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Specificity in percentage of voxels within language ROIs, and sensitivity in number of voxels within language ROIs, for resting-state fMRI, task-fMRI, taskIC-fMRI, for each subject. The horizontal line shows the mean value in each case. ∗∗∗ = differences at p < 0.001.
Source publication
Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance an...
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Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named “shared and specific independent component analysis” (SSICA) to perform between-group comparisons i...
Previous studies have observed reduced suppression of the default mode network (DMN) during cognitive tasks in schizophrenia, suggesting inefficient DMN suppression is critical for the cognitive deficits of schizophrenia. Cognitive function in schizophrenia patients, however, varies from relatively intact to severely impaired. This study, which com...
Citations
... After spatially transformed to an individual subject's space, such templates can help clinical fMRI analysis to evaluate language laterality from tb-or rs-fMRI (Agarwal et al., 2018;Gohel et al., 2019;Pillai & Zaca, 2011;Ruff et al., 2008) and to guide seed selection for mapping the language network with rs-fMRI (Hsu et al., 2020). In addition, previous studies have demonstrated the feasibility of categorizing functional networks from independent component analysis (ICA) of rs-fMRI by using an automated template-matching process and showed success in identifying language networks for presurgical mapping (Branco et al., 2016;Tie et al., 2014). ...
... These causes of anatomic variability in the language function highlight the difficulty of finding a template for presurgical fMRI applications. To address this difficulty, this study aimed to evaluate and compare four publicly available language templates that have been used in previously published clinical fMRI studies (Branco et al., 2016;Gohel et al., 2019;Hsu et al., 2020;Zacà et al., 2018). Each template was analyzed for its ability to capture the maximum amount of PLA activation from presurgical fMRI of brain tumor patients, while minimizing the inclusion of activations that are not in the PLAs. ...
... (1) anatomically determined with Harvard-Oxford Atlas (Caviness et al., 1996) (Template A), (2) generated based on tb-fMRI study (Branco et al., 2016;Fedorenko et al., 2010) (Template B), (3) generated based on rs-fMRI study (Shirer et al., 2012;Zacà et al., 2018) (Template C), and (4) obtained from meta-analysis results from Neurosynth with anatomical constraints (Hsu et al., 2020;Yarkoni et al., 2011) (Template D) ( Figure 1). More details about the construction of these atlas can be found in Section 4. For each template, only ROIs in left hemisphere were included for the comparison. ...
Introduction
Functional brain templates are often used in the analysis of clinical functional MRI (fMRI) studies. However, these templates are mostly built based on anatomy or fMRI of healthy subjects, which have not been fully vetted in clinical cohorts. Our aim was to evaluate language templates by comparing with primary language areas (PLAs) detected from presurgical fMRI of brain tumor patients.
Methods
Four language templates (A–D) based on anatomy, task‐based fMRI, resting‐state fMRI, and meta‐analysis, respectively, were compared with PLAs detected by fMRI with word generation and sentence completion paradigms. For each template, the fraction of PLA activations enclosed by the template (positive inclusion fraction, [PIF]), the fraction of activations within the template but that did not belong to PLAs (false inclusion fraction, [FIF]), and their Dice similarity coefficient (DSC) with PLA activations were calculated.
Results
For anterior PLAs, Template A had the greatest PIF (median, 0.95), whereas Template D had both the lowest FIF (median, 0.074), and the highest DSC (median, 0.30), which were all significant compared to other templates. For posterior PLAs, Templates B and D had similar PIF (median, 0.91 and 0.90, respectively) and DSC (both medians, 0.059), which were all significantly higher than that of Template C. Templates B and C had significantly lower FIF (median, 0.061 and 0.054, respectively) compared to Template D.
Conclusion
This study demonstrated significant differences between language templates in their inclusiveness of and spatial agreement with the PLAs detected in the presurgical fMRI of the patient cohort. These findings may help guide the selection of language templates tailored to their applications in clinical fMRI studies.
... Researchers have used independent component analysis (ICA) to isolate the independent component most like a template. These studies so far have had small sample sizes (n = 15) and wide variation in overlap between individual-specific and canonical language networks (Branco et al., 2016;Smitha et al., 2019). While promising, such ICA approaches are affected by the number of components selected, cannot give region-level analyses, and bias the estimate toward the template, which was asymmetric in the former paper and symmetric in the latter. ...
Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term “Wernicke’s area” near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.
