No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Correlated structural and functional abnormalities in the default mode network in schizophrenia
Abstract
There is increasing evidence of default mode network (DMN) dysfunction in schizophrenia. It has also been suggested that brain structural changes are maximal in a medial frontal area which overlaps with the anterior midline node of this network.
Brain deactivations were examined in 14 schizophrenic patients and 14 controls during performance of two tasks requiring identification or labelling of facial emotions. Grey matter and white matter volumes were compared using voxel-based morphometry.
Relative to the controls, the schizophrenic patients showed failure to deactivate in the anterior and posterior midline nodes of the default mode network, as well as other areas considered to be part of the network. Grey matter volume reductions in the patients were found in medial cortical regions which overlapped with the same parts of the network. The functional and structural changes showed significant correlations in a number of medial cortical areas.
Failure of deactivation in the default mode network is seen in schizophrenic patients when they perform facial emotion tasks. This failure is more extensive than that seen during performance of working memory tasks. The study also supports recent findings of brain structural changes in schizophrenia in the territory of the default mode network.
... 102 Second, individuals with SCZ have routinely been shown to have dysfunctional connections within the DMN. 104,106 Multiple studies support smooth pursuit eye-tracking abnormalities in SCZ patients, as evidenced by an increased number of nonvisually guided saccades. 103,105 This is hypothesized to be due to impairments within the smooth pursuit EM system secondary to disruption(s) in the frontal-thalamic-cerebellar circuitry. ...
... 103,105 This is hypothesized to be due to impairments within the smooth pursuit EM system secondary to disruption(s) in the frontal-thalamic-cerebellar circuitry. 103,104 So far, we have discussed theories explaining EMDR's efficacy, the neurophysiology of the oculomotor circuit, and how it relates to EMDR and clinical groups. Below, we discuss the function of the DMN and cerebellum, and their neural correlates within PTSD pathophysiology. ...
... Abnormal signaling and connectivity of the DMN has been observed in multiple psychopathologies besides PTSD, including SCZ, major depressive disorder, and bipolar disorder. 104,106,149 Moreover, individuals with anxiety disorders demonstrate a failure to deactivate the mPFC during stressful tasks. 150 Thereby, predictive bilateral and smooth pursuit EMs might be a practical tool for attenuating DMN activation in people with these psychiatric disorders while they complete concomitant psychotherapy. ...
Eye movement desensitization and reprocessing (EMDR), a form of psychotherapy for individuals with post-traumatic stress disorder (PTSD), has long been a controversial topic, hampered in part by a lack of understanding of the neural mechanisms that contribute to its remedial effect. Here, we review current theories describing EMDR's potential neurobiological mechanisms of action involving working memory, interhemispheric communication, de-arousal, and memory reconsolidation. We then discuss recent studies describing the temporal and spatial aspects of smooth pursuit and predictive saccades, which resemble those made during EMDR, and their neural correlates within the default mode network (DMN) and cerebellum. We hypothesize that if the production of bilateral predictive eye movements is supportive of DMN and cerebellum activation, then therapies that shift the brain towards this state correspondingly would benefit the processes regulated by these structures (i.e., memory retrieval, relaxation, and associative learning), all of which are essential components for PTSD recovery. We propose that the timing of sensory stimulation may be relevant to treatment effect and could be adapted across different patients depending on their baseline saccade metrics. Empirical data in support of this model are reviewed and experimental predictions are discussed.
... Las personas atendidas por lo general no comunican a los profesionales sus intenciones con respecto a la toma de medicación ni tampoco existe un método estandarizado, validado y fiable para pronosticar la adherencia al tratamiento. El insight (entendido como la capacidad del paciente para reconocer que padece una enfermedad mental, y la habilidad para su auto-observación y autoconocimiento respecto a las experiencias psicopatológicas, así como la conciencia del tipo, severidad y consecuencias 10 ); y la actitud hacia la medicación (entendida como las respuestas subjetivas negativas y/o desagradables que comúnmente se presentan ante el consumo de medicamento antipsicóticos) constituyen dos factores claves con respecto a la adherencia al tratamiento 11 que según la Organización Mundial de la Salud la considera como el grado en que el comportamiento de una persona al tomar el medicamento, seguir un régimen alimentario y ejecutar cambios del modo de vida se corresponden con las recomendaciones acordadas de un prestador de asistencia sanitaria 12 . En segundo lugar, Beck en un estudio de 150 pacientes, concluyó que las intervenciones para mejorar la adherencia a la medicación pueden ser más eficaces si se centran en las actitudes relacionadas con el tratamiento 13 . ...
... son la esquizofrenia (8)(9)(10)(11)(12)(13), la depresión mayor (15) o el trastorno bipolar (16)(17). Es preciso examinar si alguna de estas alteraciones en el TLP puede realmente representar también un fracaso de deactivación, ya que la hiperactivación puede resultar de una mayor activación o reducción de la desactivación en la condición de interés (18). ...
Como demuestran recientes estudios, el
sesgo de género parece afectar a las derivaciones
que se llevan a cabo en recursos
tanto hospitalarios como de rehabilitación
psicosocial comunitaria en el caso de las
personas diagnosticadas de Trastorno Mental
Grave, ya que los resultados obtenidos tienden
a mostrar que éstos atienden al doble
de hombres que de mujeres. Con el objetivo
de indagar si este dato también se da en el
caso de algunos de los recursos que gestiona
la organización Hermanas Hospitalarias,
se extraen los datos correspondientes a las
derivaciones a cuatro de sus centros (Línea
de Rehabilitación Psicosocial, Clínica San
Miguel, Complejo Asistencial Benito Menni
de Ciempozuelos y Complejo Asistencial de
Málaga) desde el año 2012 hasta el 2018
desagregado por sexo dichos datos. Los resultados
obtenidos muestran que el porcentaje
de hombres derivados a los diferentes
recursos analizados supera al de mujeres en
buena parte de los recursos analizados, si
bien, la diferencia previamente planteada,
únicamente se daría en el caso de los Centros
de Rehabilitación Laboral (CRL) (31% vs
69%), siendo la productiva-laboral, un área
especialmente atravesada por los mandatos
de género. Dichos datos, a pesar de ser meramente
descriptivos, pueden servir para, en
primer lugar, hacer estudios de mayor envergadura
de cara a comprobar este aspecto y,
en segundo lugar, en caso de confirmarse,
poner en marcha diferentes estrategias destinadas
a disminuir la brecha de género.
... Las personas atendidas por lo general no comunican a los profesionales sus intenciones con respecto a la toma de medicación ni tampoco existe un método estandarizado, validado y fiable para pronosticar la adherencia al tratamiento. El insight (entendido como la capacidad del paciente para reconocer que padece una enfermedad mental, y la habilidad para su auto-observación y autoconocimiento respecto a las experiencias psicopatológicas, así como la conciencia del tipo, severidad y consecuencias 10 ); y la actitud hacia la medicación (entendida como las respuestas subjetivas negativas y/o desagradables que comúnmente se presentan ante el consumo de medicamento antipsicóticos) constituyen dos factores claves con respecto a la adherencia al tratamiento 11 que según la Organización Mundial de la Salud la considera como el grado en que el comportamiento de una persona al tomar el medicamento, seguir un régimen alimentario y ejecutar cambios del modo de vida se corresponden con las recomendaciones acordadas de un prestador de asistencia sanitaria 12 . En segundo lugar, Beck en un estudio de 150 pacientes, concluyó que las intervenciones para mejorar la adherencia a la medicación pueden ser más eficaces si se centran en las actitudes relacionadas con el tratamiento 13 . ...
... son la esquizofrenia (8)(9)(10)(11)(12)(13), la depresión mayor (15) o el trastorno bipolar (16)(17). Es preciso examinar si alguna de estas alteraciones en el TLP puede realmente representar también un fracaso de deactivación, ya que la hiperactivación puede resultar de una mayor activación o reducción de la desactivación en la condición de interés (18). ...
Los días 2 y 3 de Octubre de 2019 tuvieron lugar en Caixa
Fórum de Madrid las “VIII Jornadas de Salud Mental y Rehabilitación
Psicosocial”, organizadas por Hermanas Hospitalarias,
que llevaron por título “Construir ciudadanía: Estrategias de capacitación
y participación de personas con trastornos mentales
graves”.
... Two initial studies (Garrity et al., 2007;Harrison et al., 2007) found increased de-activation or a mixed pattern of increased activation and failure of de-activation, respectively. Since then, however, the almost invariable finding has been failure of de-activation, which is typically seen in the medial frontal cortex (Pomarol-Clotet et al., 2008;Whitfield-Gabrieli et al., 2009;Mannell et al., 2010;Salgado-Pineda et al., 2011;Schneider et al., 2011;Dreher et al., 2012;Haatveit et al., 2016), although the posterior cingulate gyrus/precuneus has also sometimes been found to be affected (Salgado-Pineda et al., 2011;Schneider et al., 2011). There appear to be only two exceptions: using a visual working memory task with various levels of difficulty, Hahn et al. (2017) found that 21 schizophrenic patients and 16 controls showed no differences in de-activation across 13 regions of interest placed in the default mode network, and at the two hardest levels de-activation was significantly greater in the patients. ...
... Two initial studies (Garrity et al., 2007;Harrison et al., 2007) found increased de-activation or a mixed pattern of increased activation and failure of de-activation, respectively. Since then, however, the almost invariable finding has been failure of de-activation, which is typically seen in the medial frontal cortex (Pomarol-Clotet et al., 2008;Whitfield-Gabrieli et al., 2009;Mannell et al., 2010;Salgado-Pineda et al., 2011;Schneider et al., 2011;Dreher et al., 2012;Haatveit et al., 2016), although the posterior cingulate gyrus/precuneus has also sometimes been found to be affected (Salgado-Pineda et al., 2011;Schneider et al., 2011). There appear to be only two exceptions: using a visual working memory task with various levels of difficulty, Hahn et al. (2017) found that 21 schizophrenic patients and 16 controls showed no differences in de-activation across 13 regions of interest placed in the default mode network, and at the two hardest levels de-activation was significantly greater in the patients. ...
Background:
The brain functional correlates of autobiographical recall are well established, but have been little studied in schizophrenia. Additionally, autobiographical memory is one of a small number of cognitive tasks that activates rather than de-activates the default mode network, which has been found to be dysfunctional in this disorder.
Methods:
Twenty-seven schizophrenic patients and 30 healthy controls underwent functional magnetic resonance imaging while viewing cue words that evoked autobiographical memories. Control conditions included both non-memory-evoking cues and a low level baseline (cross fixation).
Results:
Compared to both non-memory evoking cues and low level baseline, autobiographical recall was associated with activation in default mode network regions in the controls including the medial frontal cortex, the posterior cingulate cortex and the hippocampus, as well as other areas. Clusters of de-activation were seen outside the default mode network. There were no activation differences between the schizophrenic patients and the controls, but the patients showed clusters of failure of de-activation in non-default mode network regions.
Conclusions:
According to this study, patients with schizophrenia show intact activation of the default mode network and other regions associated with recall of autobiographical memories. The finding of failure of de-activation outside the network suggests that schizophrenia may be associated with a general difficulty in de-activation rather than dysfunction of the default mode network per se.
... "poor mental coordination" (Andreasen, Paradiso, & O'Leary, 1998) reported in schizophrenia. A number of task-based fMRI studies show that individuals with schizophrenia fail to deactivate the DMN (Anticevic, Repovs, & Barch, 2013;Calhoun, Maciejewski, Pearlson, & Kiehl, 2008;Camchong et al., 2011;Garrity et al., 2007;Hasenkamp, James, Boshoven, & Duncan, 2011;Kim et al., 2009;Pomarol-Clotet et al., 2008;Salgado-Pineda et al., 2011;Wang et al., 2011;Whitfield-Gabrieli et al., 2009) we show that this inability to suppress DMN activity is evident even in the resting state. ...
