Hemispheric lateralization abnormalities of the white matter microstructure in patients with schizophrenia and bipolar disorder

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers

BACKGROUND

Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing treatment. Diagnostic biomarkers could significantly improve clinical care by reducing dependence on symptomatic presentation.

METHODS

We used deep learning analysis (DLA) of resting electroencephalograph (EEG) to differentiate healthy control (HC) subjects (N = 239), from those with major depressive disorder (MDD) (N = 105), MDD-atypical (MDD-A) (N = 27), MDD-psychotic (MDD-P) (N = 35), bipolar disorder-depressed episode (BD-DE) (N = 71), BD-manic episode (BD-ME) (N = 49), and schizophrenia (SCZ) (N = 122) and also differentiate subjects with mental disorders on a pair-wise basis. DSM-III-R diagnoses were determined and supplemented by computerized Quick Diagnostic Interview Schedule. After EEG preprocessing, robust exact low-resolution electromagnetic tomography (ReLORETA) computed EEG sources for 82 brain regions. 20 % of all subjects were then set aside for independent testing. Feature selection methods were then used for the remaining subjects to identify brain source regions that are discriminating between diagnostic categories.

RESULTS

Pair-wise classification accuracies between 90 % and 100 % were obtained using independent test subjects whose data were not used for training purposes. The most frequently selected features across various pairs are in the postcentral, supramarginal, and fusiform gyri, the hypothalamus, and the left cuneus. Brain sites discriminating SCZ from HC were mainly in the left hemisphere while those separating BD-ME from HC were on the right.

LIMITATIONS

The use of superseded DSM-III-R diagnostic system and relatively small sample size in some disorder categories that may increase the risk of overestimation.

CONCLUSIONS

DLA of EEG could be trained to autonomously classify psychiatric disorders with over 90 % accuracy compared to an expert clinical team using standardized operational methods.

Lateralization of major white matter tracts during infancy is time-varying and tract-specific

Lateralization patterns are a major structural feature of brain white matter and have been investigated as a neural architecture that indicates and supports the specialization of cognitive processing and observed behaviors, e.g. language skills. Many neurodevelopmental disorders have been associated with atypical lateralization, reinforcing the need for careful measurement and study of this structural characteristic. Unfortunately, there is little consensus on the direction and magnitude of lateralization in major white matter tracts during the first months and years of life-the period of most rapid postnatal brain growth and cognitive maturation. In addition, no studies have examined white matter lateralization in a longitudinal pediatric sample-preventing confirmation of if and how white matter lateralization changes over time. Using a densely sampled longitudinal data set from neurotypical infants aged 0-6 months, we aim to (i) chart trajectories of white matter lateralization in 9 major tracts and (ii) link variable findings from cross-sectional studies of white matter lateralization in early infancy. We show that patterns of lateralization are time-varying and tract-specific and that differences in lateralization results during this period may reflect the dynamic nature of lateralization through development, which can be missed in cross-sectional studies.

Oligodendrocytes matter: a review of animal studies on early adversity

Exposure to adversities in early life appears to affect the development of white matter, especially oligodendrocytes. Furthermore, altered myelination is present in regions subjected to maturation during the developmental time when early adversities are experienced. In this review, studies applying two well-established animal models of early life adversity, namely maternal separation and maternal immune activation, focusing on oligodendrocyte alterations and resulting implications for psychiatric disorders are discussed. Studies revealed that myelination is reduced as a result of altered oligodendrocyte expression. Furthermore, early adversity is associated with increased cell death, a simpler morphology, and inhibited oligodendrocyte maturation. However, these effects seem to be region- specific as some brain regions show increased expression while others show decreased expression of oligodendroglia-related genes, and they occur especially in regions of ongoing development. Some studies furthermore suggest that early adversity leads to premature differentiation of oligodendrocytes. Importantly, especially early exposure results in stronger oligodendrocyte-related impairments. However, resulting alterations are not restricted to exposure during the early pre- and postnatal days as social isolation after weaning leads to fewer internodes and branches and shorter processes of oligodendrocytes in adulthood. Eventually, the found alterations may lead to dysfunction and long-lasting alterations in structural brain development associated with psychiatric disorders. To date, only few preclinical studies have focused on the effects of early adversity on oligodendrocytes. More studies including several developmental stages are needed to further disentangle the role of oligodendrocytes in the development of psychiatric disorders.

