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

Acute neural effects of the mood stabiliser lamotrigine on emotional processing in healthy volunteers: a randomised control trial

Lamotrigine is an effective mood stabiliser, largely used for the management and prevention of depression in bipolar disorder. The neuropsychological mechanisms by which lamotrigine acts to relieve symptoms as well as its neural effects on emotional processing remain unclear. The primary objective of this current study was to investigate the impact of an acute dose of lamotrigine on the neural response to a well-characterised fMRI task probing implicit emotional processing relevant to negative bias. 31 healthy participants were administered either a single dose of lamotrigine (300 mg, n = 14) or placebo (n = 17) in a randomized, double-blind design. Inside the 3 T MRI scanner, participants completed a covert emotional faces gender discrimination task. Brain activations showing significant group differences were identified using voxel-wise general linear model (GLM) nonparametric permutation testing, with threshold free cluster enhancement (TFCE) and a family wise error (FWE)-corrected cluster significance threshold of p < 0.05. Participants receiving lamotrigine were more accurate at identifying the gender of fearful (but not happy or angry) faces. A network of regions associated with emotional processing, including amygdala, insula, and the anterior cingulate cortex (ACC), was significantly less activated in the lamotrigine group compared to the placebo group across emotional facial expressions. A single dose of lamotrigine reduced activation in limbic areas in response to faces with both positive and negative expressions, suggesting a valence-independent effect. However, at a behavioural level lamotrigine appeared to reduce the distracting effect of fear on face discrimination. Such effects may be relevant to the mood stabilisation effects of lamotrigine.

Whole-brain intrinsic functional connectivity predicts symptoms and functioning in early psychosis

Theories of psychotic illness suggest that abnormal intrinsic functional connectivity may explain its characteristic positive and disorganization symptoms as well as lead to impaired general functioning. Here we used resting state functional magnetic resonance imaging (fMRI) to evaluate associations between these symptoms and the degree to which global connectivity is abnormal in early psychosis (EP). Eighty-six healthy controls (HCs) and 108 individuals with EP with resting state fMRI data were included in primary analyses. The EP group included 83 participants with schizophrenia-spectrum disorders and 25 with bipolar disorder type I with psychotic features. A global intrinsic connectivity "similarity index" for each EP individual was determined by calculating its correlation with the average HC connectivity matrix extracted using Schaefer atlases of multiple parcellations (100, 200, 300, and 400 region parcellations). As hypothesized, connectivity similarity with the average HC matrix was negatively associated with Brief Psychiatric Rating Scale total score, Scale for the Assessment of Positive Symptoms total score, and disorganization symptoms. Similarity was also positively associated with Global Assessment of Functioning score. Results were not driven by sex or diagnosis effects and were consistent across parcellation schemes. These results support the hypothesis that changes in whole-brain connectivity patterns are associated with psychosis symptoms and support the use of functional connectivity as a biomarker for these symptoms in EP.

EEG Spatial-temporal Dynamics of Resting-state Activity in Young Women with Anorexia Nervosa: Preliminary Evidence

The aim of this study was to provide preliminary evidence on temporal dynamics of resting-state brain networks in youth with anorexia nervosa (AN) using electroencephalography (EEG). Resting-state EEG data were collected in 18 young women with AN and 18 healthy controls (HC). Between-group differences in brain networks were assessed using microstates analyses. Five microstates were identified across all subjects (A, B, C, D, E). Using a single set of maps representative of the whole dataset, group differences were identified for microstates A, C, and E. A common-for-all template revealed a relatively high degree of consistency in results for reduced time coverage of microstate C, but also an increased presence of microstate class E. AN and HC had different microstate transition probabilities, largely involving microstate A. Using LORETA, for microstate D, we found that those with AN had augmented activations in the left frontal inferior operculum, left insula, and bilateral paracentral lobule, compared with HC. For microstate E, AN had augmented activations in the para-hippocampal gyrus, caudate, pallidum, cerebellum, and cerebellar vermis. Our findings suggest altered microstates in young women with AN associated with integration of sensory and bodily signals, monitoring of internal/external mental states, and self-referential processes. Future research should examine how EEG-derived microstates could be applied to develop diagnostic and prognostic models of AN.

