Connectome and schizophrenia

Double-blind, randomized, placebo-controlled pilot clinical trial with gamma-band transcranial alternating current stimulation for the treatment of schizophrenia refractory auditory hallucinations

Gamma oscillations are essential for brain communication. The 40 Hz neural oscillation deficits in schizophrenia impair left frontotemporal connectivity and information communication, causing auditory hallucinations. Transcranial alternating current stimulation is thought to enhance connectivity between different brain regions by modulating brain oscillations. In this work, we applied a frontal-temporal-parietal 40 Hz-tACS stimulation strategy for treating auditory hallucinations and further explored the effect of tACS on functional connectivity of brain networks. 32 schizophrenia patients with refractory auditory hallucinations received 20daily 20-min, 40 Hz, 1 mA sessions of active or sham tACS on weekdays for 4 consecutive weeks, followed by a 2-week follow-up period without stimulation. Auditory hallucination symptom scores and 64-channel electroencephalograms were measured at baseline, week2, week4 and follow-up. For clinical symptom score, we observed a significant interaction between group and time for auditory hallucinations symptoms (F(3,90) = 26.964, p < 0.001), and subsequent analysis showed that the 40Hz-tACS group had a higher symptom reduction rate than the sham group at week4 (p = 0.036) and follow-up (p = 0.047). Multiple comparisons of corrected EEG results showed that the 40Hz-tACS group had higher functional connectivity in the right frontal to parietal (F (1,30) = 7.24, p = 0.012) and right frontal to occipital (F (1,30) = 7.98, p = 0.008) than the sham group at week4. Further, functional brain network controllability outcomes showed that the 40Hz-tACS group had increased average controllability (F (1,30) = 6.26, p = 0.018) and decreased modality controllability (F (1,30) = 6.50, p = 0.016) in the right frontal lobe compared to the sham group. Our polit study indicates that 40Hz-tACS combined with medicine may be an effective treatment for targeting symptoms specific to auditory hallucinations and altering functional connectivity and controllability at the network level.

Brain Connectivity, Neural Networks, and Resilience in Aging and Neurodegeneration

The importance of complex systems has become increasingly evident in recent years. The nervous system is one such example, with neural networks sitting at the intersection of complex networks and biology. A particularly exciting feature is the resilience of complex systems. For example, the ability of the nervous system to perform even in the face of challenges that include neuronal loss, neuroinflammation, protein accumulation, axonal disruptions, and metabolic stress is an intriguing and exciting line of investigation. In neurodegenerative diseases, neural network resilience is responsible for the time between the earliest disease-linked changes and clinical symptom onset and disease diagnosis. In this way, connectivity resilience of neurons within the complex network of cells that make up the nervous system has significant implications. This review provides an overview of relevant concepts related to complex systems with a focus on the connectivity of the nervous system. It discusses the development of the neural network and how a delicate balance determines how this complex system responds to injury, with examples illustrating maladaptive plasticity. The review then addresses the implications of these concepts, methods to understand brain connectivity and neural networks, and recent research efforts aimed at understanding neurodegeneration from this perspective. This study aims to provide foundational knowledge and an overview of current research directions in this evolving and exciting area of neuroscience.

Altered topology in cortical morphometric similarity network in recurrent major depressive disorder

BACKGROUND

Recurrent major depressive disorder (RDD) is increasingly understood to be associated with a 'disconnection' within the brain areas. But, the true understanding of cortical connectivities remains challenging. Morphometric similarity network (MSN) with multi-modal magnetic resonance imaging (MRI) could provide more information about cortical micro-architecture changes in individuals with RDD.

METHODS

Here, we integrated multi-modal features from T1-weighted imaging, diffusion tensor imaging (DTI), and inhomogeneous magnetization transfer imaging (ihMT) to construct MSN. We used graph theory to calculate topological changes in MSN and explore their relationship with the severity and recurrence. The topological properties of 42 RDD patients were compared with 56 age, sex, and education-matched healthy controls.

RESULTS

RDD subjects showed significantly decreased global efficiency, increased characteristic path length, reduced nodal efficiencies in the parietal lobe, subcortical area, and temporal lobe, increased betweenness centrality in the left supplementary motor area (SMA), decreased intra-modular connections in the parietal module and decreased inter-modular connections between the parietal and prefrontal modules. Notably, the global efficiency, characteristic path length, local efficiency of the right superior parietal gyrus, and inter-modular connections between the parietal and prefrontal modules were significantly associated with the number of depressive episodes. The betweenness centrality in SMA and the intra-modular connections in the parietal module showed a positive relationship with 17-item Hamilton Rating Scale for Depression (HAMD) scores.

CONCLUSIONS

The altered topology of MSN may serve as potential underlying pathological mechanisms of RDD. The impaired information integration of the network, particularly the disconnection within the fronto-parietal network, may be associated with the recurrence of depression. The SMA and the fronto-parietal network may be related to the severity of depression.

Advances in the labelling and selective manipulation of synapses

Synapses are highly specialized neuronal structures that are essential for neurotransmission, and they are dynamically regulated throughout the lifetime. Although accumulating evidence indicates that these structures are crucial for information processing and storage in the brain, their precise roles beyond neurotransmission are yet to be fully appreciated. Genetically encoded fluorescent tools have deepened our understanding of synaptic structure and function, but developing an ideal methodology to selectively visualize, label and manipulate synapses remains challenging. Here, we provide an overview of currently available synapse labelling techniques and describe their extension to enable synapse manipulation. We categorize these approaches on the basis of their conceptual bases and target molecules, compare their advantages and limitations and propose potential modifications to improve their effectiveness. These methods have broad utility, particularly for investigating mechanisms of synaptic function and synaptopathy.

Dynamic effective connectivity in the cerebellar dorsal dentate nucleus and the cerebrum, cognitive impairment, and clinical correlates in patients with schizophrenia

BACKGROUND

Schizophrenia (SZ) is characterized by disconnected cerebral networks. Recent studies have shown that functional connectivity between the cerebellar dorsal dentate nucleus (dDN) and cerebrum is correlated with psychotic symptoms, and processing speed in SZ patients. Dynamic effective connectivity (dEC) is a reliable indicator of brain functional status. However, the dEC between the dDN and cerebrum in patients with SZ remains largely unknown.

METHODS

Resting-state functional MRI data, symptom severity, and cognitive performance were collected from 74 SZ patients and 53 healthy controls (HC). Granger causality analysis and sliding time window methods were used to calculate dDN-based dEC maps for all subjects, and k-means clustering was performed to obtain several dEC states. Finally, between-group differences in dynamic effective connectivity variability (dECV) and clinical correlations were obtained using two-sample t-tests and correlation analysis.

RESULTS

We detected four dEC states from the cerebrum to the right dDN (IN states) and three dEC states from the right dDN to the cerebrum (OUT states), with SZ group having fewer transitions in the OUT states. SZ group had increased dECV from the right dDN to the right middle frontal gyrus (MFG) and left lingual gyrus (LG). Correlations were found between the dECV from the right dDN to the right MFG and symptom severity and between the dECV from the right dDN to the left LG and working memory performance.

CONCLUSIONS

This study reveals a dynamic causal relationship between cerebellar dDN and the cerebrum in SZ and provides new evidence for the involvement of cerebellar neural circuits in neurocognitive functions in SZ.

Association between degree centrality and neurocognitive impairments in patients with Schizophrenia: A Longitudinal rs-fMRI Study

BACKGROUND

Evidence indicates that patients with schizophrenia (SZ) experience significant changes in their functional connectivity during antipsychotic treatment. Despite previous reports of changes in brain network degree centrality (DC) in patients with schizophrenia, the relationship between brain DC changes and neurocognitive improvement in patients with SZ after antipsychotic treatment remains elusive.

METHODS

A total of 74 patients with acute episodes of chronic SZ and 53 age- and sex-matched healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS), Symbol Digit Modalities Test, digital span test (DST), and verbal fluency test were used to evaluate the clinical symptoms and cognitive performance of the patients with SZ. Patients with SZ were treated with antipsychotics for six weeks starting at baseline and underwent MRI and clinical interviews at baseline and after six weeks, respectively. We then divided the patients with SZ into responding (RS) and non-responding (NRS) groups based on the PANSS scores (reduction rate of PANSS ≥50%). DC was calculated and analyzed to determine its correlation with clinical symptoms and cognitive performance.

RESULTS

After antipsychotic treatment, the patients with SZ showed significant improvements in clinical symptoms, semantic fluency performance. Correlation analysis revealed that the degree of DC increase in the left anterior inferior parietal lobe (aIPL) after treatment was negatively correlated with changes in the excitement score (r = -0.256, p = 0.048, adjusted p = 0.080), but this correlation failed the multiple test correction. Patients with SZ showed a significant negative correlation between DC values in the left aIPL and DST scores after treatment, which was not observed at the baseline (r = -0.359, p = 0.005, adjusted p = 0.047). In addition, we did not find a significant difference in DC between the RS and NRS groups, neither at baseline nor after treatment.

