Anatomical dysconnectivity in bipolar disorder compared with schizophrenia: A selective review of structural network analyses using diffusion MRI

Age Trajectories of the Structural Connectome in Child and Adolescent Offspring of Individuals With Bipolar Disorder or Schizophrenia

Background

Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at elevated risk of developing psychiatric illness owing to both genetic predisposition and increased burden of environmental stress. Emerging evidence indicates a disruption of brain network connectivity in young offspring of patients with bipolar disorder and schizophrenia, but the age trajectories of these brain networks in this high-familial-risk population remain to be elucidated.

Methods

A total of 271 T1-weighted and diffusion-weighted scans were obtained from 174 offspring of at least 1 parent diagnosed with bipolar disorder (n = 74) or schizophrenia (n = 51) and offspring of parents without severe mental illness (n = 49). The age range was 8 to 23 years; 97 offspring underwent 2 scans. Anatomical brain networks were reconstructed into structural connectivity matrices. Network analysis was performed to investigate anatomical brain connectivity.

Results

Offspring of parents with schizophrenia had differential trajectories of connectivity strength and clustering compared with offspring of parents with bipolar disorder and parents without severe mental illness, of global efficiency compared with offspring of parents without severe mental illness, and of local connectivity compared with offspring of parents with bipolar disorder.

Conclusions

The findings of this study suggest that familial high risk of schizophrenia is related to deviations in age trajectories of global structural connectome properties and local connectivity strength.

Non-linear development of brain morphometry in child and adolescent offspring of individuals with bipolar disorder or schizophrenia

Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at increased risk of developing psychopathology. Structural brain alterations have been found in child and adolescent offspring of patients with bipolar disorder and schizophrenia, but the developmental trajectories of brain anatomy in this high-familial-risk population are still unclear. 300 T1-weighted scans were obtained of 187 offspring of at least one parent diagnosed with bipolar disorder (n=80) or schizophrenia (n=53) and offspring of parents without severe mental illness (n=54). The age range was 8 to 23 years old; 113 offspring underwent two scans. Global brain measures and regional cortical thickness and surface area were computed. A generalized additive mixed model was used to capture non-linear age trajectories. Offspring of parents with schizophrenia had smaller total brain volume than offspring of parents with bipolar disorder (d=-0.20, p=0.004) and control offspring (d=-0.22, p=0.005) and lower mean cortical thickness than control offspring (d=-0.23, p<0.001). Offspring of parents with schizophrenia showed differential age trajectories of mean cortical thickness and cerebral white matter volume compared with control offspring (both p's=0.003). Regionally, offspring of parents with schizophrenia had a significantly different trajectory of cortical thickness in the middle temporal gyrus versus control offspring (p<0.001) and bipolar disorder offspring (p=0.001), which was no longer significant after correcting for mean cortical thickness. These findings suggest that particularly familial high risk of schizophrenia is related to reductions and deviating developmental trajectories of global brain structure measures, which were not driven by specific regions.

Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder

OBJECTIVE

Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms.

METHODS

Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups.

RESULTS

Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively.

CONCLUSION

This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.

Diagnostic value of regional homogeneity and fractional amplitude of low-frequency fluctuations in the classification of schizophrenia and bipolar disorders

Schizophrenia (SCZ) and bipolar disorders (BD) show significant neurobiological and clinical overlap. In this study, we wanted to identify indexes of intrinsic brain activity that could differentiate these disorders. We compared the diagnostic value of the fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) estimated from resting-state functional magnetic resonance imaging in a support vector machine classification of 59 healthy controls (HC), 40 individuals with SCZ, and 43 individuals with BD type I. The best performance, measured by balanced accuracy (BAC) for binary classification relative to HC was achieved by a stacking model (87.4% and 90.6% for SCZ and BD, respectively), with ReHo performing better than fALFF, both in SCZ (86.2% vs. 79.4%) and BD (89.9% vs. 76.9%). BD were better differentiated from HC by fronto-temporal ReHo and striato-temporo-thalamic fALFF. SCZ were better classified from HC using fronto-temporal-cerebellar ReHo and insulo-tempo-parietal-cerebellar fALFF. In conclusion, we provided evidence of widespread aberrancies of spontaneous activity and local connectivity in SCZ and BD, demonstrating that ReHo features exhibited superior discriminatory power compared to fALFF and achieved higher classification accuracies. Our results support the complementarity of these measures in the classification of SCZ and BD and suggest the potential for multivariate integration to improve diagnostic precision.

Increased grey matter volumes in the temporal lobe and its relationship with cognitive functioning in euthymic patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by episodic mood dysregulation, although a significant portion of patients suffer persistent cognitive impairment during euthymia. Previous magnetic resonance imaging (MRI) research suggests BD patients may have accelerated brain aging, observed as lower grey matter volumes. How these neurostructural alterations are related to the cognitive profile of BD is unclear.

METHODS

We aim to explore this relationship in euthymic BD patients with multimodal structural neuroimaging. A sample of 27 euthymic BD patients and 24 healthy controls (HC) underwent structural grey matter MRI and diffusion-weighted imaging (DWI). BD patient's cognition was also assessed. FreeSurfer algorithms were used to obtain estimations of regional grey matter volumes. White matter pathways were reconstructed using TRACULA, and four diffusion metrics were extracted. ANCOVA models were performed to compare BD patients and HC values of regional grey matter volume and diffusion metrics. Global brain measures were also compared. Bivariate Pearson correlations were explored between significant brain results and five cognitive domains.

RESULTS

Euthymic BD patients showed higher ventricular volume (F(1, 46) = 6.04; p = 0.018) and regional grey matter volumes in the left fusiform (F(1, 46) = 15.03; pFDR = 0.015) and bilateral parahippocampal gyri compared to HC (L: F(1, 46) = 12.79, pFDR = 0.025/ R: F(1, 46) = 15.25, pFDR = 0.015). Higher grey matter volumes were correlated with greater executive function (r = 0.53, p = 0.008).

LIMITATIONS

We evaluated a modest sample size with concurrent pharmacological treatment.

CONCLUSIONS

Higher medial temporal volumes in euthymic BD patients may be a potential signature of brain resilience and cognitive adaptation to a putative illness neuroprogression. This knowledge should be integrated into further efforts to implement imaging into BD clinical management.

Children at Familial High risk of Schizophrenia and Bipolar Disorder Exhibit Altered Connectivity Patterns During Pre-attentive Processing of an Auditory Prediction Error

BACKGROUND AND HYPOTHESIS

Individuals with schizophrenia or bipolar disorder have attenuated auditory mismatch negativity (MMN) responses, indicating impaired sensory information processing. Computational models of effective connectivity between brain areas underlying MMN responses show reduced connectivity between fronto-temporal areas in individuals with schizophrenia. Here we ask whether children at familial high risk (FHR) of developing a serious mental disorder show similar alterations.

STUDY DESIGN

We recruited 67 children at FHR for schizophrenia, 47 children at FHR for bipolar disorder as well as 59 matched population-based controls from the Danish High Risk and Resilience study. The 11-12-year-old participants engaged in a classical auditory MMN paradigm with deviations in frequency, duration, or frequency and duration, while we recorded their EEG. We used dynamic causal modeling (DCM) to infer on the effective connectivity between brain areas underlying MMN.

STUDY RESULTS

DCM yielded strong evidence for differences in effective connectivity among groups in connections from right inferior frontal gyrus (IFG) to right superior temporal gyrus (STG), along with differences in intrinsic connectivity within primary auditory cortex (A1). Critically, the 2 high-risk groups differed in intrinsic connectivity in left STG and IFG as well as effective connectivity from right A1 to right STG. Results persisted even when controlling for past or present psychiatric diagnoses.

CONCLUSIONS

We provide novel evidence that connectivity underlying MMN responses in children at FHR for schizophrenia and bipolar disorder is altered at the age of 11-12, echoing findings that have been found in individuals with manifest schizophrenia.

Dynamic functional connectivity in schizophrenia and bipolar disorder: A review of the evidence and associations with psychopathological features

Alterations of functional network connectivity have been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). Recent studies also suggest that the temporal dynamics of functional connectivity (dFC) can be altered in these disorders. Here, we summarized the existing literature on dFC in SCZ and BD, and their association with psychopathological and cognitive features. We systematically searched PubMed, Web of Science, and Scopus for studies investigating dFC in SCZ and BD and identified 77 studies. Our findings support a general model of dysconnectivity of dFC in SCZ, whereas a heterogeneous picture arose in BD. Although dFC alterations are more severe and widespread in SCZ compared to BD, dysfunctions of a triple network system underlying goal-directed behavior and sensory-motor networks were present in both disorders. Furthermore, in SCZ, positive and negative symptoms were associated with abnormal dFC. Implications for understanding the pathophysiology of disorders, the role of neurotransmitters, and treatments on dFC are discussed. The lack of standards for dFC metrics, replication studies, and the use of small samples represent major limitations for the field.