Application of TBSS-based machine learning models in the diagnosis of pediatric autism

Objective

To explore the microstructural changes of white matter in children with pediatric autism by using diffusion kurtosis imaging (DKI), and evaluate whether the combination of tract-based spatial statistics (TBSS) and back-propagation neural network (BPNN)/support vector machine (SVM)/logistic regression (LR) was feasible for the classification of pediatric autism.

Methods

DKI data were retrospectively collected from 32 children with autism and 27 healthy controls (HCs). Kurtosis fractional anisotropy (FAK), mean kurtosis (MK), axial kurtosis (KA), radial kurtosis (RK), fractional anisotropy (FA), axial diffusivity (DA), mean diffusivity (MD) and Radial diffusivity (DR) were generated by iQuant workstation. TBSS was used to detect the regions of parameters values abnormalities and for the comparison between these two groups. In addition, we also introduced the lateralization indices (LI) to study brain lateralization in children with pediatric autism, using TBSS for additional analysis. The parameters values of the differentiated regions from TBSS were then calculated for each participant and used as the features in SVM/BPNN/LR. All models were trained and tested with leave-one-out cross validation (LOOCV).

Results

Compared to the HCs group, the FAK, DA, and KA values of multi-fibers [such as the bilateral superior longitudinal fasciculus (SLF), corticospinal tract (CST) and anterior thalamic radiation (ATR)] were lower in pediatric autism group (p < 0.05, TFCE corrected). And we also found DA lateralization abnormality in Superior longitudinal fasciculus (SLF) (the LI in HCs group was higher than that in pediatric autism group). However, there were no significant differences in FA, MD, MK, DR, and KR values between HCs and pediatric autism group (P > 0.05, TFCE corrected). After performing LOOCV to train and test three model (SVM/BPNN/LR), we found the accuracy of BPNN (accuracy = 86.44%) was higher than that of LR (accuracy = 76.27%), but no different from SVM (RBF, accuracy = 81.36%; linear, accuracy = 84.75%).

Conclusion

Our proposed method combining TBSS findings with machine learning (LR/SVM/BPNN), was applicable in the classification of pediatric autism with high accuracy. Furthermore, the FAK, DA, and KA values and Lateralization index (LI) value could be used as neuroimaging biomarkers to discriminate the children with pediatric autism or not.

Handedness as a neurodevelopmental marker in schizophrenia: Results from the FACE-SZ cohort

OBJECTIVES

High rates of non-right-handedness (NRH) including mixed-handedness have been reported in neurodevelopmental disorders. In schizophrenia (SZ), atypical handedness has been inconsistently related to impaired features. We aimed to determine whether SZ subjects with NRH and mixed-handedness had poorer clinical and cognitive outcomes compared to their counterparts.

METHODS

667 participants were tested with a battery of neuropsychological tests, and assessed for laterality using the Edinburg Handedness Inventory. Clinical symptomatology was assessed. Learning disorders and obstetrical complications were recorded. Biological parameters were explored.

RESULTS

The prevalence of NRH and mixed-handedness was high (respectively, 42.4% and 34.1%). In the multivariable analyses, NRH was associated with cannabis use disorder (p = 0.045). Mixed-handedness was associated with positive symptoms (p = 0.041), current depressive disorder (p = 0.005)), current cannabis use (p = 0.024) and less akathisia (p = 0.019). A history of learning disorder was associated with NRH. No association was found with cognition, trauma history, obstetrical complications, psychotic symptoms, peripheral inflammation.

CONCLUSIONS

Non-right and mixed-handedness are very high in patients with SZ, possibly reflecting a neurodevelopmental origin. NRH is associated with learning disorders and cannabis use. Mixed-handedness is associated with positive symptoms, current depressive disorder, cannabis use and less akathisia. However, this study did not confirm greater cognitive impairment in these patients.