... While there is strong evidence on lack of DMN suppression during goal-directed cognition in schizophrenia (Anticevic et al., 2012a;Calhoun et al., 2008;Camchong et al., 2011;Garrity et al., 2007;Hasenkamp et al., 2011;Kim et al., 2009;Pomarol-Clotet et al., 2008;Salgado-Pineda et al., 2011;Wang et al., 2011;Whitfield-Gabrieli et al., 2009), its exact causes remain unclear, fundamentally due to our limited understanding of the mechanisms underlying the functional antagonism between DMN and task-positive networks (Anticevic et al., 2012a). A few neuropharmacological studies have implicated defective synaptic mechanisms in psychotic conditions, mediated by certain monoaminergics that prevent inhibitory interneuronal functions in the cortex (Anticevic et al., 2012b;Carhart-Harris et al., 2012;Dang, O'Neil, & Jagust, 2012;Minzenberg, Yoon, & Carter, 2011). ...
Complex human behavior emerges from dynamic patterns of neural activity that transiently synchronize between distributed brain networks. This study aims to model the dynamics of neural activity in individuals with schizophrenia and to investigate whether the attributes of these dynamics associate with the disorder's behavioral and cognitive deficits. A hidden Markov model (HMM) was inferred from resting‐state functional magnetic resonance imaging (fMRI) data that was temporally concatenated across individuals with schizophrenia (n = 41) and healthy comparison individuals (n = 41). Under the HMM, fluctuations in fMRI activity within 14 canonical resting‐state networks were described using a repertoire of 12 brain states. The proportion of time spent in each state and the mean length of visits to each state were compared between groups, and canonical correlation analysis was used to test for associations between these state descriptors and symptom severity. Individuals with schizophrenia activated default mode and executive networks for a significantly shorter proportion of the 8‐min acquisition than healthy comparison individuals. While the default mode was activated less frequently in schizophrenia, the duration of each activation was on average 4–5 s longer than the comparison group. Severity of positive symptoms was associated with a longer proportion of time spent in states characterized by inactive default mode and executive networks, together with heightened activity in sensory networks. Furthermore, classifiers trained on the state descriptors predicted individual diagnostic status with an accuracy of 76–85%.
... Hence, multi-modal learning frameworks have emerged as effective tools for analyzing data from multiple sources, including neuroimaging [17,20,26,27] and genetic data [18,28]. Past research has demonstrated significant correlations between structural and functional changes in the brain and mental disorders [29,30]. Moreover, existing scientific literature points to a promising area of exploration: the correlation between genetic variants and neural activity concerning neuropsychiatric disease-related degeneration [23,24,31]. ...
Multi-modal learning has emerged as a powerful technique that leverages diverse data sources to enhance learning and decision-making processes. Adapting this approach to analyzing data collected from different biological domains is intuitive, especially for studying neuropsychiatric disorders. A complex neuropsychiatric disorder like schizophrenia (SZ) can affect multiple aspects of the brain and biologies. These biological sources each present distinct yet correlated expressions of underlying physiological processes. Joint learning from these data sources can improve our understanding of the disorder. However, combining these biological sources is challenging for several reasons: (i) observations are domains-specific, leading to data being represented in dissimilar subspaces, and (ii) fused data is often noisy and high-dimensional, making it challenging to identify relevant information. To address these challenges, we propose a multi-modal artificial intelligence (AI) model with a novel fusion module inspired by a bottleneck attention module (BAM). We use deep neural networks (DNN) to learn latent space representations of the input streams. Next, we introduce a two-dimensional (spatio-modality) attention module to regulate the intermediate fusion for SZ classification. We implement spatial attention via a dilated convolutional neural network that creates large receptive fields for extracting significant contextual patterns. The resulting joint learning framework maximizes complementarity allowing us to explore the correspondence among the modalities. We test our model on a multi-modal imaging-genetic dataset and achieve an SZ prediction accuracy of 94.10% (P < 0.0001), outperforming state-of-the-art unimodal and multi-modal models for the task. Moreover, the model provides inherent interpretability that helps identify concepts significant for the neural network decision and explains the underlying physiopathology of the disorder. Results also show that functional connectivity among subcortical, sensorimotor, and cognitive control domains plays an important role in characterizing SZ. Analysis of the spatio-modality attention scores suggests that structural components like the supplementary motor area, caudate, and insula play a significant role in SZ. Biclustering the attention scores discover a multi-modal cluster that includes genes CSMD1, ATK3, MOB4, and HSPE1, all of which have been identified as relevant to schizophrenia. In summary, feature attribution appears to be especially useful for probing the transient and confined but decisive patterns of complex disorders, and it shows promise for extensive applicability in future studies.
... In Humans, neuroimaging assessments reveal decreased BA24ab' activity in SZ versus control subjects at rest (100) while also exhibiting reduced deactivation during a facial emotion discrimination requiring matching/labeling of fear and anger depictions (101). Similar studies show patients diagnosed as having high negative schizotypy with anhedonia demonstrate reduced FC between BA24ab' and amygdala under fear and happy conditions (102). ...
Schizophrenia (SZ) and bipolar disorder (BP) patients share overlapping and distinct neurocognitive deficits. Neuroimaging of these patients and postmortem gene expression analyses suggest that compromised cingulate gyrus GABA-ergic interneurons may contribute to cognitive impairments in SZ and BP. Therefore, we investigated potential gene expression signatures for SZ and BP using interneuron cell-type specific markers including glutamic acid decarboxylase (GAD67), parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP) within cingulate Brodmann areas (BA). We report reduced GAD67 mRNA in anterior midcingulate cortex (aMCC) of SZ and BP subjects with BA24c being most dysregulated across disorders, demonstrating reduced PV (SZ), SST (BP), and VIP mRNA (SZ and BP). Dorsal posterior cingulate (dPCC) displayed decreased SST (BP) whereas retrosplenial cortex (RSC) showed reduced PV (SZ and BP) and SST mRNA (BP). Our results show shared and unique transcription signatures of two disorders in specific cingulate gyrus regions and cell types. SZ and BP show a similar profile of aMCC gene expression reductions suggesting subregional dysregulation within areas associated with error/action monitoring and the saliency network. In dPCC/RSC, transcriptional changes are associated with disease-specific gene/subregion signatures, possibly underlying differential effects on allocation of attentional resources and visuospatial memory processing unique to each disorder.
... The observed reduction in SC-FC coupling in the limbic network and default mode network during baseline may indicate pathophysiological alterations that are linked to schizophrenia. Prior research has linked both networks to this disorder(Hua et al., 2020;Salgado-Pineda et al., 2011). ...
Auditory verbal hallucinations (AVH) are distinctive clinical manifestations of schizophrenia. While low‐frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated potential in mitigating AVH, the precise mechanisms by which it operates remain obscure. This study aimed to investigate alternations in structural connectivity and functional connectivity (SC‐FC) coupling among schizophrenia patients with AVH prior to and following treatment with 1 Hz rTMS that specifically targets the left temporoparietal junction. Initially, patients exhibited significantly reduced macroscopic whole brain level SC‐FC coupling compared to healthy controls. Notably, SC‐FC coupling increased significantly across multiple networks, including the somatomotor, dorsal attention, ventral attention, frontoparietal control, and default mode networks, following rTMS treatment. Significant alternations in SC‐FC coupling were noted in critical nodes comprising the somatomotor network and the default mode network, such as the precentral gyrus and the ventromedial prefrontal cortex, respectively. The alternations in SC‐FC coupling exhibited a correlation with the amelioration of clinical symptom. The results of our study illuminate the intricate relationship between white matter structures and neuronal activity in patients who are receiving low‐frequency rTMS. This advances our understanding of the foundational mechanisms underlying rTMS treatment for AVH.
... However, advancements in neuroimaging techniques, particularly the utilization of voxelbased morphometry (VBM) [62], have expanded the scope of investigation to include a comprehensive analysis of multiple brain regions, such as the diencephalon, midbrain, and cerebellum. The efficacy of VBM has been substantiated in the examination of various neurological and psychiatric conditions, including schizophrenia [73], aging, and Alzheimer's disease [74]. ...
Alcohol-related cognitive disorders have long been an area of study, yet they continue to pose challenges in the diagnosis, treatment, and understanding of underlying neuropsychiatric mechanisms. The present article offers a comprehensive review of Wernicke’s Encephalopathy and Korsakoff’s Syndrome, two conditions often seen on a continuum of alcohol-related brain damage. Drawing on current medical literature, neuroimaging studies, and clinical case reports, we explore the neuropsychiatric and neuropsychological profiles, symptomatology, and differential diagnoses of these disorders. We delve into the biochemical pathways implicated in the development of WE and KS, notably thiamine deficiency and its impact on neurotransmitter systems and neural networks. The article also addresses the challenges in early diagnosis, often complicated by non-specific symptoms and co-occurring psychiatric conditions. Furthermore, we review the current state of treatment protocols, including pharmacological and non-pharmacological interventions. Finally, the article highlights gaps in current knowledge and suggests directions for future research to improve diagnosis, treatment, and patient outcomes. Understanding the nuanced interplay between the neuropsychiatric and neuropsychological aspects of WE and KS is crucial for both clinicians and researchers alike, in order to provide effective treatment and to advance our understanding of these complex conditions.
... A specific network connectivity change thought to be particularly impactful on the symptoms of psychosis is the loss of negative connectivity, i.e., decreased anticorrelation, between the DMN and CEN [28]. In healthy participants, task-triggered switching from an active DMN to an active CEN is observed, while impaired deactivation, or suppression, of the DMN has been found across multiple tasks in patients with schizophrenia [29][30][31]. The salience network, particularly the anterior insula, has been found to mediate switching between the DMN and CEN [32]. ...
Purpose of review
This review uses a dysconnectivity-based lens for understanding schizophrenia pathophysiology. From this vantage recent studies on the clinical utility of transcranial magnetic stimulation in schizophrenia are consolidated, with particular attention to studies reporting resting-state network functional connectivity (FC) changes after treatment.
Recent findings
In schizophrenia, functional connectivity is predominantly decreased across brain regions and functional networks. Specific networks implicated in symptomatology include the default mode network and central executive network. TMS modalities which increase functional connectivity, particularly when targeting the dorsolateral PFC, have shown relative efficacy in treating negative symptoms of schizophrenia. However, post-treatment changes in specific network connectivity vary by study design and by degree of concordance with symptom improvement.
Summary
Generally, increased functional connectivity between brain networks seems to confer some benefit of TMS in schizophrenia, particularly for negative symptoms. Among studies conducted thus far, there has been substantial variation in both target selection and observed post-treatment connectivity changes. While there is convincing evidence for pathological DMN-CEN connectivity in the disease process of schizophrenia, as well as evidence that dlPFC-targeted TMS modulates the DMN-CEN in depression, restoration of this particular network aberrancy by TMS in schizophrenia has not been observed.
... The SCG was selected as the second target, following a growing neurobiological reasoning that describes, in schizophrenia-related executive functions tasks, poor activation of the anterior node of the default mode network (Pomarol-Clotet et al., 2010) and a deactivation deficit in SCG (Salgado-Pineda et al., 2011). This node included consistently the SCG (Cg25) in tractography and connectomic studies (Corripio et al., 2022;Mikell et al., 2016;Fornito et al., 2013;Li et al., 2020;Ellison-Wright and Bullmore, 2009). ...
Background:
Schizophrenia is a complex and disabling disorder. Around 30% of patients have treatment-resistant schizophrenia (TRS).
Objective:
This study summarizes the outcomes after three years follow-up of the first series of patients with TRS treated with deep brain stimulation (DBS) and discuss surgical, clinical and imaging analysis.
Methods:
Eight patients with TRS treated with DBS in the nucleus accumbens (NAcc) or the subgenual cingulate gyrus (SCG) were included. Symptoms were rated with the PANSS scale and normalized using the illness density index (IDI). A reduction in IDI-PANSS of ≥25% compared to baseline was the criterion of good response. The volume of activated tissue was calculated to perform a connectomic analysis for each patient. An estimation of the tracts and cortical areas modulated was generated.