Bipolar disorder and the gut microbiota: a bibliometric analysis

Background

Previous studies have explored the relationship between bipolar disorder and gut microbiota. However, there has been no bibliometric analysis to summarize and analyze these publications. Our objective was to perform a bibliometric analysis to investigate the current status and frontiers of the publications in the field of the association between bipolar disorder and the gut microbiota.

Methods

We retrieved publications concerning the interplay between the gut microbiota and bipolar disorder from the Web of Science Core Collection (WoSCC). The analysis was executed using WoSCC's literature analysis tool and VOSviewer 1.6.16.

Results

In total, we identified 177 publications originating from 362 institutions across 39 countries/regions, and these articles were disseminated in 104 different journals. The most productive institutions, authors, countries/regions, and journals were Zhejiang University contributing 18 publications, Shaohua Hu authoring 12 publications, China with 53 publications, and Frontiers in Psychiatry with 11 publications. The first high-cited document was published in the Journal of Psychiatric Research in 2017, and authored by Evans. In this article, they found gut microbiome composition was associated with BD and its illness severity, and they concluded that targeting the gut microbiota may be helpful to develop the effective treatment for bipolar disorder. The top 5 keywords with the highest frequency except for bipolar disorder and gut microbiota were as follows: depression, inflammation, probiotic, gut-brain axis, and anxiety.

Conclusion

In conclusion, this is the first bibliometric analysis to explore the publications in the field of the association between bipolar disorder and the gut microbiota. The main research hotspots regarding this field were the characteristics, abundance, and diversity of gut microbiome in bipolar disorder, the role of treatment and gut microbiome in bipolar disorder, microbiome-brain connections in bipolar disorder, and interventions for bipolar disorder based on microbiota composition modification. The number of studies about the association between gut microbiota and bipolar disorder is relatively small, and more studies are needed to expand our understanding the association between gut microbiota and bipolar disorder.

Brain functional changes across mood states in bipolar disorder: from a large-scale network perspective

BACKGROUND

Exploring the neural basis related to different mood states is a critical issue for understanding the pathophysiology underlying mood switching in bipolar disorder (BD), but research has been scarce and inconsistent.

METHODS

Resting-state functional magnetic resonance imaging data were acquired from 162 patients with BD: 33 (hypo)manic, 64 euthymic, and 65 depressive, and 80 healthy controls (HCs). The differences of large-scale brain network functional connectivity (FC) between the four groups were compared and correlated with clinical characteristics. To validate the generalizability of our findings, we recruited a small longitudinal independent sample of BD patients (n = 11). In addition, we examined topological nodal properties across four groups as exploratory analysis.

RESULTS

A specific strengthened pattern of network FC, predominantly involving the default mode network (DMN), was observed in (hypo)manic patients when compared with HCs and bipolar patients in other mood states. Longitudinal observation revealed an increase in several network FCs in patients during (hypo)manic episode. Both samples evidenced an increase in the FC between the DMN and ventral attention network, and between the DMN and limbic network (LN) related to (hypo)mania. The altered network connections were correlated with mania severity and positive affect. Bipolar depressive patients exhibited decreased FC within the LN compared with HCs. The exploratory analysis also revealed an increase in degree in (hypo)manic patients.

CONCLUSIONS

Our findings identify a distributed pattern of large-scale network disturbances in the unique context of (hypo)mania and thus provide new evidence for our understanding of the neural mechanism of BD.

Innovative Neuroimaging Biomarker Distinction of Major Depressive Disorder and Bipolar Disorder through Structural Connectome Analysis and Machine Learning Models

Major depressive disorder (MDD) and bipolar disorder (BD) share clinical features, which complicates their differentiation in clinical settings. This study proposes an innovative approach that integrates structural connectome analysis with machine learning models to discern individuals with MDD from individuals with BD. High-resolution MRI images were obtained from individuals diagnosed with MDD or BD and from HCs. Structural connectomes were constructed to represent the complex interplay of brain regions using advanced graph theory techniques. Machine learning models were employed to discern unique connectivity patterns associated with MDD and BD. At the global level, both BD and MDD patients exhibited increased small-worldness compared to the HC group. At the nodal level, patients with BD and MDD showed common differences in nodal parameters primarily in the right amygdala and the right parahippocampal gyrus when compared with HCs. Distinctive differences were found mainly in prefrontal regions for BD, whereas MDD was characterized by abnormalities in the left thalamus and default mode network. Additionally, the BD group demonstrated altered nodal parameters predominantly in the fronto-limbic network when compared with the MDD group. Moreover, the application of machine learning models utilizing structural brain parameters demonstrated an impressive 90.3% accuracy in distinguishing individuals with BD from individuals with MDD. These findings demonstrate that combined structural connectome and machine learning enhance diagnostic accuracy and may contribute valuable insights to the understanding of the distinctive neurobiological signatures of these psychiatric disorders.