Handedness in bipolar disorders is associated with specific neurodevelopmental features: results of the BD-FACE cohort

OBJECTIVES

High rates of non-right-handedness (NRH) and mixed-handedness exist in neurodevelopmental disorders. Dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of bipolar disorders (BD), at least in some subgroups. Yet little is known about correlates of NRH and mixed-handedness in BD. The objectives of this national study are to determine (i) the prevalence of NRH and mixed-handedness in a well-stabilized sample of BD individuals; (ii) if NRH/mixed-handedness in BD is associated with a different clinical, biological and neurocognitive profile.

METHODS

We included 2174 stabilized individuals. Participants were tested with a comprehensive battery of neuropsychological tests. Handedness was assessed using a single oral question. Learning and/or language disorders and obstetrical complications were recorded using childhood records. Common environmental, clinical and biological parameters were assessed.

RESULTS

The prevalence of NRH and mixed-handedness were, respectively, 11.6 and 2.4%. Learning/language disorders were found in 9.7% out of the total sample and were associated with atypical handedness (only dyslexia for mixed-handedness (p < 0.01), and dyslexia and dysphasia for NRH (p = 0.01 and p = 0.04, respectively). In multivariate analyses, NRH was associated with a younger age of BD onset (aOR 0.98 (95% CI 0.96-0.99) and lifetime substance use disorder (aOR 1.40 (95% CI 1.03-1.82) but not with any of the cognitive subtasks. Mixed-handedness was associated in univariate analyses with lifetime substance use disorder, lifetime cannabis use disorder (all p < 0.01) and less mood stabilizer prescription (p = 0.028). No association was found between NRH or mixed-handedness and the following parameters: trauma history, obstetrical complications, prior psychotic symptoms, bipolar subtype, attention deficit/hyperactivity disorder, peripheral inflammation or body mass index.

CONCLUSIONS

Handedness may be associated with specific features in BD, possibly reflecting a specific subgroup with a neurodevelopmental load.

Structural and diffusion MRI based schizophrenia classification using 2D pretrained and 3D naive Convolutional Neural Networks

The ability of automatic feature learning makes Convolutional Neural Network (CNN) potentially suitable to uncover the complex and widespread brain changes in schizophrenia. Despite that, limited studies have been done on schizophrenia identification using interpretable deep learning approaches on multimodal neuroimaging data. Here, we developed a deep feature approach based on pre-trained 2D CNN and naive 3D CNN models trained from scratch for schizophrenia classification by integrating 3D structural and diffusion magnetic resonance imaging (MRI) data. We found that the naive 3D CNN models outperformed the pretrained 2D CNN models and the handcrafted feature-based machine learning approach using support vector machine during both cross-validation and testing on an independent dataset. Multimodal neuroimaging-based models accomplished performance superior to models based on a single modality. Furthermore, we identified brain grey matter and white matter regions critical for illness classification at the individual- and group-level which supported the salience network and striatal dysfunction hypotheses in schizophrenia. Our findings underscore the potential of CNN not only to automatically uncover and integrate multimodal 3D brain imaging features for schizophrenia identification, but also to provide relevant neurobiological interpretations which are crucial for developing objective and interpretable imaging-based probes for prognosis and diagnosis in psychiatric disorders.

Pretreatment abnormalities in white matter integrity predict one-year clinical outcome in first episode schizophrenia

Schizophrenia is a serious mental illness for which the mainstay of treatment is antipsychotics. Up to 30% of schizophrenia patients show limited response to antipsychotics. Identifying these patients before treatment could guide individualized treatment for improving outcomes in those not likely to show robust benefit from antipsychotics. Diffusion tensor imaging was performed with 56 drug-naïve first-episode schizophrenia patients and 69 matched healthy controls. Patients were followed clinically after one-year of antipsychotic treatment and classified at that point into groups of 17 poor outcome and 39 good outcome patients based on whether they showed at least a 50% reduction of Positive and Negative Syndrome Scale (PANSS) scores from baseline. Tract-based spatial statistics were applied to assess white matter microstructure in the two patient subgroups and healthy controls. Poor outcome patients showed reduced pretreatment fractional anisotropy (FA) in left cingulum and anterior thalamic radiation and increased FA in right superior and inferior longitudinal fasciculus compared with good outcome patients. FA in each of these four tracts was decreased in both patient subgroups relative to healthy controls. Considered together, the four altered tracts showed promising ability to differentiate poor from good outcome patients (sensitivity = 74.4%, specificity = 95.2%, AUC = 0.90, p < 0.001), and superior prediction of clinical outcome to baseline PANSS scores (p < 0.015). Prediction of outcomes using DTI features was not related to duration of untreated psychosis. Baseline alterations in white matter integrity may identify schizophrenia patients less likely to respond to treatment, which could be useful information for stratification in clinical trials and for individualized treatment planning.