Results:
Five women and three men were analyzed. After 3 years' follow-up, positive symptoms improved in 50% of the SCG group and 75% of the NAcc group (p = 0.06), and general symptoms improved in 25% and 50% respectively (p = 0.06). The SCG group showed activation of the cingulate bundle and modulation of orbitofrontal and frontomesial regions; in contrast, the NAcc group showed activation of the ventral tegmental area projections pathway and modulation of regions associated with the "default mode network" (precuneus) and Brodmann areas 19 and 20.
Conclusions:
These results showed a trend toward improvement for positive and general symptoms in patients with TRS treated with DBS. The connectomic analysis will help us understand the interaction of this treatment with the disease to pursue future trial designs.
... 13 However, the coordinated interaction among these networks is affected in schizophrenia. 14 When performing WM tasks, patients tend to show non-suppression of the DMN 15,16 with disrupted anticorrelation with the task-positive network. [17][18][19][20] At the whole-brain connectome level, patients display an inefficient topological profile with increased segregation of brain networks with a shift in the degree distribution towards a more homogeneous form of connectivity, associated with reduced WM performance. ...
Background and hypothesis:
The integration of information that typifies working memory (WM) operation requires a flexible, dynamic functional relationship among brain regions. In schizophrenia, though WM capacity is prominently impaired at higher loads, the mechanistic underpinnings are unclear. As a result, we lack convincing cognitive remediation of load-dependent deficits. We hypothesize that reduced WM capacity arises from a disruption in dynamic functional connectivity when patients face cognitive demands.
Study design:
We calculate the dynamic voxel-wise degree centrality (dDC) across the functional connectome in 142 patients with schizophrenia and 88 healthy controls (HCs) facing different WM loads during an n-back task. We tested associations of the altered variability in dDC and clinical symptoms and identified intermediate connectivity configurations (clustered states) across time during WM operation. These analyses were repeated in another independent dataset of 169 subjects (102 with schizophrenia).
Study results:
Compared with HCs, patients showed an increased dDC variability of supplementary motor area (SMA) for the "2back vs. 0back" contrast. This instability at the SMA seen in patients correlated with increased positive symptoms and followed a limited "U-shape" pattern at rest-condition and 2 loads. In the clustering analysis, patients showed reduced centrality in the SMA, superior temporal gyrus, and putamen. These results were replicated in a constrained search in the second independent dataset.
Conclusions:
Schizophrenia is characterized by a load-dependent reduction of stable centrality in SMA; this relates to the severity of positive symptoms, especially disorganized behaviour. Restoring SMA stability in the presence of cognitive demands may have a therapeutic effect in schizophrenia.
... It is widely considered to reflect dysfunction of the default mode network [29,30], a set of brain regions, including the medial frontal cortex, the posterior cingulate cortex/precuneus and the angular gyrus, that are normally active at rest but which de-activate during performance of a wide range of attention-demanding tasks. While failure of de-activation in schizophrenia has been most commonly been found to affect the medial frontal cortex, it has also been found in the posterior cingulate cortex/precuneus in some studies [31,32]. What distinguishes the sentence condition is presence of sentential meaning, i.e., the fact that thoughts are expressed. ...
The experience of auditory verbal hallucinations (AVH, "hearing voices") in schizophrenia has been found to be associated with reduced auditory cortex activation during perception of real auditory stimuli like tones and speech. We re-examined this finding using 46 patients with schizophrenia (23 with frequent AVH and 23 hallucination-free), who underwent fMRI scanning while they heard words, sentences and reversed speech. Twenty-five matched healthy controls were also examined. Perception of words, sentences and reversed speech all elicited activation of the bilateral superior temporal cortex, the inferior and lateral prefrontal cortex, the inferior parietal cortex and the supplementary motor area in the patients and the healthy controls. During the sentence and reversed speech conditions, the schizophrenia patients as a group showed reduced activation in the left primary auditory cortex (Heschl's gyrus) relative to the healthy controls. No differences were found between the patients with and without hallucinations in any condition. This study therefore fails to support previous findings that experience of AVH attenuates speech-perception-related brain activations in the auditory cortex. At the same time, it suggests that schizophrenia patients, regardless of presence of AVH, show reduced activation in the primary auditory cortex during speech perception, a finding which could reflect an early information processing deficit in the disorder.
... It has also been reported as the strongest contributor to the structural differences in communities [42]. Most importantly, this dysfunction of functional connectivity in DMN is associated with positive symptoms in clinical symptoms, including delusions and hallucinations [43]. Therefore, schizophrenia is related to changes in the time frequency and spatial location of the DMN. ...
Research has shown that abnormal brain networks in patients with schizophrenia appear at different frequencies, but the relationship between these different frequencies is unclear. Therefore, it is necessary to use a multilayer network model to evaluate the integration of information from different frequency bands. To explore the mechanism of integration and separation in the multilayer network of schizophrenia, we constructed multilayer frequency brain network models in 50 patients with schizophrenia and 69 healthy subjects, and the entropy of the multiplex degree (EMD) and multilayer clustering coefficient (MCC) were calculated. The results showed that the ability to integrate and separate information in the multilayer network of patients was significantly higher than that of normal people. This difference was mainly reflected in the default mode network, sensorimotor network, subcortical network, and visual network. Among them, the subcortical network was different in both MCC and EMD outcomes. Furthermore, differences were found in the posterior cingulate gyrus, hippocampus, amygdala, putamen, pallidum, and thalamus. The thalamus and posterior cingulate gyrus were associated with the patient’s symptom scores. Our results showed that the cross-frequency interaction ability of patients with schizophrenia was significantly enhanced, among which the subcortical network was the most active. This interaction may serve as a compensation mechanism for intralayer dysfunction.
... 70 A more recent wave of studies has also documented a third functional imaging abnormality-failure of deactivation in the medial frontal cortex during cognitive task performance. [74][75][76][77][78][79][80] Occasional negative findings 81,82 or reports of increased deactivation [81][82][83][84] have not prevented failure of medial frontal cortex deactivation from becoming well accepted. ...
Schizophrenia, characterised by psychotic symptoms and in many cases social and occupational decline, remains an aetiological and therapeutic challenge. Contrary to popular belief, the disorder is modestly more common in men than in women. Nor is the outcome uniformly poor. A division of symptoms into positive, negative, and disorganisation syndromes is supported by factor analysis. Catatonic symptoms are not specific to schizophrenia and so-called first rank symptoms are no longer considered diagnostically important. Cognitive impairment is now recognised as a further clinical feature of the disorder. Lateral ventricular enlargement and brain volume reductions of around 2% are established findings. Brain functional changes occur in different subregions of the frontal cortex and might ultimately be understandable in terms of disturbed interaction among large-scale brain networks. Neurochemical disturbance, involving dopamine function and glutamatergic N-methyl-D-aspartate receptor function, is supported by indirect and direct evidence. The genetic contribution to schizophrenia is now recognised to be largely polygenic. Birth and early life factors also have an important aetiological role. The mainstay of treatment remains dopamine receptor-blocking drugs; a psychological intervention, cognitive behavioural therapy, has relatively small effects on symptoms. The idea that schizophrenia is better regarded as the extreme end of a continuum of psychotic symptoms is currently influential. Other areas of debate include cannabis and childhood adversity as causative factors, whether there is progressive brain change after onset, and the long-term success of early intervention initiatives.
... For instance, Fornito et al. (2009) found by a meta-analysis of 37 studies that people with schizophrenia showed widespread loss of GM in the frontal lobe and limbic and subcortical areas. In particular, decreased GM volume in the default mode network (DMN) and visual network (VIS) were also reported in schizophrenia (Chatterjee et al., 2020;Salgado-Pineda et al., 2011). In addition, the GM networks of schizophrenia patients manifested as a decreased degree of connectivity in the frontal lobe (Tijms et al., 2015) and decreased efficiency in the superior occipital gyrus . ...
Schizophrenia is often regarded as a psychiatric disorder caused by disrupted connections in the brain. Evidence suggests that the gray matter of schizophrenia patients is damaged in a modular pattern. Recently, abnormal topological organization was observed in the gray matter networks of patients with schizophrenia. However, the modular-level alteration of gray matter networks in schizophrenia remains unclear. In this study, single-subject gray matter networks were constructed for a total of 217 subjects (116 patients with schizophrenia and 101 controls). We analyzed the topological characteristics of the brain network and the strengths of connections between and within modules. Compared with the outcomes in the control group, the global efficiency and participation coefficient values of the single-subject gray matter networks in schizophrenic patients were significantly reduced. The nodal participation coefficient of the regions involving the frontoparietal attention network, default mode network and subcortical network were significantly decreased in subjects with schizophrenia. The intermodule connections between the frontoparietal attention network and visual network and between the default mode network and subcortical network, in the frontoparietal attention network were significantly reduced in the patient group. In the frontoparietal attention network, the intramodule nodal connection strength of the left orbital inferior frontal gyrus and right inferior parietal gyrus was significantly decreased in schizophrenia patients. Reduced intermodule nodal connection strength between the frontoparietal attention network and visual network was associated with the severity of schizophrenia symptoms. These findings suggest that abnormal intramodule and intermodule connections in the structural brain network may a biomarker of schizophrenia symptoms.
... Another functional imaging abnormality that has been found in schizophrenia is failure of the de-activation during performance of attention-demanding tasks. First reported using the n-back working memory task (Pomarol-Clotet et al., 2008;Whitfield-Gabrieli et al., 2009), failure of de-activation in the medial frontal cortex, and also in the posterior cingulate cortex/precuneus in some studies, has since been found with a range of other tasks (Haatveit et al., 2016;Mannell et al., 2010;Salgado-Pineda et al., 2011;Schneider et al., 2011; for a review see (Hu et al., 2017)). This failure of de-activation is widely considered to reflect dysfunction of the default mode network, a set of brain regions that are normally active at rest but which de-activate during performance of a wide range of cognitive tasks (Buckner et al., 2008;Gusnard and Raichle, 2001;Raichle et al., 2001). ...
The Stroop task, which examines an aspect of executive function/cognitive control, the ability to inhibit prepotent responses, has been relatively little examined in schizophrenia, and the findings have been inconsistent. Whether performance of this task is associated with failure of de-activation in the disorder is also uncertain. We examined 42 schizophrenic patients and 61 healthy controls during performance of an fMRI-adapted version of the Stroop task, the counting Stroop task. Task-related activations (incongruent > congruent condition) and de-activations (baseline > incongruent) were examined using whole-brain, voxel-based methods. In the healthy controls, task performance was found to be associated with activations in the left dorsolateral prefrontal cortex and the dorsal anterior cingulate cortex, among other regions. De-activations were seen in the medial frontal cortex, the middle and posterior cingulate gyrus and cuneus, the parahippocampal gyrus and the hippocampus. The schizophrenic patients did not show reduced activation compared to the healthy controls. They did, however, show failure of de-activation in the medial frontal cortex. Our negative finding with respect to hypoactivation during performance of a task requiring inhibition of prepotent responses suggests that brain functional abnormality in schizophrenia may not affect all aspects of executive function/cognitive control. The finding of medial frontal cortex failure of de-activation adds to existing findings of default mode network dysfunction in the disorder.
... Some reports indicate that, compared to healthy controls, patients with schizophrenia have structural abnormalities within the CEN, including reduced volume in the lateral PFC as well as in posterior areas of the parietal lobes [61] and reduced integrity of the nerve fibers connecting these areas [62]. Other reports show that structural abnormalities are present also in the cortical areas [63] and connections [64] of the DMN. Finally, there are reports of structural abnormalities in the anterior cingulate and insula [65] and the integrity of nerve fibers connecting the brain areas [66] that constitute the SN. ...
