and low-power TD-DOT devices to be built. A prototype TD-DOT system is proposed and demonstrated, with the long-term aim to design a portable system based on independent modules, each supporting a time-of-flight detector and a pulsed source. The operation is demonstrated of components that can be integrated in a portable system: silicon photodetectors, integrated circuit-based signal conditioning and time detection -- built using a combination of off-the-shelf components and reconfigurable hardware, standard computer interfaces, and data acquisition and calibration software. The only external elements are a PC and a pulsed laser source. This thesis describes the design process, and results are reported on the performance of a 2-channel system with online histogram generation, used for phantom imaging. Possible future development of the hardware is also discussed.
... Like fMRI signals, fNIRS also offers the potential to examine the human brain at resting state by measuring concentration changes of HbO and HbR in the vasculature of the cortical tissues below sensing channels (Obrig and Villringer, 2003;Scholkmann et al., 2014). fNIRS has been effectively employed to characterize the resting-state brain in adults (Obrig et al., 2000;White et al., 2009;Lu et al., 2010;Mesquita et al., 2010;Sasai et al., 2011;de Souza Rodrigues et al., 2019), infants or children (Homae et al., 2010;White et al., 2012;Molavi et al., 2013;Watanabe et al., 2017;Bulgarelli et al., 2019Bulgarelli et al., , 2020Wang et al., 2020), and to assess differences between experimental groups (Keehn et al., 2013;Ieong et al., 2019;Arun et al., 2020). The most common RSFC analysis of fNIRS data involves evaluating the temporal relationship between time series of the preprocessed data from recording units, for example, through the Pearson's correlation. ...
Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05–0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.
... By using a structural prior to model field propagation within the head, imaging techniques such as DOT are enabled which produce images that spatially localise activation on the cortex (rather than relying on the position of sources and detectors on the scalp to interpret results, as is done in conventional fNIRS). In the last two decades, a large body of research applying DOT to the study of the neonatal brain has been established, such as studies of functional activation (Austin et al., 2006;Hebden, 2003;Karen et al., 2019;White, Liao, Ferradal, Inder, & Culver, 2012), neuropathology (Chalia et al., 2016;Dempsey et al., 2014;Plomgaard et al., 2016;Singh et al., 2016), and monitoring the brain for extended periods (Brigadoi et al., 2019). Previous work with infants has also employed prior structural information as a space to which functional data can be registered (Papademetriou et al., 2013). ...
The neonatal brain undergoes dramatic structural and functional changes over the last trimester of gestation. The accuracy of source localisation of brain activity recorded from the scalp therefore relies on accurate age-specific head models. Although an age-appropriate population-level atlas could be used, detail is lost in the construction of such atlases, in particular with regard to the smoothing of the cortical surface, and so such a model is not representative of anatomy at an individual level. In this work, we describe the construction of a database of individual structural priors of the neonatal head using 215 individual-level datasets at ages 29-44 weeks postmenstrual age from the Developing Human Connectome Project. We have validated a method to segment the extra-cerebral tissue against manual segmentation. We have also conducted a leave-one-out analysis to quantify the expected spatial error incurred with regard to localising functional activation when using a best-matching individual from the database in place of a subject-specific model; the median error was calculated to be 8.3 mm (median absolute deviation 3.8 mm). The database can be applied for any functional neuroimaging modality which requires structural data whereby the physical parameters associated with that modality vary with tissue type and is freely available at www.ucl.ac.uk/dot-hub.
... Despite the apparent absence of a tight neurovascular coupling in perinatal rodent models Zehendner et al., 2013), we demonstrated for the first time in human infants, a clear association between a direct measure of neural (EEG) and positive functional hemodynamic activity (fMRI). Whilst in rodents, neurovascular coupling matures postnatally together with the development of long-range connectivity patterns , in humans this connectivity can be readily identified by the late preterm period, thus suggesting that neuronal and hemodynamic activity are already closely linked by this time Doria et al., 2010;White et al., 2012). This relationship is developmentally regulated across the neonatal period resulting in changing hemodynamic responses and is validated by the presence of localised positive BOLD activation in the primary auditory and somatosensory cortices following sound and passive motor stimulation respectively Baldoli et al., 2015;Erberich et al., 2003). ...
The human infant cerebral cortex undergoes substantial development during the equivalent of the last trimester of gestation. Here I focus on the maturation of two key cortical functions: the somatosensory and the sleep-wake systems. The developmental milestones of these two functions were investigated by recording electrical brain activity in infants aged between 28 and 43 corrected gestational weeks. In Chapter 1 I summarise current knowledge on the developmental neurophysiology of the mammalian cortex, and in Chapter 2 I describe my methodology. In Chapter 3 I show that contraction of the limb (hand) or respiratory (diaphragm) muscle is associated with feedback somatosensory cortical activity, which comprises immature fast oscillations that decline towards term age. In Chapter 4 I interrogate the maturation of somatosensory functioning further by applying mechanical stimulation to the body surface. The complete cortical response to touching the hand and face emerges before that following foot stimulation, with a gradual involvement of the ipsilateral hemisphere. In Chapter 5 I demonstrate the emergence of state-dependency of spontaneous slow cortical oscillations at full-term. These data show that immediately prior to normal birth, in parallel with a period of rapid structural development of the cortex and its afferents, there is i) a transition in cortical somatosensory encoding from rudimentary responses to hierarchical bi-hemispheric processing, with a rostro-caudal body gradient, and ii) emergence of sleep-wake state-dependent cortical functioning. The results provide converging evidence of a switch point immediately prior to full-term birth, in which brain circuits are primed for an increased and more complex sensorimotor experience that is state-dependent.
... One of the studies reported a disruption of rsFC using a wavelet coherence analysis of fNIRS for cerebral infarction (Tan et al. 2015). Another study used fNIRS for bedside monitoring of neonates to assess the prognosis longitudinally (White et al. 2012).Our study recruited right handed subjects for the experiment. The LSS group showed disrupted ipsilesional connectivity and an increased contra-lesional rsFC after the onset of stroke. ...
Resting-state functional imaging has been used to study the functional reorganization of the brain. The application of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (rsFC) has already been demonstrated in recent years. The present study aimed to identify the difference in rsFC patterns during the recovery from the upper-limb deficit due to stroke. Twenty patients with mild stroke having an onset of four to eight weeks were recruited from the stroke clinic of our institute and an equal number of healthy volunteers were included in the study after ethical committee approval. The fNIRS signals were recorded bilaterally over the premotor area and supplementary motor area and over the primary motor cortex. Pearson Correlation is the method used to compute rsFC for the healthy group and patient group. For the healthy group, both intra-hemispheric and inter-hemispheric connections were stronger. RSFC analysis demonstrated changes from the healthy pattern for the patient group with an upper-limb deficit. The left hemisphere affected group showed disrupted ipsilesional and an increased contra-lesional connectivity. The longitudinal data analysis of rsFC showed improvement in the connections in the ipsilesional hemisphere between the primary motor area, somatosensory area, and premotor areas. In the future, the rsFC changes during the recovery could be used to predict the extent of recovery from stroke motor deficits.
... We have shown the ability to rapidly conduct transillumination measurements across the infant head with the CW measurement approach that has not previously been possible. Variations of fNIRS-DOT techniques have been used to study the resting-state functional connectivity in newborn infants at the bedside [34], [35], and this field was originally established using the BOLD signals in fMRI research: correlating spontaneous oscillations of the BOLD fMRI signal among brain regions allows one to distinguish resting state functional networks [36]. In our current design, the total data acquisition time required 8 minutes, due to the mechanical, rotating mask controlled by a servo motor and the substantial readout time of the CCD. ...
Although Blood Oxygenation Level Dependent (BOLD) functional MRI (fMRI) is widely used to examine brain function in adults, the need for general anesthesia limits its practical utility in infants and small children. Functional Near-Infrared Spectroscopy – Diffuse Optical Tomography (fNIRS-DOT) imaging promises to be an alternative brain network imaging technique. Yet current versions of continuous-wave fNIRS-DOT systems are restricted to the cortical surface measurements and do not probe deep structures that are frequently injured especially in premature infants. Herein we report a transcranial near infrared optical imaging system, called Cap-based Transcranial Optical Tomography (CTOT) able to image whole brain hemodynamic activity with 3 seconds of data acquisition time. We show the system is capable of whole brain oxygenation mapping in an awake child, and that tomographically reconstructed static CTOT-derived oxy- and deoxygenated blood volumes are spatially correlated with the time-averaged BOLD fMRI volumes. By removing time bottlenecks in the current system, dynamic CTOT mapping should be possible, which would then enable evaluation of functional connectivity in awake infants.
... Apart from fMRI and electrophysiological recordings, near-infrared spectroscopy (NIRS) also offers the potential to examine RSFC by measuring concentration changes of oxyhemoglobin (HbO 2 ) and deoxyhemoglobin (HbR) in the vasculature of the cortical tissue below measurement channels. 16,17 NIRS has been effectively employed to characterize RSFC in adults 18 and infants, [19][20][21] and to assess differences in RSFC patterns between experimental groups. 22 The most common NIRS RSFC analysis involves evaluating the temporal relationship between time series of the preprocessed data per channel, for example, through relatedness measures, such as the Pearson's correlation. ...