Can reduced leftward asymmetry of white matter integrity be a marker of transition to psychosis in at-risk mental state?

As a biomarker for the degree of psychosis development, the lateral asymmetry of white matter (WM) integrity in each area of the cerebrum has been investigated; as a result, a reduced leftward asymmetry of WM integrity has been reported in patients with schizophrenia. Although individuals with an at-risk mental state for psychosis (ARMS) who subsequently develop psychosis are believed to have poorer social functioning, only a few studies have actually examined the associations between WM abnormalities and social functioning. The aim of the present study was to clarify the possibly predictive association between a reduced asymmetry of WM integrity and impairments in social functioning in patients with ARMS. Thirty ARMS subjects underwent MRI scanning and were assessed using the Social Functioning Scale (SFS). We examined the fractional anisotropy (FA) values in the cingulum bundle (CB) and the uncinate fasciculus (UF) using a tract-specific analysis. Lateral asymmetry was assessed using the laterality index (LI). The LI of the FA value was positive (leftward) in the CB and negative (rightward) in the UF. Although the LI was not correlated with the Scale of Prodromal Symptoms (SOPS) score, the LI in the CB was positively correlated with the SFS score. In ARMS patients, the degree of reduced leftward asymmetry in the CB might affect deteriorations in social functioning and may be useful as a biomarker for predicting future outcomes at an early stage of psychosis.

Weaker Cerebellocortical Connectivity Within Sensorimotor and Executive Networks in Schizophrenia Compared to Healthy Controls: Relationships with Processing Speed

Background: The cognitive dysmetria theory of schizophrenia proposes that communication between the cerebellum and cerebral cortex is disrupted by structural and functional abnormalities, resulting in psychotic symptoms and cognitive deficits. Methods: Using publicly available data, resting-state functional connectivity (rsFC) was calculated from 20 hemispheric cerebellar lobules as seed regions of interest to the rest of the brain. Group differences in rsFC between individuals with schizophrenia (SZ) and healthy controls (HCs) were computed, and relationships between rsFC and symptom severity and cognitive functioning were explored. Results: HCs demonstrated stronger connectivity than SZ between several cerebellar lobules and cortical regions, most robustly between motor-related cerebellar lobules (V and VIIIa/b) and temporal and parietal cortices. In addition, seven of nine lobules in which reduced cerebellocortical connectivity was observed showed diagnosis × processing speed interactions; HC showed a positive relationship between connectivity and processing speed, whereas SZ did not show this relationship. Other cognitive domains and symptom severity did not show relationships with connectivity. Conclusions: These findings partially support the cognitive dysmetria theory, and suggest that disrupted cerebellocortical connectivity is associated with slowed processing speed in schizophrenia. Impact statement We show in this work that in chronic schizophrenia, there is weaker functional connectivity between previously unstudied inferior posterior cerebellar lobules and cortical association areas. These findings align and extend previous work showing abnormal connectivity of anterior cerebellar lobules. Further, we present a novel finding that these connectivity deficits are differentially associated with processing speed in the schizophrenia versus healthy control groups. Findings provide further evidence for cerebellocortical dysconnectivity and processing speed deficits as biomarkers of schizophrenia, which may have implications for downstream effects on higher order cognitive functions, in line with the cognitive dysmetria theory.