CONCLUSIONS

The results suggested that DC changes in patients with SZ after antipsychotic treatment are correlated with neurocognitive performance. Our findings provide new insights into the neuropathological mechanisms underlying antipsychotic treatment of SZ.

Connectome-Based Neurosurgery in Primary Intra-Axial Neoplasms: Beyond the Traditional Modular Conception of Brain Architecture for the Preservation of Major Neurological Domains and Higher-Order Cognitive Functions

Despite the therapeutical advancements in the surgical treatment of primary intra-axial neoplasms, which determined both a significative improvement in OS and QoL and a reduction in the incidence of surgery-induced major neurological deficits, nowadays patients continue to manifest subtle post-operative neurocognitive impairments, preventing them from a full reintegration back into social life and into the workforce. The birth of connectomics paved the way for a profound reappraisal of the traditional conception of brain architecture, in favour of a model based on large-scale structural and functional interactions of a complex mosaic of cortical areas organized in a fluid network interconnected by subcortical bundles. Thanks to these advancements, neurosurgery is facing a new era of connectome-based resections, in which the core principle is still represented by the achievement of an ideal onco-functional balance, but with a closer eye on whole-brain circuitry, which constitutes the foundations of both major neurological functions, to be intended as motricity; language and visuospatial function; and higher-order cognitive functions such as cognition, conation, emotion and adaptive behaviour. Indeed, the achievement of an ideal balance between the radicality of tumoral resection and the preservation, as far as possible, of the integrity of local and global brain networks stands as a mandatory goal to be fulfilled to allow patients to resume their previous life and to make neurosurgery tailored and gentler to their individual needs.

The effect of using group-averaged or individualized brain parcellations when investigating connectome dysfunction in psychosis

Functional magnetic resonance imaging (fMRI) is widely used to investigate functional coupling (FC) disturbances in a range of clinical disorders. Most analyses performed to date have used group-based parcellations for defining regions of interest (ROIs), in which a single parcellation is applied to each brain. This approach neglects individual differences in brain functional organization and may inaccurately delineate the true borders of functional regions. These inaccuracies could inflate or underestimate group differences in case-control analyses. We investigated how individual differences in brain organization influence group comparisons of FC using psychosis as a case study, drawing on fMRI data in 121 early psychosis patients and 57 controls. We defined FC networks using either a group-based parcellation or an individually tailored variant of the same parcellation. Individualized parcellations yielded more functionally homogeneous ROIs than did group-based parcellations. At the level of individual connections, case-control FC differences were widespread, but the group-based parcellation identified approximately 7.7% more connections as dysfunctional than the individualized parcellation. When considering differences at the level of functional networks, the results from both parcellations converged. Our results suggest that a substantial fraction of dysconnectivity previously observed in psychosis may be driven by the parcellation method, rather than by a pathophysiological process related to psychosis.

Rich-club connectivity and structural connectome organization in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia

Brain dysconnectivity has been posited as a biological marker of schizophrenia. Emerging schizophrenia connectome research has focused on rich-club organization, a tendency for brain hubs to be highly-interconnected but disproportionately vulnerable to dysconnectivity. However, less is known about rich-club organization in individuals at clinical high-risk for psychosis (CHR-P) and how it compares with abnormalities early in schizophrenia (ESZ). Combining diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI), we examined rich-club and global network organization in CHR-P (n = 41) and ESZ (n = 70) relative to healthy controls (HC; n = 74) after accounting for normal aging. To characterize rich-club regions, we examined rich-club MRI morphometry (thickness, surface area). We also examined connectome metric associations with symptom severity, antipsychotic dosage, and in CHR-P specifically, transition to a full-blown psychotic disorder. ESZ had fewer connections among rich-club regions (ps < .024) relative to HC and CHR-P, with this reduction specific to the rich-club even after accounting for other connections in ESZ relative to HC (ps < .048). There was also cortical thinning of rich-club regions in ESZ (ps < .013). In contrast, there was no strong evidence of global network organization differences among the three groups. Although connectome abnormalities were not present in CHR-P overall, CHR-P converters to psychosis (n = 9) had fewer connections among rich-club regions (ps < .037) and greater modularity (ps < .037) compared to CHR-P non-converters (n = 19). Lastly, symptom severity and antipsychotic dosage were not significantly associated with connectome metrics (ps < .012). Findings suggest that rich-club and connectome organization abnormalities are present early in schizophrenia and in CHR-P individuals who subsequently transition to psychosis.

Altered brain connectivity during visual stimulation in schizophrenia

Schizophrenia (SCZ) can be described as a functional dysconnectivity syndrome that affects brain connectivity and circuitry. However, little is known about how sensory stimulation modulates network parameters in schizophrenia, such as their small-worldness (SW) during visual processing. To address this question, we applied graph theory algorithms to multi-electrode EEG recordings obtained during visual stimulation with a checkerboard pattern-reversal stimulus. Twenty-six volunteers participated in the study, 13 diagnosed with schizophrenia (SCZ; mean age = 38.3 years; SD = 9.61 years) and 13 healthy controls (HC; mean age = 28.92 years; SD = 12.92 years). The visually evoked potential (VEP) showed a global amplitude decrease (p < 0.05) for SCZ patients as opposed to HC but no differences in latency (p > 0.05). As a signature of functional connectivity, graph measures were obtained from the Magnitude-Squared Coherence between signals from pairs of occipital electrodes, separately for the alpha (8-13 Hz) and low-gamma (36-55 Hz) bands. For the alpha band, there was a significant effect of the visual stimulus on all measures (p < 0.05) but no group interaction between SCZ and HZ (p > 0.05). For the low-gamma spectrum, both groups showed a decrease of Characteristic Path Length (L) during visual stimulation (p < 0.05), but, contrary to the HC group, only SCZ significantly lowered their small-world (SW) connectivity index during visual stimulation (SCZ p < 0.05; HC p > 0.05). This indicates dysconnectivity of the functional network in the low-gamma band of SCZ during stimulation, which might indirectly reflect an altered ability to react to new sensory input in patients. These results provide novel evidence about a possible electrophysiological signature of the global deficits revealed by the application of graph theory onto electroencephalography in schizophrenia.

Reorganization of the functional connectome from rest to a visual perception task in schizophrenia and bipolar disorder

Functional connectome organization is altered in schizophrenia (SZ) and bipolar disorder (BD). However, it remains unclear whether network reorganization during a task relative to rest is also altered in these disorders. This study examined connectome organization in patients with SZ (N = 43) and BD (N = 42) versus healthy controls (HC; N = 39) using fMRI data during a visual object-perception task and at rest. Graph analyses were conducted for the whole-brain network using indices selected a priori: three reflecting network segregation (clustering coefficient, local efficiency, modularity), two reflecting integration (characteristic path length, global efficiency). Group differences were limited to network segregation and were more evident in SZ (clustering coefficient, modularity) than in BD (clustering coefficient) compared to HC. State differences were found across groups for segregation (local efficiency) and integration (characteristic path length). There was no group-by-state interaction for any graph index. In summary, aberrant network organization compared to HC was confirmed, and was more evident in SZ than in BD. Yet, reorganization was largely intact in both disorders. These findings help to constrain models of dysconnection in SZ and BD, suggesting that the extent of functional dysconnectivity in these disorders tends to persist across changes in mental state.

Controllability of Functional Brain Networks and Its Clinical Significance in First-Episode Schizophrenia

BACKGROUND AND HYPOTHESIS

Disrupted control of brain state transitions may contribute to the diverse dysfunctions of cognition, emotion, and behavior that are fundamental to schizophrenia. Control theory provides the rationale for evaluating brain state transitions from a controllability perspective, which may help reveal the brain mechanism for clinical features such as cognitive control deficits associated with schizophrenia. We hypothesized that brain controllability would be altered in patients with schizophrenia, and that controllability of brain networks would be related to clinical symptomatology.

STUDY DESIGN

Controllability measurements of functional brain networks, including average controllability and modal controllability, were calculated and compared between 125 first-episode never-treated patients with schizophrenia and 133 healthy controls (HCs). Associations between controllability metrics and clinical symptoms were evaluated using sparse canonical correlation analysis.

STUDY RESULTS

Compared to HCs, patients showed significantly increased average controllability (PFDR = .023) and decreased modal controllability (PFDR = .023) in dorsal anterior cingulate cortex (dACC). General psychopathology symptoms and positive symptoms were positively correlated with average controllability in regions of default mode network and negatively associated with average controllability in regions of sensorimotor, dorsal attention, and frontoparietal networks.