Near-infrared spectroscopy (NIRS) offers the potential to characterize resting-state functional connectivity (RSFC) in populations that are not easily assessed otherwise, such as young infants. In addition to the advantages of NIRS, one should also consider that the RS-NIRS signal requires specific data preprocessing and analysis. In particular, the RS-NIRS signal shows a colored frequency spectrum, which can be observed as temporal autocorrelation, thereby introducing spurious correlations. To address this issue, prewhitening of the RS-NIRS signal has been recently proposed as a necessary step to remove the signal temporal autocorrelation and therefore reduce false-discovery rates. However, the impact of this step on the analysis of experimental RS-NIRS data has not been thoroughly assessed prior to the present study. Here, the results of a standard preprocessing pipeline in a RS-NIRS dataset acquired in infants are compared with the results after incorporating two different prewhitening algorithms. Our results with a standard preprocessing replicated previous studies. Prewhitening altered RSFC patterns and disrupted the antiphase relationship between oxyhemoglobin and deoxyhemoglobin. We conclude that a better understanding of the effect of prewhitening on RS-NIRS data is still needed before directly considering its incorporation to the standard preprocessing pipeline.
... 2 Despite these advances, HD-DOT has limited coverage and wearability due to mechanical challenges: increasing the coverage requires increasing the number of fibers, sources, and detectors, which results in heavier imaging caps and larger system sizes. 5 Current large field-of-view HD-DOT caps, therefore, require significant infrastructure to support fiber weight in the cap. For routine and wide application, HD-DOT needs to become more wearable. ...
Though optical imaging of human brain function is gaining momentum, widespread adoption is restricted in part by a tradeoff among cap wearability, field of view, and resolution. To increase coverage while maintaining functional magnetic resonance imaging (fMRI)-comparable image quality, optical systems require more fibers. However, these modifications drastically reduce the wearability of the imaging cap. The primary obstacle to optimizing wearability is cap weight, which is largely determined by fiber diameter. Smaller fibers collect less light and lead to challenges in obtaining adequate signal-to-noise ratio. Here, we report on a design that leverages the exquisite sensitivity of scientific CMOS cameras to use fibers with
∼
30
×
smaller cross-sectional area than current high-density diffuse optical tomography (HD-DOT) systems. This superpixel sCMOS DOT (SP-DOT) system uses
200
-
μ
m
-diameter fibers that facilitate a lightweight, wearable cap. We developed a superpixel algorithm with pixel binning and electronic noise subtraction to provide high dynamic range (
>
10
5
), high frame rate (
>
6
Hz
), and a low effective detectivity threshold (
∼
200
fW
/
Hz
1
/
2
-
mm
2
), each comparable with previous HD-DOT systems. To assess system performance, we present retinotopic mapping of the visual cortex (
n
=
5
subjects). SP-DOT offers a practical solution to providing a wearable, large field-of-view, and high-resolution optical neuroimaging system.
... Given the similarities with the BOLD contrast, resting-state functional connectivity methods have been adapted to study spontaneous brain activity in the developing brain using fNIRS systems. Because of technical and logistical challenges involved with the design and implementation of large arrays, early reports were only limited to producing functional connectivity maps of single cortical region such as the visual cortex in term and prematurely born infants ( White et al., 2012). Alternatively, other research groups have prioritized head coverage over imaging capability, using the time series of single NIRS channels (i.e., single source-detector measurements) rather than voxel data ( Homae et al., 2010). ...
Early brain development, from embryonic period to infancy, is characterized by rapid structural and functional changes. These changes can be studied using structural and physiological neuroimaging methods. In order to optimally acquire and accurately interpret this data, concepts from adult neuroimaging cannot be directly transferred. Instead, one must have a basic understanding of fetal and neonatal structural and physiological brain development, and understand important modulators of this process. Here, we first review the major developmental milestones of transient cerebral structures and structural connectivity (axonal connectivity) followed by a summary of the contributions from ex vivo and in vivo MRI. Next, we discuss the basic biology of neuronal circuitry development (synaptic connectivity, i.e. ensemble of direct chemical and electrical connections between neurons), physiology of neurovascular coupling, baseline metabolic needs of the fetus and the infant, and functional connectivity (defined as statistical dependence of low-frequency spontaneous fluctuations seen with functional magnetic resonance imaging (fMRI)). The complementary roles of magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS) are discussed. We include a section on modulators of brain development where we focus on the placenta and emerging placental MRI approaches. In each section we discuss key technical limitations of the imaging modalities and some of the limitations arising due to the biology of the system. Although neuroimaging approaches have contributed significantly to our understanding of early brain development, there is much yet to be done and a dire need for technical innovations and scientific discoveries to realize the future potential of early fetal and infant interventions to avert long term disease.
... While MRI affords several advantages for studying these associations, including improved spatial resolution and anatomic specificity, future investigations may utilize other complementary modalities for assessing brain development and function. These include functional near infrared spectroscopy (fNIRS), which measures hemodynamic contrasts [207][208][209] and electroencephalography (EEG), which assesses the coherence of cortical electrical activity and has been used to successfully model brain connectivity-behavior associations [210]. In addition, diffuse optical tomography (DOT) enables measurements of functional connectivity which align with rs-fMRI, though with a more limited field of view [211,212]. ...
Background
Despite advances in antenatal and neonatal care, preterm birth remains a leading cause of neurological disabilities in children. Infants born prematurely, particularly those delivered at the earliest gestational ages, commonly demonstrate increased rates of impairment across multiple neurodevelopmental domains. Indeed, the current literature establishes that preterm birth is a leading risk factor for cerebral palsy, is associated with executive function deficits, increases risk for impaired receptive and expressive language skills and is linked with higher rates of co-occurring attention deficit hyperactivity disorder, anxiety and autism spectrum disorders. These same infants also demonstrate elevated rates of aberrant cerebral structural and functional connectivity, with persistent changes evident across advanced magnetic resonance imaging modalities as early as the neonatal period. Emerging findings from cross-sectional and longitudinal investigations increasingly suggest that aberrant connectivity within key functional networks and white matter tracts may underlie the neurodevelopmental impairments common in this population.
Main Body
This review begins by highlighting the elevated rates of neurodevelopmental disorders across domains in this clinical population, describes the patterns of aberrant structural and functional connectivity common in prematurely-born infants and children and then reviews the increasingly established body of literature delineating the relationship between these brain abnormalities and adverse neurodevelopmental outcomes. We also detail important, typically understudied, clinical and social variables that may influence these relationships among preterm children, including heritability and psychosocial risks.
Conclusion
Future work in this domain should continue to leverage longitudinal evaluations of preterm infants which include both neuroimaging and detailed serial neurodevelopmental assessments to further characterize relationships between imaging measures and impairment, information necessary for advancing our understanding of modifiable risk factors underlying these disorders and best practices for improving neurodevelopmental trajectories in this high-risk clinical population.
Background:
Unstable cerebral hemodynamics places preterm infants at high risk of brain injury. We adapted an innovative, fiber-free, wearable diffuse speckle contrast flow-oximetry (DSCFO) device for continuous monitoring of both cerebral blood flow (CBF) and oxygenation in neonatal piglets and preterm infants.
Methods:
DSCFO uses two small laser diodes as focused-point and a tiny CMOS camera as a high-density two-dimensional detector to detect spontaneous spatial fluctuation of diffuse laser speckles for CBF measurement, and light intensity attenuations for cerebral oxygenation measurement. The DSCFO was first validated against the established diffuse correlation spectroscopy (DCS) in neonatal piglets and then utilized for continuous CBF and oxygenation monitoring in preterm infants during intermittent hypoxemia (IH) events.
Results:
Significant correlations between the DSCFO and DCS measurements of CBF variations in neonatal piglets were observed. IH events induced fluctuations in CBF, cerebral oxygenation, and peripheral cardiorespiratory vitals in preterm infants. However, no consistent correlation patterns were observed among peripheral and cerebral monitoring parameters.
Conclusions:
This pilot study demonstrated the feasibility of DSCFO technology to serve as a low-cost wearable sensor for continuous monitoring of multiple cerebral hemodynamic parameters. The results suggested the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations.
Impact:
The innovative DSCFO technology may serve as a low-cost wearable sensor for continuous bedside monitoring of multiple cerebral hemodynamic parameters in neonatal intensive care units. Concurrent DSCFO and DCS measurements of CBF variations in neonatal piglet models generated consistent results. No consistent correlation patterns were observed among peripheral and cerebral monitoring parameters in preterm neonates, suggesting the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations during IH events. Integrating and correlating multiple cerebral functional parameters with clinical outcomes may identify biomarkers for prediction and management of IH associated brain injury.
Background: Unstable cerebral hemodynamics places preterm infants at high risk of brain injury. We adapted an innovative, fiber-free, wearable diffuse speckle contrast flow-oximetry (DSCFO) device for continuous monitoring of both cerebral blood flow (CBF) and oxygenation in neonatal piglets and preterm infants.
Methods: DSCFO uses two small laser diodes as focused-point and a tiny CMOS camera as a high-density two-dimensional detector to detect spontaneous spatial fluctuation of diffuse laser speckles for CBF measurement, and light intensity attenuations for cerebral oxygenation measurement. The DSCFO was first validated against the established diffuse correlation spectroscopy (DCS) in neonatal piglets and then utilized for continuous CBF and oxygenation monitoring in preterm infants during intermittent hypoxemia (IH) events.
Results: Consistent results between the DSCFO and DCS measurements of CBF variations in neonatal piglets were observed. IH events induced fluctuations in CBF, cerebral oxygenation, and peripheral cardiorespiratory vitals in preterm infants. However, no consistent correlation patterns were observed among peripheral and cerebral monitoring parameters.