Disrupted Rich Club Organization of Hemispheric White Matter Networks in Bipolar Disorder

Neuroimaging studies suggest disrupted connections of the brain white matter (WM) network in bipolar disorder (BD). A group of highly interconnected high-density structures, termed the 'rich club,' represents an important network for brain functioning. Recent works have revealed abnormal rich club organization in brain networks in BD. However, little is known regarding changes in the rich club organization of the hemispheric WM network in BD. Forty-nine BD patients and fifty-five age- and sex-matched normal controls (NCs) underwent diffusion tensor imaging (DTI). Graph theory approaches were applied to quantify group-specific rich club organization and nodal degree of hemispheric WM networks. We demonstrated that rich club organization of hemispheric WM networks in BD was disrupted, with disrupted feeder and local connections among hub and peripheral regions located in the default mode network (DMN) and the control execution network (CEN). In addition, BD patients showed abnormal asymmetry in the feeder and local connections, involving the hub and peripheral regions associated with emotion regulation and visuospatial functions. Moreover, the clinical symptoms of BD showed a significant correlation with the aberrant asymmetry in the regional degree of peripheral regions. These findings reveal that BD is closely associated with disrupted feeder and local connections but no alteration in rich-club connections in the rich club organization of hemispheric WM networks and provide novel insight into the changes of brain functions in BD.

The Amygdala in Schizophrenia and Bipolar Disorder: A Synthesis of Structural MRI, Diffusion Tensor Imaging, and Resting-State Functional Connectivity Findings

Frequently implicated in psychotic spectrum disorders, the amygdala serves as an important hub for elucidating the convergent and divergent neural substrates in schizophrenia and bipolar disorder, the two most studied groups of psychotic spectrum conditions. A systematic search of electronic databases through December 2017 was conducted to identify neuroimaging studies of the amygdala in schizophrenia and bipolar disorder, focusing on structural MRI, diffusion tensor imaging (DTI), and resting-state functional connectivity studies, with an emphasis on cross-diagnostic studies. Ninety-four independent studies were selected for the present review (49 structural MRI, 27 DTI, and 18 resting-state functional MRI studies). Also selected, and analyzed in a separate meta-analysis, were 33 volumetric studies with the amygdala as the region-of-interest. Reduced left, right, and total amygdala volumes were found in schizophrenia, relative to both healthy controls and bipolar subjects, even when restricted to cohorts in the early stages of illness. No volume abnormalities were observed in bipolar subjects relative to healthy controls. Shape morphometry studies showed either amygdala deformity or no differences in schizophrenia, and no abnormalities in bipolar disorder. In contrast to the volumetric findings, DTI studies of the uncinate fasciculus tract (connecting the amygdala with the medial- and orbitofrontal cortices) largely showed reduced fractional anisotropy (a marker of white matter microstructure abnormality) in both schizophrenia and bipolar patients, with no cross-diagnostic differences. While decreased amygdalar-orbitofrontal functional connectivity was generally observed in schizophrenia, varying patterns of amygdalar-orbitofrontal connectivity in bipolar disorder were found. Future studies can consider adopting longitudinal approaches with multimodal imaging and more extensive clinical subtyping to probe amygdalar subregional changes and their relationship to the sequelae of psychotic disorders.

Altered biochemical metabolism and its lateralization in the cortico-striato-cerebellar circuit of unmedicated bipolar II depression

OBJECTIVES

Evidence of the relationship between neurometabolic changes in the cortico-striato-cerebellar (CSC) circuit and bipolar disorder (BD) is still limited. To elucidate the pathogenesis of BD, we investigated the underlying neurometabolic changes and their effect on CSC lateralization circuits in unmedicated patients with bipolar II depression.

METHODS

Forty unmedicated participants with bipolar II depression and forty healthy controls underwent proton magnetic resonance spectroscopy (¹H-MRS). We obtained bilateral metabolic ratios of N-acetylaspartate (NAA)/creatine (Cr) and choline (Cho)/Cr in the prefrontal white matter (PWM), anterior cingulate cortex (ACC), basal ganglia (BG) and the cerebellum. Metabolic ratios were characterized using a laterality index (LI) for left-right asymmetry.