... Recent results have highlighted the importance of white matter structural disconnections in the disruption of functional connectivity 53 , and this disruption has been linked to behavioural and cognitive dysfunction 54,55 . Therefore, being able to identify these RSN white matter "highways" would propel our understanding of disconnection symptoms, improve recovery prognostics, and inform preoperative brain surgery planning 56 . To facilitate these efforts, we released the WhiteRest tool (as a module of the Functionnectome) that quantifies the presence of RSNs in a specific region of the brain's white matter. ...
Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain’s white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.
... Similar to the task-based fMRI method, the correlation of behavior performance in language processing and resting-state brain activity has been found to be an effective measure of the neural mechanism underlying language comprehension. Several studies have found that the brain region and network identified by the correlation of behavior performance and resting-state brain activity overlapped with those observed by task-based functional brain-imaging studies [26][27][28][29]. ...
... ALFF [30] and fALFF [31] reflect the intensity of local brain activity as local indicators while FC reflects the strength of functional connectivity between brain regions [33]. Healthy individuals' resting-state ALFF/fALFF and resting-state FC have been reliably found to correlate with task-evoked BOLD responses and participants' behavioral measures [27], such as semantic processing [28], word-reading skill [29], individuals' reading ability [34], phonological processing [35], and language preoperative planning [26]. Given the robustness of these measures, in the present study we investigated whether indirect replies could attenuate recipients' negative emotional experience and if so, whether their spontaneous brain activity is related to individual variations in emotional reduction, using ALFF/fALFF and FC of resting state fMRI signals. ...
During daily conversations, people prefer indirect replies in face-threatening situations. Existent studies have indicated that recipients tend to perceive the information conveyed by indirect replies as negative and emotion regions are engaged in indirect replies processing in face-threatening situations. In this study, we examined whether indirect replies can reduce recipients’ experience of negative emotion and what are the underlying cerebral structures that may give rise to individual differences in the effectiveness of such replies in attenuating negative emotion. Behavior ratings and resting-stating functional magnetic resonance imaging (rs-fMRI) techniques were combined to explore these questions. We created dialogues expressing refusal or negative opinion with direct/indirect replies. Participants were asked to rate their emotional valence and arousal when they received such replies. The rating scores were used to correlate with spontaneous brain activity. Results showed that indirect replies indeed attenuated recipients’ negative emotion experience. Moreover, the left caudate, the right anterior cingulate cortex (rACC), and the connectivity of rACC and left medial prefrontal cortex (lmPFC) were found to be positively correlated to individual differences in such emotion attenuation. Our findings provide direct empirical evidence for the face-saving function of indirect replies and reveal that the intrinsic brain activities of emotion network and theory of mind (ToM) network are related to individual differences in such emotion attenuation.
... [43][44][45] Others have highlighted issues with within-subject testretest reproducibility 46 and proposed alternative task-based 42 and resting-state fMRI approaches to preoperative language mapping. [47][48][49][50] Although the application of these emerging methods may have further refined the language activation maps, we chose to use well-established approaches to fMRI data processing. ...
Background
For patients with drug-resistant epilepsy, surgery may be effective in controlling their disease. Surgical evaluation may involve localization of the language areas using functional magnetic resonance imaging (fMRI) or Wada testing. We evaluated the accuracy of task-based fMRI versus Wada-based language lateralization in a cohort of our epilepsy patients.
Methods
In a single-center, retrospective analysis, we identified patients with medically intractable epilepsy who participated in presurgical language mapping (n = 35) with fMRI and Wada testing. Demographic variables and imaging metrics were obtained. We calculated the laterality index (LI) from task-evoked fMRI activation maps across language areas during auditory and reading tasks to determine lateralization. Possible scores for LI range from −1 (strongly left-hemisphere dominant) to 1 (strongly right-hemisphere dominant). Concordance between fMRI and Wada was estimated using Cohen’s Kappa coefficient. Association between the LI scores from the auditory and reading tasks was tested using Spearman’s rank correlation coefficient.
Results
The fMRI-based laterality indices were concordant with results from Wada testing in 91.4% of patients during the reading task ( κ = .55) and 96.9% of patients during the auditory task ( κ = .79). The mean LIs for the reading and auditory tasks were −0.52 ± 0.43 and −0.68 ± 0.42, respectively. The LI scores for the language and reading tasks were strongly correlated, r(30) = 0.57 ( p = 0.001).
Conclusion
Our findings suggest that fMRI is generally an accurate, low-risk alternative to Wada testing for language lateralization. However, when fMRI indicates atypical language lateralization (e.g., bilateral dominance), patients may benefit from subsequent Wada testing or intraoperative language mapping.