Multi-Site Statistical Mapping of Along-Tract Microstructural Abnormalities in Bipolar Disorder with Diffusion MRI Tractometry

Investigating alterations in brain circuitry associated with bipolar disorder (BD) may offer a valuable approach to discover brain biomarkers for genetic and interventional studies of the disorder and related mental illnesses. Some diffusion MRI studies report evidence of microstructural abnormalities in white matter regions of interest, but we lack a fine-scale spatial mapping of brain microstructural differences along tracts in BD. We also lack large-scale studies that integrate tractometry data from multiple sites, as larger datasets can greatly enhance power to detect subtle effects and assess whether effects replicate across larger international datasets. In this multisite diffusion MRI study, we used BUndle ANalytics (BUAN, Chandio 2020), a recently developed analytic approach for tractography, to extract, map, and visualize profiles of microstructural abnormalities on 3D models of fiber tracts in 148 participants with BD and 259 healthy controls from 6 independent scan sites. Modeling site differences as random effects, we investigated along-tract white matter (WM) microstructural differences between diagnostic groups. QQ plots showed that group differences were gradually enhanced as more sites were added. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic, interhemispheric, and posterior pathways; higher FA was also noted in posterior bundles, relative to controls. By integrating tractography and anatomical information, BUAN effectively captures unique effects along white matter (WM) tracts, providing valuable insights into anatomical variations that may assist in the classification of diseases.

Along-Tract Statistical Mapping of Microstructural Abnormalities in Bipolar Disorder: A Pilot Study

Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN)-a recently developed analytic approach for tractography-to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean fractional anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls.Clinical Relevance- BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.

Abnormal dynamic functional network connectivity in patients with early-onset bipolar disorder

Objective

To explore the changes in dynamic functional brain network connectivity (dFNC) in patients with early-onset bipolar disorder (BD).

Methods

Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 39 patients with early-onset BD and 22 healthy controls (HCs). Four repeated and stable dFNC states were characterised by independent component analysis (ICA), sliding time windows and k-means clustering, and three dFNC temporal metrics (fraction of time, mean dwell time and number of transitions) were obtained. The dFNC temporal metrics and the differences in dFNC between the two groups in different states were evaluated, and the correlations between the differential dFNC metrics and neuropsychological scores were analysed.

Results

The dFNC analysis showed four connected patterns in all subjects. Compared with the HCs, the dFNC patterns of early-onset BD were significantly altered in all four states, mainly involving impaired cognitive and perceptual networks. In addition, early-onset BD patients had a decreased fraction of time and mean dwell time in state 2 and an increased mean dwell time in state 3 (p < 0.05). The mean dwell time in state 3 of BD showed a positive correlation trend with the HAMA score (r = 0.4049, p = 0.0237 × 3 > 0.05 after Bonferroni correction).

Conclusion

Patients with early-onset BD had abnormal dynamic properties of brain functional network connectivity, suggesting that their dFNC was unstable, mainly manifesting as impaired coordination between cognitive and perceptual networks. This study provided a new imaging basis for the neuropathological study of emotional and cognitive deficits in early-onset BD.

A review of resting-state fMRI correlations with executive functions and social cognition in bipolar disorder

BACKGROUND

Deficits in executive functions (EF) and social cognition (SC) are often observed in bipolar disorder (BD), leading to a severe impairment in engaging a functional interaction with the others and the surrounding environment. Therefore, in recent years, resting-state functional magnetic resonance imaging (rs-fMRI) studies on BD tried to identify the neural underpinnings of these cognitive domains by exploring the association between the intrinsic functional connectivity (FC) and the scores in clinical scales evaluating these domains.

METHODS

A bibliographic search on PubMed and Scopus of studies evaluating the correlations between rs-fMRI findings and EF and/or SC in BD was conducted until March 2022. Ten studies met the inclusion criteria.

RESULTS

Overall, the results of the reviewed studies showed that BD patients had FC deficits compared to healthy controls (HC) in selective resting-state networks involved in EF and SC, which include the default mode network, especially the link between medial prefrontal cortex and posterior cingulate cortex, and the sensory-motor network. Finally, it also emerged the predominant role of alterations in prefrontal connections in explaining the cognitive deficits in BD patients.

LIMITATIONS

The heterogeneity of the reviewed studies, in terms of cognitive domains explored and neuroimaging acquisitions, limited the comparability of the findings.

CONCLUSIONS

rs-fMRI studies could help deepen the brain network alterations underlying EF and SC deficits in BD, pointing the attention on the neuronal underpinning of cognition, whose knowledge may lead to the development of new neurobiological-based approaches to improve the quality of life of these patients.

Along-Tract Statistical Mapping of Microstructural Abnormalities in Bipolar Disorder: A Pilot Study

Investigating brain circuitry involved in bipolar disorder (BD) is key to discovering brain biomarkers for genetic and interventional studies of the disorder. Even so, prior research has not provided a fine-scale spatial mapping of brain microstructural differences in BD. In this pilot diffusion MRI dataset, we used BUndle ANalytics (BUAN), a recently developed analytic approach for tractography, to extract, map, and visualize the profile of microstructural abnormalities on a 3D model of fiber tracts in people with BD (N=38) and healthy controls (N=49), and investigate along-tract white matter (WM) microstructural differences between these groups. Using the BUAN pipeline, BD was associated with lower mean Fractional Anisotropy (FA) in fronto-limbic and interhemispheric pathways and higher mean FA in posterior bundles relative to controls. BUAN combines tractography and anatomical information to capture distinct along-tract effects on WM microstructure that may aid in classifying diseases based on anatomical differences.

Shared and Specific Patterns of Structural Brain Connectivity Across Affective and Psychotic Disorders

BACKGROUND

Altered brain structural connectivity has been implicated in the pathophysiology of psychiatric disorders including schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). However, it is unknown which part of these connectivity abnormalities are disorder specific and which are shared across the spectrum of psychotic and affective disorders. We investigated common and distinct brain connectivity alterations in a large sample (N = 1743) of patients with SZ, BD, or MDD and healthy control (HC) subjects.

METHODS

This study examined diffusion-weighted imaging-based structural connectome topology in 720 patients with MDD, 112 patients with BD, 69 patients with SZ, and 842 HC subjects (mean age of all subjects: 35.7 years). Graph theory-based network analysis was used to investigate connectome organization. Machine learning algorithms were trained to classify groups based on their structural connectivity matrices.

RESULTS

Groups differed significantly in the network metrics global efficiency, clustering, present edges, and global connectivity strength with a converging pattern of alterations between diagnoses (e.g., efficiency: HC > MDD > BD > SZ, false discovery rate-corrected p = .028). Subnetwork analysis revealed a common core of edges that were affected across all 3 disorders, but also revealed differences between disorders. Machine learning algorithms could not discriminate between disorders but could discriminate each diagnosis from HC. Furthermore, dysconnectivity patterns were found most pronounced in patients with an early disease onset irrespective of diagnosis.

CONCLUSIONS

We found shared and specific signatures of structural white matter dysconnectivity in SZ, BD, and MDD, leading to commonly reduced network efficiency. These results showed a compromised brain communication across a spectrum of major psychiatric disorders.

Multimodal data fusion of cortical-subcortical morphology and functional network connectivity in psychotic spectrum disorder

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Overlap has been noted disorders which fall on the psychotic spectrum.

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Univariate studies may miss joint brain features across diagnostic categories.

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mCCA with jICA is paired with features across the psychotic spectrum to produce joint components.

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One joint component displayed a significant relationship with cognitive scores.

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The replicate trends of cortical-subcortical irregularity in psychotic spectrum disorders.