RESULTS

Overall, aberrant lateralization in the CSC circuit was characteristic in patients with bipolar II depression. Patients with bipolar II depression showed significantly lower NAA/Cr ratios in the left PWM, right ACC, left BG and left cerebellum when compared with the healthy controls. For bipolar II depression, we found lower NAA/Cr LI in the PWM, BG, and cerebellum, higher NAA/Cr LI in the ACC, and higher Cho/Cr LI in the BG and cerebellum when compared to the standard value (1.0). For healthy controls, we found lower NAA/Cr LI only in the BG and higher Cho/Cr LI in the cerebellum when compared to 1.0.

LIMITATIONS

As a cross-sectional study with a small sample size, progressive changes and complex metabolic interactions with treatment were not observed.

CONCLUSIONS

Our findings suggest that abnormal biochemical metabolism with aberrant lateralization in the CSC circuit may be an underlying pathophysiology of bipolar II depression.

Brain lateralization probed by water diffusion at the atomic to micrometric scale

Combined neutron scattering and diffusion nuclear magnetic resonance experiments have been used to reveal significant interregional asymmetries (lateralization) in bovine brain hemispheres in terms of myelin arrangement and water dynamics at micron to atomic scales. Thicker myelin sheaths were found in the left hemisphere using neutron diffraction. 4.7 T dMRI and quasi-elastic neutron experiments highlighted significant differences in the properties of water dynamics in the two hemispheres. The results were interpreted in terms of hemisphere-dependent cellular composition (number of neurons, cell distribution, etc.) as well as specificity of neurological functions (such as preferential networking).

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.

Aberrant transcriptomes and DNA methylomes define pathways that drive pathogenesis and loss of brain laterality/asymmetry in schizophrenia and bipolar disorder

Although the loss of brain laterality is one of the most consistent modalities in schizophrenia (SCZ) and bipolar disorder (BD), its molecular basis remains elusive. Our limited previous studies indicated that epigenetic modifications are key to the asymmetric transcriptomes of brain hemispheres. We used whole-genome expression microarrays to profile postmortem brain samples from subjects with SCZ, psychotic BD [BD[+]] or non-psychotic BD [BD(-)], or matched controls (10/group) and performed whole-genome DNA methylation (DNAM) profiling of the same samples (3-4/group) to identify pathways associated with SCZ or BD[+] and genes/sites susceptible to epigenetic regulation. qRT-PCR and quantitative DNAM analysis were employed to validate findings in larger sample sets (35/group). Gene Set Enrichment Analysis (GSEA) demonstrated that BMP signaling and astrocyte and cerebral cortex development are significantly (FDR q < 0.25) coordinately upregulated in both SCZ and BD[+], and glutamate signaling and TGFβ signaling are significantly coordinately upregulated in SCZ. GSEA also indicated that collagens are downregulated in right versus left brain of controls, but not in SCZ or BD[+] patients. Ingenuity Pathway Analysis predicted that TGFB2 is an upstream regulator of these genes (p = .0012). While lateralized expression of TGFB2 in controls (p = .017) is associated with a corresponding change in DNAM (p ≤ .023), lateralized expression and DNAM of TGFB2 are absent in SCZ or BD. Loss of brain laterality in SCZ and BD corresponds to aberrant epigenetic regulation of TGFB2 and changes in TGFβ signaling, indicating potential avenues for disease prevention/treatment.

Age-related deficits in intracortical myelination in young adults with bipolar disorder type I

BACKGROUND

Previous studies have implicated white-matter-related changes in the pathophysiology of bipolar disorder. However, most of what is known is derived from in vivo subcortical white-matter imaging or postmortem studies. In this study, we investigated whole-brain intracortical myelin (ICM) content in people with bipolar disorder type I and controls.

METHODS

Between Sept. 1, 2014, and Jan. 31, 2017, we used a 3 T General Electric scanner to collect T1-weighted images in 45 people with bipolar disorder type I and 60 controls aged 17 to 45 years using an optimized sequence that was sensitive to ICM content. We analyzed images using a surfacebased approach. We used general linear models with quadratic age terms to examine the signal trajectory of ICM across the age range.