Conclusions: This pilot study demonstrated the feasibility of DSCFO technology to serve as a low-cost wearable sensor for continuous monitoring of multiple cerebral hemodynamic parameters. The results suggested the importance of multi-parameter measurements for understanding deep insights of peripheral and cerebral regulations.
The role of the lymphatics in the clearance of cerebrospinal fluid (CSF) from the brain has been implicated in multiple neurodegenerative conditions. In premature infants, intraventricular hemorrhage causes increased CSF production and, if clearance is impeded, hydrocephalus and severe developmental disabilities can result. In this work, we developed and deployed near-infrared fluorescence (NIRF) tomography and imaging to assess CSF ventricular dynamics and extracranial outflow in similarly sized, intact non-human primates (NHP) following microdose of indocyanine green (ICG) administered to the right lateral ventricle. Fluorescence optical tomography measurements were made by delivering ~10 mW of 785 nm light to the scalp by sequential illumination of 8 fiber optics and imaging the 830 nm emission light collected from 22 fibers using a gallium arsenide intensified, charge coupled device. Acquisition times were 16 seconds. Image reconstruction used the diffusion approximation and hard-priors obtained from MRI to enable dynamic mapping of ICG-laden CSF ventricular dynamics and drainage into the subarachnoid space (SAS) of NHPs. Subsequent, planar NIRF imaging of the scalp confirmed extracranial efflux into SAS and abdominal imaging showed ICG clearance through the hepatobiliary system. Necropsy confirmed imaging results and showed that deep cervical lymph nodes were the routes of extracranial CSF egress. The results confirm the ability to use trace doses of ICG to monitor ventricular CSF dynamics and extracranial outflow in NHP. The techniques may also be feasible for similarly-sized infants and children who may suffer impairment of CSF outflow due to intraventricular hemorrhage.
Studies of cortical function in newborn infants in clinical settings are extremely challenging to undertake with traditional neuroimaging approaches. Partly in response to this challenge, functional near-infrared spectroscopy (fNIRS) has become an increasingly common clinical research tool but has significant limitations including a low spatial resolution and poor depth specificity. Moreover, the bulky optical fibres required in traditional fNIRS approaches present significant mechanical challenges, particularly for the study of vulnerable newborn infants. A new generation of wearable, modular, high-density diffuse optical tomography (HD-DOT) technologies has recently emerged that overcomes many of the limitations of traditional, fibre-based and low-density fNIRS measurements. Driven by the development of this new technology, we have undertaken the first cot-side study of newborn infants using wearable HD-DOT in a clinical setting. We use this technology to study functional brain connectivity (FC) in newborn infants during sleep and assess the effect of neonatal sleep states, active sleep (AS) and quiet sleep (QS), on resting state FC. Our results demonstrate that it is now possible to obtain high-quality functional images of the neonatal brain in the clinical setting with few constraints. Our results also suggest that sleep states differentially affect FC in the neonatal brain, consistent with prior reports.
Near‐infrared spectroscopy (NIRS) is a noninvasive optical technique that uses the near‐infrared spectrum for functional neuroimaging by measuring oxygenation and hemodynamic changes in the cerebral cortex. The advantages of NIRS include its portability and ease of application, which allows for testing with the subject in natural positions, such as sitting or standing. Since 1994, NIRS has been increasingly used to conduct functional activation studies on different psychiatric disorders, most prominently schizophrenia, depression, bipolar disorder, and neurodevelopmental disorders. However, limited information on its use among child and adolescent patients is available. We herein review recent findings obtained using NIRS measurements of the brain during cognitive tasks in neurodevelopmental disorders, such as autism spectrum disorder, attention‐deficit/hyperactivity disorder, obsessive–compulsive disorder, and Tourette's disorder. This will facilitate evaluations of the causation and treatment of prefrontal cortex dysfunctions.
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
We present the methodology for the intraoperative identification of resting state networks using RGB imaging. The results show a good correlation between the resting state and the brain areas identified by electrical brain stimulation.
Diffuse optical tomography (DOT), based on functional near-infrared spectroscopy, is a portable, low-cost, noninvasive functional neuroimaging technology for studying the human brain in normal and diseased conditions. The goal of the present study was to evaluate the performance of a cap-based brain-wide DOT (BW-DOT) framework in mapping brain-wide networked activities. We first analyzed point-spread-function (PSF)-based metrics on a realistic head geometry. Our simulation results indicated that these metrics of the optode cap varied across the brain and were of lower quality in brain areas deep or away from the optodes. We further reconstructed brain-wide resting-state networks using experimental data from healthy participants, which resembled the template networks established in the fMRI literature. The preliminary results of the present study highlight the importance of evaluating PSF-based metrics on realistic head geometries for DOT and suggest that BW-DOT technology is a promising functional neuroimaging tool for studying brain-wide neural activities and large-scale neural networks, which was not available by patch-based DOT. A full-scope evaluation and validation in more realistic head models and more participants are needed in the future to establish the findings of the present study further.Clinical relevance- Via simulations and experimental evaluation, this work establishes a novel framework to image large-scale brain networks, which benefits the patient population, such as bedridden patients, infants, etc., who otherwise cannot undergo conventional brain monitoring modalities like fMRI and PET.
Objective:
Diffuse optical tomography (DOT) has the potential in reconstructing resting-state networks (RSNs) in human brains with high spatio-temporal resolutions and multiple contrasts. While several RSNs have been reported and successfully reconstructed using DOT, its full potential in recovering a collective set of distributed brain-wide networks with the number of RSNs close to those reported using functional magnetic resonance imaging (fMRI) has not been demonstrated.
Approach:
The present study developed a novel brain-wide DOT (BW-DOT) framework that integrates a cap-based whole-head optode placement system with multiple computational approaches, i.e., finite-element modeling, inverse source reconstruction, data-driven pattern recognition, and statistical correlation tomography, to reconstruct RSNs in dual contrasts of oxygenated (HbO) and deoxygenated hemoglobins (HbR).
Main results:
Our results from the proposed framework revealed a comprehensive set of RSNs and their subnetworks, which collectively cover almost the entire neocortical surface of the human brain, both at the group level and individual participants. The spatial patterns of these DOT RSNs suggest statistically significant similarities to fMRI RSN templates. Our results also reported the networks involving the medial prefrontal cortex and precuneus that had been missed in previous DOT studies. Furthermore, RSNs obtained from HbO and HbR suggest similarity in terms of both the number of RSN types reconstructed and their corresponding spatial patterns, while HbR RSNs show statistically more similarity to fMRI RSN templates and HbO RSNs indicate more bilateral patterns over two hemispheres. In addition, the BW-DOT framework allowed consistent reconstructions of RSNs across individuals and across recording sessions, indicating its high robustness and reproducibility, respectively.
Significance:
Our present results suggest the feasibility of using the brain-wide DOT, as a neuroimaging tool, in simultaneously mapping multiple RSNs and its potential values in studying RSNs, particularly in patient populations under diverse conditions and needs, due to its advantages in accessibility over fMRI.
The proper development of sleep and sleep-wake rhythms during early neonatal life is crucial to lifelong neurological well-being. Recent data suggests that infants who have poor quality sleep demonstrate a risk for impaired neurocognitive outcomes. Sleep ontogenesis is a complex process, whereby alternations between rudimentary brain states—active vs. wake and active sleep vs. quiet sleep—mature during the last trimester of pregnancy. If the infant is born preterm, much of this process occurs in the neonatal intensive care unit, where environmental conditions might interfere with sleep. Functional brain connectivity (FC), which reflects the brain’s ability to process and integrate information, may become impaired, with ensuing risks of compromised neurodevelopment. However, the specific mechanisms linking sleep ontogenesis to the emergence of FC are poorly understood and have received little investigation, mainly due to the challenges of studying causal links between developmental phenomena and assessing FC in newborn infants. Recent advancements in infant neuromonitoring and neuroimaging strategies will allow for the design of interventions to improve infant sleep quality and quantity. This review discusses how sleep and FC develop in early life, the dynamic relationship between sleep, preterm birth, and FC, and the challenges associated with understanding these processes.
Sleep in early life is essential for proper functional brain development, which is essential for the brain to integrate and process information. This process may be impaired in infants born preterm.
The connection between preterm birth, early development of brain functional connectivity, and sleep is poorly understood.
This review discusses how sleep and brain functional connectivity develop in early life, how these processes might become impaired, and the challenges associated with understanding these processes. Potential solutions to these challenges are presented to provide direction for future research.
Functional near-infrared spectroscopy (fNIRS) is a method of monitoring brain oxygenation. This technique investigates hemodynamic changes in the cerebral cortex. fNIRS is widely used in clinical and scientific research. In this review, we focus on the applications of fNIRS on neonates. Here, applications form two distinct categories: task associated studies, and hemoglobin phase change studies. fNIRS is non-invasive, easily performed, and repeatable. However, it has limited monitoring depth and spatial resolution when used in newborns. Moreover, with recent technological advances, it is now possible to explore neuronal activity patterns using fNIRS in both healthy and pathological conditions. For more than 20 years, fNIRS has enabled clinicians to gain insight into cerebral development and mechanisms of injury in neonates. fNIRS is a useful supplement to existing technologies due to its ability to interrogate the neonatal brain function.