Multiple authors have noted overlapping symptoms and alterations across clinical, anatomical, and functional brain features in schizophrenia (SZ), schizoaffective disorder (SZA), and bipolar disorder (BPI). However, regarding brain features, few studies have approached this line of inquiry using analytical techniques optimally designed to extract the shared features across anatomical and functional information in a simultaneous manner. Univariate studies of anatomical or functional alterations across these disorders can be limited and run the risk of omitting small but potentially crucial overlapping or joint neuroanatomical (e.g., structural images) and functional features (e.g., fMRI-based features) which may serve as informative clinical indicators of across multiple diagnostic categories. To address this limitation, we paired an unsupervised multimodal canonical correlation analysis (mCCA) together with joint independent component analysis (jICA) to identify linked spatial gray matter (GM), resting-state functional network connectivity (FNC), and white matter fractional anisotropy (FA) features across these diagnostic categories. We then calculated associations between the identified linked features and trans-diagnostic behavioral measures (MATRICs Consensus Cognitive Battery, MCCB).

Component number 4 of the 13 identified displayed a statistically significant relationship with overall MCCB scores across GM, resting-state FNC, and FA. These linked modalities of component 4 consisted primarily of positive correlations within subcortical structures including the caudate and putamen in the GM maps with overall MCCB, sparse negative correlations within subcortical and cortical connection tracts (e.g., corticospinal tract, superior longitudinal fasciculus) in the FA maps with overall MCCB, and negative relationships with MCCB values and loading parameters with FNC matrices displaying increased FNC in subcortical-cortical regions with auditory, somatomotor, and visual regions.

Neural network of bipolar disorder: Toward integration of neuroimaging and neurocircuit-based treatment strategies

Bipolar disorder (BD) is a complex psychiatric disorder characterized by dysfunctions in three domains including emotional processing, cognitive processing, and psychomotor dimensions. However, the neural underpinnings underlying these clinical profiles are not well understood. Based on the reported data, we hypothesized that (i) the core neuropathology in BD is damage in fronto-limbic network, which is associated with emotional dysfunction; (ii) changes in intrinsic brain network, such as sensorimotor network, salience network, default-mode network, central executive network are associated with impaired cognition function; and (iii) beyond the dopaminergic-driven basal ganglia-thalamo-cortical motor circuit modulated by other neurotransmitter systems, such as serotonin (subcortical-cortical modulation), the sensorimotor network and related motor function modulated by other non-motor networks such as the default-mode network are involved in psychomotor function. In this review, we propose a neurocircuit-based clinical characteristics and taxonomy to guide the treatment of BD. We draw on findings from neuropsychological and neuroimaging studies in BD and link variations in these clinical profiles to underlying neurocircuit dysfunctions. We consider pharmacological, psychotherapy, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions in BD. Finally, it is suggested that the methods of testing the neurocircuit-based taxonomy and important limitations to this approach should be considered in future.

Structural connectivity associated with familial risk for mental illness: A meta‐analysis of diffusion tensor imaging studies in relatives of patients with severe mental disorders

Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable conditions with overlapping genetic liability. Transdiagnostic and disorder‐specific brain changes associated with familial risk for developing these disorders remain poorly understood. We carried out a meta‐analysis of diffusion tensor imaging (DTI) studies to investigate white matter microstructure abnormalities in relatives that might correspond to shared and discrete biomarkers of familial risk for psychotic or mood disorders. A systematic search of PubMed and Embase was performed to identify DTI studies in relatives of SCZ, BD, and MDD patients. Seed‐based d Mapping software was used to investigate global differences in fractional anisotropy (FA) between overall and disorder‐specific relatives and healthy controls (HC). Our search identified 25 studies that met full inclusion criteria. A total of 1,144 relatives and 1,238 HC were included in the meta‐analysis. The overall relatives exhibited decreased FA in the genu and splenium of corpus callosum (CC) compared with HC. This finding was found highly replicable in jack‐knife analysis and subgroup analyses. In disorder‐specific analysis, compared to HC, relatives of SCZ patients exhibited the same changes while those of BD showed reduced FA in the left inferior longitudinal fasciculus (ILF). The present study showed decreased FA in the genu and splenium of CC in relatives of SCZ, BD, and MDD patients, which might represent a shared familial vulnerability marker of severe mental illness. The white matter abnormalities in the left ILF might represent a specific familial risk for bipolar disorder.

White Matter Hyperintensities after Five-Year Follow-Up and a Cross-Sectional FA Decrease in Bipolar I and Major Depressive Patients

INTRODUCTION

An increase in brain white matter hyperintensities (WMHs) and a decrease in white matter fractional anisotrophy (FA) have been detected in bipolar I (BPI), II (BPII), and major depressive disorder (MDD) patients. Their relationship, and differences in diagnostic groups are obscure. Longitudinal studies are rare.

OBJECTIVE

After 5-year follow-up, we evaluated WMHs in BPI, BPII, and MDD patients as compared with controls, and studied the effects of clinical variables. We also explored the associations of clinical variables with cross-sectional whole brain FA.

METHODS

Eight BPI, 8 BPII, 6 MDD patients, and 19 controls participated in magnetic resonance imaging at baseline and follow-up. Diffusion weighted imaging was included at follow-up. WMHs were rated by the Coffey scale, and a tract-based spatial statistics method was used for diffusion data. The general linear model, ANOVA, Fisher's exact, Wilcoxon sign, and Kruskal-Wallis tests were used for statistical analyses.

RESULTS

Periventricular WMHs were increased in BPI patients (p = 0.047) and associated with the duration of disorder and lifetime occurrence of substance use disorder (p = 0.018). FA decrease was found in the corpus callosum of BPI patients (p < 0.01). MDD patients showed FA decrease in the right cerebellar middle peduncle (RCMP) (p < 0.01). In BPI patients, the duration of disorder associated with FA increase in RCMP (p < 0.05). No FA decrease was detected in patients with WMHs as compared with those without.

CONCLUSIONS

Preceding illness burden associated modestly with WMHs, and FA increase in RCMP in BPI patients. MDD patients had FA decrease in RCMP. No association with FA decrease and WMHs was found.

Neurocognition, functional outcome, and quality of life in remitted and non-remitted schizophrenia: A comparison with euthymic bipolar I disorder and a control group

There are discrepancies about if the severity of the symptomatology in schizophrenia is related to neurocognitive performance, functional outcome, and quality of life (QoL). Also, there are controversial data about the comparison between euthymic bipolar patients and different subgroups of schizophrenia in neurocognition, functioning, and QoL level. The present study aimed to compare the neurocognitive performance, functional outcome, and QoL of remitted and non-remitted patients with SC with respect to a group of euthymic patients with BD, and a control group. It included 655 subjects: 98 patients with schizophrenia in remission (SC-R), 184 non-remitted patients with schizophrenia (SC-NR), 117 euthymic patients with bipolar I disorder (BD), and 256 healthy subjects. A comprehensive clinical, neurocognitive (six cognitive domains), functional, and QoL assessment was carried out. Remission criteria of Andreasen were used to classify schizophrenia patients as remitted or non-remitted. Compared with control subjects all groups of patients showed impaired neurocognitive performance, functioning and QoL. SC-R patients had an intermediate functioning between control subjects and SC-NR, all at a neurocognitive, functional, or QoL level. There were no significant differences between SC-R and BD. These results suggest that reaching clinical remission is essential to achieve a better level of psychosocial functioning, and QoL. Likewise, the results of this study suggest that euthymic patients with bipolar disorder and patients with schizophrenia in remission are comparable at the neurocognitive and functional levels, which might have implications in the pathophysiology of both disorders.

Common and specific patterns of functional and structural brain alterations in schizophrenia and bipolar disorder: a multimodal voxel-based meta-analysis

BACKGROUND

Schizophrenia and bipolar disorder have been linked to alterations in the functional activity and grey matter volume of some brain areas, reflected in impaired regional homogeneity and aberrant voxel-based morphometry. However, because of variable findings and methods used across studies, identifying patterns of brain alteration in schizophrenia and bipolar disorder has been difficult.

METHODS

We conducted a meta-analysis of differences in regional homogeneity and voxel-based morphometry between patients and healthy controls for schizophrenia and bipolar disorder separately, using seed-based d mapping.

RESULTS

We included 45 publications on regional homogeneity (26 in schizophrenia and 19 in bipolar disorder) and 190 publications on voxel-based morphometry (120 in schizophrenia and 70 in bipolar disorder). Patients with schizophrenia showed increased regional homogeneity in the frontal cortex and striatum and the supplementary motor area; they showed decreased regional homogeneity in the insula, primary sensory cortex (visual and auditory cortices) and sensorimotor cortex. Patients with bipolar disorder showed increased regional homogeneity in the frontal cortex and striatum; they showed decreased regional homogeneity in the insula. Patients with schizophrenia showed decreased grey matter volume in the superior temporal gyrus, inferior frontal gyrus, cingulate cortex and cerebellum. Patients with bipolar disorder showed decreased grey matter volume in the insula, cingulate cortex, frontal cortex and thalamus. Overlap analysis showed that patients with schizophrenia displayed decreased regional homogeneity and grey matter volume in the left insula and left superior temporal gyrus; patients with bipolar disorder displayed decreased regional homogeneity and grey matter volume in the left insula.