CONCLUSIONS

Our findings suggest that altered controllability of functional activity in dACC may play a critical role in the pathophysiology of schizophrenia, consistent with the importance of this region in cognitive and brain state control operations. The demonstration of associations of functional controllability with psychosis symptoms suggests that the identified alterations in average controllability of brain function may contribute to the severity of acute psychotic illness in schizophrenia.

Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia

BACKGROUND AND HYPOTHESIS

Schizophrenia is increasingly understood as a disorder of brain dysconnectivity. Recently, graph-based approaches such as graph convolutional network (GCN) have been leveraged to explore complex pairwise similarities in imaging features among brain regions, which can reveal abstract and complex relationships within brain networks.

STUDY DESIGN

We used GCN to investigate topological abnormalities of functional brain networks in schizophrenia. Resting-state functional magnetic resonance imaging data were acquired from 505 individuals with schizophrenia and 907 controls across 6 sites. Whole-brain functional connectivity matrix was extracted for each individual. We examined the performance of GCN relative to support vector machine (SVM), extracted the most salient regions contributing to both classification models, investigated the topological profiles of identified salient regions, and explored correlation between nodal topological properties of each salient region and severity of symptom.

STUDY RESULTS

GCN enabled nominally higher classification accuracy (85.8%) compared with SVM (80.9%). Based on the saliency map, the most discriminative brain regions were located in a distributed network including striatal areas (ie, putamen, pallidum, and caudate) and the amygdala. Significant differences in the nodal efficiency of bilateral putamen and pallidum between patients and controls and its correlations with negative symptoms were detected in post hoc analysis.

CONCLUSIONS

The present study demonstrates that GCN allows classification of schizophrenia at the individual level with high accuracy, indicating a promising direction for detection of individual patients with schizophrenia. Functional topological deficits of striatal areas may represent a focal neural deficit of negative symptomatology in schizophrenia.

Neural substrates of psychosis revealed by altered dependencies between brain activity and white-matter architecture in individuals with 22q11 deletion syndrome

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Function-structural dependency is altered in patients with 22q11 deletion syndrome.

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Stronger dependency in subcortical regions correlates with psychotic symptoms.

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Weaker dependency in cingulate cortex correlates with psychotic symptoms.

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Multimodal and not unimodal indexes were correlated with psychosis emergence.

Background

Dysconnectivity has been consistently proposed as a major key mechanism in psychosis. Indeed, disruptions in large-scale structural and functional brain networks have been associated with psychotic symptoms. However, brain activity is largely constrained by underlying white matter pathways and the study of function-structure dependency, compared to conventional unimodal analysis, allows a biologically relevant assessment of neural mechanisms. The 22q11.2 deletion syndrome (22q11DS) constitutes a remarkable opportunity to study the pathophysiological processes of psychosis.

Methods

58 healthy controls and 57 deletion carriers, aged from 16 to 32 years old, underwent resting-state functional and diffusion-weighted magnetic resonance imaging. Deletion carriers were additionally fully assessed for psychotic symptoms. Firstly, we used a graph signal processing method to combine brain activity and structural connectivity measures to obtain regional structural decoupling indexes (SDIs). We use SDI to assess the differences of functional structural dependency (FSD) across the groups. Subsequently we investigated how alterations in FSDs are associated with the severity of positive psychotic symptoms in participants with 22q11DS.

Results

In line with previous findings, participants in both groups showed a spatial gradient of FSD ranging from sensory-motor regions (stronger FSD) to regions involved in higher-order function (weaker FSD). Compared to controls, in participants with 22q11DS, and further in deletion carriers with more severe positive psychotic symptoms, the functional activity was more strongly dependent on the structure in parahippocampal gyrus and subcortical dopaminergic regions, while it was less dependent within the cingulate cortex. This analysis revealed group differences not otherwise detected when assessing the structural and functional nodal measures separately.

Conclusions

Our findings point toward a disrupted modulation of functional activity on the underlying structure, which was further associated to psychopathology for candidate critical regions in 22q11DS. This study provides the first evidence for the clinical relevance of function-structure dependency and its contribution to the emergence of psychosis.

Structural and Functional MRI Brain Changes in Patients with Schizophrenia Following Electroconvulsive Therapy: A Systematic Review

BACKGROUND

Schizophrenia (SZ) is a severe psychiatric disorder typically characterized by multidimensional psychotic syndromes. Electroconvulsive therapy (ECT) is a treatment option for medication-resistant patients with SZ or treating acute symptoms. Although the efficacy of ECT has been demonstrated in clinical use, its therapeutic mechanisms in the brain remain elusive.

OBJECTIVE

This study aimed to summarize brain changes on structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) after ECT.

METHODS

According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was carried out. The PubMed and Medline databases were systematically searched using the following medical subject headings (MeSH): (electroconvulsive therapy OR ECT) AND (schizophrenia) AND (MRI OR fMRI OR DTI OR DWI).

RESULTS

This review yielded 12 MRI studies, including 4 with sMRI, 5 with fMRI and 3 with multimodal MRI. Increases in volumes of the hippocampus and its adjacent regions (parahippocampal gyrus and amygdala), as well as the insula and frontotemporal regions, were noted after ECT. fMRI studies found ECT-induced changes in different brain regions/networks, including the hippocampus, amygdala, default model network, salience network and other regions/networks that are thought to highly correlate with the pathophysiologic characteristics of SZ. The results of the correlation between brain changes and symptom remissions are inconsistent.

CONCLUSION

Our review provides evidence supporting ECT-induced brain changes on sMRI and fMRI in SZ and explores the relationship between these changes and symptom remission.

Altered Coupling of Cerebral Blood Flow and Functional Connectivity Strength in First-Episode Schizophrenia Patients With Auditory Verbal Hallucinations

Objective

Auditory verbal hallucinations (AVHs) are a major symptom of schizophrenia and are connected with impairments in auditory and speech-related networks. In schizophrenia with AVHs, alterations in resting-state cerebral blood flow (CBF) and functional connectivity have been described. However, the neurovascular coupling alterations specific to first-episode drug-naïve schizophrenia (FES) patients with AVHs remain unknown.

Methods

Resting-state functional MRI and arterial spin labeling (ASL) was performed on 46 first-episode drug-naïve schizophrenia (FES) patients with AVHs (AVH), 39 FES drug-naïve schizophrenia patients without AVHs (NAVH), and 48 healthy controls (HC). Then we compared the correlation between the CBF and functional connection strength (FCS) of the entire gray matter between the three groups, as well as the CBF/FCS ratio of each voxel. Correlation analyses were performed on significant results between schizophrenia patients and clinical measures scale.

Results

The CBF/FCS ratio was reduced in the cognitive and emotional brain regions in both the AVH and NAVH groups, primarily in the crus I/II, vermis VI/VII, and cerebellum VI. In the AVH group compared with the HC group, the CBF/FCS ratio was higher in auditory perception and language-processing areas, primarily the left superior and middle temporal gyrus (STG/MTG). The CBF/FCS ratio in the left STG and left MTG positively correlates with the score of the Auditory Hallucination Rating Scale in AVH patients.

Conclusion

These findings point to the difference in neurovascular coupling failure between AVH and NAVH patients. The dysfunction of the forward model based on the predictive and computing role of the cerebellum may increase the excitability in the auditory cortex, which may help to understand the neuropathological mechanism of AVHs.

Network Controllability in Transmodal Cortex Predicts Positive Psychosis Spectrum Symptoms

BACKGROUND

The psychosis spectrum (PS) is associated with structural dysconnectivity concentrated in transmodal cortex. However, understanding of this pathophysiology has been limited by an overreliance on examining direct interregional connectivity. Using network control theory, we measured variation in both direct and indirect connectivity to a region to gain new insights into the pathophysiology of the PS.

METHODS

We used psychosis symptom data and structural connectivity in 1068 individuals from the Philadelphia Neurodevelopmental Cohort. Applying a network control theory metric called average controllability, we estimated each brain region's capacity to leverage its direct and indirect structural connections to control linear brain dynamics. Using nonlinear regression, we determined the accuracy with which average controllability could predict PS symptoms in out-of-sample testing. We also examined the predictive performance of regional strength, which indexes only direct connections to a region, as well as several graph-theoretic measures of centrality that index indirect connectivity. Finally, we assessed how the prediction performance for PS symptoms varied over the functional hierarchy spanning unimodal to transmodal cortex.