... However, the capability of rs-fMRI to identify language eloquent cortex compared to tb-fMRI has yet to be fully understood both in healthy population and in patients with brain tumors. To our knowledge, only few ICA-based studies compared language rs-fMRI maps and task-specific fMRI activations in brain tumors' patients, reporting a good level of spatial overlap between these two approaches (Branco et al., 2016;Lu et al., 2017;Sair et al., 2016). ...
... The spatial organization of the ICNs in the five glioma cases analyzed in our study is consistent with recently published seed-based rs-fMRI studies on seven left-sided glioma patients assessed at the single-subject level, as well as with group findings of left temporal lobe epileptic patients, which both positioned the seed in the left IFG (Doucet et al., 2017;Lu et al., 2017). Despite relying on a different methodology, also the ICA language components extracted in a sample of tumor/epileptic patients by Branco et al., are concordant with our findings (Branco et al., 2016). ...
... Recent studies demonstrated the capability of rs-fMRI to identify ICNs involved in several language processes in HC and neurodegenerative patients, and that these networks resembled those activated in tb-fMRI (Battistella et al., 2019(Battistella et al., , 2020Lohmann et al., 2010). However, investigations that compared rs-fMRIderived language networks to tb-fMRI language activations are scarce in brain tumor patients (Branco et al., 2016;Lu et al., 2017;Sair et al., 2016). Although a substantial subject-level variability was reported in these studies, fair to good levels of concordance were found between rs-fMRI and tb-fMRI. ...
Task-based functional MRI (tb-fMRI) represents an extremely valuable approach for the identification of language eloquent regions for presurgical mapping in patients with brain tumors. However, its routinely application is limited by patient-related factors, such as cognitive disability and difficulty in coping with long-time acquisitions, and by technical factors, such as lack of equipment availability for stimuli delivery. Resting-state fMRI (rs-fMRI) instead, allows the identification of distinct language networks in a 10-min acquisition without the need of performing active tasks and using specific equipment. Therefore, to test the feasibility of rs-fMRI as a preoperative mapping tool, we reconstructed a lexico-semantic intrinsic connectivity network (ICN) in healthy controls (HC) and in a case series of patients with gliomas and compared the organization of this language network with the one derived from tb-fMRI in the patient’s group. We studied three patients with extra-frontal gliomas who underwent functional mapping with auditory verb-generation (AVG) task and rs-fMRI with a seed in the left inferior frontal gyrus (IFG). First, we identified the functional connected areas to the IFG in HC. We qualitatively compared these areas with those that showed functional activation in AVG task derived from Neurosynth meta-analysis. Last, in each patient we performed single-subject analyses both for rs- and tb-fMRI, and we evaluated the spatial overlap between the two approaches. In HC, the IFG-ICN network showed a predominant left fronto-temporal functional connectivity in regions overlapping with the AVG network derived from a meta-analysis. In two patients, rs- and tb-fMRI showed comparable patterns of activation in left fronto-temporal regions, with different levels of contralateral activations. The third patient could not accomplish the AVG task and thus it was not possible to make any comparison with the ICN. However, in this patient, task-free approach disclosed a consistent network of fronto-temporal regions as in HC, and additional parietal regions. Our preliminary findings support the value of rs-fMRI approach for presurgical mapping, particularly for identifying left fronto-temporal core language-related areas in glioma patients. In a preoperative setting, rs-fMRI approach could represent a powerful tool for the identification of eloquent language areas, especially in patients with language or cognitive impairments.
... Additionally, in vivo studies on brain network disruption and alterations in anatomical dysconnectivity (or connectomes) in patients with brain tumors of glial cell origin have contributed to advancing our knowledge of the complex nature of the structural-functional coupling of brain tumors [82,83]. Although still under investigation, multiple studies to date have demonstrated the concordance of RS-fMRI with task-based fMRI or intraoperative mapping, substantiating its clinical utility [69,80,[84][85][86][87][88]. Whether the presence of certain connectome patterns can serve as a biomarker of cognitive outcomes of pediatric brain tumors is a subject of ongoing research [89]. ...
Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.
... Recent results have highlighted the importance of white matter structural disconnections in the disruption of functional connectivity (49), and this disruption has been linked to behavioural and cognitive dysfunction (50,51). Therefore, being able to identify these RSN white matter "highways" would propel our understanding of disconnection symptoms, improve recovery prognostics, and inform preoperative brain surgery planning (52). In order to facilitate these efforts, we released the WhiteRest module (as part of the Functionnectome) that quantifies the presence of RSNs in a specific region of the brain's white matter. ...