LIMITATIONS

The small sample size for our subgroup analysis (unmedicated versus medicated patients and substantial heterogeneity in the results for some regions could limit the interpretability and generalizability of the results.

CONCLUSION

Patients with schizophrenia and bipolar disorder shared a common pattern of regional functional and structural alterations in the insula and frontal cortex. Patients with schizophrenia showed more widespread functional and structural impairment, most prominently in the primary sensory motor areas.

Alterations of dynamic functional connectivity between visual and executive-control networks in schizophrenia

Schizophrenia is a chronic mental disorder characterized by continuous or relapsing episodes of psychosis. While previous studies have detected functional network connectivity alterations in patients with schizophrenia, and most have focused on static functional connectivity. However, brain activity is believed to change dynamically over time. Therefore, we computed dynamic functional network connectivity using the sliding window method in 38 patients with schizophrenia and 31 healthy controls. We found that patients with schizophrenia exhibited higher occurrences in the weakly and sparsely connected state (state 3) than healthy controls, positively correlated with negative symptoms. In addition, patients exhibited fewer occurrences in a strongly connected state (state 4) than healthy controls. Lastly, the dynamic functional network connectivity between the right executive-control network and the medial visual network was decreased in schizophrenia patients compared to healthy controls. Our results further prove that brain activity is dynamic, and that alterations of dynamic functional network connectivity features might be a fundamental neural mechanism in schizophrenia.

A unified model of the pathophysiology of bipolar disorder

This work provides an overview of the most consistent alterations in bipolar disorder (BD), attempting to unify them in an internally coherent working model of the pathophysiology of BD. Data on immune-inflammatory changes, structural brain abnormalities (in gray and white matter), and functional brain alterations (from neurotransmitter signaling to intrinsic brain activity) in BD were reviewed. Based on the reported data, (1) we hypothesized that the core pathological alteration in BD is a damage of the limbic network that results in alterations of neurotransmitter signaling. Although heterogeneous conditions can lead to such damage, we supposed that the main pathophysiological mechanism is traceable to an immune/inflammatory-mediated alteration of white matter involving the limbic network connections, which destabilizes the neurotransmitter signaling, such as dopamine and serotonin signaling. Then, (2) we suggested that changes in such neurotransmitter signaling (potentially triggered by heterogeneous stressors onto a structurally-damaged limbic network) lead to phasic (and often recurrent) reconfigurations of intrinsic brain activity, from abnormal subcortical-cortical coupling to changes in network activity. We suggested that the resulting dysbalance between networks, such as sensorimotor networks, salience network, and default-mode network, clinically manifest in combined alterations of psychomotricity, affectivity, and thought during the manic and depressive phases of BD. Finally, (3) we supposed that an additional contribution of gray matter alterations and related cognitive deterioration characterize a clinical-biological subgroup of BD. This model may provide a general framework for integrating the current data on BD and suggests novel specific hypotheses, prompting for a better understanding of the pathophysiology of BD.

Aberrant Subnetwork and Hub Dysconnectivity in Adult Bipolar Disorder: A Multicenter Graph Theory Analysis

Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.

Is processing speed a valid neurocognitive endophenotype in bipolar disorder? Evidence from a longitudinal, family study

BACKGROUND

Substantial evidence supports the existence of neurocognitive endophenotypes in bipolar disorder (BD), but very few longitudinal studies have included unaffected relatives. In a 5-year, follow-up, family study, we have recently suggested that deficits in manual motor speed and visual memory could be endophenotype candidates for BD. We aimed to explore whether this also applies to processing speed.

METHODS

A sample of 348 individuals, including 163 BD patients, 65 unaffected first-degree relatives (BD-Rel) and 120 genetically unrelated healthy controls (HC), was assessed with the Digit Symbol Substitution Test (DSST) on two occasions over a 2-year period (T1, T2). DSST values were controlled for age, years of education, occupational status, and subsyndromic mood symptoms. Differences between groups were evaluated with ANCOVAs.

RESULTS

At T1 BD performed significantly worse than HC (p < 0.001; Cohen's d = 1.38) and BD-Rel (p < 0.001; Cohen's d = 0.82). BD-Rel showed an intermediate performance with significant differences with HC (p < 0.01; Cohen's d = 0.50). Similarly, at T2 BD performed significantly worse than HC (p < 0.001; Cohen's d = 1.44) and BD-Rel (p < 0.01; Cohen's d = 0.51). BD-Rel performance was intermediate and significantly lower than that of HC (p < 0.01; Cohen's d = 0.97). A Repeated Measures ANOVA revealed no significant between-group differences in performance over time (p > 0.05).

CONCLUSIONS

The results of this longitudinal, family study suggest that impaired processing speed may represent a suitable cognitive endophenotype for BD. Further research on the field is required to confirm these preliminary findings.

Relation between smoking and visual processing in bipolar disorder

BACKGROUND

Although some studies have shown impairments in patients with bipolar disorder (BPD) and in smokers, it is unclear how these two factors work together. Our premise was that chronic smoking affects color discrimination and this is more pronounced in BPD. Objective: Our main purpose was to investigate the influence of smoking and BPD on color discrimination. Methods: Twenty-three smokers and 23 BPD smokers patients, aged 25-45 years old, participated in this study. Color vision testing was performed using the Trivector subtest of the Cambridge Colour Test. Participants' task was to indicate the pseudoisochromatic stimulus in four directions (up, down, right, and left). Results: It was shown that the smokers had better color vision than BPD smokers for the Protan (p < .001), Deutan (p < .001), and Tritan (p < .001) (red, green, and blue, respectively) axes. Thus, the BPD smokers' group had greater difficulty distinguishing the chromaticity variations (i.e., presented diffuse color vision impairments and not specific to any axis). Conclusions: The present study highlights a possible relationship between smoking and BPD in color discrimination. This highlights the importance of understanding the diffuse effects of this relationship.

Prenatal origins of neuropsychiatric diseases

AIM

The main objective is to review the available evidence in the literature for developmental origins of neuropsychiatric diseases and their underlying mechanisms. We also probe emerging cutting-edge prenatal MR imaging tools and their future role in advancing our understanding the prenatal footprints of neuropsychiatric disorders.

OBSERVATIONS

Both human and animal studies support early intrauterine origins of neuropsychiatric disease, particularly autism spectrum disorders (ASD), attention and hyperactivity disorders, schizophrenia, depression, anxiety and mood disorders. Specific mechanisms of intrauterine injury include infection, inflammation, hypoxia, hypoperfusion, ischaemia polysubstance use/abuse, maternal mental health and placental dysfunction.

CONCLUSIONS AND RELEVANCE

There is ample evidence to suggest developmental vulnerability of the foetal brain to intrauterine exposures that increases and individual's risk for neuropsychiatric disease, especially the risk of ASD, depression and anxiety. Elucidating the exact timing and mechanisms of injury can be difficult and require novel, non-invasive approaches to the study emerging structural and functional brain development of the foetus. Clinical care should both emphasise maternal health during pregnancy, as well as close, continued monitoring for at risk offspring throughout young adulthood for the early identification and treatment of neuropsychiatric diseases.

Altered properties of brain white matter structural networks in patients with nasopharyngeal carcinoma after radiotherapy

Previous neuroimaging studies revealed radiation-induced brain injury in patients with nasopharyngeal carcinoma (NPC) in the years after radiotherapy (RT). These injuries may be associated with structural and functional alterations. However, differences in the brain structural connectivity of NPC patients at different times after RT, especially in the early-delayed period, remain unclear. We acquired diffusion tensor imaging (DTI) data from three groups of NPC patients, 25 in the pre-RT (before RT) group, 22 in the early-delayed (1-6 months) period (post-RT-ED) group, and 33 in the late-delayed (>6 months) period (post-RT-LD) group. Then, we constructed brain white matter (WM) structural networks and used graph theory to compare their between-group differences. The NPC patients in the post-RT-ED group showed decreased global properties when compared with the pre-RT group. We also detected the nodes with between-group differences in nodal parameters. The nodes that differed between the post-RT-ED and pre-RT groups were mainly located in the default mode (DMN) and central executive networks (CEN); those that differed between the post-RT-LD and pre-RT groups were located in the limbic system; and those that differed between the post-RT-LD and post-RT-ED groups were mainly in the DMN. These findings may indicate that radiation-induced brain injury begins in the early-delayed period and that a reorganization strategy begins in the late-delayed period. Our findings may provide new insight into the pathogenesis of radiation-induced brain injury in normal-appearing brain tissue from the network perspective.