RESULTS

Average controllability outperformed all other connectivity features at predicting positive PS symptoms and was the only feature to yield above-chance predictive performance. Improved prediction for average controllability was concentrated in transmodal cortex, whereas prediction performance for strength was uniform across the cortex, suggesting that indexing indirect connections through average controllability is crucial in association cortex.

CONCLUSIONS

Examining interindividual variation in direct and indirect structural connections to transmodal cortex is crucial for accurate prediction of positive PS symptoms.

Abnormal interhemispheric functional connectivity in patients with strabismic amblyopia: a resting-state fMRI study using voxel-mirrored homotopic connectivity

Background

Previous studies have demonstrated that strabismus amblyopia can result in markedly brain function alterations. However, the differences in spontaneous brain activities of strabismus amblyopia (SA) patients still remain unclear. Therefore, the current study intended to employthe voxel-mirrored homotopic connectivity (VMHC) method to investigate the intrinsic brain activity changes in SA patients.

Purpose

To investigate the changes in cerebral hemispheric functional connections in patients with SA and their relationship with clinical manifestations using the VMHC method.

Material and methods

In the present study, a total of 17 patients with SA (eight males and nine females) and 17 age- and weight-matched healthy control (HC) groups were enrolled. Based on the VMHC method, all subjects were examined by functional magnetic resonance imaging. The functional interaction between cerebral hemispheres was directly evaluated. The Pearson’s correlation test was used to analyze the clinical features of patients with SA. In addition, their mean VMHC signal values and the receiver operating characteristic curve were used to distinguish patients with SA and HC groups.

Results

Compared with HC group, patients with SA had higher VMHC values in bilateral cingulum ant, caudate, hippocampus, and cerebellum crus 1. Moreover, the VMHC values of some regions were positively correlated with some clinical manifestations. In addition, receiver operating characteristic curves presented higher diagnostic value in these areas.

Conclusion

SA subjects showed abnormal brain interhemispheric functional connectivity in visual pathways, which might give some instructive information for understanding the neurological mechanisms of SA patients.

TMS-EEG: An emerging tool to study the neurophysiologic biomarkers of psychiatric disorders

The etiology of psychiatric disorders remains largely unknown. The exploration of the neurobiological mechanisms of mental illness helps improve diagnostic efficacy and develop new therapies. This review focuses on the application of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) in various mental diseases, including major depressive disorder, bipolar disorder, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, substance use disorder, and insomnia. First, we summarize the commonly used protocols and output measures of TMS-EEG; then, we review the literature exploring the alterations in neural patterns, particularly cortical excitability, plasticity, and connectivity alterations, and studies that predict treatment responses and clinical states in mental disorders using TMS-EEG. Finally, we discuss the potential mechanisms underlying TMS-EEG in establishing biomarkers for psychiatric disorders and future research directions.

Individual-specific functional connectome biomarkers predict schizophrenia positive symptoms during adolescent brain maturation

Even with an overarching functional dysconnectivity model of adolescent-onset schizophrenia (AOS), there have been no functional connectome (FC) biomarkers identified for predicting patients' specific symptom domains. Adolescence is a period of dramatic brain maturation, with substantial interindividual variability in brain anatomy. However, existing group-level hypotheses of AOS lack precision in terms of neuroanatomical boundaries. This study aimed to identify individual-specific FC biomarkers associated with schizophrenic symptom manifestation during adolescent brain maturation. We used a reliable individual-level cortical parcellation approach to map functional brain regions in each subject, that were then used to identify FC biomarkers for predicting dimension-specific psychotic symptoms in 30 antipsychotic-naïve first-episode AOS patients (recruited sample of 39). Age-related changes in biomarker expression were compared between these patients and 31 healthy controls. Moreover, 29 antipsychotic-naïve first-episode AOS patients (analyzed sample of 25) were recruited from another center to test the generalizability of the prediction model. Individual-specific FC biomarkers could significantly and better predict AOS positive-dimension symptoms with a relatively stronger generalizability than at the group level. Specifically, positive symptom domains were estimated based on connections between the frontoparietal control network (FPN) and salience network and within FPN. Consistent with the neurodevelopmental hypothesis of schizophrenia, the FPN-SN connection exhibited aberrant age-associated alteration in AOS. The individual-level findings reveal reproducible FPN-based FC biomarkers associated with AOS positive symptom domains, and highlight the importance of accounting for individual variation in the study of adolescent-onset disorders.

Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia

Current theories of schizophrenia emphasize the role of altered information integration as the core dysfunction of this illness. While ample neuroimaging evidence for such accounts comes from investigations of spatial connectivity, understanding temporal disruptions is important to fully capture the essence of dysconnectivity in schizophrenia. Recent electrophysiology studies suggest that long-range temporal correlation (LRTC) in the amplitude dynamics of neural oscillations captures the integrity of transferred information in the healthy brain. Thus, in this study, 25 schizophrenia patients and 25 controls (8 females/group) were recorded during two five-minutes of resting-state magnetoencephalography (once with eyes-open and once with eyes-closed). We used source-level analyses to investigate temporal dysconnectivity in patients by characterizing LRTCs across cortical and sub-cortical brain regions. In addition to standard statistical assessments, we applied a machine learning framework using support vector machine to evaluate the discriminative power of LRTCs in identifying patients from healthy controls. We found that neural oscillations in schizophrenia patients were characterized by reduced signal memory and higher variability across time, as evidenced by cortical and subcortical attenuations of LRTCs in the alpha and beta frequency bands. Support vector machine significantly classified participants using LRTCs in key limbic and paralimbic brain areas, with decoding accuracy reaching 82%. Importantly, these brain regions belong to networks that are highly relevant to the symptomology of schizophrenia. These findings thus posit temporal dysconnectivity as a hallmark of altered information processing in schizophrenia, and help advance our understanding of this pathology.

Characteristics of White Matter Structural Networks in Chronic Schizophrenia Treated With Clozapine or Risperidone and Those Never Treated

BACKGROUND

Despite its benefits, a major concern regarding antipsychotic treatment is its possible impact on the brain's structure and function. This study sought to explore the characteristics of white matter structural networks in chronic never-treated schizophrenia and those treated with clozapine or risperidone, and its potential association with cognitive function.

METHODS

Diffusion tensor imaging was performed on a unique sample of 34 schizophrenia patients treated with antipsychotic monotherapy for over 5 years (17 treated with clozapine and 17 treated with risperidone), 17 never-treated schizophrenia patients with illness duration over 5 years, and 27 healthy control participants. Graph theory and network-based statistic approaches were employed.

RESULTS

We observed a disrupted organization of white matter structural networks as well as decreased nodal and connectivity characteristics across the schizophrenia groups, mainly involving thalamus, prefrontal, and occipital regions. Alterations in nodal and connectivity characteristics were relatively milder in risperidone-treated patients than clozapine-treated patients and never-treated patients. Altered global network measures were significantly associated with cognitive performance levels. Structural connectivity as reflected by network-based statistic mediated the difference in cognitive performance levels between clozapine-treated and risperidone-treated patients.

LIMITATIONS

These results are constrained by the lack of random assignment to different types of antipsychotic treatment.

CONCLUSION

These findings provide insight into the white matter structural network deficits in patients with chronic schizophrenia, either being treated or untreated, and suggest white matter structural networks supporting cognitive function may benefit from antipsychotic treatment, especially in those treated with risperidone.

Functional brain networks in never-treated and treated long-term Ill schizophrenia patients

This study compared the topological organization of brain function in never-treated and treated long-term schizophrenia patients. In a cross-sectional study, 21 never-treated schizophrenia patients with illness duration over 5 years, 26 illness duration-matched antipsychotic-treated patients and 24 demographically-matched healthy controls underwent a resting-state functional magnetic resonance imaging (MRI) scan. The topological properties of brain functional networks were compared across groups, and then we tested for differential age-related effects in regions with significant group differences. Both never-treated and antipsychotic-treated schizophrenia patient groups showed altered nodal centralities in left pre-/postcentral gyri relative to controls. Never-treated patients demonstrated reduced global efficacy, decreased nodal centralities in right amygdala/hippocampus and bilateral putamen/caudate relative to antipsychotic-treated patients and controls. No significant relationships of age and altered functional metrics were seen in either patient group, and no alterations were greater in the treated group. These findings provide insight into brain function deficits over the longer-term course of schizophrenia independent from potential effects of antipsychotic medication. The presence of greater alterations in never-treated than treated patients suggests that long-term antipsychotic treatment may partially protect or enhance brain global and nodal topological function over the course of schizophrenia, notably involving the amygdala, hippocampus, and striatum that have long been associated with the disorder.

