Apart from the psychiatric symptoms, cognitive deficits are also the core symptoms of schizophrenia. Brain network control theory provided information on the role of a specific brain region in the cognitive control process, helping understand the neural mechanism of cognitive impairment in schizophrenia.

To characterize the control properties of functional brain network in first-episode untreated patients with schizophrenia and the relationships between controllability and psychiatric symptoms, as well as exploring the predictive value of controllability in differentiating patients from healthy controls (HCs).

Average and modal controllability of brain networks were calculated and compared between 133 first-episode untreated patients with schizophrenia and 135 HCs. The associations between controllability and clinical symptoms were evaluated using sparse canonical correlation analysis. Support vector machine (SVM) and SVM-recursive feature elimination combined with the controllability were performed to establish the individual prediction model.

Compared to HCs, the patients with schizophrenia showed increased average controllability and decreased modal controllability in dorsal anterior cingulate cortex (dACC). Brain controllability predominantly in somatomotor, default mode, and visual networks was associated with the positive symptomatology of schizophrenia. The established model could identify patients with an accuracy of 0.68. Furthermore, the most discriminative features were located in dACC, medial prefrontal lobe, precuneus and superior temporal gyrus.

Altered controllability in dACC may play a critical role in the neuropathological mechanisms of cognitive deficit in schizophrenia, which could drive the brain function to different states to cope with varied cognitive tasks. As symptom-related biomarkers, controllability could be also beneficial to individual prediction in schizophrenia.

No significant relationships.

Emerging functional imaging studies suggest that schizophrenia is associated with aberrant spatiotemporal interaction which may result in aberrant global and local dynamic properties.

We investigated the dynamic functional connectivity (FC) by using instantaneous phase method based on Hilbert transform to detect abnormal spatiotemporal interaction in schizophrenia. Based on resting-state functional magnetic resonance imaging, two independent datasets were included, with 114 subjects from COBRE [51 schizophrenia patients (SZ) and 63 healthy controls (HCs)] and 96 from OpenfMRI (36 SZ and 60 HCs). Phase differences and instantaneous coupling matrices were firstly calculated at all time points by extracting instantaneous parameters. Global [global synchrony and intertemporal closeness (ITC)] and local dynamic features [strength of FC (sFC) and variability of FC (vFC)] were compared between two groups. Support vector machine (SVM) was used to estimate the ability to discriminate two groups by using all aberrant features.

We found SZ had lower global synchrony and ITC than HCs on both datasets. Furthermore, SZ had a significant decrease in sFC but an increase in vFC, which were mainly located at prefrontal cortex, anterior cingulate cortex, temporal cortex and visual cortex or temporal cortex and hippocampus, forming significant dynamic subnetworks. SVM analysis revealed a high degree of balanced accuracy (85.75%) on the basis of all aberrant dynamic features.

SZ has worse overall spatiotemporal stability and extensive FC subnetwork lesions compared to HCs, which to some extent elucidates the pathophysiological mechanism of schizophrenia, providing insight into time-variation properties of patients with other mental illnesses.

Although aberrant intrinsic functional connectivity has been reported in attention-deficit/hyperactivity disorder (ADHD), we have a limited understanding of whether connectivity alterations are related to the familial risk of ADHD.

Fifty-three probands with ADHD, their unaffected siblings (n = 53) and typically developing controls (n = 53) underwent resting-state functional magnetic resonance imaging scans. A seed-based approach with the bilateral precuneus/posterior cingulate cortex (PCC) was used to derive a whole-brain functional connectivity map in each subject. The differences in functional connectivity among the three groups were tested with one-way ANOVA using randomized permutation. Comparisons between two groups were also performed to examine the increase or decrease in connectivity. The severity of ADHD symptoms was used to identify brain regions where symptom severity is correlated to the strength of intrinsic functional connectivity.

When compared to controls, both probands and unaffected siblings showed increased functional connectivity in the left insula and left inferior frontal gyrus. The connectivity in these regions was linked to better performance in response inhibition in the control group but absent in other groups. Higher ADHD symptom severity was correlated with increased functional connectivity in bilateral fronto-parietal-temporal regions only noted in probands with ADHD.

Alterations in resting-state functional connectivities with the precuneus/PCC, hubs of default-mode network, account for the underlying familial risks of ADHD. Since the left insula and left inferior frontal gyri are key regions of the salience and frontoparietal network, respectively, future studies focusing on alterations of cross-network functional connectivity as the familial risk of ADHD are suggested.

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder, yet the search for definite genetic etiologies remains elusive. Delineating ASD endophenotypes can boost the statistical power to identify the genetic etiologies and pathophysiology of ASD. We aimed to test for endophenotypes of neuroanatomy and associated intrinsic functional connectivity (iFC) via contrasting male youth with ASD, their unaffected brothers and typically developing (TD) males.

The 94 participants (aged 9–19 years) – 20 male youth with ASD, 20 unaffected brothers and 54 TD males – received clinical assessments, and undertook structural and resting-state functional magnetic resonance imaging scans. Voxel-based morphometry was performed to obtain regional gray and white matter volumes. A seed-based approach, with seeds defined by the regions demonstrating atypical neuroanatomy shared by youth with ASD and unaffected brothers, was implemented to derive iFC. General linear models were used to compare brain structures and iFC among the three groups. Assessment of familiality was investigated by permutation tests for variance of the within-family pair difference.