In recent years, interest has grown in measuring executive function in schizophrenia with ecological and virtual reality (VR) tools. However, there is a lack of critical analysis comparing those tools with traditional ones. This paper aims to characterize executive dysfunction in schizophrenia by comparing ecological and virtual reality assessments with traditional tools, and to describe the neurobiological and psychopathological correlates. The analysis revealed that ecological and VR tests have higher levels of verisimilitude and similar levels of veridicality compared to traditional tools. Both negative symptoms and disorganization correlate significantly with executive dysfunction as measured by traditional tools, but their relationships with measures based on ecological and VR methods are still unclear. Although there is much research on brain correlates of executive impairments in schizophrenia with traditional tools, it is uncertain if these results will be confirmed with the use of ecological and VR tools. In the diagnosis of executive dysfunction, it is important to use a variety of neuropsychological methods—especially those with confirmed ecological validity—to properly recognize the underlying characteristics of the observed deficits and to implement effective forms of therapy.
... The DMN, SVN, and VN have shown significantly reduced small worldness in the patient group when compared to the control group. Involvement of the structural and functional abnormality of the DMN has been thought to be one of the most important candidates for the neural basis of schizophrenia [45][46][47]. This abnormality of the DMN is thought to be related to various domains of the illness, including the level of positive symptoms [48], social functioning [49,50], and the long-term clinical outcome [51]. ...
Anhedonia is one of the major negative symptoms in schizophrenia and defined as the loss of hedonic experience to various stimuli in real life. Although structural magnetic resonance imaging has provided a deeper understanding of anhedonia-related abnormalities in schizophrenia, network analysis of the grey matter focusing on this symptom is lacking. In this study, single-subject grey matter networks were constructed in 123 patients with schizophrenia and 160 healthy controls. The small-world property of the grey matter network and its correlations with the level of physical and social anhedonia were evaluated using graph theory analysis. In the global scale whole-brain analysis, the patients showed reduced small-world property of the grey matter network. The local-scale analysis further revealed reduced small-world property in the default mode network, salience/ventral attention network, and visual network. The regional-level analysis showed an altered relationship between the small-world properties and the social anhedonia scale scores in the cerebellar lobule in patients with schizophrenia. These results indicate that anhedonia in schizophrenia may be related to abnormalities in the grey matter network at both the global whole-brain scale and local–regional scale.
... Thus, once again, the data suggest that pivotal brain areas that contribute significantly to EFs, such as PFC, ACC, and basal ganglia, act within spatially distributed networks and include other structures that may also be relevant to explain EFs. This point is echoed in studies of neuropsychiatric disorders that exhibit impairments in EFs, and that reveal aberrant development and functional connectivity in spatially distributed brain networks (Assaf et al., 2010;Baker et al., 2014;Bassett et al., 2012;Cerliani et al., 2015;Chai et al., 2011;Cherkassky et al., 2006;dos Santos Siqueira et al., 2014;Du et al., 2016;Fan et al., 2012;Fassbender et al., 2009;Franzen et al., 2013;Garrity et al., 2007;Hull et al., 2017;Itahashi et al., 2014;Jafri et al., 2008;Jang et al., 2011;Liddle et al., 2011;Lin et al., 2015;Manoliu et al., 2014;Meda et al., 2014;Murias et al., 2007;Ö ngür et al., 2010;Orliac et al., 2013;Paakki et al., 2010;Pomarol-Clotet et al., 2008;Roiser et al., 2013;Rotarska-Jagiela et al., 2010;Salgado-Pineda et al., 2011;Sripada et al., 2014;Sun et al., 2014;Swanson et al., 2011;Tian et al., 2008;Tu et al., 2013;Uddin et al., 2008;van Buuren et al., 2012;Wang et al., 2005;Weng et al., 2010;Whitfield-Gabrieli et al., 2009;Wilson et al., 2011;Woodward et al., 2011). ...
“Executive functions” (EFs) is an umbrella term for higher cognitive control functions such as working memory, inhibition, and cognitive flexibility. One of the most challenging problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to a breakthrough in understanding how the brain controls and regulates itself. We propose to re-conceptualize EFs as emergent consequences of highly distributed brain processes that communicate with a pool of highly connected hub regions, thus precluding the need for a central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and helps to refine our understanding of the mechanisms underlying EFs by providing new, testable hypotheses and resolves empirical and theoretical inconsistencies in the EF literature.
... The DMN has been a focus of imaging research into neuropsychiatric disorders, including schizophrenia (Alonso-Solis et al., 2015;Garrity et al., 2007;Hu et al., 2017;Salgado-Pineda et al., 2011;Zhao et al., 2018). The most common finding in recent studies is hyperconnectivity within the DMN in patients with schizophrenia, compared to healthy controls (Hu et al., 2017;Liu et al., 2012;Whitfield-Gabrieli et al., 2009). ...
Background
A dysfunctional default mode network (DMN) has been reported in patients with schizophrenia. However, the stability of the deficits has not been determined across different stages of the disorder.
Methods
We examined the functional connectivity of the DMN subsystems of 125 patients with first-episode schizophrenia (FES) or recurrent schizophrenia (RES), compared to that of 82 healthy controls. We tested the robustness of the findings in an independent cohort of 158 patients and 39 healthy controls. We performed resting-state functional connectivity analysis, and examined the strength of the connections within and between the three subsystems of the DMN (core, dorsal medial prefrontal cortex [dMPFC], and medial temporal lobe [MTL]). We also analyzed the connectivity correlations to symptoms and illness duration.
Results
We found reduced connectivity strength between the core and MTL subsystems in schizophrenia patients compared to controls, with no differences between the FES and RES patient groups; these findings were validated in the second sample. Schizophrenia patients also showed a significant reduction in connectivity within the MTL and between the dMPFC−MTL subsystems, similarly between FES and RES groups. The connectivity strength within the core subsystem was negatively correlated with clinical symptoms in schizophrenia. There was no significant correlation between the DMN subsystem connectivity and illness duration.
Conclusions
DMN subsystem connectivity deficits are present in schizophrenia, and the homochronicity of their appearance indicates the trait-like nature of these alterations. The DMN deficit may be useful for early diagnosis, and MTL dysfunction may be a crucial mechanism underlying schizophrenia.
... DMN is also critical for retrieval of episodic memory [70,[120][121][122][123] and altered connectivity has been observed in patients with Alzheimer's disease [70,[124][125][126][127][128]. Altered DMN connectivity, and the subsequent inability to deactivate it for cognitive tasks, has also been observed in patients with schizophrenia [129,130], depression [131][132][133], epilepsy [134][135][136], multiple sclerosis [137], Autism Spectrum ...
Collision sports athletes experience many head acceleration events (HAEs) per season. The effects of these subconcussive events are largely understudied since HAEs may produce no overt symptoms, and are likely to diffusely manifest across multiple scales of study (e.g., molecular, cellular network, and behavior). This study integrated resting-state fMRI with metabolome, transcriptome and computational virtual reality (VR) behavior measures to assess the effects of exposure to HAEs on players in a collegiate American football team. Permutation-based mediation and moderation analysis was used to investigate relationships between network fingerprint, changes in omic measures and VR metrics over the season. Change in an energy cycle fatty acid, tridecenedioate, moderated the relationship between 1) miR-505 and DMN fingerprint and 2) the relationship between DMN fingerprint and worsening VR Balance measures (all p less than or equal to 0.05). In addition, the similarity in DMN over the season was negatively related to cumulative number of HAEs above 80G, and DMN fingerprint was less similar across the season in athletes relative to age-matched non-athletes. miR-505 was also positively related to average number of HAEs above 25G per session. It is important to note that tridecenedioate has a double bond making it a candidate for ROS scavenging. These findings between a candidate ROS-related metabolite, inflammatory miRNA, altered brain imaging and diminished behavioral performance suggests that impact athletes may experience chronic neuroinflammation. The rigorous permutation-based mediation/moderation may provide a methodology for investigating complex multi-scale biological data within humans alone and thus assist study of other functional brain problems.
... At baseline, greater DMN BOLD response was observed in SZ compared to HC in the posterior cingulate cortex and the precuneus. Our results are consistent with previous findings of DMN hyper-activation in SZ across a variety of cognitive tasks (70)(71)(72)(73). ...
There is no pharmacological treatment to remediate cognitive impairment in schizophrenia (SZ). It is imperative to characterize underlying pathologies of memory processing in order to effectively develop new treatments. In this longitudinal study, we combined functional magnetic resonance imaging during a memory encoding task with proton MR spectroscopy to measure hippocampal glutamate + glutamine (Glx). Seventeen SZ were scanned while unmedicated and after 6 weeks of treatment with risperidone and compared to a group of matched healthy controls (HC) scanned 6 weeks apart. Unmedicated patients showed reduced blood oxygen level dependent (BOLD) response in several regions, including the hippocampus, and greater BOLD response in regions of the default mode network (DMN) during correct memory encoding. Post hoc contrasts from significant group by time interactions indicated reduced hippocampal BOLD response at baseline with subsequent increase following treatment. Hippocampal Glx was not different between groups at baseline, but at week 6, hippocampal Glx was significantly lower in SZ compared to HC. Finally, in unmedicated SZ, higher hippocampal Glx predicted less deactivation of the BOLD response in regions of the DMN. Using 2 brain imaging modalities allowed us to concurrently investigate different mechanisms involved in memory encoding dysfunction in SZ. Hippocampal pathology during memory encoding stems from decreased hippocampal recruitment and faulty deactivation of the DMN, and hippocampal recruitment during encoding can be modulated by antipsychotic treatment. High Glx in unmedicated patients predicted less deactivation of the DMN; these results suggest a mechanism by which faulty DMN deactivation, a hallmark of pathological findings in SZ, is achieved.
... Recent studies found that SHR (ADHD) children usually exhibit abnormal DMN network 32 . It has also been reported that mental disorder such as Alzheimer 33,34 , depression 35 , schizophrenia 36 , and ASD 37 can render DMN abnormal. It remains a pressing task to clarify whether the transition of double powers to single power correlates with abnormal DMN. ...
In the past two decades neuroscience has offered many popular methods for the analysis of mental disorder, such as seed-based analysis, ICA, and graph methods. They are widely used in the study of brain network. We offer a new procedure that can simplify the analysis and has a high ROC index over 0.9. This method uses the graph theory to build a connectivity network, which is characterized by degrees and measures the number of effective links for each voxel. When the degree is ranked from low to high, the network equation can be fit by the power-law distribution. It has been proposed that distinct and yet robust exponents of the power law can differentiate human behavior. Using the mentally disordered SHR and WKY rats as samples, we employ chi2 algorithm and Decision Tree to classify different states of mental disorder by analyzing different traits in degree of connectivity.
... Thus, adequate balance between these intrinsic networks seems necessary for adaptive cognitive functioning, and a failure in its regulation might be linked to psychiatric symptoms. Alterations in the DMN are well-established in schizophrenia (Dreher et al., 2012;Haatveit et al., 2016;Pomarol-Clotet et al., 2008;Salgado-Pineda et al., 2011;Schneider et al., 2011). Some authors have proposed that there is a stable difference in the DMN structure and its connections with the salience network and the central executive network (Menon, 2011;Woodward et al., 2011). ...
Background:
An alteration in self/other differentiation has been proposed as a basis for several symptoms in schizophrenia, including delusions of reference and social functioning deficits. Dysfunction of the right temporo-parietal junction (TPJ), a region linked with social cognition, has been proposed as the basis of this alteration. However, imaging studies of self- and other-processing in schizophrenia have shown, so far, inconsistent results.
Methods:
Patients with schizophrenia and healthy controls underwent fMRI scanning while performing a task with three conditions: self-reflection, other-reflection and semantic processing.
Results:
Both groups activated similar brain regions for self- and other-reflection compared to semantic processing, including the medial prefrontal cortex, the precuneus and the TPJ. Compared to healthy subjects, patients hyperactivated the left lateral frontal cortex during self- and other-reflection. In other-reflection, compared to self-reflection, patients failed to increase right TPJ activity.