Optical neuromonitoring provides insight into neurovascular physiology and brain structure and function. These methods rely on spectroscopy to relate light absorption changes to variation of concentrations of physiologic chromophores such as oxy- and deoxyhemoglobin. In clinical or preclinical practice, data quality can vary significantly across wavelengths. In such situations, standard spectroscopic methods may perform poorly, resulting in data loss and limiting field-of-view. To address this issue, and thereby improve the robustness of optical neuromonitoring, we develop, in this manuscript, novel methods to perform spectroscopy even when data quality exhibits wavelength-dependent spatial variation. We sought to understand the impact of spatial, wavelength-based censoring on the physiologic accuracy and utility of hemoglobin spectroscopy. The principles of our analysis are quite general, but to make the methodology tangible we focused on optical intrinsic signal imaging of resting-state functional connectivity in mice. Starting with spectroscopy using four sources, all possible subset spectroscopy matrices were assessed theoretically, using simulated data, and using experimental data. These results were compared against the use of the full spectroscopy matrix to determine which subsets yielded robust results. Our results demonstrated that accurate calculation of changes in hemoglobin concentrations and the resulting functional connectivity network maps was possible even with censoring of some wavelengths. Additionally, we found that the use of changes in total hemoglobin (rather than oxy- or deoxyhemoglobin) yielded results more robust to experimental noise and allowed for the preservation of more data. This new and rigorous image processing method should improve the fidelity of clinical and preclinical functional neuroimaging studies.
We adapted and tested an innovative noncontact speckle contrast diffuse correlation tomography (scDCT) system for 3D imaging of cerebral blood flow (CBF) variations in perinatal disease models utilizing neonatal piglets, which closely resemble human neonates. CBF variations were concurrently measured by the scDCT and an established diffuse correlation spectroscopy (DCS) during global ischemia, intraventricular hemorrhage, and asphyxia; significant correlations were observed. Moreover, CBF variations associated reasonably with vital pathophysiological changes. In contrast to DCS measurements of mixed signals from local scalp, skull and brain, scDCT generates 3D images of CBF distributions at prescribed depths within the head, thus enabling specific determination of regional cerebral ischemia. With further optimization and validation in animals and human neonates, scDCT has the potential to be a noninvasive imaging tool for both basic neuroscience research in laboratories and clinical applications in neonatal intensive care units.
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Significance: Attention-deficit/hyperactivity disorder (ADHD) is the most common psychologi- cal disease in childhood. Currently, widely used neuroimaging techniques require complete body confinement and motionlessness and thus are extremely hard for brain scanning of ADHD children.
Aim: We present resting-state functional near-infrared spectroscopy (fNIRS) as an imaging tech- nique to record spontaneous brain activity in children with ADHD.
Approach: The brain functional connectivity was calculated, and the graph theoretical analysis was further applied to investigate alterations in the global and regional properties of the brain network in the patients. In addition, the relationship between brain network features and core symptoms was examined.
Results: ADHD patients exhibited significant decreases in both functional connectivity and global network efficiency. Meanwhile, the nodal efficiency in children with ADHD was also found to be altered, e.g., increase in the visual and dorsal attention networks and decrease in somatomotor and default mode networks, compared to the healthy controls. More importantly, the disrupted functional connectivity and nodal efficiency significantly correlated with dimen- sional ADHD scores.
Conclusions: We clearly demonstrate the feasibility and potential of fNIRS-based connectome technique in ADHD or other neurological diseases in the future.
Brain injury sustained during the neonatal period may disrupt development of critical structural and functional connectivity networks leading to subsequent neurodevelopmental impairment in affected children. These networks can be characterized using structural (via diffusion MRI) and functional (via resting state-functional MRI) neuroimaging techniques. Advances in neuroimaging have led to expanded application of these approaches to study term- and prematurely-born infants, providing improved understanding of cerebral development and the deleterious effects of early brain injury. Across both modalities, neuroimaging data are conducive to analyses ranging from characterization of individual white matter tracts and/or resting state networks through advanced 'connectome-style' approaches identifying highly connected network hubs and investigating metrics of network topology such as modularity and small-worldness. We begin this review by summarizing the literature detailing structural and functional connectivity findings in healthy term and preterm infants without brain injury during the postnatal period, including discussion of early connectome development. We then detail common forms of brain injury in term- and prematurely-born infants. In this context, we next review the emerging body of literature detailing studies employing diffusion MRI, resting state-functional MRI and other complementary neuroimaging modalities to characterize structural and functional connectivity development in infants with brain injury. We conclude by reviewing technical challenges associated with neonatal neuroimaging, highlighting those most relevant to studying infants with brain injury and emphasizing the need for further targeted study in this high-risk population.
A variety of specialized studies are available for evaluating the nervous system of the newborn. In this chapter, we review several commonly used tests: cerebrospinal fluid examination, evoked responses (with emphasis on auditory evoked responses), electroencephalography (EEG), cranial ultrasound, and magnetic resonance imaging (MRI). We also touch on some tests that are not yet in common clinical use: near-infrared spectroscopy and magnetoencephalography. The discussion of EEG includes a description of the changes in EEG associated with early brain development and a brief review of amplitude-integrated EEG. The discussion of MRI covers conventional structural imaging (including diffusion imaging) as well as spectroscopy and functional imaging. Overall, we focus on the adaptations necessary to optimize these tests for infants. We also describe the characteristics and nuances relevant to their effective clinical use. The application of most of these tests for diagnostic purposes is mentioned in various other chapters of this book.
Brain activity is associated with changes in optical properties of brain tissue. Optical measurements during brain activation can assess haemoglobin oxygenation, cytochrome-c-oxidase redox state, and two types of changes in light scattering reflecting either membrane potential (fast signal) or cell swelling (slow signal), respectively. In previous studies of exposed brain tissue, optical imaging of brain activity has been achieved at high temporal and microscopical spatial resolution. Now, using near-infrared light that can penetrate biological tissue reasonably well, it has become possible to assess brain activity in human subjects through the intact skull non-invasively. After early studies employing single-site near-infrared spectroscopy, first near-infrared imaging devices are being applied successfully for low-resolution functional brain imaging. Advantages of the optical methods include biochemical specificity, a temporal resolution in the millisecond range, the potential of measuring intracellular and intravascular events simultaneously and the portability of the devices enabling bedside examinations.
Diffuse optical tomography (DOT) is a non-invasive brain imaging technique that uses low-levels of near-infrared light to measure optical absorption changes due to regional blood flow and blood oxygen saturation in the brain. By arranging light sources and detectors in a grid over the surface of the scalp, DOT studies attempt to spatially localize changes in oxy- and deoxy-hemoglobin in the brain that result from evoked brain activity during functional experiments. However, the reconstruction of accurate spatial images of hemoglobin changes from DOT data is an ill-posed linearized inverse problem, which requires model regularization to yield appropriate solutions. In this work, we describe and demonstrate the application of a parametric restricted maximum likelihood method (ReML) to incorporate multiple statistical priors into the recovery of optical images. This work is based on similar methods that have been applied to the inverse problem for magnetoencephalography (MEG). Herein, we discuss the adaptation of this model to DOT and demonstrate that this approach provides a means to objectively incorporate reconstruction constraints and demonstrate this approach through a series of simulated numerical examples.
The functions of the resting state networks (RSNs) revealed by functional MRI remain unclear, but it has seemed possible that networks emerge in parallel with the development of related cognitive functions. We tested the alternative hypothesis: that the full repertoire of resting state dynamics emerges during the period of rapid neural growth before the normal time of birth at term (around 40 wk of gestation). We used a series of independent analytical techniques to map in detail the development of different networks in 70 infants born between 29 and 43 wk of postmenstrual age (PMA). We characterized and charted the development of RSNs from recognizable but often fragmentary elements at 30 wk of PMA to full facsimiles of adult patterns at term. Visual, auditory, somatosensory, motor, default mode, frontoparietal, and executive control networks developed at different rates; however, by term, complete networks were present, several of which were integrated with thalamic activity. These results place the emergence of RSNs largely during the period of rapid neural growth in the third trimester of gestation, suggesting that they are formed before the acquisition of cognitive competencies in later childhood.
Aerobic glycolysis is defined as glucose utilization in excess of that used for oxidative phosphorylation despite sufficient oxygen to completely metabolize glucose to carbon dioxide and water. Aerobic glycolysis is present in the normal human brain at rest and increases locally during increased neuronal activity; yet its many biological functions have received scant attention because of a prevailing energy-centric focus on the role of glucose as substrate for oxidative phosphorylation. As an initial step in redressing this neglect, we measured the regional distribution of aerobic glycolysis with positron emission tomography in 33 neurologically normal young adults at rest. We show that the distribution of aerobic glycolysis in the brain is differentially present in previously well-described functional areas. In particular, aerobic glycolysis is significantly elevated in medial and lateral parietal and prefrontal cortices. In contrast, the cerebellum and medial temporal lobes have levels of aerobic glycolysis significantly below the brain mean. The levels of aerobic glycolysis are not strictly related to the levels of brain energy metabolism. For example, sensory cortices exhibit high metabolic rates for glucose and oxygen consumption but low rates of aerobic glycolysis. These striking regional variations in aerobic glycolysis in the normal human brain provide an opportunity to explore how brain systems differentially use the diverse cell biology of glucose in support of their functional specializations in health and disease.
