Common abnormality of gray matter integrity in substance use disorder and obsessive‐compulsive disorder: A comparative voxel‐based meta‐analysis

The objective of the current study is to determine robust transdiagnostic brain structural markers for compulsivity by capitalizing on the increasing number of case‐control studies examining gray matter volume (GMV) alterations in substance use disorders (SUD) and obsessive‐compulsive disorder (OCD). Voxel‐based meta‐analysis within the individual disorders and conjunction analysis were employed to reveal common GMV alterations between SUDs and OCD. Meta‐analytic coordinates and signed brain volumetric maps determining directed (reduced/increased) GMV alterations between the disorder groups and controls served as the primary outcome. The separate meta‐analysis demonstrated that SUD and OCD patients exhibited widespread GMV reductions in frontocortical regions including prefrontal, cingulate, and insular. Conjunction analysis revealed that the left inferior frontal gyrus (IFG) consistently exhibited decreased GMV across all disorders. Functional characterization suggests that the IFG represents a core hub in the cognitive control network and exhibits bidirectional (Granger) causal interactions with the striatum. Only OCD showed increased GMV in the dorsal striatum with higher changes being associated with more severe OCD symptomatology. Together the findings demonstrate robustly decreased GMV across the disorders in the left IFG, suggesting a transdiagnostic brain structural marker. The functional characterization as a key hub in the cognitive control network and casual interactions with the striatum suggest that deficits in inhibitory control mechanisms may promote compulsivity and loss of control that characterize both disorders.     

Temporal variability of regional intrinsic neural activity in drug‐naïve patients with obsessive–compulsive disorder

Obsessive–compulsive disorder (OCD) displays alterations in regional brain activity represented by the amplitude of low‐frequency fluctuation (ALFF), but the time‐varying characteristics of this local neural activity remain to be clarified. We aimed to investigate the dynamic changes of intrinsic brain activity in a relatively large sample of drug‐naïve OCD patients using univariate and multivariate analyses. We applied a sliding‐window approach to calculate the dynamic ALFF (dALFF) and compared the difference between 73 OCD patients and age‐ and sex‐matched healthy controls (HCs). We also utilized multivariate pattern analysis to determine whether dALFF could differentiate OCD patients from HCs at the individual level. Compared with HCs, OCD patients exhibited increased dALFF mainly within regions of the cortical–striatal–thalamic–cortical (CSTC) circuit, including the bilateral dorsal anterior cingulate cortex, medial prefrontal cortex and striatum, and right dorsolateral prefrontal cortex (dlPFC). Decreased dALFF was identified in the bilateral inferior parietal lobule (IPL), posterior cingulate cortex, insula, fusiform gyrus, and cerebellum. Moreover, we found negative correlations between illness duration and dALFF values in the right IPL and between dALFF values in the left cerebellum and Hamilton Depression Scale scores. Furthermore, dALFF can distinguish OCD patients from HCs with the most discriminative regions located in the IPL, dlPFC, middle occipital gyrus, and cuneus. Taken together, in the current study, we demonstrated a characteristic pattern of higher variability of regional brain activity within the CSTC circuits and lower variability in regions outside the CSTC circuits in drug‐naïve OCD patients.     

Age differences in functional network reconfiguration with working memory training

Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10 days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task‐related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default‐mode network for younger adults, it enhanced efficiency within a task‐specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default‐mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between‐network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age‐related trajectories in functional network reorganization with WM training.     

Increased functional connectivity between presupplementary motor area and inferior frontal gyrus associated with the ability of motor response inhibition in obsessive–compulsive disorder