The clinical relevance of gray matter atrophy and microstructural brain changes across the psychosis continuum

Patients with psychotic spectrum disorders (PSD) exhibit similar patterns of atrophy and microstructural changes that may be associated with common symptomatology (e.g., symptom burden and/or cognitive impairment). Gray matter concentration values (proxy for atrophy), fractional anisotropy (FA), mean diffusivity (MD), intracellular neurite density (Vic) and isotropic diffusion volume (Viso) measures were therefore compared in 150 PSD (schizophrenia, schizoaffective disorder, and bipolar disorder Type I) and 63 healthy controls (HC). Additional analyses evaluated whether regions showing atrophy and/or microstructure abnormalities were better explained by DSM diagnoses, symptom burden or cognitive dysfunction. PSD exhibited increased atrophy within bilateral medial temporal lobes and subcortical structures. Gray matter along the left lateral sulcus showed evidence of increased atrophy and MD. Increased MD was also observed in homotopic fronto-temporal regions, suggesting it may serve as a precursor to atrophic changes. Global cognitive dysfunction, rather than DSM diagnoses or psychotic symptom burden, was the best predictor of increased gray matter MD. Regions of decreased FA (i.e., left frontal gray and white matter) and Vic (i.e., frontal and temporal regions and along central sulcus) were also observed for PSD, but were neither spatially concurrent with atrophic regions nor associated with clinical symptoms. Evidence of expanding microstructural spaces in gray matter demonstrated the greatest spatial overlap with current and potentially future regions of atrophy, and was associated with cognitive deficits. These results suggest that this particular structural abnormality could potentially underlie global cognitive impairment that spans traditional diagnostic categories.

Specificity and Continuity of Schizophrenia and Bipolar Disorder: Relation to Biomarkers

Schizophrenia and bipolar disorder overlap considerably in terms of symptoms, familial patterns, risk genes, outcome, and treatment response. This article provides an overview of the specificity and continuity of schizophrenia and mood disorders on the basis of biomarkers, such as genes, molecules, cells, circuits, physiology and clinical phenomenology. Overall, the discussions herein provided support for the view that schizophrenia, schizoaffective disorder and bipolar disorder are in the continuum of severity of impairment, with bipolar disorder closer to normality and schizophrenia at the most severe end. This approach is based on the concept that examining biomarkers in several modalities across these diseases from the dimensional perspective would be meaningful. These considerations are expected to help develop new treatments for unmet needs, such as cognitive dysfunction, in psychiatric conditions.

Altered dynamic functional connectivity across mood states in bipolar disorder

BACKGROUND

This study aims to identify how the large-scale brain dynamic functional connectivity (dFC) differs between mood states in bipolar disorder (BD). The authors analyzed dFC in subjects with BD in depressed and euthymic states using resting-state functional magnetic resonance imaging (rsfMRI) data, and compared these states to healthy controls (HCs).

METHOD

20 subjects with BD in a depressive episode, 23 euthymic BD subjects, and 31 matched HCs underwent rsfMRI scans. Using an existing parcellation of the whole brain, we measured dFC between brain regions and identified the different patterns of brain network connections between groups.

RESULTS

In the analysis of whole brain dFC, the connectivity between the left Superior Temporal Gyrus (STG) in the somatomotor network (SMN), the right Middle Temporal Gyrus (MTG) in the default mode network (DMN) and the bilateral Postcentral Gyrus (PoG) in the DMN of depressed BD was greater than that of euthymic BD, while there was no significant difference between euthymic BD and HCs in these brain regions. Euthymic BD patients had abnormalities in the frontal-striatal-thalamic (FST) circuit compared to HCs.

CONCLUSIONS

Differences in dFC within and between DMN and SMN can be used to distinguish depressed and euthymic states in bipolar patients. The hyperconnectivity within and between DMN and SMN may be a state feature of depressed BD. The abnormal connectivity of the FST circuit can help identify euthymic BD from HCs.

Recent advances of deep learning in psychiatric disorders

Deep learning (DL) is a recently proposed subset of machine learning methods that has gained extensive attention in the academic world, breaking benchmark records in areas such as visual recognition and natural language processing. Different from conventional machine learning algorithm, DL is able to learn useful representations and features directly from raw data through hierarchical nonlinear transformations. Because of its ability to detect abstract and complex patterns, DL has been used in neuroimaging studies of psychiatric disorders, which are characterized by subtle and diffuse alterations. Here, we provide a brief review of recent advances and associated challenges in neuroimaging studies of DL applied to psychiatric disorders. The results of these studies indicate that DL could be a powerful tool in assisting the diagnosis of psychiatric diseases. We conclude our review by clarifying the main promises and challenges of DL application in psychiatric disorders, and possible directions for future research.

Resting state auditory-language cortex connectivity is associated with hallucinations in clinical and biological subtypes of psychotic disorders

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Transdiagnostic evidence for neural disruption in psychotic hallucinations.

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Hallucinations associated increased connectivity in auditory association cortex.

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Brain regions for auditory-verbal language comprehension linked to hallucinations.

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Interhemispheric connectivity alterations related to subgroup-specific findings.

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Hallucinations link to auditory rs-connectivity tested in 243 psychosis patients.

Background

Auditory hallucinations are prevalent across the major psychotic disorders, but their underlying mechanism is poorly understood. Limited prior work supports a hypothesis of altered auditory/language brain systems. To more definitively assess this, we examined whether alterations in resting state connectivity of auditory and language cortices are associated with hallucination severity in a large sample of individuals in the schizo-bipolar spectrum.

Methods

Whole brain resting state connectivity of auditory and language cortex (primary auditory cortex, unimodal auditory association cortex, Wernicke’s area [speech and heteromodal association cortex] and Broca’s area [speech production motor]) was evaluated for 243 subjects with schizophrenia, schizoaffective, or bipolar disorder with psychosis and 186 healthy controls from the Bipolar Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Regression analyses were conducted to evaluate whether resting state connectivity of auditory and language cortex was a significant predictor of current overall hallucination severity (information about specific modality of hallucinations experienced was not available).

Results

Increased connectivity between lower and higher order regions of left temporal-parietal auditory/language processing cortex was associated with worse hallucination severity for all psychosis patients. Additionally, within bipolar subjects, increased interhemispheric connectivity between higher order temporal-parietal auditory/language regions was related to greater hallucination severity. When patients were categorized by B-SNIP biomarker-based Biotype groups, interhemispheric connectivity between left auditory association cortex and right core auditory cortex was related to greater hallucination severity for Biotype 1 patients. Exploratory analyses resulted in different patterns of connectivity of auditory/language cortex in patients and controls, unrelated to current hallucination severity.

Conclusions

Although the findings cannot be precisely attributed to auditory hallucination severity or possible differences in such experiences between groups, increased connectivity among the left hemisphere auditory and receptive language cortex may represent a significant factor contributing to hallucination severity across psychotic disorders, and additional subgroup specific connectivity alterations may also be present.

Resting-State Network Patterns Underlying Cognitive Function in Bipolar Disorder: A Graph Theoretical Analysis

Background: Synchronous and antisynchronous activity between neural elements at rest reflects the physiological processes underlying complex cognitive ability. Regional and pairwise connectivity investigations suggest that perturbations in these activity patterns may relate to widespread cognitive impairments seen in bipolar disorder (BD). Here we take a network-based perspective to more meaningfully capture interactions among distributed brain regions compared to focal measurements and examine network-cognition relationships across a range of commonly affected cognitive domains in BD in relation to healthy controls. Methods: Resting-state networks were constructed as matrices of correlation coefficients between regionally averaged resting-state time series from 86 cortical/subcortical brain regions (FreeSurferv5.3.0). Cognitive performance measured using the Wechsler Adult Intelligence Scale, Cambridge Automated Neuropsychological Test Battery (CANTAB), and Reading the Mind in the Eyes tests was examined in relation to whole-brain connectivity measures and patterns of connectivity using a permutation-based statistical approach. Results: Faster response times in controls (n = 49) related to synchronous activity between frontal, parietal, cingulate, temporal, and occipital regions, while a similar response times in BD (n = 35) related to antisynchronous activity between regions of this subnetwork. Across all subjects, antisynchronous activity between the frontal, parietal, temporal, occipital, cingulate, insula, and amygdala regions related to improved memory performance. No resting-state subnetworks related to intelligence, executive function, short-term memory, or social cognition performance in the overall sample or in a manner that would explain deficits in these facets in BD. Conclusions: Our results demonstrate alterations in the intrinsic connectivity patterns underlying response timing in BD that are not specific to performance or errors on the same tasks. Across all individuals, no strong effects of resting-state global topology on cognition are found, while distinct functional networks supporting episodic and spatial memory highlight intrinsic inhibitory influences present in the resting state that facilitate memory processing. Impact Statement Regional and pairwise-connectivity investigations suggest altered interactions between brain areas may contribute to impairments in cognition that are observed in bipolar disorder. However, the distributed nature of these interactions across the brain remains poorly understood. Using recent advances in network neuroscience, we examine functional connectivity patterns associated with multiple cognitive domains in individuals with and without bipolar disorder. We discover distinct patterns of connectivity underlying response-timing performance uniquely in bipolar disorder and, independent of diagnosis, inhibitory interactions that relate to memory performance.