Conclusions:
Altered activity in the right TPJ supports a disturbance in self/other differentiation in schizophrenia, which could be linked with psychotic symptoms and affect social functioning in patients. Hyperactivity of the lateral frontal cortex for self- and other-reflection suggests the presence of greater cognitive demand to perform the task in the patient group.
... Moreover, a recent study found that the DMN interacted with the central executive network and the salience network in smoking schizophrenia patients, indicating the potential role of the DMN in the symptomatology of the disorder (Liao et al., 2018). At the same time, the structural and functional alterations in the DMN in schizophrenia patients have been shown to be related to impairment in working memory and attention (Garrity et al., 2007;Hu et al., 2017;Pomarol-Clotet et al., 2008;Salgado-Pineda et al., 2011;Whitfield-Gabrieli & Ford, 2012). Previous studies have also suggested that the fusiform gyrus and the temporal lobe may be discriminative features for classification Tang et al., 2012). ...
Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging research. However, direct replication studies and studies seeking to investigate generalizability are scarce. To address these issues, we assessed within-site and between-site generalizability of a machine learning classification framework which achieved excellent performance in a previous study using two independent resting-state functional magnetic resonance imaging data sets collected from different sites and scanners. We established within-site generalizability of the classification framework in the main data set using cross-validation. Then, we trained a model in the main data set and investigated between-site generalization in the validated data set using external validation. Finally, recognizing the poor between-site generalization performance, we updated the unsupervised algorithm to investigate if transfer learning using additional unlabeled data were able to improve between-site classification performance. Cross-validation showed that the published classification procedure achieved an accuracy of 0.73 using majority voting across all selected components. External validation found a classification accuracy of 0.55 (not significant) and 0.70 (significant) using the direct and transfer learning procedures, respectively. The failure of direct generalization from one site to another demonstrates the limitation of within-site cross-validation and points toward the need to incorporate efforts to facilitate application of machine learning across multiple data sets. The improvement in performance with transfer learning highlights the importance of taking into account the properties of data when constructing predictive models across samples and sites. Our findings suggest that machine learning classification result based on a single study should be interpreted cautiously.
... Results always show the activation of a set of regions including medial prefrontal and parietal cortex, and posterior temporo-parietal areas around the temporo-parietal junction Frith, 2006, 2007), a network of areas largely overlapping with the DMN (e.g., Mars et al., 2012). In particular, the left parietal and posterior midline nodes of the DMN are involved in processing emotional facial expressions, both in healthy individuals (Sreenivas et al., 2012) and in patients with different psychopathological conditions including social phobia (Gentili et al., 2009) and schizophrenia (Salgado-Pineda et al., 2011). Schilbach et al. (2008) explored the relationship between the neural basis for social cognition and the DMN, and found that the core nodes of the DMN overlap with those involved in social cognition (Vogeley and Fink, 2003;Schilbach et al., 2006). ...
Major adverse events, like an earthquake, trigger different kinds of emotional dysfunctions or psychiatric disorders in the exposed subjects. Recent literature has also shown that exposure to natural disasters can increase threat detection. In particular, we previously found a selective enhancement in the ability to read emotional facial expressions in L’Aquila earthquake witnesses, suggesting hypervigilance to stimuli signaling a threat. In light of previous neuroimaging data showing that trauma exposure is related to derangement of resting-state brain activity, in the present study we investigated the neurofunctional changes related to the recognition of emotional faces in L’Aquila earthquake witnesses. Specifically, we tested the relationships between accuracy in recognizing facial expressions and activity of the visual network (VN) and of the default-mode network (DMN). Resting-state functional connectivity (FC) with the main hub of the VN (primary, ventral, right-dorsal, and left-dorsal visual cortices) and DMN (posterior cingulate/precuneus, medial prefrontal, and right and left inferior parietal cortices) was investigated through a seed-based functional magnetic resonance imaging (fMRI) analysis in both earthquake-exposed subjects and non-exposed persons who did not live in an earthquake-affected area. The results showed that, in earthquake-exposed subjects, there is a significant reduction in the correlation between accuracy in recognizing facial expressions and the FC of the dorsal seed of the VN with the right inferior occipito-temporal cortex and the left lateral temporal cortex, and of two parietal seeds of DMN, i.e., lower parietal and medial prefrontal cortex, with the precuneus bilaterally. These findings suggest that a functional modification of brain systems involved in detecting and interpreting emotional faces may represent the neurophysiological basis of the specific “emotional expertise” observed in the earthquake witnesses.
... This latter abnormality, affecting particularly the medial frontal cortex, has been documented in schizophrenia (e.g. Pomarol-Clotet et al., 2008;Mannell et al., 2010;Whitfield-Gabrieli et al., 2009;Salgado-Pineda et al., 2011;Schneider et al., 2011;Dreher et al., 2012) and major affective disorder, including both major depression (Broyd et al., 2009;Grimm et al., 2009;Marchetti et al., 2012) and bipolar disorder (Pomarol-Clotet et al., 2012;Fernández-Corcuera et al., 2013). A not-dissimilar pattern of de-activation failure has also been described in autism (Kennedy and Courchesne, 2008;Spencer et al., 2012). ...
Background
Although executive and other cognitive deficits have been found in patients with borderline personality disorder (BPD), whether these have brain functional correlates has been little studied. This study aimed to examine patterns of task-related activation and de-activation during the performance of a working memory task in patients with the disorder.
Methods
Sixty-seven DSM-IV BPD patients and 67 healthy controls underwent fMRI during the performance of the n -back task. Linear models were used to obtain maps of within-group activations and areas of differential activation between the groups.
Results
On corrected whole-brain analysis, there were no activation differences between the BPD patients and the healthy controls during the main 2-back v. baseline contrast, but reduced activation was seen in the precentral cortex bilaterally and the left inferior parietal cortex in the 2-back v. 1-back contrast. The patients showed failure of de-activation affecting the medial frontal cortex and the precuneus, plus in other areas. The changes did not appear to be attributable to previous history of depression, which was present in nearly half the sample.
Conclusions
In this study, there was some, though limited, evidence for lateral frontal hypoactivation in BPD during the performance of an executive task. BPD also appears to be associated with failure of de-activation in key regions of the default mode network.
... Recently, magnetic resonance has been developed rapidly in neurosciences, which is divided into structural and functional types, and widely applied in various investigations of nerve and mental disorders, such as schizophrenia, [8] Alzheimer's disease (AD), [9] and epilepsy. [10] Using these magnetic resonance techniques in PI is useful for further exploring the disease as well as clinical application. ...
The aim of the study was to study the changes in brain structure and functional connectivity in primary insomnia (PI) patients, as well as to explore the biological characteristics of PI abnormality and the pathophysiological mechanism underlying the brain structure and the abnormal functional connectivity under depression.
Voxel-based morphometry (VBM) technique and resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) techniques were used to investigate the brain structure and rs-fc in PI and light-moderate primary insomnia with depression (PID) patients; healthy individuals were used as the normal control (NC) group. The differences between the 3 groups, the correlation between the brain network connection of the anterior cingulate cortex (ACC), and clinical information were compared.
Compared with the NC group, patients in PI and PID groups showed changes in brain structure and brain functional connectivity, which might be related to the pathophysiological mechanism of primary insomnia. PI patients had enhanced connections in the left anterior cingulate cortex/insula, left posterior cingulate, and the right limbic lobe/cingulate gyrus/paracingulate gyrus with ACC. Compared with PI patients, PID patients had weaker brain functional connectivity in the left corpus callosum/posterior cingulate with ACC and enhanced functional connectivity in the frontal and limbic lobes with ACC, suggesting that PI patients with depression had abnormal brain network connection.
Primary insomnia has abnormalities in intracephalic multisystem structure and neural network connection. The interaction and influence between depression and insomnia aggravate the cognitive function damage. This study provided the theoretical basis for exploring the neuropathology underlying the PID disorder and cognitive function.
... 33 Supporting this suggestion, deactivation of regions considered to be part of the DMN during encoding of novel information has been found to be associated with successful retrieval of the learned information while a reduction or failure to deactivate DMN regions has been linked with worsened memory performance. 36 Failure to deactivate DMN regions has also been reported in several neurological disorders that impact cognitive function such as AD 37,38 and depression. 39,40 Our findings reinforce the view that there are differences between BDNF Val66Met genetic groups within cognitive networks. ...
Introduction
Medial temporal lobe epilepsy (mTLE) is the most common refractory focal epilepsy in adults. Around 30%‐40% of patients have prominent memory impairment and experience significant postoperative memory and language decline after surgical treatment. BDNF Val66Met polymorphism has also been associated with cognition and variability in structural and functional hippocampal indices in healthy controls and some patient groups.
Aims
We examined whether BDNF Val66Met variation was associated with cognitive impairment in mTLE.
Methods
In this study, we investigated the association of Val66Met polymorphism with cognitive performance (n = 276), postoperative cognitive change (n = 126) and fMRI activation patterns during memory encoding and language paradigms in 2 groups of patients with mTLE (n = 37 and 34).
Results
mTLE patients carrying the Met allele performed more poorly on memory tasks and showed reduced medial temporal lobe activation and reduced task‐related deactivations within the default mode networks in both the fMRI memory and language tasks than Val/Val patients.
Conclusions
Although cognitive impairment in epilepsy is the result of a complex interaction of factors, our results suggest a role of genetic factors on cognitive impairment in mTLE.
... Integration of modalities is an attractive strategy to follow in the development of a comprehensive map of the pathophysiological brain networks of fatigue. This multimodal approach has demonstrated a more comprehensive understanding of brain changes in disorders such as amyotrophic lateral sclerosis [146], schizophrenia [147][148][149][150][151][152][153][154][155][156][157], bipolar disorder [158][159][160][161], characterization of tumours [162], traumatic brain injury [163], Parkinson's disease [164], psychosis [165,166], Alzheimer's disease [167,168] and mild cognitive impairment [169][170][171]. Therefore, it should be expected that the integration of techniques may help to elucidate further brain mechanisms of fatigue. ...
While fatigue is prevalent in chronic diseases, the neural mechanisms underlying this symptom remain unknown. Magnetic resonance imaging (MRI) has the potential to enable us to characterize this symptom. The aim of this review was to gather and appraise the current literature on MRI studies of fatigue in chronic diseases. We systematically searched the following databases: MedLine, PsycInfo, Embase and Scopus (inception to April 2016). We selected studies according to a predefined inclusion and exclusion criteria. We assessed the quality of the studies and conducted descriptive statistical analyses. We identified 26 studies of varying design and quality. Structural and functional MRI, alongside diffusion tensor imaging (DTI) and functional connectivity (FC) studies, identified significant brain indicators of fatigue. The most common regions were the frontal lobe, parietal lobe, limbic system and basal ganglia. Longitudinal studies offered more precise and reliable analysis. Brain structures found to be related to fatigue were highly heterogeneous, not only between diseases, but also for different studies of the same disease. Given the different designs, methodologies and variable results, we conclude that there are currently no well-defined brain indicators of fatigue in chronic diseases.
... Thus, the lack of activation in the same-side vs. opposite-side contrast for the patient group, coupled with the increased activation in healthy volunteers, strongly implicates DMN dysregulation in psychosis and converges with prior work indicating a failure of DMN to deactivate during cognitive tasks in patients (Hasenkamp et al. 2011;Jeong and Kubicki 2010;D. I. Kim et al. 2009;Metzak et al. 2012;Salgado-Pineda et al. 2011). ...