Recent evidence suggests that presupplementary motor area (pre‐SMA) and inferior frontal gyrus (IFG) play an important role in response inhibition. However, no study has investigated the relationship between these brain networks at resting‐state and response inhibition in obsessive–compulsive disorder (OCD). We performed resting‐state functional magnetic resonance imaging scans and then measured the response inhibition of 41 medication‐free OCD patients and 49 healthy control (HC) participants by using the stop‐signal task outside the scanner. We explored the differences between OCD and HC groups in the functional connectivity of pre‐SMA and IFG associated with the ability of motor response inhibition. OCD patients showed a longer stop‐signal reaction time (SSRT). Compared to HC, OCD patients exhibit different associations between the ability of motor response inhibition and the functional connectivity between pre‐SMA and IFG, inferior parietal lobule, dorsal anterior cingulate cortex, insula, and anterior prefrontal cortex. Additional analysis to investigate the functional connectivity difference from the seed ROIs to the whole brain voxels revealed that, compared to HC, OCD exhibited greater functional connectivity between pre‐SMA and IFG. Also, this functional connectivity was positively correlated with the SSRT score. These results provide additional insight into the characteristics of the resting‐state functional connectivity of the regions belonging to the cortico‐striato‐thalamo‐cortical circuit and the cingulo‐opercular salience network, underlying the impaired motor response inhibition of OCD. In particular, we emphasize the importance of altered functional connectivity between pre‐SMA and IFG for the pathophysiology of motor response inhibition in OCD.     

Abnormal brain functional network dynamics in obsessive–compulsive disorder patients and their unaffected first‐degree relatives

We utilized dynamic functional network connectivity (dFNC) analysis to compare participants with obsessive–compulsive disorder (OCD) with their unaffected first‐degree relative (UFDR) and healthy controls (HC). Resting state fMRI was performed on 46 OCD, 24 UFDR, and 49 HCs, along with clinical assessments. dFNC analyses revealed two distinct connectivity states: a less frequent, integrated state characterized by the predominance of between‐network connections (State I), and a more frequent, segregated state with strong within‐network connections (State II). OCD patients spent more time in State II and less time in State I than HC, as measured by fractional windows and mean dwell time. Time in each state for the UFDR were intermediate between OCD patients and HC. Within the OCD group, fractional windows of time spent in State I was positively correlated with OCD symptoms (as measured by the obsessive compulsive inventory‐revised [OCI‐R], r = .343, p<.05, FDR correction) and time in State II was negatively correlated with symptoms (r = −.343, p<.05, FDR correction). Within each state we also examined connectivity within and between established intrinsic connectivity networks, and found that UFDR were similar to the OCD group in State I, but more similar to the HC groups in State II. The similarities between OCD and UFDR groups in temporal properties and State I connectivity indicate that these features may reflect the endophenotype for OCD. These results indicate that the temporal dynamics of functional connectivity could be a useful biomarker to identify those at risk.     

Altered brain functional network dynamics in obsessive–compulsive disorder

Obsessive–compulsive disorder (OCD) is a debilitating and disabling neuropsychiatric disorder, whose neurobiological basis remains unclear. Although traditional static resting‐state magnetic resonance imaging (rfMRI) studies have found aberrant functional connectivity (FC) in OCD, alterations in whole‐brain FC and topological properties in the context of brain dynamics remain relatively unexplored. The rfMRI data of 29 patients with OCD and 40 healthy controls were analyzed using group independent component analysis to obtain independent components (ICs) and a sliding‐window approach to generate dynamic functional connectivity (dFC) matrices. dFC patterns were clustered into three reoccurring states, and state transition metrics were obtained. Then, graph‐theory methods were applied to dFC matrices to calculate the variability of network topological organization. The occurrence of a state (State 1) with the highest modularity index and lowest mean FC between networks was increased significantly in OCD, and the fractional time in brain State 1 was positively correlated with anxiety level in patients. State 1 was characterized by having positive connections within default mode (DMN) and salience networks (SAN), and negative coupling between the two networks. Additionally, ICs belonging to DMN and SAN showed lower temporal variability of nodal degree centrality and efficiency in patients, which was related to longer illness duration and higher current obsession ratings. Our results provide evidence of clinically relevant aberrant dynamic brain activity in OCD. Increased functional segregation among networks and impaired functional flexibility in connections among brain regions in DMN and SAN may play important roles in the neuropathology of OCD.     