Disrupted Corollary Discharge in Schizophrenia: Evidence From the Oculomotor System

Corollary discharge (CD) signals are motor-related signals that exert an influence on sensory processing. They allow mobile organisms to predict the sensory consequences of their imminent actions. Among the many functions of CD is to provide a means by which we can distinguish sensory experiences caused by our own actions from those with external causes. In this way, they contribute to a subjective sense of agency. A disruption in the sense of agency is central to many of the clinical symptoms of schizophrenia, and abnormalities in CD signaling have been theorized to underpin particularly those agency-related psychotic symptoms of the illness. Characterizing abnormal CD associated with eye movements in schizophrenia and their resulting influence on visual processing and subsequent action plans may have advantages over other sensory and motor systems. That is because the most robust psychophysiological and neurophysiological data regarding the dynamics and influence of CD as well as the neural circuitry implicated in CD generation and transmission comes from the study of eye movements in humans and nonhuman primates. We review studies of oculomotor CD signaling in the schizophrenia spectrum and possible neurobiological correlates of CD disturbances. We conclude by speculating on the ways in which oculomotor CD dysfunction, specifically, may invoke specific experiences, clinical symptoms, and cognitive impairments. These speculations lay the groundwork for empirical study, and we conclude by outlining potentially fruitful research directions.

Abnormal synchronization of functional and structural networks in schizophrenia

Synchronization is believed to play an important role in information processing of the brain. Mounting evidence supports the hypothesis that schizophrenia is related to impaired neural synchrony. However, most previous studies characterize brain synchronization from the perspective of temporal coordination of distributed neural activity, rather than network properties. Our aim was to investigate the network synchronization alterations in schizophrenia using publically available data. Resting-state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were performed in 96 schizophrenia patients and 120 healthy controls. The whole-brain functional and structural networks were constructed and analyzed using graph theoretical approaches. Inter-group differences in network synchronization were investigated. Both the binary and weighted functional networks of schizophrenia patients exhibited decreased synchronizability (increased eigenratio) than those of healthy controls. With respect to the structural binary networks, schizophrenia patients showed a trend towards excessive synchronizability (decreased eigenratio). In addition, the excessive synchronizability of the structural binary networks was associated with more severe negative symptoms in schizophrenia patients. Our findings provide novel biological evidence that schizophrenia involves a disruption of neural synchrony from the perspective of network properties.

Linking resting-state networks and social cognition in schizophrenia and bipolar disorder

Individuals with schizophrenia and bipolar disorder show alterations in functional neural connectivity during rest. However, resting-state network (RSN) disruptions have not been systematically compared between the two disorders. Further, the impact of RSN disruptions on social cognition, a key determinant of functional outcome, has not been studied. Forty-eight individuals with schizophrenia, 46 with bipolar disorder, and 48 healthy controls completed resting-state functional magnetic resonance imaging. An atlas-based approach was used to examine functional connectivity within nine RSNs across the cortex. RSN connectivity was assessed via nonparametric permutation testing, and associations with performance on emotion perception, mentalizing, and emotion management tasks were examined. Group differences were observed in the medial and lateral visual networks and the sensorimotor network. Individuals with schizophrenia demonstrated reduced connectivity relative to healthy controls in all three networks. Individuals with bipolar disorder demonstrated reduced connectivity relative to controls in the medial visual network and connectivity within this network was significantly positively correlated with emotion management. In healthy controls, connectivity within the medial and lateral visual networks positively correlated with mentalizing. No significant correlations were found for either visual network in schizophrenia. Results highlight the role of altered early visual processing in social cognitive deficits in both schizophrenia and bipolar disorder. However, individuals with bipolar disorder appear to compensate for disrupted visual network connectivity on social cognitive tasks, whereas those with schizophrenia do not. The current study adds clarity on the neurophysiology underlying social cognitive deficits that result in impaired functioning in serious mental illness.

Altered short-term neural plasticity related to schizotypal traits: Evidence from visual adaptation

Abnormalities in synaptic plasticity are argued to underlie the neural dysconnectivity observed in schizophrenia. One way to measure synaptic plasticity is through sensory adaptation, whereby sensory neurons exhibit reduced sensitivity after sustained stimulus exposure. Evidence for decreased adaptation in individuals with schizophrenia is currently inconclusive, possibly due to heterogeneity in clinical and medication status across samples. Here we circumvent these confounds by examining whether altered adaptation is represented sub-clinically in the general population. To test this we used three paradigms from visual perception research that provide a precise and non-invasive index of adaptation in the visual system. Two paradigms involve a class of illusory percepts termed visual aftereffects. The third relies on a visual phenomenon termed binocular rivalry, where incompatible stimuli are presented to the two eyes and observers alternate between perceiving exclusively one stimulus or a combination of the two (i.e. mixed perception). We analyzed the strength and dynamics of visual adaptation in these paradigms, in relation to schizotypy. Our results showed that increased schizotypal traits were related to reduced orientation, but not luminance, aftereffect strength (Exp. 1). Further, increased schizotypy was related to a greater proportion of mixed perception during binocular rivalry (Exp. 1 and 2). Given that visual adaption is well understood at cellular and computational levels, our data suggest that short-term plasticity in the visual system can provide important information about the disease mechanisms of schizophrenia.

White matter connectivity reductions in the pre-clinical continuum of psychosis: A connectome study

Widespread white matter connectivity disruptions have commonly been reported in schizophrenia. However, it is questionable whether structural connectivity decline is specifically associated with schizophrenia or whether it extends along a continuum of psychosis into the healthy population. Elucidating brain structure changes associated with psychotic-like experiences in healthy individuals is insofar important as it is a necessary first step towards our understanding of brain pathology preceding florid psychosis. High resolution, multishell diffusion-weighted magnetic resonance images (MRI) were acquired from 89 healthy individuals. Whole-brain white matter fibre tracking was performed to quantify the strength of white matter connections. Network-based statistics were applied to white matter connections in a regression model in order to test for a linear relationship between streamline count and psychotic-like experiences. A significant subnetwork was identified whereby streamline count declined with increasing psychotic-like experiences. This network of structural connectivity reductions affected all cortical lobes, subcortical structures and the cerebellum and spanned along prominent association and commissural white matter pathways. A widespread network of linearly declining connectivity strength with increasing number of psychotic-like experiences was identified in healthy individuals. This finding is in line with white matter connectivity reductions reported from early to chronic stages of schizophrenia and might therefore aid the development of tools to identify individuals at risk of transitioning to psychosis.

Increased resting-state global functional connectivity density of default mode network in schizophrenia subjects treated with electroconvulsive therapy

Modified electroconvulsive therapy (MECT) has been widely applied to help treat schizophrenia patients who are treatment-resistant to pharmaceutical therapy. Although the technique is increasingly prevalent, the underlying neural mechanisms have not been well clarified. We conducted a longitudinal study to investigate the alteration of global functional connectivity density (gFCD) in schizophrenia patients undergoing MECT using resting state fMRI (functional magnetic resonance imaging). Two groups of schizophrenia inpatients were recruited. One group received a four-week MECT together with antipsychotic drugs (ECT+Drug, n=21); the other group only received antipsychotic drugs (Drug, n=21). Both groups were compared to a sample of healthy controls (HC, n=23). fMRI scans were obtained from the schizophrenia patients twice at baseline (t₁) and after 4-week treatment (t₂), and from healthy controls at baseline. gFCD was computed using resting state fMRI. Repeated ANCOVA showed a significant interaction effect of group×time in the schizophrenia patients in left precuneus (Pcu), ventral medial prefrontal cortex (vMPFC), and dorsal medial prefrontal cortex (dMPFC) (GRF-corrected P<0.05), which are mainly located within the default mode network (DMN). Post-hoc analysis revealed that compared with baseline (t₁), an increased gFCD was found in the ECT+Drug group in the dMPFC (t=3.87, p=0.00095), vMPFC (t=3.95, p=0.00079) and left Pcu (t=3.33, p=0.0034), but no significant effect was identified in the Drug group. The results suggested that increased global functional connectivity density within the DMN might be one important neural mechanism of MECT in schizophrenia.

Cortical Dysconnectivity Measured by Structural Covariance Is Associated With the Presence of Psychotic Symptoms in 22q11.2 Deletion Syndrome

BACKGROUND

22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphology is a method of exploring connectivity among brain regions that to date has not been employed in 22q11DS.

METHODS

In the present study we employed structural covariance of cortical thickness to explore connectivity alterations in a group of 108 patients with 22q11DS compared with 96 control subjects. We subsequently divided patients into two subgroups of 31 subjects each according to the presence of attenuated psychotic symptoms. FreeSurfer software was used to obtain the mean cortical thickness in 148 brain regions from T1-weighted 3T images. For each population we reconstructed a brain graph using Pearson correlation between the average thickness of each couple of brain regions, which we characterized in terms of mean correlation strength and in terms of network architecture using graph theory.