Intrinsic timescales and predictive allostatic interoception in brain health and disease

The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.

Advances in functional MRI research in bipolar disorder: from the perspective of mood states

Bipolar disorder is characterised by recurrent and alternating episodes of mania/hypomania and depression. Current breakthroughs in functional MRI techniques have uncovered the functional neuroanatomy of bipolar disorder. However, the pathophysiology underlying mood instability, mood switching and the development of extreme mood states is less well understood. This review presents a comprehensive overview of current evidence from functional MRI studies from the perspective of mood states. We first summarise the disrupted brain activation patterns and functional connectivity that have been reported in bipolar disorder, irrespective of the mood state. We next focus on research that solely included patients in a single mood state for a better understanding of the pathophysiology of bipolar disorder and research comparing patients with different mood states to dissect mood state-related effects. Finally, we briefly summarise current theoretical models and conclude this review by proposing potential avenues for future research. A comprehensive understanding of the pathophysiology with consideration of mood states could not only deepen our understanding of how acute mood episodes develop at a neurophysiological level but could also facilitate the identification of biological targets for personalised treatment and the development of new interventions for bipolar disorder.

State- and trait-related dysfunctions in bipolar disorder across different mood states: a graph theory study

BACKGROUND

The interplay between state- and trait-related disruptions in structural networks remains unclear in bipolar disorder (BD), but graph theory can offer insights into global and local network changes. We sought to use diffusion-tensor imaging (DTI) and graph theory approaches to analyze structural topological properties across distinct mood states and identify high-risk individuals by examining state- and trait-related impairments in BD.

METHODS

We studied changes in white matter network among patients with BD and healthy controls, exploring relationships with clinical variables. Secondary analysis involved comparing patients with BD with unaffected people at high genetic risk for BD.

RESULTS

We included 152 patients with BD, including 52 with depressive BD (DBD), 64 with euthymic BD (EBD) and 36 with manic BD (MBD); we also included 75 healthy controls. Secondary analyses involved 27 unaffected people at high genetic risk for BD. Patients with DBD and MBD exhibited significantly lower global efficiencies than those with EBD and healthy controls, with patients with DBD showing the lowest global efficiencies. In addition, patients with DBD displayed impaired local efficiency and normalized clustering coefficient (γ). At a global level, γ correlated negatively with depression and anxiety. Compared with healthy controls, and across mood states, patients with BD showed abnormal shortest path lengths in the frontolimbic circuit, a trend mirrored among those at high genetic risk for BD.

LIMITATIONS

Considerations include medication effects, absence of recorded BD episode counts and the cross-sectional nature of the study.

CONCLUSION

Mood-specific whole-brain network metrics could serve as potential biomarkers in BD for transitions between mood states. Moreover, these findings contribute to evidence of trait-related frontolimbic circuit irregularities, shedding light on underlying pathophysiological mechanisms in BD.

Aberrant resting-state functional connectivity underlies cognitive and functional impairments in remitted patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is commonly associated with cognitive impairments, that directly contribute to patients' functional disability. However, there is no effective treatment targeting cognition in BD. A key reason for the lack of pro-cognitive interventions is the limited insight into the brain correlates of cognitive impairments in these patients. This is the first study investigating the resting-state neural underpinnings of cognitive impairments in different neurocognitive subgroups of patients with BD.

METHOD

Patients with BD in full or partial remission and healthy controls (final sample of n = 144 and n = 50, respectively) underwent neuropsychological assessment and resting-state functional magnetic resonance imaging. We classified the patients into cognitively impaired (n = 83) and cognitively normal (n = 61) subgroups using hierarchical cluster analysis of the four cognitive domains. We used independent component analysis (ICA) to investigate the differences between the neurocognitive subgroups and healthy controls in resting-state functional connectivity (rsFC) in the default mode network (DMN), executive central network (ECN), and frontoparietal network (FPN).