Large‐scale white matter network reorganization in posttraumatic stress disorder

Recently, graph theoretical approaches applied to neuroimaging data have advanced understanding of the human brain connectome and its abnormalities in psychiatric disorders. However, little is known about the topological organization of brain white matter networks in posttraumatic stress disorder (PTSD). Seventy‐six patients with PTSD and 76 age, gender, and years of education‐matched trauma‐exposed controls were studied after the 2008 Sichuan earthquake using diffusion tensor imaging and graph theoretical approaches. Topological properties of brain networks including global and nodal measurements and modularity were analyzed. At the global level, patients showed lower clustering coefficient (p = .016) and normalized characteristic path length (p = .035) compared with controls. At the nodal level, increased nodal centralities in left middle frontal gyrus, superior and inferior temporal gyrus and right inferior occipital gyrus were observed (p < .05, corrected for false‐discovery rate). Modularity analysis revealed that PTSD patients had significantly increased inter‐modular connections in the fronto‐parietal module, fronto‐striato‐temporal module, and visual and default mode modules. These findings indicate a PTSD‐related shift of white matter network topology toward randomization. This pattern was characterized by an increased global network integration, reflected by increased inter‐modular connections with increased nodal centralities involving fronto‐temporo‐occipital regions. This study suggests that extremely stressful life experiences, when they lead to PTSD, are associated with large‐scale brain white matter network topological reconfiguration at global, nodal, and modular levels.     

The anxiety‐specific hippocampus–prefrontal cortex pathways links to procrastination through self‐control

Procrastination, which is defined as delaying an intended course of action despite negative outcomes, is demonstrated to have a deal with negative emotion including trait anxiety. Although highly anxious individuals showed impoverished control ability, no studies have indicated the role of self‐control in the relationship between trait anxiety and procrastination, and its neural correlates. To this end, we used the sliding window method to calculate the temporal deviation of dynamic functional connectivity (FC) in 312 healthy participants who underwent the resting‐state functional magnetic resonance imaging (fMRI) scanning. In line with our hypothesis, higher trait anxiety is linked to more procrastination via poorer self‐control. Besides, the dynamic FC analyses showed that trait anxiety was positively correlated with dynamic FC variability in hippocampus–prefrontal cortex (HPC–PFC) pathways, including left rostral hippocampus–left superior frontal gyrus (left rHPC–left SFG), and left rHPC–right middle frontal gyrus (left rHPC–‐MFG). Furthermore, the structural equation modeling (SEM) uncovered a mediated role of self‐control in the association between the anxiety‐specific brain connectivity and procrastination. These findings suggest that the HPC–PFC pathways may reflect impoverished regulatory ability over the negative thoughts for anxious individuals, and thereby incurs more procrastination, which enhances our understanding of how trait anxiety links to procrastination.     

Pre‐supplementary motor network connectivity and clinical outcome of magnetic stimulation in obsessive–compulsive disorder

A large proportion of patients with obsessive–compulsive disorder (OCD) respond unsatisfactorily to pharmacological and psychological treatments. An alternative novel treatment for these patients is repetitive transcranial magnetic stimulation (rTMS). This study aimed to investigate the underlying neural mechanism of rTMS treatment in OCD patients. A total of 37 patients with OCD were randomized to receive real or sham 1‐Hz rTMS (14 days, 30 min/day) over the right pre‐supplementary motor area (preSMA). Resting‐state functional magnetic resonance imaging data were collected before and after rTMS treatment. The individualized target was defined by a personalized functional connectivity map of the subthalamic nucleus. After treatment, patients in the real group showed a better improvement in the Yale–Brown Obsessive Compulsive Scale than the sham group (F _1,35 = 6.0, p = .019). To show the neural mechanism involved, we identified an “ideal target connectivity” before treatment. Leave‐one‐out cross‐validation indicated that this connectivity pattern can significantly predict patients'' symptom improvements (r = .60, p = .009). After real treatment, the average connectivity strength of the target network significantly decreased in the real but not in the sham group. This network‐level change was cross‐validated in three independent datasets. Altogether, these findings suggest that personalized magnetic stimulation on preSMA may alleviate obsessive–compulsive symptoms by decreasing the connectivity strength of the target network.     