We found that atypical gray matter volume in the mid-cingulate cortex was shared between male youth with ASD and their unaffected brothers as compared with TD males. Moreover, reduced iFC between the mid-cingulate cortex and the right inferior frontal gyrus, and increased iFC between the mid-cingulate cortex and bilateral middle occipital gyrus were the shared features of male ASD youth and unaffected brothers.

Atypical neuroanatomy and iFC surrounding the mid-cingulate cortex may be a potential endophenotypic marker for ASD in males.

The efficient organization and communication of brain networks underlie cognitive processing and their disruption can lead to pathological behaviours. Few studies have focused on whole-brain networks in obesity and binge eating disorder (BED). Here we used multi-echo resting-state functional magnetic resonance imaging (rsfMRI) along with a data-driven graph theory approach to assess brain network characteristics in obesity and BED.

Multi-echo rsfMRI scans were collected from 40 obese subjects (including 20 BED patients) and 40 healthy controls and denoised using multi-echo independent component analysis (ME-ICA). We constructed a whole-brain functional connectivity matrix with normalized correlation coefficients between regional mean blood oxygenation level-dependent (BOLD) signals from 90 brain regions in the Automated Anatomical Labeling atlas. We computed global and regional network properties in the binarized connectivity matrices with an edge density of 5%–25%. We also verified our findings using a separate parcellation, the Harvard–Oxford atlas parcellated into 470 regions.

Obese subjects exhibited significantly reduced global and local network efficiency as well as decreased modularity compared with healthy controls, showing disruption in small-world and modular network structures. In regional metrics, the putamen, pallidum and thalamus exhibited significantly decreased nodal degree and efficiency in obese subjects. Obese subjects also showed decreased connectivity of cortico-striatal/cortico-thalamic networks associated with putaminal and cortical motor regions. These findings were significant with ME-ICA with limited group differences observed with conventional denoising or single-echo analysis.

Using this data-driven analysis of multi-echo rsfMRI data, we found disruption in global network properties and motor cortico-striatal networks in obesity consistent with habit formation theories. Our findings highlight the role of network properties in pathological food misuse as possible biomarkers and therapeutic targets.

Local structural and metabolic as well as inter-regional connectivity abnormalities have been implicated in the neuropathology of major depressive disorder (MDD). How local tissue properties affect intrinsic functional connectivity is, however, unclear. Using a cross-sectional, multi-modal imaging approach, we investigated the relationship between local cortical tissue abnormalities and intrinsic resting-state functional connectivity (RSFC) in MDD.

A total of 20 MDD in-patients and 20 healthy controls underwent magnetic resonance imaging at 3 T for structural and functional imaging. Whole-brain cortical thickness was calculated and compared between groups. Regions with reduced cortical thickness defined seeds for subsequent whole-brain RSFC analyses. Contributions of structural tissue abnormalities on inter-regional RSFC were explicitly investigated.

Lower cortical thickness was observed in MDD in the right dorsomedial prefrontal cortex (PFC), superior temporal gyrus/temporal pole, middle-posterior cingulate cortex, and dorsolateral PFC. No differences in local fractional amplitude of low-frequency fluctuations were observed. Lower thickness in patients' dorsomedial PFC further directly and selectively affected its RSFC with the precuneus, which was unaffected by symptom severity. No effects of cortical thickness in other regions showing abnormal thickness were observed to influence functional connectivity.

Abnormal cortical thickness in the dorsomedial PFC in MDD patients was observed to selectively and directly affect its intrinsic connectivity with the precuneus in MDD patients independent of depression severity, thereby marking a potential vulnerability for maladaptive mood regulation. Future studies should include an unmedicated sample and replicate findings using independent component analysis to test for morphometric effects on network integrity.

Convergent studies have highlighted the dysfunction of the amygdala, prefrontal cortex and hippocampus in post-traumatic stress disorder (PTSD). However, only a few studies have investigated the functional connectivity between brain regions in PTSD patients during the resting state, which may improve our understanding of the neuropathophysiology of PTSD. The aim of this study was to investigate patterns of whole-brain functional connectivity in treatment-naive PTSD patients without co-morbid conditions who experienced the 8.0-magnitude earthquake in the Sichuan province of China.

A total of 72 PTSD patients and 86 trauma-exposed non-PTSD controls participated in the resting-state functional magnetic resonance imaging study. All these subjects were recruited from the disaster zone of the 2008 Sichuan earthquake. Functional connectivities between 90 paired brain regions in PTSD patients were compared with those in trauma-exposed non-PTSD controls. Furthermore, Pearson correlation analysis was performed between significantly abnormal connectivities in PTSD patients and their clinician-administered PTSD scale (CAPS) scores.

Compared with non-PTSD controls, PTSD patients showed weaker positive connectivities between the middle prefrontal cortex (mPFC) and the amygdala, hippocampus, parahippocampal gyrus and rectus, as well as between the inferior orbitofrontal cortex and the hippocampus. In addition, PTSD patients showed stronger negative connectivity between the posterior cingulate cortex (PCC) and the insula. The CAPS scores in PTSD patients correlated negatively with the connectivity between the amygdala and the mPFC.

PTSD patients showed abnormalities in whole-brain functional connectivity, primarily affecting the connectivities between the mPFC and limbic system, and connectivity between the PCC and insula.