RESULTS

Cognitively impaired patients displayed greater positive rsFC within the DMN and less negative rsFC within the ECN than healthy controls. Across cognitively impaired patients, lower positive connectivity within DMN and lower negative rsFC within ECN correlated with worse global cognitive performance.

CONCLUSION

Cognitive impairments in BD seem to be associated with a hyper-connectivity within the DMN, which may explain the failure to suppress task-irrelevant DMN activity during the cognitive performance, and blunted anticorrelation in the ECN. Thus, aberrant connectivity within the DMN and ECN may serve as brain targets for pro-cognitive interventions.

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.

Aberrant functional connectivity within and between brain networks in patients with early-onset bipolar disorder

OBJECTIVE

This study used independent component analysis (ICA) to investigate the connectivity patterns of resting-state functional large-scale brain networks in patients with early-onset bipolar disorder (BD).

METHODS

ICA was used to extract brain functional network components from 43 early-onset BD patients and 21 healthy controls (HCs). Then, the functional connectivity (FC) and functional network connectivity (FNC) within and between the independent brain networks was calculated, and the correlation between the connectivity changes and neuropsychological scale was evaluated.

RESULTS

Compared with HCs, FC increased in the right hippocampus and inferior temporal gyrus, and left triangular inferior frontal gyrus of the anterior default mode network (aDMN); right median cingulate and paracingulate gyri, and inferior parietal lobule of the posterior DMN (pDMN); and right precentral and postcentral gyrus of the sensorimotor network (SMN) in early-onset BD patients. However, FC decreased in the left superior frontal gyrus of the aDMN, left paracentral lobule of the SMN, and left lingual gyrus and calcarine of the visual network in early-onset BD patients. There was no significant correlation between FC values of differential brain regions within resting-state networks (RSNs) and neuropsychological scores (uncorrected p > 0.05). In addition, the FNC among the pDMN-auditory network, pDMN-visual network, left frontoparietal network (lFPN)-visual network, lFPN-aDMN and dorsal attention network-ventral attention network (DAN-VAN) were increased in early-onset BD patients. The zFNC of the pDMN-visual network was positively correlated with the anxiety/somatization score (r = 0.5833, p < 0.0001) and sleep disorders (r = 0.6150, p < 0.0001). The zFNC of the lFPN-aDMN was positively correlated with despair (r = 0.4505, p = 0.004 × 10 < 0.05 after Bonferroni correction). The zFNC of the DAN-VAN was positively correlated with cognitive impairment (r = 0.4598, p = 0.0032 × 10 < 0.05 after Bonferroni correction). The zFNC of the DAN-VAN showed a positive correlation trend with the Hamilton Depression Scale (HAMD) total score (r = 0.4404, p = 0.005 × 10 = 0.05 after Bonferroni correction).

CONCLUSIONS

Patients with early-onset BD showed changes in a wide range of neural functional networks, involving changes in executive control, attention, perceptual regulation, cognition and other neural networks, which may provide new imaging evidence for understanding the pathogenesis of early-onset BD and for therapeutic intervention targets.

Cross-attractor modeling of resting-state functional connectivity in psychiatric disorders