Structural and functional brain alterations in anorexia nervosa:A multimodal meta‐analysis of neuroimaging studies

Anorexia nervosa (AN) is a complex psychiatric disorder with poorly understood etiology. Numerous voxel‐based morphometry (VBM) and resting‐state functional imaging studies have provided strong evidence of abnormal brain structure and intrinsic and functional activities in AN, but with inconsistent conclusions. Herein, a whole‐brain meta‐analysis was conducted on VBM (660 patients with AN, and 740 controls) and resting‐state functional imaging (425 patients with AN, and 461 controls) studies that measured differences in the gray matter volume (GMV) and intrinsic functional activity between patients with AN and healthy controls (HCs). Overall, patients with AN displayed decreased GMV in the bilateral median cingulate cortex (extending to the bilateral anterior and posterior cingulate cortex), and left middle occipital gyrus (extending to the left inferior parietal lobe). In resting‐state functional imaging studies, patients with AN displayed decreased resting‐state functional activity in the bilateral anterior cingulate cortex and bilateral median cingulate cortex, and increased resting‐state functional activity in the right parahippocampal gyrus. This multimodal meta‐analysis identified reductions of gray matter and functional activity in the anterior and median cingulate in patients with AN, which contributes to further understanding of the pathophysiology of AN.     

Disentangling age‐ and disease‐related alterations in schizophrenia brain network using structural equation modeling: A graph theoretical study based on minimum spanning tree

Functional brain networks have been shown to undergo fundamental changes associated with aging or schizophrenia. However, the mechanism of how these factors exert influences jointly or interactively on brain networks remains elusive. A unified recognition of connectomic alteration patterns was also hampered by heterogeneities in network construction and thresholding methods. Recently, an unbiased network representation method regardless of network thresholding, so called minimal spanning tree algorithm, has been applied to study the critical skeleton of the brain network. In this study, we aimed to use minimum spanning tree (MST) as an unbiased network reconstruction and employed structural equation modeling (SEM) to unravel intertwined relationships among multiple phenotypic and connectomic variables in schizophrenia. First, we examined global and local brain network properties in 40 healthy subjects and 40 schizophrenic patients aged 21–55 using resting‐state functional magnetic resonance imaging (rs‐fMRI). Global network alterations are measured by graph theoretical metrics of MSTs and a connectivity‐transitivity two‐dimensional approach was proposed to characterize nodal roles. We found that networks of schizophrenic patients exhibited a more star‐like global structure compared to controls, indicating excessive integration, and a loss of regional transitivity in the dorsal frontal cortex (corrected p <.05). Regional analysis of MST network topology revealed that schizophrenia patients had more network hubs in frontal regions, which may be linked to the “overloading” hypothesis. Furthermore, using SEM, we found that the level of MST integration mediated the influence of age on negative symptom severity (indirect effect 95% CI [0.026, 0.449]). These findings highlighted an altered network skeleton in schizophrenia and suggested that aging‐related enhancement of network integration may undermine functional specialization of distinct neural systems and result in aggravated schizophrenic symptoms.     

The “vestibular neuromatrix”: A proposed,expanded vestibular network from graph theory in post‐concussive vestibular dysfunction

Convergent clinical and neuroimaging evidence suggests that higher vestibular function is subserved by a distributed network including visuospatial, cognitive–affective, proprioceptive, and integrative brain regions. Clinical vestibular syndromes may perturb this network, resulting in deficits across a variety of functional domains. Here, we leverage structural and functional neuroimaging to characterize this extended network in healthy control participants and patients with post‐concussive vestibular dysfunction (PCVD). Then, 27 healthy control subjects (15 females) and 18 patients with subacute PCVD (12 female) were selected for participation. Eighty‐two regions of interest (network nodes) were identified based on previous publications, group‐wise differences in BOLD signal amplitude and connectivity, and multivariate pattern analysis on affective tests. Group‐specific “core” networks, as well as a “consensus” network comprised of connections common to all participants, were then generated based on probabilistic tractography and functional connectivity between the 82 nodes and subjected to analyses of node centrality and community structure. Whereas the consensus network was comprised of affective, integrative, and vestibular nodes, PCVD participants exhibited diminished integration and centrality among vestibular and affective nodes and increased centrality of visual, supplementary motor, and frontal and cingulate eye field nodes. Clinical outcomes, derived from dynamic posturography, were associated with approximately 62% of all connections but best predicted by amygdalar, prefrontal, and cingulate connectivity. No group‐wise differences in diffusion metrics or tractography were noted. These findings indicate that cognitive, affective, and proprioceptive substrates contribute to vestibular processing and performance and highlight the need to consider these domains during clinical diagnosis and treatment planning.     