Do patients with hallucinations imagine speech right?

A direct relationship between auditory verbal hallucinations (AVHs) and decreased left-hemispheric lateralization in speech perception has been often described, although it has not been conclusively proven. The specific lateralization of AVHs has been poorly explored. However, patients with verbal hallucinations show a weak Right Ear Advantage (REA) in verbal perception compared to non AVHs listeners suggesting that left-hemispheric language area are involved in AVHs. In the present study, 29 schizophrenia patients with AVHs, 31 patients with psychotic bipolar disorder who experienced frequent AVHs, 27 patients with schizophrenia who had never experienced AVHs and 57 healthy controls were required to imagine hearing a voice in one ear alone. In line with previous evidence healthy controls confirmed the expected REA for auditory imagery, and the same REA was also found in non-hallucinator patients. However, in line with our hypothesis, patients with schizophrenia and psychotic bipolar disorder with AVHs showed no lateral bias. Results extend the relationship between abnormal asymmetry for verbal stimuli and AVHs to verbal imagery, suggesting that atypical verbal imagery may reflect a disruption of inter-hemispheric connectivity between areas implicated in the generation and monitoring of verbal imagery and may be predictive of a predisposition for AVHs. Results also indicate that the relationship between AVHs and hemispheric lateralization for auditory verbal imagery is not specific to schizophrenia but may extend to other disorders as well.

Impaired attentional modulation of sensorimotor control and cortical excitability in schizophrenia

Impairments in attentional, working memory and sensorimotor processing have been consistently reported in schizophrenia. However, the interaction between cognitive and sensorimotor impairments and the underlying neural mechanisms remains largely uncharted. We hypothesized that altered attentional processing in patients with schizophrenia, probed through saccadic inhibition, would partly explain impaired sensorimotor control and would be reflected as altered task-dependent modulation of cortical excitability and inhibition. Twenty-five stabilized patients with schizophrenia, 17 unaffected siblings and 25 healthy control subjects were recruited. Subjects performed visuomotor grip force-tracking alone (single-task condition) and with increased cognitive load (dual-task condition). In the dual-task condition, two types of trials were randomly presented: trials with visual distractors (requiring inhibition of saccades) or trials with addition of numbers (requiring saccades and addition). Both dual-task trial types required divided visual attention to the force-tracking target and to the distractor or number. Gaze was measured during force-tracking tasks, and task-dependent modulation of cortical excitability and inhibition were assessed using transcranial magnetic stimulation. In the single-task, patients with schizophrenia showed increased force-tracking error. In dual-task distraction trials, force-tracking error increased further in patients, but not in the other two groups. Patients inhibited fewer saccades to distractors, and the capacity to inhibit saccades explained group differences in force-tracking performance. Cortical excitability at rest was not different between groups and increased for all groups during single-task force-tracking, although, to a greater extent in patients (80%) compared to controls (40%). Compared to single-task force-tracking, the dual-task increased cortical excitability in control subjects, whereas patients showed decreased excitability. Again, the group differences in cortical excitability were no longer significant when failure to inhibit saccades was included as a covariate. Cortical inhibition was reduced in patients in all conditions, and only healthy controls increased inhibition in the dual-task. Siblings had similar force-tracking and gaze performance as controls but showed altered task-related modulation of cortical excitability and inhibition in dual-task conditions. In patients, neuropsychological scores of attention correlated with visuomotor performance and with task-dependant modulation of cortical excitability. Disorganization symptoms were greatest in patients with weakest task-dependent modulation of cortical excitability. This study provides insights into neurobiological mechanisms of impaired sensorimotor control in schizophrenia showing that deficient divided visual attention contributes to impaired visuomotor performance and is reflected in impaired modulation of cortical excitability and inhibition. In siblings, altered modulation of cortical excitability and inhibition is consistent with a genetic risk for cortical abnormality.

Detecting Abnormal Brain Regions in Schizophrenia Using Structural MRI via Machine Learning

Utilizing neuroimaging and machine learning (ML) to differentiate schizophrenia (SZ) patients from normal controls (NCs) and for detecting abnormal brain regions in schizophrenia has several benefits and can provide a reference for the clinical diagnosis of schizophrenia. In this study, structural magnetic resonance images (sMRIs) from SZ patients and NCs were used for discriminative analysis. This study proposed an ML framework based on coarse-to-fine feature selection. The proposed framework used two-sample t-tests to extract the differences between groups first, then further eliminated the nonrelevant and redundant features with recursive feature elimination (RFE), and finally utilized the support vector machine (SVM) to learn the decision models with selected gray matter (GM) and white matter (WM) features. Previous studies have tended to report differences at the group level instead of at the individual level and cannot be widely applied. The method proposed in this study extends the diagnosis to the individual level and has a higher recognition rate than previous methods. The experimental results of this study demonstrate that the proposed framework distinguishes SZ patients from NCs, with the highest classification accuracy reaching over 85%. The identified biomarkers are also consistent with previous literature findings. As a universal method, the proposed framework can be extended to diagnose other diseases.

A comparative meta-analysis of neurocognition in first-degree relatives of patients with schizophrenia and bipolar disorder

Objective:

Cognitive impairment is a familial and heritable aspect of major psychoses and might be a shared vulnerability marker for schizophrenia and BP. However, it is not clear whether some aspects of cognitive deficits are uniquely associated with risk for specific diagnoses.

Methods:

A novel meta-analysis of cognitive functions in first-degree relatives of probands with bipolar disorder (BP-Rel) and schizophrenia (Sch-Rel) was conducted. Current meta-analysis included 20 studies and compared cognitive functions of 1341 Sch-Rel, 939 BP-Rel and 1427 healthy controls.

Results:

Sch-Rel was associated with cognitive deficits in all domains (d = 0.20–0.58) and BP-Rel underperformed healthy controls in processing speed, verbal fluency and speed based executive function tests (d = 0.33–0.41). Sch-Rel underperformed BP-Rel in general intellectual ability, working memory, verbal memory, planning, processing speed and fluency (d = 0.24–0.42).

Conclusions:

Inefficiency in processing information and impaired processing speed might be common vulnerability factors for major psychoses. On the other hand, low performance in accuracy based tasks and deficits in general intellectual ability, verbal learning, planning and working memory might be more specifically associated with risk for schizophrenia.

Frontolimbic, Frontoparietal, and Default Mode Involvement in Functional Dysconnectivity in Psychotic Bipolar Disorder

BACKGROUND

Functional abnormalities, mostly involving functionally specialized subsystems, have been associated with disorders of emotion regulation such as bipolar disorder (BD). Understanding how independent functional subsystems integrate globally and how they relate with anatomical cortical and subcortical networks is key to understanding how the human brain's architecture constrains functional interactions and underpins abnormalities of mood and emotion, particularly in BD.

METHODS

Resting-state functional magnetic resonance time series were averaged to obtain individual functional connectivity matrices (using AFNI software); individual structural connectivity matrices were derived using deterministic non-tensor-based tractography (using ExploreDTI, version 4.8.6), weighted by streamline count and fractional anisotropy. Structural and functional nodes were defined using a subject-specific cortico-subcortical mapping (using Desikan-Killiany Atlas, FreeSurfer, version 5.3). Whole-brain connectivity alongside a permutation-based statistical approach and structure-function coupling were employed to investigate topological variance in individuals with predominantly euthymic BD relative to psychiatrically healthy control subjects.