Functional near infrared spectroscopy (fNIRS) is a portable monitor of cerebral hemodynamics with wide clinical potential. However, in fNIRS, the vascular signal from the brain is often obscured by vascular signals present in the scalp and skull. In this paper, we evaluate two methods for improving in vivo data from adult human subjects through the use of high-density diffuse optical tomography (DOT). First, we test whether we can extend superficial regression methods (which utilize the multiple source-detector pair separations) from sparse optode arrays to application with DOT imaging arrays. In order to accomplish this goal, we modify the method to remove physiological artifacts from deeper sampling channels using an average of shallow measurements. Second, DOT provides three-dimensional image reconstructions and should explicitly separate different tissue layers. We test whether DOT's depth-sectioning can completely remove superficial physiological artifacts. Herein, we assess improvements in signal quality and reproducibility due to these methods using a well-characterized visual paradigm and our high-density DOT system. Both approaches remove noise from the data, resulting in cleaner imaging and more consistent hemodynamic responses. Additionally, the two methods act synergistically, with greater improvements when the approaches are used together.
Preterm birth is associated with variable degrees of brain injury and adverse neurodevelopmental outcomes. Neuroimaging has been investigated as a predictor of outcome in this population. Head ultrasound allows for rapid bedside evaluation of the neonatal brain for early intraventricular hemorrhage surveillance and later detection of periventricular leukomalacia. Computed tomography can provide excellent views for bones, hemorrhage, extra-axial space, and the ventricles but is rarely used for prognostic purposes. Magnetic resonance imaging allows for high-resolution images of brain structures, differentiation of white and gray matter, visualization of the brain stem and posterior fossa, and getting additional physiological information with specialized sequences. Though controversial, the use of magnetic resonance imaging, at term equivalent, as a predictor of later outcome in preterm infants has been increasing and has been advocated by some as a standard practice. In this article, we review and contrast the use of these various imaging modalities in predicting neurodevelopmental outcome of premature infants.
The neurodevelopmental outcome of neonatal intensive care unit (NICU) infants is a major clinical concern with many infants displaying neurobehavioral deficits in childhood. Functional neuroimaging may provide early recognition of neural deficits in high-risk infants. Near-infrared spectroscopy (NIRS) has the advantage of providing functional neuroimaging in infants at the bedside. However, limitations in traditional NIRS have included contamination from superficial vascular dynamics in the scalp. Furthermore, controversy exists over the nature of normal vascular, responses in infants. To address these issues, we extend the use of novel high-density NIRS arrays with multiple source-detector distances and a superficial signal regression technique to infants. Evaluations of healthy term-born infants within the first three days of life are performed without sedation using a visual stimulus. We find that the regression technique significantly improves brain activation signal quality. Furthermore, in six out of eight infants, both oxy- and total hemoglobin increases while deoxyhemoglobin decreases, suggesting that, at term, the neurovascular coupling in the visual cortex is similar to that found in healthy adults. These results demonstrate the feasibility of using high-density NIRS arrays in infants to improve signal quality through superficial signal regression, and provide a foundation for further development of high-density NIRS as a clinical tool.
Despite the unique brain imaging capabilities and advantages of functional near-infrared spectroscopy (fNIRS), including portability and comprehensive hemodynamic measurement, widespread acceptance in the neuroimaging community has been hampered by low spatial resolution and image localization errors. While recent technical developments such as high-density diffuse optical tomography (HD-DOT) have, in principle, been shown to have superior in silico image quality, the majority of optical imaging studies are still conducted with sparse fNIRS arrays, perhaps partially because the performance increases of HD-DOT appear incremental. Without a quantitative comparative analysis between HD-DOT and fNIRS, using both simulation and in vivo neuroimaging, the implications of the new HD-DOT technology have been difficult to judge. We present a quantitative comparison of HD-DOT and two commonly used fNIRS geometries using (1) standard metrics of image quality, (2) simulated brain mapping tasks, and (3) in vivo visual cortex mapping results in adult humans. The results show that better resolution and lower positional errors are achieved with HD-DOT and that these improvements provide a substantial advancement in neuroimaging capability. In particular, we demonstrate that HD-DOT enables detailed phase-encoded retinotopic mapping, while sparse arrays are limited to imaging individual block-design visual stimuli.
Functional magnetic resonance imaging (fMRI) research often attributes blood oxygen level-dependent (BOLD) signal variance to measurement-related confounds. However, what is typically considered "noise" variance in data may be a vital feature of brain function. We examined fMRI signal variability during fixation baseline periods, and then compared SD- and mean-based spatial patterns and their relations with chronological age (20-85 years). We found that not only was the SD-based pattern robust, it differed greatly, both spatially and statistically, from the mean-based pattern. Notably, the unique age-predictive power of the SD-based pattern was more than five times that of the mean-based pattern. This reliable SD-based pattern of activity highlights an important "signal" within what is often considered measurement-related "noise." We suggest that examination of BOLD signal variability may reveal a host of novel brain-related effects not previously considered in neuroimaging research.
Human cognition and behaviors are subserved by global networks of neural mechanisms. Although the organization of the brain is a subject of interest, the process of development of global cortical networks in early infancy has not yet been clarified. In the present study, we explored developmental changes in these networks from several days to 6 months after birth by examining spontaneous fluctuations in brain activity, using multichannel near-infrared spectroscopy. We set up 94 measurement channels over the frontal, temporal, parietal, and occipital regions of the infant brain. The obtained signals showed complex time-series properties, which were characterized as 1/f fluctuations. To reveal the functional connectivity of the cortical networks, we calculated the temporal correlations of continuous signals between all the pairs of measurement channels. We found that the cortical network organization showed regional dependency and dynamic changes in the course of development. In the temporal, parietal, and occipital regions, connectivity increased between homologous regions in the two hemispheres and within hemispheres; in the frontal regions, it decreased progressively. Frontoposterior connectivity changed to a "U-shaped" pattern within 6 months: it decreases from the neonatal period to the age of 3 months and increases from the age of 3 months to the age of 6 months. We applied cluster analyses to the correlation coefficients and showed that the bilateral organization of the networks begins to emerge during the first 3 months of life. Our findings suggest that these developing networks, which form multiple clusters, are precursors of the functional cerebral architecture.
We assessed the effects of very preterm birth (gestational age <32 weeks or birth weight <1501 g) and prematurity-related morbidities on health care costs during the fifth year of life.
The study population consisted of 588 very preterm children and 176 term control subjects born in 2001-2002. Costs of hospitalizations, visits to health care professionals and therapists, and the use of other social welfare services were assessed during the fifth year of life. Hospital visits were derived from register data and other health care contacts, and the use of social welfare services were derived from parental reports. The effects of 6 prematurity-related morbidities (cerebral palsy [CP], seizure disorder, obstructive airway disease, hearing loss, visual disturbances or blindness, and other ophthalmologic problems) on the costs of health care were studied.
The average health care costs during the fifth year of life were 749 euro in the term control subjects, 1023 euro in the very preterm children without morbidities, and 3265 euro in those with morbidities. The costs of social welfare services and therapies exceeded the hospitalization costs in all groups. Among children who were born preterm, CP was associated with 5125 euro higher costs, whereas later obstructive airway diseases increased the costs by 819 euro compared with individuals without these morbidities.
The health care costs during the fifth year of life in very preterm children with morbidities were 4.4-fold and in those without morbidities 1.4-fold compared with those of term control subjects. This emphasizes the importance of prevention of morbidities, especially CP, to reduce the long-term costs of prematurity.
Approximately 15 years ago we reported that cytochrome c oxidase (CcO) was persistently inhibited as a consequence of endogenous induction and activation of nitric oxide ((*)NO) synthase-2 (NOS2) in astrocytes. Furthermore, the reactive nitrogen species implicated was peroxynitrite. In contrast to the reversible inhibition by (*)NO, which occurs rapidly, in competition with O(2), and has signaling regulatory implications, the irreversible CcO damage by peroxynitrite is progressive in nature and follows and/or is accompanied by damage to other key mitochondrial bioenergetic targets. In purified CcO it has been reported that the irreversible inhibition occurs through a mechanism involving damage of the heme a(3)-Cu(B) binuclear center leading to an increase in the K(m) for oxygen. Astrocyte survival, as a consequence of peroxynitrite exposure, is preserved due to their robust bioenergetic and antioxidant defense mechanisms. However, by releasing peroxynitrite to the neighboring neurons, whose antioxidant defense can, under certain conditions, be fragile, activated astrocytes trigger bioenergetic stress leading to neuronal cell death. Thus, such irreversible inhibition of CcO by peroxynitrite may be a plausible mechanism for the neuronal death associated with neurodegenerative diseases, in which the activation of astrocytes plays a crucial role.
We have established a population average surface-based atlas of human cerebral cortex at term gestation and used it to compare infant and adult cortical shape characteristics. Accurate cortical surface reconstructions for each hemisphere of 12 healthy term gestation infants were generated from structural magnetic resonance imaging data using a novel segmentation algorithm. Each surface was inflated, flattened, mapped to a standard spherical configuration, and registered to a target atlas sphere that reflected shape characteristics of all 24 contributing hemispheres using landmark constrained surface registration. Population average maps of sulcal depth, depth variability, three-dimensional positional variability, and hemispheric depth asymmetry were generated and compared with previously established maps of adult cortex. We found that cortical structure in term infants is similar to the adult in many respects, including the pattern of individual variability and the presence of statistically significant structural asymmetries in lateral temporal cortex, including the planum temporale and superior temporal sulcus. These results indicate that several features of cortical shape are minimally influenced by the postnatal environment.