The effect of conscientiousness on procrastination: The interaction between the self‐control and motivation neural pathways

Procrastination is a prevalent and universal problematic behavior, largely impairing individual''s health, wealth and well‐being. Substantial studies have confirmed that conscientiousness, one of the big five personality, showed markedly inverse relation with procrastination. However, it is hitherto unknown about the neural basis underlying the impact of conscientiousness on procrastination. To address this issue, we employed the voxel‐based morphometry (VBM) and resting‐state functional connectivity (RSFC) methods to explore the neural substrates of conscientiousness responsible for procrastination (N = 330). In line with previous findings, the behavioral results showed a strong negative correlation between conscientiousness and procrastination (r = −.75). The VBM analysis found that conscientiousness was positively correlated with gray matter (GM) volumes in the left dorsal‐lateral prefrontal cortex (dlPFC), right orbital frontal cortex (OFC) and right putamen, but negatively correlated with that in the left insula. Moreover, the RSFC results revealed that both dlPFC‐IPL (inferior parietal lobule) and dlPFC‐PCC (posterior cingulate gyrus) functional connectivity were positively associated with conscientiousness, while the functional connectivity of parahippocampal gyrus (PHC)‐putamen and insula‐IPL were negatively associated with conscientiousness. More importantly, the structural equation modeling (SEM) integrating RSFC results were well fitted for the influence process of conscientiousness on procrastination by both self‐control (i.e., dlPFC‐IPL, dlPFC‐PCC) and motivation pathways (i.e., PHC‐putamen, insula‐IPL). The current findings suggest that self‐control and motivation could be the two neural pathways underlying the impact of conscientiousness on procrastination, which provides a new perspective to understand the relationship between conscientiousness and procrastination.     

Modulation of the rat hippocampal‐cortex network and episodic‐like memory performance following entorhinal cortex stimulation

AimsEntorhinal cortex (EC) deep brain stimulation (DBS) has shown a memory enhancement effect. However, its brain network modulation mechanisms remain unclear. The present study aimed to investigate the functional connectivity in the rat hippocampal‐cortex network and episodic‐like memory performance following EC‐DBS.Methods7.0 T functional MRI (fMRI) scans and episodic‐like memory tests were performed 3 days and 28 days after EC‐DBS in healthy rats. The fMRI data processing was focused on the power spectra, functional connectivity, and causality relationships in the hippocampal‐cortex network. In addition, the exploration ratio for each object and the discrimination ratio of the “when” and “where” factors were calculated in the behavioral tests.ResultsEC‐DBS increased the power spectra and the functional connectivity in the prefrontal‐ and hippocampal‐related networks 3 days after stimulation and recovered 4 weeks later. Both networks exhibited a strengthened connection with the EC after EC‐DBS. Further seed‐based functional connectivity comparisons showed increased connectivity among the prefrontal cortex, hippocampus and EC, especially on the ipsilateral side of DBS. The dentate gyrus is a hub region closely related to both the EC and the prefrontal cortex and receives information flow from both. Moreover, acute EC‐DBS also enhanced the discrimination ratio of the “where” factor in the episodic‐like memory test on Day 3.ConclusionEC‐DBS caused a reversible modulation effect on functional connectivity in the hippocampal‐cortex network and episodic‐like memory performance.     