Resting-state functional connectivity (RSFC) is altered across various psychiatric disorders. Brain network modeling (BNM) has the potential to reveal the neurobiological underpinnings of such abnormalities by dynamically modeling the structure-function relationship and examining biologically relevant parameters after fitting the models with real data. Although innovative BNM approaches have been developed, two main issues need to be further addressed. First, previous BNM approaches are primarily limited to simulating noise-driven dynamics near a chosen attractor (or a stable brain state). An alternative approach is to examine multi(or cross)-attractor dynamics, which can be used to better capture non-stationarity and switching between states in the resting brain. Second, previous BNM work is limited to characterizing one disorder at a time. Given the large degree of co-morbidity across psychiatric disorders, comparing BNMs across disorders might provide a novel avenue to generate insights regarding the dynamical features that are common across (vs. specific to) disorders. Here, we address these issues by (1) examining the layout of the attractor repertoire over the entire multi-attractor landscape using a recently developed cross-attractor BNM approach; and (2) characterizing and comparing multiple disorders (schizophrenia, bipolar, and ADHD) with healthy controls using an openly available and moderately large multimodal dataset from the UCLA Consortium for Neuropsychiatric Phenomics. Both global and local differences were observed across disorders. Specifically, the global coupling between regions was significantly decreased in schizophrenia patients relative to healthy controls. At the same time, the ratio between local excitation and inhibition was significantly higher in the schizophrenia group than the ADHD group. In line with these results, the schizophrenia group had the lowest switching costs (energy gaps) across groups for several networks including the default mode network. Paired comparison also showed that schizophrenia patients had significantly lower energy gaps than healthy controls for the somatomotor and visual networks. Overall, this study provides preliminary evidence supporting transdiagnostic multi-attractor BNM approaches to better understand psychiatric disorders' pathophysiology.

Prefrontal, parietal, and limbic condition-dependent differences in bipolar disorder: a large-scale meta-analysis of functional neuroimaging studies

BACKGROUND

Over the past few decades, neuroimaging research in Bipolar Disorder (BD) has identified neural differences underlying cognitive and emotional processing. However, substantial clinical and methodological heterogeneity present across neuroimaging experiments potentially hinders the identification of consistent neural biomarkers of BD. This meta-analysis aims to comprehensively reassess brain activation and connectivity in BD in order to identify replicable differences that converge across and within resting-state, cognitive, and emotional neuroimaging experiments.

METHODS

Neuroimaging experiments (using fMRI, PET, or arterial spin labeling) reporting whole-brain results in adults with BD and controls published from December 1999-June 18, 2019 were identified via PubMed search. Coordinates showing significant activation and/or connectivity differences between BD participants and controls during resting-state, emotional, or cognitive tasks were extracted. Four parallel, independent meta-analyses were calculated using the revised activation likelihood estimation algorithm: all experiment types, all resting-state experiments, all cognitive experiments, and all emotional experiments. To confirm reliability of identified clusters, two different meta-analytic significance tests were employed.

RESULTS

205 published studies yielding 506 individual neuroimaging experiments (150 resting-state, 134 cognitive, 222 emotional) comprising 5745 BD and 8023 control participants were included. Five regions survived both significance tests. Individuals with BD showed functional differences in the right posterior cingulate cortex during resting-state experiments, the left amygdala during emotional experiments, including those using a mixed (positive/negative) valence manipulation, and the left superior and right inferior parietal lobules during cognitive experiments, while hyperactivating the left medial orbitofrontal cortex during cognitive experiments. Across all experiments, there was convergence in the right caudate extending to the ventral striatum, surviving only one significance test.

CONCLUSIONS

Our findings indicate reproducible localization of prefrontal, parietal, and limbic differences distinguishing BD from control participants that are condition-dependent, despite heterogeneity, and point towards a framework for identifying reproducible differences in BD that may guide diagnosis and treatment.

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.

Reductions in regional theta power and fronto-parietal theta-gamma phase-amplitude coupling during gaze processing in bipolar disorder

Impaired social cognition is common in bipolar disorder (BD) and predicts poor functional outcomes. A critical determinant of social cognition is the ability to discriminate others' gaze direction, and its alteration may contribute to functional impairment in BD. However, the neural mechanisms underlying gaze processing in BD are unclear. Because neural oscillations are crucial neurobiological mechanisms supporting cognition, we aimed to understand their role in gaze processing in BD. Using electroencephalography (EEG) data recorded during a gaze discrimination task for 38 BD and 34 controls (HC), we examined: theta and gamma power over bilateral posterior and midline anterior locations associated with early face processing and higher-level cognitive processing, and theta-gamma phase-amplitude coupling (PAC) between locations. Compared to HC, BD showed reduced midline-anterior and left-posterior theta power, and diminished bottom-up/top-down theta-gamma PAC between anterior/posterior sites. Reduced theta power and theta-gamma PAC related to slower response times. These findings suggest that altered theta oscillations and anterior-posterior cross-frequency coupling between areas associated with higher-level cognition and early face processing may underlie impaired gaze processing in BD. This is a crucial step towards translational research that may inform novel social cognitive interventions (e.g., neuromodulation to target specific oscillatory dynamics) to improve functioning in BD.