RESULTS

Patients with 22q11DS presented increased mean correlation strength, but there was no difference in global architecture compared with control subjects. However, symptomatic patients presented increased mean correlation strength coupled with increased segregation and decreased integration compared with both control subjects and nonsymptomatic patients. They also presented increased centrality for a cluster of anterior cingulate and dorsomedial prefrontal regions.

CONCLUSIONS

These results confirm the importance of cortical dysconnectivity in the physiopathology of psychosis. Moreover they support the significance of aberrant anterior cingulate connectivity.

Superficial white matter damage in anti-NMDA receptor encephalitis

BACKGROUND

Clinical brain MRI is normal in the majority of patients with anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis. However, extensive deep white matter damage wasrecently identifiedin these patients using diffusion weighted imaging. Here, our aim was to study a particularly vulnerable brain compartment, the late myelinating superficial white matter.

METHODS

Forty-six patients with anti-NMDAR encephalitis were included. Ten out of these were considered neurologically recovered (modified Rankin scale of zero), while 36 patients were non-recovered. In addition, 30 healthy controls were studied. MRI data were collected from all subjects and superficial white matter mean diffusivity derived from diffusion tensor imaging was compared between groups in whole brain, lobar and vertex-based analyses. Patients underwent comprehensive cognitive testing, and correlation analyses were performed between cognitive performance and superficial white matter integrity.

RESULTS

Non-recovered patients showed widespread superficial white matter damage in comparison to recovered patients and healthy controls. Vertex-based analyses revealed that damage predominated in frontal and temporal lobes. In contrast, the superficial white matter was intact in recovered patients. Importantly, persistent cognitive impairments in working memory, verbal memory, visuospatial memory and attention significantly correlated with damage of the superficial white matter in patients.

CONCLUSIONS

Anti-NMDAR encephalitis is associated with extensive superficial white matter damage in patients with incomplete recovery. The strong association with impairment in several cognitive domains highlights the clinical relevance of white matter damage in this disorder and warrants investigations of the underlying pathophysiological mechanisms.

Aberrant patterns of local and long-range functional connectivity densities in schizophrenia

Schizophrenia is a disorder of brain dysconnectivity, and both the connection strength and connection number are disrupted in patients with schizophrenia. The functional connectivity density (FCD) can reflect alterations in the connection number. Alterations in the global FCD (gFCD) in schizophrenia were previously demonstrated; however, alterations in two other indices of the pathological characteristics of the brain, local FCD (lFCD) and long-range FCD (lrFCD), have not been revealed. To investigate lFCD and lrFCD alterations in patients with schizophrenia, 95 patients and 93 matched healthy controls were examined using structural and resting-state functional magnetic resonance imaging scanning. lFCD and lrFCD were measured using FCD mapping, and differences were identified using a two-sample t-test in a voxel-wise manner, with age and gender considered to increase variability. Multiple comparisons were performed using a false discovery rate method with a corrected threshold of P<0.05. Our analysis showed that lFCD was primarily decreased in the postcentral gyrus, right calcarine sulcus, and inferior occipital gyrus lobule, but increased in the bilateral subcortical regions. The differences in lFCD were more pronounced and complicated than those in lrFCD. In summary, in contrast with previous studies that focused on the connection strength, our findings, from the perspective of connection number, indicate that schizophrenia is a disorder of brain dysconnectivity, particularly affecting the local functional connectivity network, and support the hypothesis that schizophrenia is associated with a widespread cortical functional connectivity/activity deficit, with hyper- and/or hypo-connectivity/activity coexisting in some cortical or subcortical regions.

Neural correlates of socio-emotional perception in 22q11.2 deletion syndrome

Background

Social impairments are described as a common feature of the 22q11.2 deletion syndrome (22q11DS). However, the neural correlates underlying these impairments are largely unknown in this population. In this study, we investigated neural substrates of socio-emotional perception.

Methods

We used event-related functional magnetic resonance imaging (fMRI) to explore neural activity in individuals with 22q11DS and healthy controls during the visualization of stimuli varying in social (social or non-social) or emotional (positive or negative valence) content.

Results

Neural hyporesponsiveness in regions of the default mode network (inferior parietal lobule, precuneus, posterior and anterior cingulate cortex and frontal regions) in response to social versus non-social images was found in the 22q11DS population compared to controls. A similar pattern of activation for positive and negative emotional processing was observed in the two groups. No correlation between neural activation and social functioning was observed in patients with the 22q11DS. Finally, no social × valence interaction impairment was found in patients.

Conclusions

Our results indicate atypical neural correlates of social perception in 22q11DS that appear to be independent of valence processing. Abnormalities in the social perception network may lead to social impairments observed in 22q11DS individuals.

Electronic supplementary material

The online version of this article (10.1186/s11689-018-9232-2) contains supplementary material, which is available to authorized users.

Post-genomic behavioral genetics: From revolution to routine

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www.

RESEARCH

va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

Frontal dysconnectivity in 22q11.2 deletion syndrome: an atlas-based functional connectivity analysis

BACKGROUND

22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental syndrome associated with deficits in cognitive and emotional processing. This syndrome represents one of the highest risk factors for the development of schizophrenia. Previous studies of functional connectivity (FC) in 22q11DS report aberrant connectivity patterns in large-scale networks that are associated with the development of psychotic symptoms.

METHODS

In this study, we performed a functional connectivity analysis using the CONN toolbox to test for differential connectivity patterns between 54 individuals with 22q11DS and 30 healthy controls, between the ages of 17-25 years old. We mapped resting-state fMRI data onto 68 atlas-based regions of interest (ROIs) generated by the Desikan-Killany atlas in FreeSurfer, resulting in 2278 ROI-to-ROI connections for which we determined total linear temporal associations between each. Within the group with 22q11DS only, we further tested the association between prodromal symptoms of psychosis and FC.

RESULTS

We observed that relative to controls, individuals with 22q11DS displayed increased FC in lobar networks involving the frontal-frontal, frontal-parietal, and frontal-occipital ROIs. In contrast, FC between ROIs in the parietal-temporal and occipital lobes was reduced in the 22q11DS group relative to healthy controls. Moreover, positive psychotic symptoms were positively associated with increased functional connections between the left precuneus and right superior frontal gyrus, as well as reduced functional connectivity between the bilateral pericalcarine. Positive symptoms were negatively associated with increased functional connectivity between the right pericalcarine and right postcentral gyrus.

CONCLUSIONS

Our results suggest that functional organization may be altered in 22q11DS, leading to disruption in connectivity between frontal and other lobar substructures, and potentially increasing risk for prodromal psychosis.

Meta-analysis of mismatch negativity to simple versus complex deviants in schizophrenia

Mismatch negativity (MMN) deficits in schizophrenia (SCZ) have been studied extensively since the early 1990s, with the vast majority of studies using simple auditory oddball task deviants that vary in a single acoustic dimension such as pitch or duration. There has been a growing interest in using more complex deviants that violate more abstract rules to probe higher order cognitive deficits. It is still unclear how sensory processing deficits compare to and contribute to higher order cognitive dysfunction, which can be investigated with later attention-dependent auditory event-related potential (ERP) components such as a subcomponent of P300, P3b. In this meta-analysis, we compared MMN deficits in SCZ using simple deviants to more complex deviants. We also pooled studies that measured MMN and P3b in the same study sample and examined the relationship between MMN and P3b deficits within study samples. Our analysis reveals that, to date, studies using simple deviants demonstrate larger deficits than those using complex deviants, with effect sizes in the range of moderate to large. The difference in effect sizes between deviant types was reduced significantly when accounting for magnitude of MMN measured in healthy controls. P3b deficits, while large, were only modestly greater than MMN deficits (d=0.21). Taken together, our findings suggest that MMN to simple deviants may still be optimal as a biomarker for SCZ and that sensory processing dysfunction contributes significantly to MMN deficit and disease pathophysiology.

Tracing neuronal circuits in transgenic animals by transneuronal control of transcription (TRACT)

Understanding the computations that take place in brain circuits requires identifying how neurons in those circuits are connected to one another. We describe a technique called TRACT (TRAnsneuronal Control of Transcription) based on ligand-induced intramembrane proteolysis to reveal monosynaptic connections arising from genetically labeled neurons of interest. In this strategy, neurons expressing an artificial ligand (‘donor’ neurons) bind to and activate a genetically-engineered artificial receptor on their synaptic partners (‘receiver’ neurons). Upon ligand-receptor binding at synapses the receptor is cleaved in its transmembrane domain and releases a protein fragment that activates transcription in the synaptic partners. Using TRACT in Drosophila we have confirmed the connectivity between olfactory receptor neurons and their postsynaptic targets, and have discovered potential new connections between neurons in the circadian circuit. Our results demonstrate that the TRACT method can be used to investigate the connectivity of neuronal circuits in the brain.