Prior functional magnetic resonance imaging (fMRI) studies have investigated the neural mechanisms underlying cognitive control in patients with psychosis with findings of both hypo- and hyperfrontality. One factor that may contribute to inconsistent findings is the use of complex and polyfactorial tasks to investigate frontal lobe functioning. In the current study we employed a simple response conflict task during fMRI to examine differences in brain activation between patients experiencing their first-episode of psychosis (n = 33) and age- and sex-matched healthy volunteers (n = 33). We further investigated whether baseline brain activation among patients predicted changes in symptom severity and treatment response following 12 weeks of controlled antipsychotic treatment. During the task subjects were instructed to press a response button on the same side or opposite side of a circle that appeared on either side of a central fixation point. Imaging data revealed that for the contrast of opposite-side vs. same-side, patients showed significantly greater activation compared with healthy volunteers in the anterior cingulate cortex and intraparietal sulcus. Among patients, greater baseline anterior cingulate cortex, temporal-parietal junction, and superior temporal cortex activation predicted greater symptom reduction and therapeutic response following treatment. All findings remained significant after covarying for task performance. Intact performance on this relatively parsimonious task was associated with frontal hyperactivity suggesting the need for patients to utilize greater neural resources to achieve task performance comparable to healthy individuals. Moreover, frontal hyperactivity observed using a simple fMRI task may provide a biomarker for predicting treatment response in first-episode psychosis.
... Thus, the lack of activation in the same-side vs. opposite-side contrast for the patient group, coupled with the increased activation in healthy volunteers, strongly implicates DMN dysregulation in psychosis and converges with prior work indicating a failure of DMN to deactivate during cognitive tasks in patients (Hasenkamp et al. 2011;Jeong and Kubicki 2010;D. I. Kim et al. 2009;Metzak et al. 2012;Salgado-Pineda et al. 2011). ...
Prior functional magnetic resonance imaging (fMRI) studies have investigated the neural mechanisms underlying cognitive control in patients with psychosis with findings of both hypo- and hyperfrontality. One factor that may contribute to inconsistent findings is the use of complex and polyfactorial tasks to investigate frontal lobe functioning. In the current study we employed a simple response conflict task during fMRI to examine differences in brain activation between patients experiencing their first-episode of psychosis (n=33) and age-and sex-matched healthy volunteers (n=33). We further investigated whether baseline brain activation among patients predicted changes in symptom severity and treatment response following 12 weeks of controlled antipsychotic treatment. During the task subjects were instructed to press a response button on the same side or opposite side of a circle that appeared on either side of a central fixation point. Imaging data revealed that for the contrast of opposite-side vs. same-side, patients showed significantly greater activation compared with healthy volunteers in the anterior cingulate cortex and intraparietal sulcus. Among patients, greater baseline anterior cingulate cortex, temporal-parietal junction, and superior temporal cortex activation predicted greater symptom reduction and therapeutic response following treatment. All findings remained significant after covarying for task performance. Intact performance on this relatively parsimonious task was associated with frontal hyperactivity suggesting the need for patients to utilize greater neural resources to achieve task performance comparable to healthy individuals. Moreover, frontal hyperactivity observed using a simple fMRI task may provide a biomarker for predicting treatment response in first-episode psychosis.
... The posterior cingulum and precuneus are two core regions of the default mode network in humans, the role of which, even though not completely understood, seem to be relevant for attending to external and internal stimuli (Gusnard, Akbudak, Shulman, & Raichle, 2001;Raichle et al., 2001) and for self-referential and reflective activity such as inner speech, recall of personal experiences, mental imagery, and planning of future events (Greicius, Krasnow, Reiss, & Menon, 2003). Dysfunction of the default mode network in schizophrenia has been studied, but there is not yet sufficient clearcut evidence to build a coherent theory (Pomarol-Clotet et al., 2008;Salgado-Pineda et al., 2011;Wolf et al., 2011). ...
Cannabis-induced psychotic disorder is a debated nosological construct. Most of the
available literature deals with the so-called “cannabis psychosis,” which includes several
different entities. In 1994, substance-induced disorders appeared in the DSM-IV, but
no clear-cut criteria were defined for different substances. Difficulties in the diagnosis
of this disorder brought a lack of studies on the topic. During the last decade, laboratory
studies proved the possible psychotomimetic effects of Δ9-tetrahydrocannabinol in
healthy subjects. Differential diagnosis remains challenging in clinical settings due to
overlapping features with primary psychotic disorders and the high prevalence of comorbidity
between primary psychotic disorders and cannabis use disorder. The incidence of
cannabis-induced psychotic disorder is thought to be 2.7 per 100,000 person-years, with
a conversion rate to a schizophrenia-spectrum disorders ranging between one-third and
one-half. No specific guidelines exist for the treatment of cannabis-induced psychotic
disorder. Symptom-guided management is recommended using acute psychopharmacological
interventions, mainly benzodiazepines and second-generation antipsychotics.
... 18 Given these findings, 1 advantage of using a task-driven approach to define the DM network is that the same paradigm can be used to derive the activation and responses, so that any hemodynamic differences between the patient and control populations will equally affect the activation and deactivation BOLD responses. Because the DM network is implicated in many aspects of brain function 15 and disruption of the DM has been reported to negatively impact attention, working memory, and emotional capacity, 19 an altered DM network in SCD may account for the some of the neurocognitive changes associated with SCD. While the core elements of the DM network are now well-defined, some areas show more variable deactivation, with the presence and/or strength of the deactivation being modulated by the nature of the stimulus. ...
Background and purpose:
Declines in both functional activation and functional connectivity have been reported in patients with sickle cell disease. In this study, we derived the functional and default mode responses to a word stem paradigm in age-, ethnicity-, and background-matched subjects with sickle cell disease and control groups, with the aim of testing whether both networks were similarly attenuated and whether the changes were related to physiologic parameters that characterize sickle cell disease.
Materials and methods:
Both the functional and default mode responses were obtained from age- and background-matched controls and the sickle cell population by using a visually presented word stem paradigm on a 3T scanner.
Results:
We observed an attenuated response to both activation and deactivation in the sickle cell disease group. There were no significant differences in the activation response between the 2 groups for the contrast control > sickle cell disease; however, significant differences were observed in the medial parietal cortex, the auditory cortex, and the angular gyrus for the default mode. For the sickle cell group, a significant correlation between the activation z scores and the physiologic parameters was observed; for the deactivation, the results were not significant but the trend was similar.
Conclusions:
The results indicate that the physiologic parameters modulate the activation in the expected fashion, but that the effect was weaker for deactivation. Given that significant differences between the 2 groups were only seen for deactivation, additional factors must modulate the deactivation in sickle cell disease.
... The DMN plays a role in social cognition and emotional regulation 26,27 , dysfunction of which is frequently reported in schizophrenia 28,29 . The structural and functional impairments in the ACC have been found in both schizophrenia patients and their first-degree relatives 4,30,31 . In consistent with previous studies 32 , we found that the structural impairment of the ACC was correlated with clinical symptoms. ...
Diverse brain structural and functional changes have been reported in schizophrenia. Identifying different types of brain changes may help to understand the neural mechanisms and to develop reliable biomarkers in schizophrenia. We aimed to categorize different grey matter changes in schizophrenia based on grey matter volume (GMV) and cerebral blood flow (CBF). Structural and perfusion magnetic resonance imaging data were acquired in 100 schizophrenia patients and 95 healthy comparison subjects. Voxel-based GMV comparison was used to show structural changes, CBF analysis was used to demonstrate functional changes. We identified three types of grey matter changes in schizophrenia: structural and functional impairments in the anterior cingulate cortex and insular cortex, displaying reduction in both GMV and CBF; structural impairment with preserved function in the frontal and temporal cortices, demonstrating decreased GMV with normal CBF; pure functional abnormality in the anterior cingulate cortex and lateral prefrontal cortex and putamen, showing altered CBF with normal GMV. By combination of GMV and CBF, we identified three types of grey matter changes in schizophrenia. These findings may help to understand the complex manifestations and to develop reliable biomarkers in schizophrenia.
... Functional Magnetic Resonance Imaging (fMRI) studies of cognition reported less pronounced task-induced DMN deactivation in people with schizophrenia (PSZ) than in healthy control subjects (HCS; Pomarol-Clotet et al., 2008;Whitfield-Gabrieli et al., 2009;Hasenkamp et al., 2011;Schneider et al., 2011;Salgado-Pineda et al., 2011;Nygard et al., 2012;Dreher et al., 2012;Anticevic et al., 2013;Madre et al., 2013;Fryer et al., 2013;Haatveit et al., 2016). Such findings led to suggestions that an inability to down-regulate task-independent thought processes may contribute to cognitive impairment in PSZ. ...
... Indeed, correlations between DMN structure and function have been noted in healthy individuals (e.g., Greicius et al. 2009, Zhang et al. 2008). Most salient for this review, in patients with schizophrenia there was a positive correlation between DMN gray matter and DMN task suppression (i.e., greater DMN gray matter correlated with greater DMN task suppression) ( Salgado-Pineda et al. 2011). ...
BACKGROUND
Clinical features and genetics overlap in schizophrenia (SCZ) and bipolar disorder (BD). Identifying brain alterations associated with genetic vulnerability for SCZ and BD could help to discover intermediate phenotypes, quantifiable biological traits with greater prevalence in unaffected relatives (REL), and early recognition biomarkers in ultra-high risk populations. However, a comprehensive meta-analysis of structural (sMRI) and functional magnetic resonance imaging (fMRI) studies examining REL of patients with SCZ and BD has not been perfomed yet.
METHODS
We systematically searched PubMed, Scopus and Web of Science for sMRI and fMRI studies investigating REL and healthy controls (HC). 230 eligible neuroimaging studies (6274 SCZ-REL, 1900 BD-REL, 10789 HC) were identified. We conducted coordinate-based activation likelihood estimation meta-analyses on 26 sMRI and 81 fMRI investigations, including stratification by task-type. We also meta-analysed regional and global volumetric changes. Lastly, we performed a meta-analysis of all MRI studies combined.
RESULTS
Reduced thalamic volume was present in both SCZ and BD. Moreover, SCZ-REL showed alterations in cortico-striatal-thalamic networks, spanning the dorsolateral-prefrontal cortex and temporal regions, while BD-REL showed altered thalamo-cortical and limbic regions including the ventrolateral-prefrontal cortex, superior parietal and medial temporal cortices, with fronto-parietal alterations in BD-I.
CONCLUSIONS
Familiarity for SCZ and BD is associated with alterations in the thalamo-cortical circuits, which may be the expression of the shared genetic mechanism underlying both disorders. Furthermore, the involvement of different prefrontocortical and temporal nodes may be associated with a differential symptom expression in the two disorders.
How invariant structural architecture of brain coupling with variant functionality is still unclear in neuroscience. The previous exploration of relationships between large-scale structural and functional brain networks mainly focused on whole or partial statistical correlation, ignoring network context information, such as network topology structure. Here we applied a network representation learning approach to create high-order representations of structural or functional networks while preserving network context information for studying the function-structure coupling of the brain at topological subnetwork levels. We found that the structural and functional network obtained from the network representation learning method was more stable and more tightly coupled than those from the conventional correlation method, primarily distributed in high-order cognitive networks. Application on schizophrenia patients showed decoupling on the default-mode network, dorsal attention network, executive control network, and salience network, as well as the over-coupling on the sensorimotor network, compared with healthy controls. Overall, network representation learning can more effectively capture the higher-order coupling between brain structure and function and provides a good technical means for us to study mental illness.
Classifying mental disorder is a big issue in psychology in recent years. This article focuses on offering a relation between decision tree and encoding of fMRI that can simplify the analysis of different mental disorders and has a high ROC over 0.9. Here we encode fMRI information to the power-law distribution with integer elements by the graph theory in which the network is characterized by degrees that measure the number of effective links exceeding the threshold of Pearson correlation among voxels. When the degrees are ranked from low to high, the network equation can be fit by the power-law distribution. Here we use the mentally disordered SHR and WKY rats as samples and employ decision tree from chi2 algorithm to classify different states of mental disorder. This method not only provides the decision tree and encoding, but also enables the construction of a transformation matrix that is capable of connecting different metal disorders. Although the latter attempt is still in its fancy, it may have a contribution to unraveling the mystery of psychological processes.