A Primer on Interoception and its Importance in Psychiatry

Interoception is the perception of signals from inside the body. It plays a significant role in the nervous, cardiovascular, respiratory, gastrointestinal, genitourinary, and endocrine systems. It is also closely related to the autonomic nervous system and inflammatory pathways and plays a significant role in our optimal functioning. Recently, interoception has gained more attention in neuropsychiatric research. Anatomical and physiological aspects of interoception like relevant brain areas, the role of the vagus nerve, and the autonomic nervous system are gradually being understood. Different facets of interoception like interoceptive attention, detection, magnitude, discrimination, accuracy, awareness, and appraisal have been proposed and their assessments and importance are being evaluated. Further, interoception is often dysregulated or abnormal in psychiatric disorders. It has been implicated in the psychopathology, etiopathogenesis, clinical features and treatment of mood, anxiety, psychotic, personality and addiction-related disorders. This narrative review attempts to provide a nuanced understanding of the pathway(s), components, functions, assessments, and problems of interoception and will help us to detect its disturbances and evaluate its impact on psychiatric disorders, leading to a better perspective and management. This will also advance interoception-related research.

The Role of the Gut Microbiome in Bipolar Disorder and its Common Comorbidities

Bipolar disorder is a decidedly heterogeneous and multifactorial disease, with significant psychosocial and medical disease burden. Much difficulty has been encountered in developing novel therapeutics and objective biomarkers for clinical use in this population. In that regard, gut-microbial homeostasis appears to modulate several key pathways relevant to a variety of psychiatric, metabolic, and inflammatory disorders. Microbial impact on immune, endocrine, endocannabinoid, kynurenine, and other pathways are discussed throughout this review. Emphasis is placed on this system's relevance to current pharmacology, diet, and comorbid illness in bipolar disorder. Despite the high level of optimism promoted in many reviews on this topic, substantial obstacles exist before any microbiome-related findings can provide meaningful clinical utility. Beyond a comprehensive overview of pathophysiology, this review hopes to highlight several key areas where progress is needed. As well, novel microbiome-associated suggestions are presented for future research.

The anatomical networks based on probabilistic structurally connectivity in bipolar disorder across mania, depression, and euthymic states

BACKGROUNDS

There have pieces of evidence of the distinct aberrant functional network topology profile in bipolar disorder (BD) across mania, depression, and euthymic episodes. However, the underlying anatomical network topology pattern in BD across different episodes is unclear.

METHODS

We calculated the whole-brain probabilistic structurally connectivity across 143 subjects (72 with BD [34 depression; 13 mania; 25 euthymic] and 53 healthy controls), and used graph theory to examine the trait- and state-related topology alterations of the structural connectome in BD. The correlation analysis was further conducted to explore the relationship between detected network measures and clinical symptoms.

RESULTS

There no omnibus alteration of any global network metrics were observed across all diagnostic groups. In the regional network metrics level, bipolar depression showed increased clustering coefficient in the right lingual gyrus compared with all other groups, and the increased clustering coefficient in the right lingual gyrus positively correlated with depression, anxiety, and illness burden symptoms but negatively correlated with mania symptoms; manic and euthymic patients showed decreased clustering coefficient in the left inferior occipital gyrus compared with HCs.

LIMITATIONS

The moderate sample size of all patient groups (especially for subjects with mania) might have contributed to the negative findings of the trait feature in this study.

CONCLUSIONS

We demonstrated the altered regional connectivity pattern in the occipital lobe of the bipolar depression and mania episode, especially the lingual gyrus. The association of the clustering coefficient in the lingual gyrus with clinical symptoms helps monitor the state of 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.

Statistical power in network neuroscience

Network neuroscience has emerged as a leading method to study brain connectivity. The success of these investigations is dependent not only on approaches to accurately map connectivity but also on the ability to detect real effects in the data - that is, statistical power. We review the state of statistical power in the field and discuss sample size, effect size, measurement error, and network topology as key factors that influence the power of brain connectivity investigations. We use the term 'differential power' to describe how power can vary between nodes, edges, and graph metrics, leaving traces in both positive and negative connectome findings. We conclude with strategies for working with, rather than around, power in connectivity studies.