One of the main obstacles to understanding how the brain works is that we know relatively little about how its nerve cells or neurons are connected to one another. These connections make up the brain’s wiring diagram. Current methods for revealing this wiring all have limitations. The most popular method – serial electron microscopy – can reveal the connections in a small region of the brain in great detail, but it cannot show connections between neurons that are far apart.

Huang et al. have now created a genetic system for visualizing these connections. For neurons to communicate, one neuron must produce a signal called a ligand. This ligand can then bind to and activate its partner neuron. Huang et al. modified the DNA of neurons so that every time those cells produced a specific ligand, they also produced a red fluorescent protein. Similar modifications ensured that every time the ligand activated a partner neuron, the activated neuron produced a green fluorescent protein. Viewing the red and green neurons under a microscope enabled Huang et al. to see which cells were communicating with which others.

While these experiments took place in fruit flies, the same approach should also work in other laboratory animals, including fish, mice and rats. Once we know the wiring diagram of the brain, the next step is to investigate the role of the various connections. To understand how a computer works, for example, we might change the connections between its circuit components and look at how this affects the computer’s output. With this new method, we can change how neurons communicate with one another in the brain, and then look at the effects on behavior. This should provide insights into the workings of the human brain, and clues to what goes wrong in disorders like schizophrenia and autism.

Applications of Resting State Functional MR Imaging to Neuropsychiatric Diseases

Resting state studies in neuropsychiatric disorders have already provided much useful information, but the field is regarded as being at a relatively preliminary stage and subject to several design issues that set limits on the overall utility.

On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification

Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc.

Psychosis in Parkinson's disease: From the soft signs to the hard science

Patients with Parkinson's disease (PD) may develop a wide spectrum of non-motor symptoms during the course of illness. Psychosis is one such commonly observed non-motor symptoms of PD. Although several studies based on neuroimaging, genetics, retinal imaging, and neuropsychological evaluations have explored the pathogenesis of psychosis in PD; exact neural correlates are yet to be understood. Identification of factors related to psychosis in PD is important, as psychosis has been reported to be associated with higher rates of mortality, caregiver distress, and nursing home placements. This review highlights the potential of the previous studies to gain further insights into the soft signs and hard science related to psychosis in PD. Studies based on neuropsychological evaluations have revealed significant dysfunction in attention, executive and visuospatial functions in patients with PD and psychosis. Neuroimaging studies reveal grey matter atrophy in regions of the brain corresponding to both dorsal and ventral visual pathways, hippocampus, and cholinergic structures. Meanwhile, functional imaging studies suggest existence of an aberrant top-to-bottom visual processing system, which dominates the normal bottom-to-top system in patients with PD and visual hallucinations. Although nucleotide polymorphisms of several genes have been studied in PD patients with psychosis, those on -45C>T polymorphisms of cholecystokinin gene (CCK) have shown the greatest promise because of its association with psychosis in PD. All these taken together, cohesively unfold the current status of research in patients with PD and psychosis. This paper also highlights the missing links and discusses the approach to future research in this field.

The application of tDCS for the treatment of psychiatric diseases

Neuroplasticity represents the dynamic structural and functional reorganization of the central nervous system, including its connectivity, due to environmental and internal demands. It is recognized as a major physiological basis for adaption of cognition and behaviour, and, thus, of utmost importance for normal brain function. Cognitive dysfunctions are major symptoms in psychiatric disorders, which are often associated with pathological alteration of neuroplasticity. Transcranial direct current stimulation (tDCS), a recently developed non-invasive brain stimulation technique, is able to induce and modulate cortical plasticity in humans via the application of relatively weak current through the scalp of the head. It has the potential to alter pathological plasticity and restore dysfunctional cognitions in psychiatric diseases. In the last decades, its efficacy to treat psychiatric disorders has been explored increasingly. This review will give an overview of pathological alterations of plasticity in psychiatric diseases, gather clinical studies involving tDCS to ameliorate symptoms, and discuss future directions of application, with an emphasis on optimizing stimulation effects.

Disruptions in the left frontoparietal network underlie resting state endophenotypic markers in schizophrenia

Advances in functional brain imaging have improved the search for potential endophenotypic markers in schizophrenia. Here, we employed independent component analysis (ICA) and dynamic causal modeling (DCM) in resting state fMRI on a sample of 35 schizophrenia patients, 20 first-degree relatives and 35 control subjects. Analysis on ICA-derived networks revealed increased functional connectivity between the left frontoparietal network (FPN) and left temporal and parietal regions in schizophrenia patients (P < 0.001). First-degree relatives shared this hyperconnectivity, in particular in the supramarginal gyrus (SMG; P = 0.008). DCM analysis was employed to further explore underlying effective connectivity. Results showed increased inhibitory connections to the left angular gyrus (AG) in schizophrenia patients from all other nodes of the left FPN (P < 0.001), and in particular from the left SMG (P = 0.001). Relatives also showed a pattern of increased inhibitory connections to the left AG (P = 0.008). Furthermore, the patient group showed increased excitatory connectivity between the left fusiform gyrus and the left SMG (P = 0.002). This connection was negatively correlated to inhibitory afferents to the left AG (P = 0.005) and to the negative symptom score on the PANSS scale (P = 0.001, r = -0.51). Left frontoparietotemporal dysfunction in schizophrenia has been previously associated with a range of abnormalities, including formal thought disorder, working memory dysfunction and sensory hallucinations. Our analysis uncovered new potential endophenotypic markers of schizophrenia and shed light on the organization of the left FPN in patients and their first-degree relatives. Hum Brain Mapp 38:1741-1750, 2017. © 2017 Wiley Periodicals, Inc.

Connectomics-based structural network alterations in obsessive-compulsive disorder

Given the strong involvement of affect in obsessive-compulsive disorder (OCD) and recent findings, the current cortico-striato-thalamo-cortical (CSTC) model of pathophysiology has repeatedly been questioned regarding the specific role of regions involved in emotion processing such as limbic areas. Employing a connectomics approach enables us to characterize structural connectivity on a whole-brain level, extending beyond the CSTC circuitry. Whole-brain structural networks of 41 patients and 42 matched healthy controls were analyzed based on 83 × 83 connectivity matrices derived from cortical and subcortical parcellation of structural T1-weighted magnetic resonance scans and deterministic fiber tracking based on diffusion tensor imaging data. To assess group differences in structural connectivity, the framework of network-based statistic (NBS) was applied. Graph theoretical measures were calculated to further assess local and global network characteristics. The NBS analysis revealed a single network consistently displaying decreased structural connectivity in patients comprising orbitofrontal, striatal, insula and temporo-limbic areas. In addition, graph theoretical measures indicated local alterations for amygdala and temporal pole while the overall topology of the network was preserved. To the best of our knowledge, this is the first study combining the NBS with graph theoretical measures in OCD. Along with regions commonly described in the CSTC model of pathophysiology, our results indicate an involvement of mainly temporo-limbic regions typically associated with emotion processing supporting their importance for neurobiological alterations in OCD.

Reduced Amplitude of Low-Frequency Brain Oscillations in the Psychosis Risk Syndrome and Early Illness Schizophrenia

Low-frequency oscillations (LFOs) of the blood oxygen level-dependent (BOLD) signal are gaining interest as potential biomarkers sensitive to neuropsychiatric pathology. Schizophrenia has been associated with alterations in intrinsic LFOs that covary with cognitive deficits and symptoms. However, the extent to which LFO dysfunction is present before schizophrenia illness onset remains unknown. Resting-state FMRI data were collected from clinical high-risk (CHR; n=45) youth, early illness schizophrenia (ESZ; n=74) patients, and healthy controls (HCs; n=85) aged 12-35 years. Age-adjusted voxelwise fractional amplitude of low-frequency fluctuations (fALFF; 0.01-0.08 Hz) of the BOLD signal was compared among the three groups. Main effects of Group (p<0.005 height threshold, familywise error cluster-level corrected p<0.05) were followed up via Tukey-corrected pairwise comparisons. Significant main effects of Group (p<0.05) revealed decreased fALFF in ESZ and CHR groups relative to HCs, with values in the CHR group falling between those of ESZ and HC groups. These differences were identified primarily in posterior cortex, including temporoparietal regions, extending into occipital and cerebellar lobes. Less LFO activity was related to greater symptom severity in both CHR and ESZ groups in several of these posterior cortical regions. These data support an intermediate phenotype of reduced posterior cortical LFO amplitude in CHR individuals, with resting fALFF values smaller than in HCs but higher than in ESZ patients. Findings indicate that LFO magnitude alterations relate to clinical symptoms and predate psychosis onset but are more pronounced in the early stages of schizophrenia.