“Executive functions” (EFs) is an umbrella term for higher cognitive functions such as working memory, inhibition, and cognitive flexibility. These functions refer to dissociable mechanisms that are also intricately related, justifying the view of EF as a unitary mental faculty. One of the most challenging theoretical problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to breakthrough in understanding how the brain controls and regulates itself, and no single brain system underlying a ‘central executive’ has yet been identified. We discuss how a distributed control network view can help to refine our understanding of the neurophysiological mechanisms underlying EFs. In this view, executive control functions are realized by spatially distributed brain networks, thus precluding the need for a modular central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and how neuroscience network research endeavors to investigate clinical neuropathology of disrupted EFs.
Traumatic brain injury (TBI) is characterized by a host of persisting mental health (cognitive and psychiatric), motor and neurological sequelae, including progressive, degenerative change in the hippocampi. This thesis postulates that hippocampal volume loss may contribute to the increased risk of psychotic disorder that is observed in this population, through dysregulation of dopaminergic networks. The thesis also posits that TBI is implicated in the substantial mental health deficits observed in persons experiencing homelessness. This thesis specifically investigated (1) The relationship between increased psychotic symptom severity and hippocampal volume loss from 5 to 12 months post-injury and (2) The relationship between TBI and cognitive/psychiatric dysfunction among persons experiencing homelessness. A significant association between increasing hippocampal degeneration and increasing psychotic symptom severity was demonstrated. TBI was also demonstrated to bear strong associations with mental health dysfunction among homeless populations.
Different medical disciplines have adopted biomarkers in order to establish a diagnosis and predict clinical and functional outcome of a disease. In psychiatry, the search for biomarkers could lead to substantial improvement in mental disorder diagnosis and care. Different neuroimaging techniques have contributed to improve our understanding of brain structure and functioning in patients with psychotic disorders. However, though a large number of studies have reported differences between patients with psychotic disorders and healthy controls in structural and functional neuroimaging measures, only few results are robust and consistent. In addition, so far, even robust and consistent findings have differences at group level, which so far did not translate into applications at the individual level. The heterogeneity of psychotic disorders, the use of medications, and the infrequent replication of findings in independent patient cohorts from different centers have limited the identification of reliable neuroimaging biomarkers for diagnosis and outcome prediction of psychotic disorders. Machine-learning algorithms might represent a good opportunity for the progress in this field.
Disturbances in implicit self-processing have been reported both in psychotic patients with bipolar disorder (BD) and schizophrenia. It remains unclear whether these two psychotic disorders show disturbed functional connectivity during explicit self-reflection, which is associated with social functioning and illness symptoms. Therefore, we investigated functional connectivity during explicit self-reflection in BD with past psychosis and schizophrenia. Twenty-three BD-patients, 17 schizophrenia-patients and 21 health controls (HC) performed a self-reflection task, including the conditions self-reflection, close other-reflection and semantic control. Functional connectivity was investigated with generalized psycho-physiological interaction (gPPI). During self-reflection compared to semantic, BD-patients had decreased connectivity between several cortical-midline structures (CMS) nodes (i.e., anterior cingulate cortex, ventromedial prefrontal cortex), the insula and the head of the caudate while HC showed increased connectivities. Schizophrenia-patients, during close other-reflection compared to semantic, demonstrated reduced ventral-anterior insula-precuneus/posterior cingulate cortex (PCC) functional connectivity, whereas this was increased in HC. There were no differences between BD and schizophrenia during self- and close other-reflection. We propose that decreased functional connectivity between the CMS nodes/insula and head of the caudate in BD-patients may imply a reduced involvement of the motivational system during self-reflection; and the reduced functional connectivity between the ventral-anterior insula and precuneus/PCC during close other-reflection in schizophrenia-patients may subserve difficulties in information integration of autobiographical memory and emotional awareness in relation to close others. These distinctive impaired patterns of functional connectivity in BD and schizophrenia (compared to HC) deserve further investigation to determine their robustness and associations with differences in clinical presentation.
Recent years have witnessed a rapid growth of interest in moving functional magnetic resonance imaging (fMRI) beyond simple scan-length averages and into approaches that can integrate structural MRI measures and capture rich multimodal interactions. It is becoming increasingly clear that multimodal fusion is able to provide more information for individual subjects by exploiting covariation between modalities, rather an analysis of each modality alone. Multimodal fusion is a more complicated endeavor that must be approached carefully and efficient methods should be developed to draw generalized and valid conclusions out of high dimensional data with a limited number of subjects, such as patients with brain disorders. Numerous research efforts have been reported in the field based on various statistical models, including independent component analysis (ICA), canonical correlation analysis (CCA), and partial least squares (PLS). In this chapter, we survey a number of methods previously shown in multimodal fusion reports, performed with or without prior information, and with their possible strengths and limitations addressed. To examine the function-structure associations of the brain in a more comprehensive and integrated manner, we also reviewed a number of multimodal studies that combined fMRI and structural (sMRI and/or diffusion tensor MRI) measures, which could reveal important brain alterations that may not be fully detected by employing separate analysis of individual modalities, and also enable us to identify potential brain illness biomarkers.
It is becoming increasingly clear that combining multimodal brain imaging data provides more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e., capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multimodal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this article, we start by introducing the basic reasons why multimodal data fusion is important and what it can do and, importantly, how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multimodal fusion including deep learning and multimodal classification that show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential to mitigate misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. Multimodal " is a widely used phrase in the context of brain imaging studies. Collecting multiple modalities of magnetic resonance imaging (MRI) data from the same individual has been popular in brain imaging studies. There is increasing evidence that multimodal brain imaging studies can help provide a more complete understanding of the brain and its disorders; for example, it can inform us about how brain structure shapes brain function, in which way they are impacted by psychopathology, and which functional or structural aspects of physiology could drive human behavior and cognition. In this article, we first provide some basic motivation regarding the benefits of multimodal imaging and also introduce some basic terminology for characterizing multimodal data analysis. Next, we review a large class of multivariate approaches for performing multimodal data fusion, the most powerful type of multimodal analysis. Followed by this, we survey some of the existing articles that have applied multi-modal imaging to study psychopathology. Finally, we discuss some exciting emerging trends and approaches. TERMINOLOGY We now present some basic terminology with which to describe existing multimodal imaging work. On one end of the spectrum is visual inspection, which is basically inferring the multimodal information by separately visualizing results from essentially unimodal analyses. This is the least informative but is used quite extensively and can highlight the different results that are provided by each modality in a qualitative manner. An alternative approach, which we call data integration (1–3), is to analyze each data type separately and overlay them, thereby not allowing for an examination of interaction among data types. For example, a data integration approach would not detect a change in gray matter concentration between patients and control subjects that is related to functional MRI (fMRI) activation maps, as shown in the example. A third approach, called one-sided or asymmetric data fusion, is the use of one data set to constrain another, as in diffusion MRI (dMRI) (4–6) or magnetoencephalography/ electroencephalography (MEG/EEG) (7–9) being constrained by structural MRI (sMRI) or fMRI data. While these techniques are powerful, a restriction is that they impose potentially unrealistic assumptions on the dMRI or EEG data, which are of an essentially different nature than fMRI data. Finally, symmetric data fusion utilizes and treats multiple image types equally to take full advantage of the joint information in multiple data sets. The approaches just described are shown in Figure 1. The use of joint information is only qualitatively used on the far left and maximally used on the far right. 230
Neuroimaging studies have found evidence of altered brain structure and function in schizophrenia, but have had complex findings regarding the localization of abnormality. We applied multimodal imaging (voxel-based morphometry (VBM), functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) combined with tractography) to 32 chronic schizophrenic patients and matched healthy controls. At a conservative threshold of P=0.01 corrected, structural and functional imaging revealed overlapping regions of abnormality in the medial frontal cortex. DTI found that white matter abnormality predominated in the anterior corpus callosum, and analysis of the anatomical connectivity of representative seed regions again implicated fibres projecting to the medial frontal cortex. There was also evidence of convergent abnormality in the dorsolateral prefrontal cortex, although here the laterality was less consistent across techniques. The medial frontal region identified by these three imaging techniques corresponds to the anterior midline node of the default mode network, a brain system which is believed to support internally directed thought, a state of watchfulness, and/or the maintenance of one's sense of self, and which is of considerable current interest in neuropsychiatric disorders.
A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.
• functional MRI
• functional connectivity
• spontaneous activity
The "default mode" has been defined as a baseline condition of brain function and is of interest because its component brain regions are believed to be abnormal in schizophrenia. It was hypothesized that the default mode network would show abnormal activation and connectivity in patients with schizophrenia.
Patients with schizophrenia (N=21) and healthy comparison subjects (N=22) performed an auditory oddball task during functional magnetic resonance imaging (fMRI). Independent component analysis was used to identify the default mode component. Differences in the spatial and temporal aspects of the default mode network were examined in patients versus comparison subjects.
Healthy comparison subjects and patients had significant spatial differences in the default mode network, most notably in the frontal, anterior cingulate, and parahippocampal gyri. In addition, activity in patients in the medial frontal, temporal, and cingulate gyri correlated with severity of positive symptoms. The patients also showed significantly higher frequency fluctuations in the temporal evolution of the default mode.
Schizophrenia is associated with altered temporal frequency and spatial location of the default mode network. The authors hypothesized that this network may be under- or overmodulated by key regions, including the anterior and posterior cingulate cortex. In addition, the altered temporal fluctuations in patients may result from a change in the connectivity of these regions with other brain networks.
Thirty years of brain imaging research has converged to define the brain's default network-a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.
Functional imaging studies using working memory tasks have documented both prefrontal cortex (PFC) hypo- and hyperactivation in schizophrenia. However, these studies have often failed to consider the potential role of task-related deactivation.
Thirty-two patients with chronic schizophrenia and 32 age- and sex-matched normal controls underwent functional magnetic resonance imaging (fMRI) scanning while performing baseline, 1-back and 2-back versions of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups.
The controls showed activation in the expected frontal regions. There were also clusters of deactivation, particularly in the anterior cingulate/ventromedial PFC and the posterior cingulate cortex/precuneus. Compared to the controls, the schizophrenic patients showed reduced activation in the right dorsolateral prefrontal cortex (DLPFC) and other frontal areas. There was also an area in the anterior cingulate/ventromedial PFC where the patients showed apparently greater activation than the controls. This represented a failure of deactivation in the schizophrenic patients. Failure to activate was a function of the patients' impaired performance on the n-back task, whereas the failure to deactivate was less performance dependent.
Patients with schizophrenia show both failure to activate and failure to deactivate during performance of a working memory task. The area of failure of deactivation is in the anterior prefrontal/anterior cingulate cortex and corresponds to one of the two midline components of the 'default mode network' implicated in functions related to maintaining one's sense of self.
Schizophrenia is characterized by a lack of integration between thought, emotion, and behavior. A disruption in the connectivity between brain processes may underlie this schism. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were used to evaluate functional and anatomical brain connectivity in schizophrenia.
In all, 29 chronic schizophrenia patients (11 females, age: mean=41.3, SD=9.28) and 29 controls (11 females, age: mean=41.1, SD=10.6) were recruited. Schizophrenia patients were assessed for severity of negative and positive symptoms and general cognitive abilities of attention/concentration and memory. Participants underwent a resting-fMRI scan and a DTI scan. For fMRI data, a hybrid independent components analysis was used to extract the group default mode network (DMN) and accompanying time-courses. Voxel-wise whole-brain multiple regressions with corresponding DMN time-courses was conducted for each subject. A t-test was conducted on resulting DMN correlation maps to look between-group differences. For DTI data, voxel-wise statistical analysis of the fractional anisotropy data was carried out to look for between-group differences. Voxel-wise correlations were conducted to investigate the relationship between brain connectivity and behavioral measures.
Results revealed altered functional and anatomical connectivity in medial frontal and anterior cingulate gyri of schizophrenia patients. In addition, frontal connectivity in schizophrenia patients was positively associated with symptoms as well as with general cognitive ability measures.
The present study shows convergent fMRI and DTI findings that are consistent with the disconnection hypothesis in schizophrenia, particularly in medial frontal regions, while adding some insight of the relationship between brain disconnectivity and behavior.