Recently, resting state functional connectivity (RSFC) studies based on fMRI and EEG/MEG have provided valuable insight into the intrinsic functional architecture of the human brain. However, whether functional near infrared spectroscopy (fNIRS), a suitable imaging method for infant and patient populations, can be used to examine RSFC remains elusive. Using an ETG-4000 Optical Topography System, the present study measured 29 adult subjects (14 females) over the sensorimotor and auditory cortexes during a resting session and a motor-localizer task session. The RSFC maps were computed by seed-based correlation analysis and data-driven cluster analysis. The results from both analyses showed robust RSFC maps, which were not only consistent with the localizer task-related activation results, but also those of previous fMRI findings. Moreover, the strong consistency between the seed-based correlation analysis and the data-driven cluster analysis further validated the use of fNIRS to assess RSFC. The potential influence of a specific low-frequency filtering range (0.04-0.15 Hz and 0.01-0.08 Hz) and three fNIRS parameters (oxy-Hb, deoxy-Hb, and total-Hb) on RSFC results were also examined.
Camera-based optical imaging of the exposed brain allows cortical hemodynamic responses to stimulation to be examined. Typical multispectral imaging systems utilize a camera and illumination at several wavelengths, allowing discrimination between changes in oxy- and deoxyhemoglobin concentration. However, most multispectral imaging systems utilize white light sources and mechanical filter wheels to multiplex illumination wavelengths, which are slow and difficult to synchronize at high frame rates. We present a new LED-based system capable of high-resolution multispectral imaging at frame rates exceeding 220 Hz. This improved performance enables simultaneous visualization of hemoglobin oxygenation dynamics within single vessels, changes in vessel diameters, blood flow dynamics from the motion of erythrocytes, and dynamically changing fluorescence.
Diffuse optical imaging is an emerging medical imaging modality based on near-infrared and visible red light. The method can be used for imaging activations in the human brain. In this study, a deformable probabilistic atlas of the distribution of tissue types within the term neonatal head was created based on MR images. The use of anatomical prior information provided by such atlas in reconstructing brain activations from optical imaging measurements was studied using Monte Carlo simulations. The results suggest that use of generic anatomical information can greatly improve the spatial accuracy and robustness of the reconstruction when noise is present in the data.
With the causes of perinatal brain injuries still unclear and the probable role of hemodynamic instability in their etiology, bedside monitoring of neonatal cerebral hemodynamics with standard values as a function of age are needed. In this study, we combined quantitative frequency domain near infrared spectroscopy (FD-NIRS) measures of cerebral tissue oxygenation (StO(2)) and cerebral blood volume (CBV) with diffusion correlation spectroscopy (DCS) measures of a cerebral blood flow index (CBF(ix)) to test the validity of the CBV-CBF relationship in premature neonates and to estimate cerebral metabolic rate of oxygen (rCMRO(2)) with or without the CBF(ix) measurement. We measured 11 premature neonates (28-34 weeks gestational age) without known neurological issues, once a week from one to six weeks of age. In nine patients, cerebral blood velocities from the middle cerebral artery were collected by transcranial Doppler (TCD) and compared with DCS values. Results show a steady decrease in StO(2) during the first six weeks of life while CBV remains stable, and a steady increase in CBF(ix). rCMRO(2) estimated from FD-NIRS remains constant but shows wide interindividual variability. rCMRO(2) calculated from FD-NIRS and DCS combined increased by 40% during the first six weeks of life with reduced interindividual variability. TCD and DCS values are positively correlated. In conclusion, FD-NIRS combined with DCS offers a safe and quantitative bedside method to assess CBV, StO(2), CBF, and rCMRO(2) in the premature brain, facilitating individual follow-up and comparison among patients. A stable CBV-CBF relationship may not be valid for premature neonates.
Resting-state data sets contain coherent fluctuations unrelated to neural processes originating from residual motion artefacts, respiration and cardiac action. Such confounding effects may introduce correlations and cause an overestimation of functional connectivity strengths. In this study we applied several multidimensional linear regression approaches to remove artificial coherencies and examined the impact of preprocessing on sensitivity and specificity of functional connectivity results in simulated data and resting-state data sets from 40 subjects. Furthermore, we aimed at clarifying possible causes of anticorrelations and test the hypothesis that anticorrelations are introduced via certain preprocessing approaches, with particular focus on the effects of regression against the global signal. Our results show that preprocessing in general greatly increased connection specificity, in particular correction for global signal fluctuations almost doubled connection specificity. However, widespread anticorrelated networks were only found when regression against the global signal was applied. Results in simulated data sets compared with result of human data strongly suggest that anticorrelations are indeed introduced by global signal regression and should therefore be interpreted very carefully. In addition, global signal regression may also reduce the sensitivity for detecting true correlations, i.e. increase the number of false negatives. Concluding from our results we suggest that is highly recommended to apply correction against realignment parameters, white matter and ventricular time courses, as well as the global signal to maximize the specificity of positive resting-state correlations.
We report on the first three-dimensional, volumetric, tomographic localization of vascular reactivity in the brain. To this end we developed a model-based iterative image reconstruction scheme that employs adjoint differentiation methods to minimize the difference between measured and predicted data. The necessary human-head geometry and optode locations were determined with a photogrammetric method. To illustrate the performance of the technique, the three-dimensional distribution of changes in the concentration of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin during a Valsalva maneuver were visualized. The observed results are consistent with previously reported effects concerning optical responses to hemodynamic perturbations.
Resting state studies of spontaneous fluctuations in the functional MRI (fMRI) blood oxygen level dependent (BOLD) signal have shown great promise in mapping the brain's intrinsic, large-scale functional architecture. An important data preprocessing step used to enhance the quality of these observations has been removal of spontaneous BOLD fluctuations common to the whole brain (the so-called global signal). One reproducible consequence of global signal removal has been the finding that spontaneous BOLD fluctuations in the default mode network and an extended dorsal attention system are consistently anticorrelated, a relationship that these two systems exhibit during task performance. The dependence of these resting-state anticorrelations on global signal removal has raised important questions regarding the nature of the global signal, the validity of global signal removal, and the appropriate interpretation of observed anticorrelated brain networks. In this study, we investigate several properties of the global signal and find that it is, indeed, global, not residing preferentially in systems exhibiting anticorrelations. We detail the influence of global signal removal on resting state correlation maps both mathematically and empirically, showing an enhancement in detection of system-specific correlations and improvement in the correspondence between resting-state correlations and anatomy. Finally, we show that several characteristics of anticorrelated networks including their spatial distribution, cross-subject consistency, presence with modified whole brain masks, and existence before global regression are not attributable to global signal removal and therefore suggest a biological basis.
Neurodevelopmental outcomes associated with preterm birth are of major health and educational concern. This study examined the neuromotor, cognitive, language and emotional/behavioural outcomes of a regional cohort of 4-year-old children born extremely preterm (EPT: 23-27 weeks' gestation), very preterm (VPT: 28-33 weeks) and full term (FT: 38-41 weeks). Of particular interest were children's risks of impairment across multiple neurodevelopmental domains.
Data were gathered as part of a prospective longitudinal study of 105 very preterm (< or = 33 weeks gestation) and 107 FT children born during 1998-2000. At 4 years corrected age, children underwent a comprehensive multidisciplinary assessment that included a paediatric neurological examination, cognitive and language testing, and an assessment of child emotional and behavioural adjustment.
At age 4 years, compared to FT children, EPT and VPT children had increased risks of cerebral palsy (EPT 18%, VPT 15%, FT 1%), cognitive delay (EPT 33%, VPT 36%, FT 13%), language delay (EPT 29%, VPT 29%, FT 10%) and emotional/behavioural adjustment problems (EPT 37%, VPT 13%, FT 11%). EPT and VPT children were three times more likely to have multiple domain impairments than FT children (EPT 30%, VPT 29%, FT 10%).
A substantial proportion of preschool children born very preterm show clinically significant problems in at least one neurodevelopmental domain, with impairment in multiple domains being common. There is a need to monitor preschool development across a range of functional domains and to consider the likely cascading effects of multiple impairments on later development.
Descent into sleep is accompanied by disengagement of the conscious brain from the external world. It follows that this process should be associated with reduced neural activity in regions of the brain known to mediate interaction with the environment. We examined blood oxygen dependent (BOLD) signal functional connectivity using conventional seed-based analyses in 3 primary sensory and 3 association networks as normal young adults transitioned from wakefulness to light sleep while lying immobile in the bore of a magnetic resonance imaging scanner. Functional connectivity was maintained in each network throughout all examined states of arousal. Indeed, correlations within the dorsal attention network modestly but significantly increased during light sleep compared to wakefulness. Moreover, our data suggest that neuronally mediated BOLD signal variance generally increases in light sleep. These results do not support the view that ongoing BOLD fluctuations primarily reflect unconstrained cognition. Rather, accumulating evidence supports the hypothesis that spontaneous BOLD fluctuations reflect processes that maintain the integrity of functional systems in the brain.
Unlike conventional functional MR imaging where external sensory/cognitive paradigms are needed to specifically activate different regions of the brain, resting functional connectivity MR imaging acquires images in the absence of cognitive demands (a resting condition) and detects brain regions, which are highly temporally correlated. Therefore, resting functional MR imaging is highly suited for the study of brain functional development in pediatric subjects. This study aimed to determine the temporal and spatial patterns of rfc in healthy pediatric subjects between 2 weeks and 2 years of age.