Somatic mutations in disorders with disrupted brain connectivity

Mutations occur during cell division in all somatic lineages. Because neurogenesis persists throughout human life, somatic mutations in the brain arise during development and accumulate with the aging process. The human brain consists of 100 billion neurons that form an extraordinarily intricate network of connections to achieve higher level cognitive functions. Due to this network architecture, perturbed neuronal functions are rarely restricted to a focal area; instead, they are often spread via the neuronal network to affect other connected areas. Although somatic diversity is an evident feature of the brain, the extent to which somatic mutations affect the neuronal structure and function and their contribution to neurological disorders associated with disrupted brain connectivity remain largely unexplored. Notably, recent reports indicate that brain somatic mutations can indeed play a critical role that leads to the structural and functional abnormalities of the brain observed in several neurodevelopmental disorders. Here, I review the extent and significance of brain somatic mutations and provide my perspective regarding these mutations as potential molecular lesions underlying relatively common conditions with disrupted brain connectivity. Moreover, I discuss emerging technical platforms that will facilitate the detection of low-frequency somatic mutations and validate the biological functions of the identified mutations in the context of brain connectivity.

Overexpression of Isoforms of Nitric Oxide Synthase 1 Adaptor Protein, Encoded by a Risk Gene for Schizophrenia, Alters Actin Dynamics and Synaptic Function

Proper communication between neurons depends upon appropriate patterning of dendrites and correct distribution and structure of spines. Schizophrenia is a neuropsychiatric disorder characterized by alterations in dendrite branching and spine density. Nitric oxide synthase 1 adaptor protein (NOS1AP), a risk gene for schizophrenia, encodes proteins that are upregulated in the dorsolateral prefrontal cortex (DLPFC) of individuals with schizophrenia. To elucidate the effects of NOS1AP overexpression observed in individuals with schizophrenia, we investigated changes in actin dynamics and spine development when a long (NOS1AP-L) or short (NOS1AP-S) isoform of NOS1AP is overexpressed. Increased NOS1AP-L protein promotes the formation of immature spines when overexpressed in rat cortical neurons from day in vitro (DIV) 14 to DIV 17 and reduces the amplitude of miniature excitatory postsynaptic currents (mEPSCs). In contrast, increased NOS1AP-S protein increases the rate of actin polymerization and the number of immature and mature spines, which may be attributed to a decrease in total Rac1 expression and a reduction in the levels of active cofilin. The increase in the number of mature spines by overexpression of NOS1AP-S is accompanied by an increase in the frequency of mEPSCs. Our findings show that overexpression of NOS1AP-L or NOS1AP-S alters the actin cytoskeleton and synaptic function. However, the mechanisms by which these isoforms induce these changes are distinct. These results are important for understanding how increased expression of NOS1AP isoforms can influence spine development and synaptic function.

Atypical functional connectivity in resting-state networks of individuals with 22q11.2 deletion syndrome: associations with neurocognitive and psychiatric functioning

BACKGROUND

22q11.2 deletion syndrome (22q11DS) is a neurogenetic condition associated with deficits in neuropsychological functioning and psychiatric disorders. This deletion confers a high risk for the development of psychosis, as approximately 30-45 % of individuals develop psychosis in adulthood. Previous reports of resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity patterns in 22q11DS have demonstrated that atypical connectivity is associated with both the emergence and severity of psychotic symptoms. However, due to sample overlap and large age ranges of samples spanning multiple critical periods of brain maturation, more independent studies with samples within the window of time when psychotic symptoms have been shown to emerge (ages 17-26) are needed. Resting-state networks (RSNs) in 22q11DS during this stage of brain development may thus provide insight into the dynamic changes in functional integration that influence the incidence of prodromal symptoms and neurocognitive deficits characteristic of this syndrome.

METHODS

Independent component analysis (ICA) was performed to identify RSNs in a combined sample of 55 individuals with 22q11DS (27 males; age range 17-26) and 29 controls (17 males; age range 17-23, consisting of 8 siblings without the deletion and 21 typically developed individuals) from two research sites. We conducted a full factorial analysis to determine group differences between 22q11DS and controls. A Poisson regression analysis was conducted in the 22q11DS group to determine relationships of rs-fMRI network connectivity with psychiatric symptoms based on factors of the 18-item Brief Psychiatric Rating Scale. Nonparametric Spearman correlations were performed to test associations between within-network functional connectivity (FC) and performance on measures of verbal memory (California Verbal Learning Test) and executive function (Behavior Rating Inventory of Executive Function Adult version) in 22q11DS.

RESULTS

Between-group network connectivity analyses revealed significant differences in 9 RSNs. Decreased network FC in 22q11DS was observed in the following networks: high-level visual processing network (HLVPN), low-level visual processing network (LLVPN), visual/precuneus network, left frontal-parietal network (LFPN), right frontal-parietal network (RFPN), and self-referential network (SRN). In contrast, greater network FC in 22q11DS was observed in subclusters of the LLVPN, visual/precuneus network, limbic network (LN), default mode network (DMN), and visuospatial processing network (VSPN). Increased functional connectivity of the right cuneus (visual/precuneus network) and right superior parietal lobule (DMN) in 22q11DS was positively associated with both thought disturbance and disorganization factors of the Brief Psychiatric Rating Scale (BPRS). Decreased functional connectivity in the left posterior cingulate (LLVPN) was associated with higher thought disturbance scores in 22q11DS. No associations with our neurocognitive measures passed correction for multiple comparisons (Bonferroni-corrected p ≤ 0.0014).

CONCLUSIONS

Our findings suggest that atypical network connectivity within RSNs may be indicative of increased risk for developing psychosis and supports the utility of RSNs as biomarkers of prodromal symptoms in 22q11DS.

Diffusion magnetic resonance imaging study of schizophrenia in the context of abnormal neurodevelopment using multiple site data in a Chinese Han population

Schizophrenia has increasingly been considered a neurodevelopmental disorder, and the advancement of neuroimaging techniques and associated computational methods has enabled quantitative re-examination of this important theory on the pathogenesis of the disease. Inspired by previous findings from neonatal brains, we proposed that an increase in diffusion magnetic resonance imaging (dMRI) mean diffusivity (MD) should be observed in the cerebral cortex of schizophrenia patients compared with healthy controls, corresponding to lower tissue complexity and potentially a failure to reach cortical maturation. We tested this hypothesis using dMRI data from a Chinese Han population comprising patients from four different hospital sites. Utilizing data-driven methods based on the state-of-the-art tensor-based registration algorithm, significantly increased MD measurements were consistently observed in the cortex of schizophrenia patients across all four sites, despite differences in psychopathology, exposure to antipsychotic medication and scanners used for image acquisition. Specifically, we found increased MD in the limbic system of the schizophrenic brain, mainly involving the bilateral insular and prefrontal cortices. In light of the existing literature, we speculate that this may represent a neuroanatomical signature of the disorder, reflecting microstructural deficits due to developmental abnormalities. Our findings not only provide strong support to the abnormal neurodevelopment theory of schizophrenia, but also highlight an important neuroimaging endophenotype for monitoring the developmental trajectory of high-risk subjects of the disease, thereby facilitating early detection and prevention.

Topological Alterations of the Intrinsic Brain Network in Patients with Functional Dyspepsia

BACKGROUND/AIMS

Previous studies reported that integrated information in the brain ultimately determines the subjective experience of patients with chronic pain, but how the information is integrated in the brain connectome of functional dyspepsia (FD) patients remains largely unclear. The study aimed to quantify the topological changes of the brain network in FD patients.

METHODS

Small-world properties, network efficiency and nodal centrality were utilized to measure the changes in topological architecture in 25 FD patients and 25 healthy controls based on functional magnetic resonance imaging. Pearson's correlation assessed the relationship of each topological property with clinical symptoms.

RESULTS

FD patients showed an increase of clustering coefficients and local efficiency relative to controls from the perspective of a whole network as well as elevated nodal centrality in the right orbital part of the inferior frontal gyrus, left anterior cingulate gyrus and left hippocampus, and decreased nodal centrality in the right posterior cingulate gyrus, left cuneus, right putamen, left middle occipital gyrus and right inferior occipital gyrus. Moreover, the centrality in the anterior cingulate gyrus was significantly associated with symptom severity and duration in FD patients. Nevertheless, the inclusion of anxiety and depression scores as covariates erased the group differences in nodal centralities in the orbital part of the inferior frontal gyrus and hippocampus.

CONCLUSIONS

The results suggest topological disruption of the functional brain networks in FD patients, presumably in response to disturbances of sensory information integrated with emotion, memory, pain modulation, and selective attention in patients.