Deficits in working memory (WM) are a consistent neurocognitive marker for schizophrenia. Previous studies have suggested that WM is the product of coordinated activity in distributed functionally connected brain regions. Independent component analysis (ICA) is a data-driven approach that can identify temporally coherent networks that underlie fMRI activity. We applied ICA to an fMRI dataset for 115 patients with chronic schizophrenia and 130 healthy controls by performing the Sternberg Item Recognition Paradigm. Here, we describe the first results using ICA to identify differences in the function of WM networks in schizophrenia compared to controls. ICA revealed six networks that showed significant differences between patients with schizophrenia and healthy controls. Four of these networks were negatively task-correlated and showed deactivation across the posterior cingulate, precuneus, medial prefrontal cortex, anterior cingulate, inferior parietal lobules, and parahippocampus. These networks comprise brain regions known as the default-mode network (DMN), a well-characterized set of regions shown to be active during internal modes of cognition and implicated in schizophrenia. Two networks were positively task-correlated, with one network engaging WM regions such as bilateral DLPFC and inferior parietal lobules while the other network engaged primarily the cerebellum. Our results suggest that DLPFC dysfunction in schizophrenia might be lateralized to the left and intrinsically tied to other regions such as the inferior parietal lobule and cingulate gyrus. Furthermore, we found that DMN dysfunction in schizophrenia exists across multiple subnetworks of the DMN and that these subnetworks are individually relevant to the pathophysiology of schizophrenia. In summary, this large multisite study identified multiple temporally coherent networks, which are aberrant in schizophrenia versus healthy controls and suggests that both task-correlated and task-anticorrelated networks may serve as potential biomarkers.
Anhedonia, as a deficit symptom, may be associated with default-mode hypofrontality in schizophrenia. To explore whether trait anhedonia in schizophrenia pertains to altered hypofrontal resting state brain function, resting state metabolic activities were compared and correlated with the Physical and Social Anhedonia Scale scores in 29 patients with schizophrenia and 21 healthy controls using (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET). In patients with schizophrenia, Physical Anhedonia Scale scores showed a trend-level negative correlation with the hypoactive dorsomedial prefrontal metabolism while Positive and Negative Symptom Scale (PANSS) negative subscale scores positively correlated with hyperactive cerebellar metabolism. Voxelwise correlation analysis showed physical anhedonia correlates in resting state activities of the supplementary motor area, ventromedial and dorsolateral prefrontal cortex, insular gyrus, and the precuneus in patients with schizophrenia while no frontal metabolic correlates were found in healthy controls. The hypoactive dorsomedial prefrontal metabolism correlated with physical anhedonia-correlated resting state regional activities. These findings provide further evidence for the relation of functional hypofrontality to the deficit syndrome and possible involvement of the functional imbalance in the cortico-cerebellar-thalamic-cortical circuit in the resting state brain function of schizophrenia.
We examined the status of the neural network mediating the default mode of brain function, which typically exhibits greater activation during rest than during task, in patients in the early phase of schizophrenia and in young first-degree relatives of persons with schizophrenia. During functional MRI, patients, relatives, and controls alternated between rest and performance of working memory (WM) tasks. As expected, controls exhibited task-related suppression of activation in the default network, including medial prefrontal cortex (MPFC) and posterior cingulate cortex/precuneus. Patients and relatives exhibited significantly reduced task-related suppression in MPFC, and these reductions remained after controlling for performance. Increased task-related MPFC suppression correlated with better WM performance in patients and relatives and with less psychopathology in all 3 groups. For WM task performance, patients and relatives had greater activation in right dorsolateral prefrontal cortex (DLPFC) than controls. During rest and task, patients and relatives exhibited abnormally high functional connectivity within the default network. The magnitudes of default network connectivity during rest and task correlated with psychopathology in the patients. Further, during both rest and task, patients exhibited reduced anticorrelations between MPFC and DLPFC, a region that was hyperactivated by patients and relatives during WM performance. Among patients, the magnitude of MPFC task suppression negatively correlated with default connectivity, suggesting an association between the hyperactivation and hyperconnectivity in schizophrenia. Hyperactivation (reduced task-related suppression) of default regions and hyperconnectivity of the default network may contribute to disturbances of thought in schizophrenia and risk for the illness.
Aberrant brain activation during facial emotion discrimination has been described in chronic schizophrenia, while little is known about early stages of the illness. The aim of the current study was to investigate valence-specific brain activation of emotion discrimination in first-episode schizophrenia. These patients provide the advantage of lacking the effects of long-term medication and chronic illness course and can hence further enhance the understanding of underlying psychopathological mechanisms.
Using event-related fMRI, we investigated 18 first-episode schizophrenia patients and 18 matched healthy subjects during an explicit emotion discrimination task presenting happy, sad and neutral monochromatic facial expressions. A repeated measure analysis of variance (ANOVA) with the factors Group (patients, healthy subjects), Gender and Emotion (happy, sad, neutral) was performed on behavioural and functional data.
Behavioural performance did not differ between groups. Valence-independent hypoactivations in patients were observed for the anterior cingulate and orbitofrontal cortex while hyperactivations emerged in the posterior cingulate and the precuneus. Emotion-specific group differences were revealed in inferior parietal and orbitofrontal brain areas and the hippocampus.
First-episode schizophrenia already affects areas involved in processing of both, emotions and primary facial information. Our study underlines the role of dysfunctional neural networks as the basis of disturbed social interactions in early schizophrenia.
Functional brain imaging in humans has revealed task-specific increases in brain activity that are associated with various mental activities. In the same studies, mysterious, task-independent decreases have also frequently been encountered, especially when the tasks of interest have been compared with a passive state, such as simple fixation or eyes closed. These decreases have raised the possibility that there might be a baseline or resting state of brain function involving a specific set of mental operations. We explore this possibility, including the manner in which we might define a baseline and the implications of such a baseline for our understanding of brain function.
A probabilistic framework is presented that enables image registration, tissue classification, and bias correction to be combined within the same generative model. A derivation of a log-likelihood objective function for the unified model is provided. The model is based on a mixture of Gaussians and is extended to incorporate a smooth intensity variation and nonlinear registration with tissue probability maps. A strategy for optimising the model parameters is described, along with the requisite partial derivatives of the objective function.
Having a self is associated with important advantages for an organism. These advantages have been suggested to include mechanisms supporting elaborate capacities for planning, decision-making, and behavioral control. Acknowledging such functionality offers possibilities for obtaining traction on investigation of neural correlates of self-hood. A method that has potential for investigating some of the brain-based properties of self arising in behavioral contexts varying in requirements for such behavioral guidance and control is functional brain imaging. Data obtained with this method are beginning to converge on a set of brain areas that appear to play a significant role in permitting conscious access to representational content having reference to self as an embodied and independent experiencer and agent. These areas have been identified in a variety of imaging contexts ranging from passive state conditions in which they appear to manifest ongoing activity associated with spontaneous and typically 'self-related' cognition, to tasks targeting explicitly experienced properties of self, to demanding task conditions where activity within them is attenuated in apparent redirection of cognitive resources in the service of task guidance and control. In this paper, these data will be reviewed and a hypothesis presented regarding a significant role for these areas in enabling degrees of self-awareness and participating in the management of such behavioral control.
Patients with schizophrenia show deficits in facial affect and facial identity recognition and exhibit structural and neurophysiological abnormalities in brain regions known to mediate these processes. Functional neuroimaging studies of neural responses to emotional facial expressions in schizophrenia have reported both increases and decreases in medial temporal lobe (MTL) activity in schizophrenia. Some of this variability may be related to the tasks performed and the baseline conditions used. Here we tested whether MTL responses to human faces in schizophrenia are abnormal when unconstrained by a cognitive task and measured relative to a low-level baseline (fixation) condition.
15 patients with schizophrenia and 16 healthy control subjects underwent functional magnetic resonance imaging (fMRI) while passively viewing human faces displaying fearful, happy, and neutral emotional expressions.
Relative to control subjects, the patients demonstrated (1) significantly greater activation of the left hippocampus while viewing all three facial expressions and (2) increased right amygdala activation during the initial presentation of fearful and neutral facial expressions.
In schizophrenia, hippocampal and amygdala activity is elevated during the passive viewing of human faces.
In recent years, multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality-specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in Matlab with a user-friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely used T-field, has been implemented in the correlation analysis for more accurate results. An example with in vivo data is presented, demonstrating the potential of the BPM methodology as a tool for multimodal image analysis.
Task-induced deactivations (TIDs) of midline cortical regions are readily observed in fMRI studies and may reflect elements of a 'default-mode' of brain function associated with self-directed mental processes at rest. In this study, we examined this TID phenomenon in schizophrenia and its relevance to patients' symptoms, task performance and level of emotional awareness. Relative to control subjects, patients showed significantly greater TID of the rostral anterior cingulate (rAC)/medial prefrontal cortex (mPFC) and precuneus (PrC)/posterior cingulate cortex (PC). The magnitude of prefrontal TIDs was associated with patients' task performance and emotional awareness for others. The nature of these associations suggests a complex interchange between cognitive and emotional influences on the resting-state activity of these prefrontal 'default mode' regions in schizophrenia.
Schizophrenia and bipolar disorder are currently diagnosed on the basis of psychiatric symptoms and longitudinal course. The determination of a reliable, biologically-based diagnostic indicator of these diseases (a biomarker) could provide the groundwork for developing more rigorous tools for differential diagnosis and treatment assignment. Recently, methods have been used to identify distinct sets of brain regions or "spatial modes" exhibiting temporally coherent brain activity. Using functional magnetic resonance imaging (fMRI) data and a multivariate analysis method, independent component analysis, we combined the temporal lobe and the default modes to discriminate subjects with bipolar disorder, chronic schizophrenia, and healthy controls. Temporal lobe and default mode networks were reliably identified in all participants. Classification results on an independent set of individuals revealed an average sensitivity and specificity of 90 and 95%, respectively. The use of coherent brain networks such as the temporal lobe and default mode networks may provide a more reliable measure of disease state than task-correlated fMRI activity. A combination of two such hemodynamic brain networks shows promise as a biomarker for schizophrenia and bipolar disorder.
To examine the neural basis and dynamics of facial affect processing in schizophrenic patients as compared to healthy controls.
Fourteen schizophrenic patients and fourteen matched controls performed a facial affect identification task during fMRI acquisition. The emotional task included an intuitive emotional condition (matching emotional faces) and a more cognitively demanding condition (labeling emotional faces). Individual analysis for each emotional condition, and second-level t-tests examining both within-, and between-group differences, were carried out using a random effects approach. Psychophysiological interactions (PPI) were tested for variations in functional connectivity between amygdala and other brain regions as a function of changes in experimental conditions (labeling versus matching).
During the labeling condition, both groups engaged similar networks. During the matching condition, schizophrenics failed to activate regions of the limbic system implicated in the automatic processing of emotions. PPI revealed an inverse functional connectivity between prefrontal regions and the left amygdala in healthy volunteers but there was no such change in patients. Furthermore, during the matching condition, and compared to controls, patients showed decreased activation of regions involved in holistic face processing (fusiform gyrus) and increased activation of regions associated with feature analysis (inferior parietal cortex, left middle temporal lobe, right precuneus).
Our findings suggest that schizophrenic patients invariably adopt a cognitive approach when identifying facial affect. The distributed neocortical network observed during the intuitive condition indicates that patients may resort to feature-based, rather than configuration-based, processing and may constitute a compensatory strategy for limbic dysfunction.
Altered functional and anatomical connectivity in schizophrenia
- J Camchong
- Iii Macdonald
- A W Bell
- C Mueller
- B A Lim
Camchong, J., Macdonald III, A.W., Bell, C., Mueller, B.A., Lim, K.O., 2009.
Altered functional and anatomical connectivity in schizophrenia.
Schizophr. Bull. 17.