Over the past two decades, the study of resting-state functional magnetic resonance imaging (fMRI) has revealed the existence of multiple brain areas displaying synchronous functional blood oxygen level-dependent signals (BOLD)-resting-state networks (RSNs). The variation in functional connectivity between the different areas of a resting-state network or between multiple networks, have been extensively studied and linked to cognitive states and pathologies. However, the white matter connections supporting each network remain only partially described. In this work, we developed a data-driven method to systematically map the white and grey matter contributing to resting-state networks. Using the Human Connectome Project, we generated an atlas of 30 resting-state networks, each with two maps: white matter and grey matter. By integrating structural and functional neuroimaging data, this method builds an atlas that unlocks the joint anatomical exploration of white and grey matter to resting-state networks. The method also allows highlighting the overlap between networks, which revealed that most (89%) of the brain's white matter is shared amongst multiple networks, with 16% shared by at least 7 resting-state networks. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the correlations and the communication within resting-state networks.
... Firstly, patients have to be able to perform the task. Patients with a tumor close to eloquent areas may be less able to cooperate because of neurological impairment [13]. Secondly, patients must be awake to perform the task. ...
... Because sedatives cannot be administered, the use of TB-fMRI is limited, for instance, in pediatric or claustrophobic patients [3]. Further drawbacks are the variability of results using different language tasks [13], motion artifacts [14], and low signal-to-noise ratio [15]. In comparison to DCS, the specificity and sensitivity of TB-fMRI are mediocre and-according to several studies-highly variable [16]. ...
... In the case of multiple functional analyses, TB-fMRI is time-consuming. Furthermore, TB-fMRI results of the underlying individual anatomy may be challenging to interpret because of the inseparability of simultaneously examined tasks, for instance, by activation of the visual cortex, attention networks, and working memory during reading, when patients perform language tasks [12,13,18]. Misinterpretations may result in a more ambiguous rate of lateralization indices, which could-in theory-lead to incorrect decisions regarding the surgical strategy. ...
Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years, the resting-state fMRI (RS-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Twenty patients suffering from brain lesions close to supposed language-relevant cortical areas were included. RS-fMRI and task-based (TB-fMRI) were performed for the purpose of preoperative language assessment. TB-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language-critical and language-supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the TB-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice index. Thereby, the RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. In general, the results suggest that determining language dominance in the human brain is feasible both with TB-fMRI and RS-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.
... The feasibility of the isolation of the language network at rest by independent component analysis has been previously demonstrated [45,46,[78][79][80][81] and validated against electrocortical mapping or the Wada test [45,81,82]. As we previously reported [45], we found that an important component of the language network, the left ANG, involved in semantic processing [15], is apparent at rest but not captured by an explicit task involving semantic processing. ...
Background
Pre-surgical mapping of language using functional MRI aimed principally to determine the dominant hemisphere. This mapping is currently performed using covert linguistic task in way to avoid motion artefacts potentially biasing the results. However, overt task is closer to natural speaking, allows a control on the performance of the task, and may be easier to perform for stressed patients and children. However, overt task, by activating phonological areas on both hemispheres and areas involved in pitch prosody control in the non-dominant hemisphere, is expected to modify the determination of the dominant hemisphere by the calculation of the lateralization index (LI).
Objective
Here, we analyzed the modifications in the LI and the interactions between cognitive networks during covert and overt speech task.
Methods
Thirty-three volunteers participated in this study, all but four were right-handed. They performed three functional sessions consisting of (1) covert and (2) overt generation of a short sentence semantically linked with an audibly presented word, from which we estimated the “Covert” and “Overt” contrasts, and a (3) resting-state session. The resting-state session was submitted to spatial independent component analysis to identify language network at rest (LANG), cingulo-opercular network (CO), and ventral attention network (VAN). The LI was calculated using the bootstrapping method.
Results
The LI of the LANG was the most left-lateralized (0.66 ± 0.38). The LI shifted from a moderate leftward lateralization for the Covert contrast (0.32 ± 0.38) to a right lateralization for the Overt contrast (− 0.13 ± 0.30). The LI significantly differed from each other. This rightward shift was due to the recruitment of right hemispheric temporal areas together with the nodes of the CO.
Conclusion
Analyzing the overt speech by fMRI allowed improvement in the physiological knowledge regarding the coordinated activity of the intrinsic connectivity networks. However, the rightward shift of the LI in this condition did not provide the basic information on the hemispheric language dominance. Overt linguistic task cannot be recommended for clinical purpose when determining hemispheric dominance for language.