Perceptual learning of tone patterns changes the effective connectivity between Heschl's gyrus and planum temporale

Learning of complex auditory sequences such as music can be thought of as optimizing an internal model of regularities through unpredicted events (or “prediction errors”). We used dynamic causal modeling (DCM) and parametric empirical Bayes on functional magnetic resonance imaging (fMRI) data to identify modulation of effective brain connectivity that takes place during perceptual learning of complex tone patterns. Our approach differs from previous studies in two aspects. First, we used a complex oddball paradigm based on tone patterns as opposed to simple deviant tones. Second, the use of fMRI allowed us to identify cortical regions with high spatial accuracy. These regions served as empirical regions‐of‐interest for the analysis of effective connectivity. Deviant patterns induced an increased blood oxygenation level‐dependent response, compared to standards, in early auditory (Heschl''s gyrus [HG]) and association auditory areas (planum temporale [PT]) bilaterally. Within this network, we found a left‐lateralized increase in feedforward connectivity from HG to PT during deviant responses and an increase in excitation within left HG. In contrast to previous findings, we did not find frontal activity, nor did we find modulations of backward connections in response to oddball sounds. Our results suggest that complex auditory prediction errors are encoded by changes in feedforward and intrinsic connections, confined to superior temporal gyrus.     

Disrupted default mode network dynamics in recuperative patients of herpes zoster pain

IntroductionPrevious studies of herpes zoster (HZ) have focused on acute patient manifestations and the most common sequela, postherpetic neuralgia (PHN), both serving to disrupt brain dynamics. Although the majority of such patients gradually recover, without lingering severe pain, little is known about life situations of those who recuperate or the brain dynamics. Our goal was to determine whether default mode network (DMN) dynamics of the recuperative population normalize to the level of healthy individuals.MethodsFor this purpose, we conducted resting‐state functional magnetic resonance imaging (fMRI) studies in 30 patients recuperating from HZ (RHZ group) and 30 healthy controls (HC group). Independent component analysis (ICA) was initially undertaken in both groups to extract DMN components. DMN spatial maps and within‐DMN functional connectivity were then compared by group and then correlated with clinical variables.ResultsRelative to controls, DMN spatial maps of recuperating patients showed higher connectivity in middle frontal gyrus (MFG), right/left medial temporal regions of cortex (RMTC/LMTC), right parietal lobe, and parahippocampal gyrus. The RHZ (vs HC) group also demonstrated significant augmentation of within‐DMN connectivity, including that of LMTC‐MFG and LMTC‐posterior cingulate cortex (PCC). Furthermore, the intensity of LMTC‐MFG connectivity correlated significantly with scoring of pain‐induced emotions and life quality.ConclusionFindings of this preliminary study indicate that a disrupted dissociative pattern of DMN persists in patients recuperating from HZ, relative to healthy controls. We have thus provisionally established the brain mechanisms accounting for major outcomes of HZ, offering heuristic cues for future research on HZ transition states.     

Differences in working memory coding of biological motion attributed to oneself and others

The question how the brain distinguishes between information about self and others is of fundamental interest to both philosophy and neuroscience. In this functional magnetic resonance imaging (fMRI) study, we sought to distinguish the neural substrates of representing a full‐body movement as one''s movement and as someone else''s movement. Participants performed a delayed match‐to‐sample working memory task where a retained full‐body movement (displayed using point‐light walkers) was arbitrarily labeled as one''s own movement or as performed by someone else. By using arbitrary associations we aimed to address a limitation of previous studies, namely that our own movements are more familiar to us than movements of other people. A searchlight multivariate decoding analysis was used to test where information about types of movement and about self‐association was coded. Movement specific activation patterns were found in a network of regions also involved in perceptual processing of movement stimuli, however not in early sensory regions. Information about whether a memorized movement was associated with the self or with another person was found to be coded by activity in the left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), bilateral supplementary motor area, and (at reduced threshold) in the left temporoparietal junction (TPJ). These areas are frequently reported as involved in action understanding (IFG, MFG) and domain‐general self/other distinction (TPJ). Finally, in univariate analysis we found that selecting a self‐associated movement for retention was related to increased activity in the ventral medial prefrontal cortex.     