RESULTS

Patients with BD (n = 41) exhibited decreased (synchronous) connectivity in a subnetwork encompassing frontolimbic and posterior-occipital functional connections (T > 3, p = .048), alongside increased (antisynchronous) connectivity within a frontotemporal subnetwork (T > 3, p = .014); all relative to control subjects (n = 56). Preserved whole-brain functional connectivity and comparable structure-function coupling among whole-brain and edge-class connections were observed in patients with BD relative to control subjects.

CONCLUSIONS

This study presents a functional map of BD dysconnectivity that differentially involves communication within nodes belonging to functionally specialized subsystems-default mode, frontoparietal, and frontolimbic systems; these changes do not extend to be detected globally and may be necessary to maintain a remitted clinical state of BD. Preserved structure-function coupling in BD despite evidence of regional anatomical and functional deficits suggests a dynamic interplay between structural and functional subnetworks.

A Systematic Review of the Potential Use of Neurofeedback in Patients With Schizophrenia

Schizophrenia (SCZ) is a neurodevelopmental disorder characterized by positive symptoms (hallucinations and delusions), negative symptoms (anhedonia, social withdrawal) and marked cognitive deficits (memory, executive function, and attention). Current mainstays of treatment, including medications and psychotherapy, do not adequately address cognitive symptoms, which are essential for everyday functioning. However, recent advances in computational neurobiology have rekindled interest in neurofeedback (NF), a form of self-regulation or neuromodulation, in potentially alleviating cognitive symptoms in patients with SCZ. Therefore, we conducted a systematic review of the literature for NF studies in SCZ to identify lessons learned and to identify steps to move the field forward. Our findings reveal that NF studies to date consist mostly of case studies and small sample, single-group studies. Despite few randomized clinical trials, the results suggest that NF is feasible and that it leads to measurable changes in brain function. These findings indicate early proof-of-concept data that needs to be followed up by larger, randomized clinical trials, testing the efficacy of NF compared to well thought out placebos. We hope that such an undertaking by the field will lead to innovative solutions that address refractory symptoms and improve everyday functioning in patients with SCZ.

Neurobiological commonalities and distinctions among 3 major psychiatric disorders: a graph theoretical analysis of the structural connectome

BACKGROUND

White matter network alterations have increasingly been implicated in major depressive disorder, bipolar disorder and schizophrenia. The aim of this study was to identify shared and distinct white matter network alterations among the 3 disorders.

METHODS

We used analysis of covariance, with age and gender as covariates, to investigate white matter network alterations in 123 patients with schizophrenia, 123 with bipolar disorder, 124 with major depressive disorder and 209 healthy controls.

RESULTS

We found significant group differences in global network efficiency (F = 3.386, p = 0.018), nodal efficiency (F = 8.015, p < 0.001 corrected for false discovery rate [FDR]) and nodal degree (F = 5.971, pFDR < 0.001) in the left middle occipital gyrus, as well as nodal efficiency (F = 6.930, pFDR < 0.001) and nodal degree (F = 5.884, pFDR < 0.001) in the left postcentral gyrus. We found no significant alterations in patients with major depressive disorder. Post hoc analyses revealed that compared with healthy controls, patients in the schizophrenia and bipolar disorder groups showed decreased global network efficiency, nodal efficiency and nodal degree in the left middle occipital gyrus. Furthermore, patients in the schizophrenia group showed decreased nodal efficiency and nodal degree in the left postcentral gyrus compared with healthy controls.

LIMITATIONS

Our findings could have been confounded in part by treatment differences.

CONCLUSION

Our findings implicate graded white matter network alterations across the 3 disorders, enhancing our understanding of shared and distinct pathophysiological mechanisms across diagnoses and providing vital insights into neuroimaging-based methods for diagnosis and research.

Bipolar Disorder and Gender Are Associated with Frontolimbic and Basal Ganglia Dysconnectivity: A Study of Topological Variance Using Network Analysis

Well-established structural abnormalities, mostly involving the limbic system, have been associated with disorders of emotion regulation. Understanding the arrangement and connections of these regions with other functionally specialized cortico-subcortical subnetworks is key to understanding how the human brain's architecture underpins abnormalities of mood and emotion. We investigated topological patterns in bipolar disorder (BD) with the anatomically improved precision conferred by combining subject-specific parcellation/segmentation with nontensor-based tractograms derived using a high-angular resolution diffusion-weighted approach. Connectivity matrices were constructed using 34 cortical and 9 subcortical bilateral nodes (Desikan-Killiany), and edges that were weighted by fractional anisotropy and streamline count derived from deterministic tractography using constrained spherical deconvolution. Whole-brain and rich-club connectivity alongside a permutation-based statistical approach was used to investigate topological variance in predominantly euthymic BD relative to healthy volunteers. BP patients (n = 40) demonstrated impairments across whole-brain topological arrangements (density, degree, and efficiency), and a dysconnected subnetwork involving limbic and basal ganglia relative to controls (n = 45). Increased rich-club connectivity was most evident in females with BD, with frontolimbic and parieto-occipital nodes not members of BD rich-club. Increased centrality in females relative to males was driven by basal ganglia and fronto-temporo-limbic nodes. Our subject-specific cortico-subcortical nontensor-based connectome map presents a neuroanatomical model of BD dysconnectivity that differentially involves communication within and between emotion-regulatory and reward-related subsystems. Moreover, the female brain positions more dependence on nodes belonging to these two differently specialized subsystems for communication relative to males, which may confer increased susceptibility to processes dependent on integration of emotion and reward-related information.

Disrupted brain structural connectivity in Pediatric Bipolar Disorder with psychosis

Bipolar disorder (BD) has been linked to disrupted structural and functional connectivity between prefrontal networks and limbic brain regions. Studies of patients with pediatric bipolar disorder (PBD) can help elucidate the developmental origins of altered structural connectivity underlying BD and provide novel insights into the aetiology of BD. Here we compare the network properties of whole-brain structural connectomes of euthymic PBD patients with psychosis, a variant of PBD, and matched healthy controls. Our results show widespread changes in the structural connectivity of PBD patients with psychosis in both cortical and subcortical networks, notably affecting the orbitofrontal cortex, frontal gyrus, amygdala, hippocampus and basal ganglia. Graph theoretical analysis revealed that PBD connectomes have fewer hubs, weaker rich club organization, different modular fingerprint and inter-modular communication, compared to healthy participants. The relationship between network features and neurocognitive and psychotic scores was also assessed, revealing trends of association between patients’ IQ and affective psychotic symptoms with the local efficiency of the orbitofrontal cortex. Our findings reveal that PBD with psychosis is associated with significant widespread changes in structural network topology, thus strengthening the hypothesis of a reduced capacity for integrative processing of information across brain regions. Localised network changes involve core regions for emotional processing and regulation, as well as memory and executive function, some of which show trends of association with neurocognitive faculties and symptoms. Together, our findings provide the first comprehensive characterisation of the alterations in local and global structural brain connectivity and network topology, which may contribute to the deficits in cognition and emotion processing and regulation found in PBD.

Role of glia in prefrontal white matter abnormalities in first episode psychosis or mania detected by diffusion tensor spectroscopy

BACKGROUND

White matter (WM) abnormalities are amongst the most commonly described neuroimaging findings in patients with psychotic disorders including schizophrenia (SZ) and bipolar disorder (BD), and may be central to pathophysiology. Few studies have directly compared WM abnormalities in patients with SZ and BD in the first episode of illness, and no studies to date have attempted to separate abnormalities of axon and myelin using complementary MRI techniques.

METHODS

We examined WM abnormalities in young adults with SZ (n = 19) or BD (n = 16) within the first year of illness onset, and healthy controls (n = 22) using a combination of diffusion tensor spectroscopy to measure NAA, creatine (Cr), and choline (Cho), and magnetization transfer ratio (MTR). MTR reflects myelin content, NAA diffusion is neuron specific, and Cr and Cho diffusion reflect both neuron and glial signal.

RESULTS

We found no differences in MTR or NAA ADC in either patient group compared to controls, but significant elevations of both Cr and Cho diffusion in patients with SZ, and elevations of Cho diffusion in patients with BD. Elevations in Cr and Cho diffusion in the absence of NAA diffusion abnormalities indicate that the aberrant signal arises in glia.

CONCLUSIONS

Glial abnormalities were present and detectable by the first episode of psychosis, whereas major abnormalities in axon and myelin were not. Examination of these neurobiological markers early in the course of illness may clarify the neuroprogressive nature of these distinct aspects of WM, and their associations with early clinical phenotypes.