RESULTS

In healthy controls, the T1-weighted signal followed an inverted-U trajectory over age; in people with bipolar disorder type I, the association between ICM and age followed a flat trajectory (p < 0.05, Bonferroni corrected). Exploratory analyses showed that ICM signal intensity was associated with duration of illness, age of onset, and anticonvulsant and antipsychotic use in people with bipolar disorder type I (p < 0.05, uncorrected).

LIMITATIONS

Because of the cross-sectional nature of the study, we were unable to comment on whether the effects were due to dysmyelination or demyelination in bipolar disorder.

CONCLUSION

This foundational study is, to our knowledge, the first to show global age-related deficits in ICM maturation throughout the cortex in bipolar disorder. Considering the impact of myelination on the maintenance of neural synchrony and the integrity of neural connections, this work may help us better understand the cognitive and behavioural deficits seen in bipolar disorder.

The Abnormality of Topological Asymmetry in Hemispheric Brain Anatomical Networks in Bipolar Disorder

Convergent evidences have demonstrated a variety of regional abnormalities of asymmetry in bipolar disorder (BD). However, little is known about the alterations in hemispheric topological asymmetries. In this study, we used diffusion tensor imaging to construct the hemispheric brain anatomical network of 49 patients with BD and 61 matched normal controls. Graph theory was then applied to quantify topological properties of the hemispheric networks. Although small-world properties were preserved in the hemispheric networks of BD, the degrees of the asymmetry in global efficiency, characteristic path length, and small-world property were significantly decreased. More changes in topological properties of the right hemisphere than those of left hemisphere were found in patients compared with normal controls. Consistent with such changes, the nodal efficiency in patients with BD also showed less rightward asymmetry mainly in the frontal, occipital, parietal, and temporal lobes. In contrast to leftward asymmetry, significant rightward asymmetry was found in supplementary motor area of BD, and attributed to more deficits in nodal efficiency of the left hemisphere. Finally, these asymmetry score of nodal efficiency in the inferior parietal lobule and rolandic operculum were significantly associated with symptom severity of BD. Our results suggested that abnormal hemispheric asymmetries in brain anatomical networks were associated with aberrant neurodevelopment, and providing insights into the potential neural biomarkers of BD by measuring the topological asymmetry in hemispheric brain anatomical networks.

Cerebral processing of facial emotions in bipolar I and II disorders: An event-related potential study

BACKGROUND

Behavioral results have shown that bipolar disorder patients have impaired recognition of facial emotions, but the detailed information processing of facial emotions in patients with bipolar I (BD I) and II (BD II) disorders remain unknown.

METHODS

We tested the cerebral event-related potentials to the static facial expressions of Neutral, Happiness, Anger and Sadness in 39 adult patients with BD I, 22 BD II, and 54 healthy volunteers. Participants' affective states were measured with the Mood Disorder Questionnaire, the Hypomania Checklist-32, and the Plutchik-van Praag Depression Inventory.

RESULTS

Over-processed right occipitotemporal cortex during N1 time window to Neutral and Happiness, and during P3b window to Sadness were found in BD I; prolonged N1 latencies to Neutral and Happiness, declined P3b amplitude to Sadness, negative correlation between P3b latency to Sadness and depression, and attenuated superior frontal activity during P3b window to Sadness were found in BD II; and the right-side dominance during facial emotion processing were found in both BD I and BD II.

LIMITATIONS

We didn't record the personality traits or medication used in patients, nor included other facial emotions such as fear and disgust.

CONCLUSIONS

When responding to facial emotions, both BD I and BD II showed a right-side processing dominance; BD I displayed enhanced processing in the right occipitotemporal cortex during structural encoding and categorical processing of facial emotions; while BD II displayed generalized impairments, less involvement of superior frontal cortex to negative emotions, and reduced ability to process negative emotions which was associated with depression.