Cortico‐striato‐thalamo‐cerebellar networks of structural covariance underlying different epilepsy syndromes associated with generalized tonic–clonic seizures

Generalized tonic–clonic seizures (GTCS) are the severest and most remarkable clinical expressions of human epilepsy. Cortical, subcortical, and cerebellar structures, organized with different network patterns, underlying the pathophysiological substrates of genetic associated epilepsy with GTCS (GE‐GTCS) and focal epilepsy associated with focal to bilateral tonic–clonic seizure (FE‐FBTS). Structural covariance analysis can delineate the features of epilepsy network related with long‐term effects from seizure. Morphometric MRI data of 111 patients with GE‐GTCS, 111 patients with FE‐FBTS and 111 healthy controls were studied. Cortico‐striato‐thalao‐cerebellar networks of structural covariance within the gray matter were constructed using a Winner‐take‐all strategy with five cortical parcellations. Comparisons of structural covariance networks were conducted using permutation tests, and module effects of disease duration on networks were conducted using GLM model. Both patient groups showed increased connectivity of structural covariance relative to controls, mainly within the striatum and thalamus, and mostly correlated with the frontal, motor, and somatosensory cortices. Connectivity changes increased as a function of epilepsy durations. FE‐FBTS showed more intensive and extensive gray matter changes with volumetric loss and connectivity increment than GE‐GTCS. Our findings implicated cortico‐striato‐thalamo‐cerebellar network changes at a large temporal scale in GTCS, with FE‐FBTS showing more severe network disruption. The study contributed novel imaging evidence for understanding the different epilepsy syndromes associated with generalized seizures.     

Ignore the faces: Neural characterisation of emotional inhibition from childhood to adulthood using MEG

The ability to effectively and automatically regulate one''s response to emotional information is a basic, fundamental skill for social functioning. The neural mechanisms underlying emotion regulation processing have been assessed, however few investigations have leveraged neurophysiological techniques, particularly magnetoencephalography (MEG) to determine the development of this critical ability. The current MEG study is the first to examine developmental changes in the neural mechanisms supporting automatic emotion regulation. We used an emotional go/no‐go task with happy and angry faces in a single‐site cohort of 97 healthy participants, 4–40 years of age. We found age‐related changes as a function of emotion and condition in brain regions key to emotion regulation, including the right inferior frontal gyrus, orbitofrontal cortices and primarily right‐lateralized temporal areas. Interaction effects, including an age by emotion and condition, were also found in the left angular gyrus, an area critical in emotion regulation and attention. Findings demonstrate protracted and nonlinear development, due to the adolescent group, of emotion regulation processing from child to adulthood, and highlight that age‐related differences in emotion regulation are modulated by emotional face type.     

Deep reasoning neural network analysis to predict language deficits from psychometry‐driven DWI connectome of young children with persistent language concerns

This study investigated whether current state‐of‐the‐art deep reasoning network analysis on psychometry‐driven diffusion tractography connectome can accurately predict expressive and receptive language scores in a cohort of young children with persistent language concerns (n = 31, age: 4.25 ± 2.38 years). A dilated convolutional neural network combined with a relational network (dilated CNN + RN) was trained to reason the nonlinear relationship between “dilated CNN features of language network” and “clinically acquired language score”. Three‐fold cross‐validation was then used to compare the Pearson correlation and mean absolute error (MAE) between dilated CNN + RN‐predicted and actual language scores. The dilated CNN + RN outperformed other methods providing the most significant correlation between predicted and actual scores (i.e., Pearson''s R/p‐value: 1.00/<.001 and .99/<.001 for expressive and receptive language scores, respectively) and yielding MAE: 0.28 and 0.28 for the same scores. The strength of the relationship suggests elevated probability in the prediction of both expressive and receptive language scores (i.e., 1.00 and 1.00, respectively). Specifically, sparse connectivity not only within the right precentral gyrus but also involving the right caudate had the strongest relationship between deficit in both the expressive and receptive language domains. Subsequent subgroup analyses inferred that the effectiveness of the dilated CNN + RN‐based prediction of language score(s) was independent of time interval (between MRI and language assessment) and age of MRI, suggesting that the dilated CNN + RN using psychometry‐driven diffusion tractography connectome may be useful for prediction of the presence of language disorder, and possibly provide a better understanding of the neurological mechanisms of language deficits in young children.