Transdiagnostic neuroimaging in psychiatry: A review

Transdiagnostic approach has a long history in neuroimaging, predating its recent ascendance as a paradigm for new psychiatric nosology. Various psychiatric disorders have been compared for commonalities and differences in neuroanatomical features and activation patterns, with different aims and rationales. This review covers both structural and functional neuroimaging publications with direct comparison of different psychiatric disorders, including schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, conduct disorder, anorexia nervosa, and bulimia nervosa. Major findings are systematically presented along with specific rationales for each comparison.

Structural connectivity in schizophrenia and bipolar disorder: Effects of chronicity and antipsychotic treatment

Previous studies based on graph theory parameters applied to diffusion tensor imaging support an alteration of the global properties of structural connectivity network in schizophrenia. However, the specificity of this alteration and its possible relation with chronicity and treatment have received small attention. We have assessed small-world (SW) and connectivity strength indexes of the structural network built using fractional anisotropy values of the white matter tracts connecting 84 cortical and subcortical regions in 25 chronic and 18 first episode (FE) schizophrenia and 24 bipolar patients and 28 healthy controls. Chronic schizophrenia and bipolar patients showed significantly smaller SW and connectivity strength indexes in comparison with controls and FE patients. SW reduction was driven by increased averaged path-length (PL) values. Illness duration but not treatment doses were negatively associated with connectivity strength, SW and PL in patients. Bipolar patients exposed to antipsychotics did not differ in SW or connectivity strength from bipolar patients without such an exposure. Executive functions and social cognition were related to SW index in the schizophrenia group. Our results support a role for chronicity but not treatment in structural network alterations in major psychoses, which may not differ between schizophrenia and bipolar disorder, and may hamper cognition.

Aberrant brain structural-functional connectivity coupling in euthymic bipolar disorder

Aberrant structural (diffusion tensor imaging [DTI]) and resting-state functional magnetic resonance imagining connectivity are core features of bipolar disorder. However, few studies have explored the integrity agreement between structural and functional connectivity (SC-FC) in bipolar disorder. We examine SC connectivity coupling index whether could potentially provide additional clinical predictive value for bipolar disorder spectrum disorders besides the intramodality network measures. By examining the structural (DTI) and resting-state functional network properties, as well as their coupling index, among 57 euthymic bipolar disorder patients (age 13-28 years, 18 females) and 42 age- and gender-matched healthy controls (age 13-28 years, 16 females), we found that compared to controls, bipolar disorder patients showed increased structural rich-club connectivity as well as decreased functional modularity. Importantly, the coupling strength between structural and functional connectome was decreased in patients compared to controls, which emerged as the most powerful feature discriminating the two groups. Our findings suggest that structural-functional coupling strength could serve as a valuable biological trait-like feature for bipolar disorder over and above the intramodality network measures. Such measure can have important clinical implications for early identification of bipolar disorder individuals, and inform strategies for prevention of bipolar disorder onset and relapse.

Increased white matter metabolic rates in autism spectrum disorder and schizophrenia

Both autism spectrum disorder (ASD) and schizophrenia are often characterized as disorders of white matter integrity. Multimodal investigations have reported elevated metabolic rates, cerebral perfusion and basal activity in various white matter regions in schizophrenia, but none of these functions has previously been studied in ASD. We used ¹⁸fluorodeoxyglucose positron emission tomography to compare white matter metabolic rates in subjects with ASD (n = 25) to those with schizophrenia (n = 41) and healthy controls (n = 55) across a wide range of stereotaxically placed regions-of-interest. Both subjects with ASD and schizophrenia showed increased metabolic rates across the white matter regions assessed, including internal capsule, corpus callosum, and white matter in the frontal and temporal lobes. These increases were more pronounced, more widespread and more asymmetrical in subjects with ASD than in those with schizophrenia. The highest metabolic increases in both disorders were seen in the prefrontal white matter and anterior limb of the internal capsule. Compared to normal controls, differences in gray matter metabolism were less prominent and differences in adjacent white matter metabolism were more prominent in subjects with ASD than in those with schizophrenia. Autism spectrum disorder and schizophrenia are associated with heightened metabolic activity throughout the white matter. Unlike in the gray matter, the vector of white matter metabolic abnormalities appears to be similar in ASD and schizophrenia, may reflect inefficient functional connectivity with compensatory hypermetabolism, and may be a common feature of neurodevelopmental disorders.

Disrupted rich club organization and structural brain connectome in unmedicated bipolar disorder

BACKGROUND

Bipolar disorder (BD) has been associated with altered brain structural and functional connectivity. However, little is known regarding alterations of the structural brain connectome in BD. The present study aimed to use diffusion-tensor imaging (DTI) and graph theory approaches to investigate the rich club organization and white matter structural connectome in BD.

METHODS

Forty-two patients with unmedicated BD depression and 59 age-, sex- and handedness-matched healthy control participants underwent DTI. The whole-brain structural connectome was constructed by a deterministic fiber tracking approach. Graph theory analysis was used to examine the group-specific global and nodal topological properties, and rich club organizations, and then nonparametric permutation tests were used for group comparisons of network parameters.

RESULTS

Compared with healthy control participants, the patients with BD showed abnormal global properties, including increased characteristic path length, and decreased global efficiency and local efficiency. Locally, the patients with BD showed abnormal nodal parameters (nodal strength, nodal efficiency, and nodal betweenness) predominantly in the parietal, orbitofrontal, occipital, and cerebellar regions. Moreover, the patients with BD showed decreased rich club and feeder connectivity density.

CONCLUSIONS

Our results may reflect the disrupted white matter topological organization in the whole-brain, and abnormal regional connectivity supporting cognitive and affective functioning in depressed BD, which, in part, be due to impaired rich club connectivity.

Measures of possible allostatic load in comorbid cocaine and alcohol use disorder: Brain white matter integrity, telomere length, and anti-saccade performance

Chronic cocaine and alcohol use impart significant stress on biological and cognitive systems, resulting in changes consistent with an allostatic load model of neurocognitive impairment. The present study measured potential markers of allostatic load in individuals with comorbid cocaine/alcohol use disorders (CUD/AUD) and control subjects. Measures of brain white matter (WM), telomere length, and impulsivity/attentional bias were obtained. WM (CUD/AUD only) was indexed by diffusion tensor imaging metrics, including radial diffusivity (RD) and fractional anisotropy (FA). Telomere length was indexed by the telomere to single copy gene (T/S) ratio. Impulsivity and attentional bias to drug cues were measured via eye-tracking, and were also modeled using the Hierarchical Diffusion Drift Model (HDDM). Average whole-brain RD and FA were associated with years of cocaine use (R2 = 0.56 and 0.51, both p < .005) but not years of alcohol use. CUD/AUD subjects showed more anti-saccade errors (p < .01), greater attentional bias scores (p < .001), and higher HDDM drift rates on cocaine-cue trials (Bayesian probability CUD/AUD > control = p > 0.99). Telomere length was shorter in CUD/AUD, but the difference was not statistically significant. Within the CUD/AUD group, exploratory regression using an elastic-net model determined that more years of cocaine use, older age, larger HDDM drift rate differences and shorter telomere length were all predictive of WM as measured by RD (model R2 = 0.79). Collectively, the results provide modest support linking CUD/AUD to putative markers of allostatic load.

Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks

The notion that specific cognitive and emotional processes arise from functionally distinct brain regions has lately shifted toward a connectivity-based approach that emphasizes the role of network-mediated integration across regions. The clinical neurosciences have likewise shifted from a predominantly lesion-based approach to a connectomic paradigm-framing disorders as diverse as stroke, schizophrenia (SCZ), and dementia as "dysconnection syndromes". Here we position bipolar disorder (BD) within this paradigm. We first summarise the disruptions in structural, functional and effective connectivity that have been documented in BD. Not surprisingly, these disturbances show a preferential impact on circuits that support emotional processes, cognitive control and executive functions. Those at high risk (HR) for BD also show patterns of connectivity that differ from both matched control populations and those with BD, and which may thus speak to neurobiological markers of both risk and resilience. We highlight research fields that aim to link brain network disturbances to the phenotype of BD, including the study of large-scale brain dynamics, the principles of network stability and control, and the study of interoception (the perception of physiological states). Together, these findings suggest that the affective dysregulation of BD arises from dynamic instabilities in interoceptive circuits which subsequently impact on fear circuitry and cognitive control systems. We describe the resulting disturbance as a "psychosis of interoception".