Rfc studies were performed on 85 children: 38 neonates (2-4 weeks of age), 26 one-year-olds, and 21 two-year-olds. All subjects were imaged while asleep; no sedation was used. Six regions of interest were chosen, including the primary motor, sensory, and visual cortices in each hemisphere. Mean signal intensity of each region of interest was used to perform correlation analysis pixel by pixel throughout the entire brain, identifying regions with high temporal correlation.
Functional connectivity was observed in all subjects in the sensorimotor and visual areas. The percent brain volume exhibiting rfc and the strength of rfc continued to increase from 2 weeks to 2 years. The growth trajectories of the percent brain volume of rfc appeared to differ between the sensorimotor and visual areas, whereas the z-score was similar. The percent brain volume of rfc in the sensorimotor area was significantly larger than that in the visual area for subjects 2 weeks of age (P = .008) and 1-year-olds (P = .017) but not for the 2-year-olds.
These findings suggest that rfc in the sensorimotor precedes that in the visual area from 2 weeks to 1 year but becomes comparable at 2 years. In contrast, the comparable z-score values between the sensorimotor and visual areas for all age groups suggest a disassociation between percent brain volume and the strength of cortical rfc.
The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.
For the first time, three-dimensional images of the newborn infant brain have been generated using measurements of transmitted light. A 32-channel time-resolved imaging system was employed, and data were acquired using custom-made helmets which couple source fibres and detector bundles to the infant head. Images have been reconstructed using measurements of mean flight time relative to those acquired on a homogeneous reference phantom, and using a head-shaped 3D finite-element-based forward model with an external boundary constrained to match the measured positions of the sources and detectors. Results are presented for a premature infant with a cerebral haemorrhage predominantly located within the left ventricle. Images representing the distribution of absorption at 780 nm and 815 nm reveal an asymmetry consistent with the haemorrhage, and corresponding maps of blood volume and fractional oxygen saturation are generally within expected physiological values.
Near-infrared (NIR) optical tomography provide estimates of the internal distribution of optical absorption and transport scattering from boundary measurement of light propagation within biological tissue. Although this is a truly three-dimensional (3D) imaging problem, most research to date has concentrated on two-dimensional modeling and image reconstruction. More recently, 3D imaging algorithms are demonstrating better estimation of the light propagation within the imaging region and are providing the basis of more accurate image construction algorithms. As 3D methods emerge, it will become increasingly important to evaluate their resolution, contrast, and localization of optical property heterogeneity. We present a concise study of 3D reconstructed resolution of a small, low-contrast, absorbing and scattering anomaly as it is placed in different locations within a cylindrical phantom. The object is an 8-mm-diameter cylinder, which represents a typical small target that needs to be resolved in NIR mammographic imaging. The best resolution and contrast is observed when the object is located near the periphery of the imaging region (12-22 mm from the edge) and is also positioned within the multiple measurement planes, with the most accurate results seen for the scatter image when the anomaly is at 17 mm from the edge. Furthermore, the accuracy of quantitative imaging is increased to almost 100% of the target values when a priori information regarding the internal structure of imaging domain is utilized.
The time courses of oxyhaemoglobin ([HbO2]), deoxyhaemoglobin ([HbR]) and total haemoglobin ([HbT]) concentration changes following cortical activation in rats by electrical forepaw stimulation were measured using diffuse optical tomography (DOT) and compared to similar measurements performed previously with fMRI at 2.0 T and 4.7 T. We also explored the qualitative effects of varying stimulus parameters on the temporal evolution of the hemodynamic response. DOT images were reconstructed at a depth of 1.5 mm over a 1 cm square area from 2 mm anterior to bregma to 8 mm posterior to bregma. The measurement set included 9 sources and 16 detectors with an imaging frame rate of 10 Hz. Both DOT [HbR] and [HbO2] time courses were compared to the fMRI BOLD time course during stimulation, and the DOT [HbT] time course was compared to the fMRI cerebral plasma volume (CPV) time course. We believe that DOT and fMRI can provide similar temporal information for both blood volume and deoxyhaemoglobin changes, which helps to cross-validate these two techniques and to demonstrate that DOT can be useful as a complementary modality to fMRI for investigating the hemodynamic response to neuronal activity.
We present a review of methods for the forward and inverse problems in optical tomography. We limit ourselves to the highly scattering case found in applications in medical imaging, and to the problem of absorption and scattering reconstruction. We discuss the derivation of the diffusion approximation and other simplifications of the full transport problem. We develop sensitivity relations in both the continuous and discrete case with special concentration on the use of the finite element method. A classification of algorithms is presented, and some suggestions for open problems to be addressed in future research are made.
An MRI time course of 512 echo-planar images (EPI) in resting human brain obtained every 250 ms reveals fluctuations in signal intensity in each pixel that have a physiologic origin. Regions of the sensorimotor cortex that were activated secondary to hand movement were identified using functional MRI methodology (FMRI). Time courses of low frequency (<0.1 Hz) fluctuations in resting brain were observed to have a high degree of temporal correlation (P < 10−3) within these regions and also with time courses in several other regions that can be associated with motor function. It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.
A time-resolved imaging system has been used to perform optical tomography on premature infants. The technique is being developed as a means of generating three-dimensional images of cerebral oxygenation, haemodynamics and metabolism at the bedside.
We describe a neuroimaging protocol that utilizes an anatomical atlas of the human head to guide diffuse optical tomography of human brain activation. The protocol is demonstrated by imaging the hemodynamic response to median-nerve stimulation in three healthy subjects, and comparing the images obtained using a head atlas with the images obtained using the subject-specific head anatomy. The results indicate that using the head atlas anatomy it is possible to reconstruct the location of the brain activation to the expected gyrus of the brain, in agreement with the results obtained with the subject-specific head anatomy. The benefits of this novel method derive from eliminating the need for subject-specific head anatomy and thus obviating the need for a subject-specific MRI to improve the anatomical interpretation of diffuse optical tomography images of brain activation.
The premise of this report is that functional Near Infrared Spectroscopy (fNIRS) imaging data contain valuable physiological information that can be extracted by using analysis techniques that simultaneously consider the components of the measured hemodynamic response [i.e., levels of oxygenated, deoxygenated and total hemoglobin (oxyHb, deoxyHb and totalHb, respectively)]. We present an algorithm for examining the spatiotemporal co-variations among the Hb components, and apply it to the data obtained from a demonstrational study that employed a well-established visual stimulation paradigm: a contrast-reversing checkerboard. Our results indicate that the proposed method can identify regions of tissue that participate in the hemodynamic response to neuronal activation, but are distinct from the areas identified by conventional analyses of the oxyHb, deoxyHb and totalHb data. A discussion is provided that compares these findings to other recent studies using fNIRS techniques.
Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon's information-theoretic approach and the projection pursuit approach. Using maximum entropy approximations of differential entropy, we introduce a family of new contrast (objective) functions for ICA. These contrast functions enable both the estimation of the whole decomposition by minimizing mutual information, and estimation of individual independent components as projection pursuit directions. The statistical properties of the estimators based on such contrast functions are analyzed under the assumption of the linear mixture model, and it is shown how to choose contrast functions that are robust and/or of minimum variance. Finally, we introduce simple fixed-point algorithms for practical optimization of the contrast functions. These algorithms optimize the contrast functions very fast and reliably.
To assess the ability of the third edition of the Bayley Scales of Infant and Toddler Development (Bayley-III) to detect developmental delay in 2-year-old children who were extremely preterm and those carried to term.
Prospective cohort study.
The state of Victoria, Australia.
Subjects were consecutive surviving children who were born either at less than 28 weeks' gestational age (extremely preterm) or with less than 1000 g birth weight (extremely low-birth-weight; n = 221) in the state of Victoria, Australia, in 2005 and randomly selected controls who were both carried to term and of normal birth weight (n = 220).
Children were assessed by psychologists blinded to knowledge of group at 2 years of age, corrected for prematurity with the new Bayley-III scale.
Follow-up rates of both cohorts were high (>92%). Mean values for all composite and subtest scores for the extremely preterm/extremely low-birth-weight group were significantly below those of the control group (P < .001), with the magnitude of all group differences being in excess of two-thirds SD. Mean values for the extremely preterm/extremely low-birth-weight group approached the normative mean, but in contrast, the mean values for the control group were higher than expected, with composite scores being between 0.55 and 1.23 SD above the normative mean. Proportions of children with developmental delay were grossly underestimated using the reference values, but were within the expected range when computed relative to the mean (standard deviation) for the controls.
The Bayley-III scale seriously underestimates developmental delay in 2-year-old Australian children.
Application of resting state functional connectivity magnetic resonance imaging (fcMRI) to the study of prematurely born infants enables assessment of the earliest forms of cerebral connectivity and characterization of its early development in the human brain. We obtained 90 longitudinal fcMRI data sets from a cohort of preterm infants aged from 26 weeks postmenstrual age (PMA) through term equivalent age at PMA-specific time points. Utilizing seed-based correlation analysis, we identified resting state networks involving varied cortical regions, the thalamus, and cerebellum. Identified networks demonstrated a regionally variable age-specific pattern of development, with more mature forms consisting of localized interhemispheric connections between homotopic counterparts. Anatomical distance was found to play a critical role in the rate of connection development. Prominent differences were noted between networks identified in term control versus premature infants at term equivalent, including in the thalamocortical connections critical for neurodevelopment. Putative precursors of the default mode network were detected in term control infants but were not identified in preterm infants, including those at term equivalent. Identified patterns of network maturation reflect the intricate relationship of structural and functional processes present throughout this important developmental period and are consistent with prior investigations of neurodevelopment in this population.