Electroencephalographic delta/alpha frequency activity differentiates psychotic disorders: a study of schizophrenia, bipolar disorder and methamphetamine-induced psychotic disorder

Electroencephalography (EEG) has been proposed as a neurophysiological biomarker to delineate psychotic disorders. It is known that increased delta and decreased alpha, which are apparent in psychosis, are indicative of inappropriate arousal state, which leads to reduced ability to attend to relevant information. On this premise, we investigated delta/alpha frequency activity, as this ratio of frequency activity may serve as an effective neurophysiological biomarker. The current study investigated differences in delta/alpha frequency activity, in schizophrenia (SCZ), bipolar I disorder with psychotic features and methamphetamine-induced psychosis. One hundred and nine participants, including individuals with SCZ (n = 28), bipolar I disorder with psychotic features (n = 28), methamphetamine-induced psychotic disorder (MPD) (n = 24) and healthy controls (CON, n = 29). Diagnosis was ascertained with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition disorders and current medication was recorded. EEG was undertaken in three testing conditions: resting eyes open, resting eyes closed and during completion of a simple cognitive task (visual continuous performance task). EEG delta/alpha frequency activity was investigated across these conditions. First, delta/alpha frequency activity during resting eyes closed was higher in SCZ and MPD globally, when compared to CON, then lower for bipolar disorder (BPD) than MPD for right hemisphere. Second, delta/alpha frequency activity during resting eyes open was higher in SCZ, BPD and MPD for all electrodes, except left frontal, when compared to CON. Third, delta/alpha frequency activity during the cognitive task was higher in BPD and MPD for all electrodes, except left frontal, when compared to CON. Assessment of EEG delta/alpha frequency activity supports the delineation of underlying neurophysiological mechanisms present in psychotic disorders, which are likely related to dysfunctional thalamo-cortical connectivity. Delta/alpha frequency activity may provide a useful neurophysiological biomarker to delineate psychotic disorders.

Diffusion imaging study of the Corpus Callosum in bipolar disorder

Structural and diffusion imaging studies have provided some evidence of abnormal organization of Corpus Callosum (CC) in Bipolar Disorder (BD). Therefore, by using Diffusion Weighted Imaging (DWI), which allows to build subtle prediction models of fiber integrity for white matter (WM) tracts, this study aims to further explore the microstructure integrity of CC in BD patients compared to matched healthy controls. Twenty-four chronic patients with BD and 35 healthy controls were included in the study. Circular regions of interest were placed, on diffusion images, in the left and right side of callosal regions (i.e. rostrum/genu, anterior body, posterior body, splenium) and the Apparent Diffusion Coefficient (ADC) was then calculated. Significantly increased ADC values were found in right anterior body and in right splenium in BD patients compared to healthy controls (all p < 0.05, Bonferroni corrected). In this study, we found abnormally increased ADC callosal values in BD suggesting microstructural anomalies specifically in the right hemisphere. Interestingly, this finding further supports the presence of an altered inter-hemispheric communication between frontal and temporo-parietal association areas in patients with BD, which may ultimately result in clinical symptoms and cognitive deficits.

Elucidation of shared and specific white matter findings underlying psychopathology clusters in schizophrenia

BACKGROUND

Schizophrenia is associated with diverse white matter (WM) brain abnormalities. In this study, we sought to examine the WM microstructural findings which underlie clinical psychopathology clusters in schizophrenia and hypothesized that these symptom clusters are associated with common and unique WM tracts.

METHODS

Overall, 76 healthy controls (HC), and 148 patients with schizophrenia (SZ) were recruited and severity of symptomatology in schizophrenia was assessed using the Positive and Negative Syndrome Scale. WM fractional anisotropy (FA) values were extracted from their diffusion tensor images. Psychopathology clusters were first determined using factor analysis and the relationship between these symptom factors and FA values were then assessed with structural equation modelling, which included covariates such as age, sex, duration of illness and medications prescribed.

RESULTS

Patients with schizophrenia had reduced FA in the genu of corpus callosum (gCC) compared to HC. A three-factor model, namely Positive, Negative, Disorganised factors, was determined as the best fit for the data. All three psychopathology factors were associated with decreased FA in the gCC and bilateral cingulate gyrus. Higher Negative factor scores were uniquely associated with decreased FA in the right sagittal striatum and right superior longitudinal fasciculus.

CONCLUSIONS

This study found shared and specific WM changes and their associations with specific symptom clusters, which potentially allows for monitoring of such white matter findings associated with clinical presentations in schizophrenia over treatment and illness course.