Development of brain functions and the structural-functional correlates of brain injury remain difficult to evaluate in the young infant. Thus, new noninvasive methods capable of early functional diagnosis are needed. This review describes the use of functional magnetic resonance imaging (fMRI) for studying localization of brain function in the developing brain when standard clinical investigations are not available or conclusive. This promising neuroimaging technique has been successfully used in healthy newborns and in newborns with brain injury using different paradigms, including passive visual, somato-sensorial, and auditory stimulation. We summarize the major findings of previous fMRI studies in young infants, describe ongoing methodological challenges, and propose exciting future developments in using resting-state protocols and functional connectivity techniques to assist in evaluating early life brain function and its recovery from injury.
Optical techniques enable portable, non-invasive functional neuroimaging. However, low lateral resolution and poor discrimination between brain hemodynamics and systemic contaminants have hampered the translation of near infrared spectroscopy from research instrument to widespread neuroscience tool. In this paper, we demonstrate that improvements in spatial resolution and signal-to-noise, afforded by recently developed high-density diffuse optical tomography approaches, now permit detailed phase-encoded mapping of the visual cortex's retinotopic organization. Due to its highly organized structure, the visual cortex has long served as a benchmark for judging neuroimaging techniques, including the original development of functional magnetic resonance imaging (fMRI) and positron emission tomography. Using phase-encoded visual stimuli that create traveling waves of cortical activations, we are able to discriminate the representations of multiple visual angles and eccentricities within an individual hemisphere, reproducing classic fMRI results. High contrast-to-noise and repeatable imaging allow the detection of inter-subject differences. These results represent a significant advancement in the level of detail that can be obtained from non-invasive optical imaging of functional brain responses. In addition, these phase-encoded paradigms and the maps they generate form a standardized model with which to judge new developments in optical algorithms and systems, such as new image reconstruction techniques and registration with anatomic imaging. With these advances in techniques and validation paradigms, optical neuroimaging can be extended into studies of higher-order brain function and of clinical utility with greater performance and confidence.
Recent progress in functional neuroimaging research has provided the opportunity to probe at the brain's intrinsic functional architecture. Synchronized spontaneous neuronal activity is present in the form of resting-state networks in the brain even in the absence of external stimuli. The objective of this study was to investigate the presence of resting-state networks in the unsedated infant brain born at full term. Using functional MRI, we investigated spontaneous low-frequency signal fluctuations in 19 healthy full-term infants. Resting-state functional MRI data acquired during natural sleep was analyzed using independent component analysis. We found five resting-state networks in the unsedated infant brain born at full term, encompassing sensory cortices, parietal and temporal areas, and the prefrontal cortex. In addition, we found evidence for a resting-state network that enclosed the bilateral basal ganglia.
Mapping resting-state networks allows insight into the brain's functional architecture and physiology and has rapidly become important in contemporary neuroscience research. Diffuse optical tomography (DOT) is an emerging functional neuroimaging technique with the advantages, relative to functional magnetic resonance imaging (fMRI), of portability and the ability to simultaneously measure both oxy- and deoxyhemoglobin. Previous optical studies have evaluated the temporal features of spontaneous resting brain signals. Herein, we develop techniques for spatially mapping functional connectivity with DOT (fc-DOT). Simultaneous imaging over the motor and visual cortices yielded robust correlation maps reproducing the expected functional neural architecture. The localization of the maps was confirmed with task-response studies and with subject-matched fc-MRI. These fc-DOT methods provide a task-less approach to mapping brain function in populations that were previously difficult to research. Our advances may permit new studies of early childhood development and of unconscious patients. In addition, the comprehensive hemoglobin contrasts of fc-DOT enable innovative studies of the biophysical origin of the functional connectivity signal.
This Applied Optics feature issue on Topics in Biomedical Optics highlights papers presented at the 2008 Biomedical Topical meeting sponsored by the Optical Society.
Diffuse optical tomography (DOT) methods observe hemodynamics in the brain by measuring light transmission through the scalp, skull, and brain. Thus, separating signals due to heart pulsations, breathing movements, and systemic blood flow fluctuations from the desired brain functional responses is critical to the fidelity of the derived maps. Herein, we applied independent component analysis (ICA) to temporal signals obtained from a high-density DOT system used for functional mapping of the visual cortex. DOT measurements were taken over the occipital cortex of human adult subjects while they viewed stimuli designed to activate two spatially distinct areas of the visual cortex. ICA was able to extract clean functional hemodynamic signals and separate brain activity sources from hemodynamic fluctuations related to heart and breathing without knowledge of the stimulus paradigm. Furthermore, independent components were found defining distinct functional responses to each stimulus type. Images generated from single ICA components were comparable, with regard to spatial extent and resolution, to images from block averaging (with knowledge of the block stimulus paradigm). Both images and estimated time-series signals demonstrated that ICA was superior to principal component analysis in extracting the true event-evoked response signals. Our results suggest that ICA can extract the time courses and the corresponding spatial extent of functional responses in DOT imaging.
Near infrared (IR) spectroscopy can give continuous, direct information about cerebral oxygenation in vivo by providing signals from oxygenated and deoxygenated haemoglobin and cytochrome aa3. Due to a lack of precise spectral information and uncertainties about optical path length it has previously been impossible to quantify the data. We have therefore obtained the cytochrome aa3 spectrum in vivo from the brains of rats after replacing the blood with a fluorocarbon substitute. Near infrared haemoglobin spectra were also obtained, at various oxygenation levels, from cuvette studies of lysed human red blood cells. Estimates of optical path length have been obtained. The data were used to construct an algorithm for calculating the changes in oxygenated and deoxygenated haemoglobin and oxygenated cytochrome aa3 in tissue from changes in near IR absorption.
Developmental coordination disorder (DCD) is defined as an impairment in the development of motor coordination that interferes with academic achievement or activities of daily living (DSM-IV). DCD has been reported to affect 5% to 9% of children in the normal population. This study describes the prevalence of DCD in a cohort of extremely low birth weight children (ELBW, < or = l800 g) at 8.9 years of age, from which were excluded children with major impairments. Seventy-three children were included in the study group, along with 18 term-born, socially matched controls. Of the 73 ELBW children, 37 (51%) were classified as having DCD. ELBW children with DCD also had significantly lower Performance IQ (PIQ) scores and were more likely (43%) to have a learning difficulty in arithmetic than ELBW children who did not have DCD. This study found that DCD is a common problem in school-aged ELBW children.
Near-infrared spectroscopy (NIRS) can be used to noninvasively measure changes in the concentrations of oxy- and deoxyhemoglobin in tissue. We have previously shown that while global changes can be reliably measured, focal changes can produce erroneous estimates of concentration changes (NeuroImage 13 (2001), 76). Here, we describe four separate sources for systematic error in the calculation of focal hemoglobin changes from NIRS data and use experimental methods and Monte Carlo simulations to examine the importance and mitigation methods of each. The sources of error are: (1). the absolute magnitudes and relative differences in pathlength factors as a function of wavelength, (2). the location and spatial extent of the absorption change with respect to the optical probe, (3). possible differences in the spatial distribution of hemoglobin species, and (4). the potential for simultaneous monitoring of multiple regions of activation. We found wavelength selection and optode placement to be important variables in minimizing such errors, and our findings indicate that appropriate experimental procedures could reduce each of these errors to a small fraction (<10%) of the observed concentration changes.
We have begun clinical trials of optical tomography of the neonatal brain. To validate this research, we have built and imaged an anatomically realistic, tissue-equivalent neonatal head phantom that is hollow, allowing contrasting objects to be placed inside it. Images were reconstructed by use of two finite-element meshes, one generated from a computed tomography image of the phantom and the other spherical. The phantom was filled with a liquid of the same optical properties as the outer region, and two perturbations were placed inside. These were successfully imaged with good separation between the absorption and scatter coefficients. The phantom was then refilled with a liquid of increased absorption compared with the background to simulate the brain, and the absolute properties of the two regions were found. These were used as a priori information for the complete reconstruction. Both perturbations were visible, superimposed on the increased absorption of the central region. The head-shaped mesh performed slightly better than the spherical mesh, particularly when the absorption of the central region of the phantom was increased.
In near-infrared spectroscopy and imaging, the sensitivity of the detected signal to brain activation and the volume of interrogated tissue are clinically important. Light propagation in adult and neonatal heads is strongly affected by the presence of a low-scattering cerebrospinal fluid layer. The effect of the heterogeneous structure of the head on light propagation in the adult brain is likely to be different from that in the neonatal brain because the thickness of the superficial tissues and the optical properties of the brain of the neonatal head are quite different from those of the adult head. In this study, light propagation in the two-dimensional realistic adult and neonatal head models, whose geometries are generated from a magnetic resonance imaging scan of the human heads, is predicted by Monte Carlo simulation. The sandwich structure, which is a low-scattering cerebrospinal fluid layer held between the high-scattering skull and gray matter, strongly affects light propagation in the brain of the adult head. The sensitivity of the absorption change in the gray matter is improved; however, the intensely sensitive region is confined to the shallow region of the gray matter. The high absorption of the neonatal brain causes a similar effect on light propagation in the head. The intensely sensitive region in the neonatal brain is confined to the gray matter; however, the spatial sensitivity profile penetrates into the deeper region of the white matter.