Toward Best Practices for Imaging Transcriptomics of the Human Brain

Modern brainwide transcriptional atlases provide unprecedented opportunities for investigating the molecular correlates of brain organization, as quantified using noninvasive neuroimaging. However, integrating neuroimaging data with transcriptomic measures is not straightforward, and careful consideration is required to make valid inferences. In this article, we review recent work exploring how various methodological choices affect 3 main phases of imaging transcriptomic analyses, including 1) processing of transcriptional atlas data; 2) relating transcriptional measures to independently derived neuroimaging phenotypes; and 3) evaluating the functional implications of identified associations through gene enrichment analyses. Our aim is to facilitate the development of standardized and reproducible approaches for this rapidly growing field. We identify sources of methodological variability, key choices that can affect findings, and considerations for mitigating false positive and/or spurious results. Finally, we provide an overview of freely available open-source toolboxes implementing current best-practice procedures across all 3 analysis phases.

Polygenic risk score for five major psychiatric disorders associated with volume of distinct brain regions in the general population

Risk genes and abnormal brain structural indices of psychiatric disorders have been extensively studied. However, whether genetic risk influences brain structure in the general population has been rarely studied. The current study enrolled 483 young Chinese adults, calculated their polygenic risk scores (PRS) for psychiatric disorders based on Psychiatric Genomics Consortium GWAS results, and examined the association between PRSs and brain volume. We found that PRSs were associated with the volume of many brain regions, with differences between PRS for different disorder, calculated at different threshold, and calculated using European or East Asian ancestry. Of them, the PRS for Major Depressive Disorder based on European ancestry was positively associated with right temporal gyrus; the PRS for schizophrenia based on East Asian ancestry was negatively associated with right precentral and postcentral gyrus; the PRS for schizophrenia based on European ancestry was positively associated with right superior temporal gyrus. All these brain regions are critical for corresponding disorders. However, no significant associations were found between PRS for Autism Spectrum Disorder / Bipolar Disorder and brain volume; and the association between PRS for Attention Deficit Hyperactivity Disorder at different thresholds and brain volume was inconsistent. These findings suggest distinct brain mechanisms underlying different psychiatric disorders.

Brain-gut microbiota multimodal predictive model in patients with bipolar depression

BACKGROUND

The "microbiota-gut-brain axis" which bridges the brain and gut microbiota is involved in the pathological mechanisms of bipolar disorder (BD), but rare is known about the exact association patterns and the potential for clinical diagnosis and treatment outcome prediction.

METHODS

At baseline, fecal samples and resting-state MRI data were collected from 103 BD depression patients and 39 healthy controls (HCs) for metagenomic sequencing and network-based functional connectivity (FC), grey matter volume (GMV) analyses. All patients then received 4-weeks quetiapine treatment and were further classified as responders and non-responders. Based on pre-treatment datasets, the correlation networks were established between gut microbiota and neuroimaging measures and the multimodal kernal combination support vector machine (SVM) classifiers were constructed to distinguish BD patients from HCs, and quetiapine responders from non-responders.

RESULTS

The multi-modal pre-treatment characteristics of quetiapine responders, were closer to the HCs compared to non-responders. And the correlation network analyses found the substantial correlations existed in HC between the Anaerotruncus_ unclassified，Porphyromonas_asaccharolytica，Actinomyces_graevenitzii et al. and the functional connectomes involved default mode network (DMN),somatomotor (SM), visual, limbic and basal ganglia networks were disrupted in BD. Moreover, in terms of the multimodal classifier, it reached optimized area under curve (AUC-ROC) at 0.9517 when classified BD from HC, and also acquired 0.8292 discriminating quetiapine responders from non-responders, which consistently better than even using the best unique modality.

LIMITATIONS

Lack post-treatment and external validation datasets; size of HCs is modest.

CONCLUSIONS

Multi-modalities of combining pre-treatment gut microbiota with neuroimaging endophenotypes might be a superior approach for accurate diagnosis and quetiapine efficacy prediction in BD.

Associations of leptin and corticostriatal connectivity in bipolar disorder

Bipolar disorder (BD) and metabolic disturbance represent a chronic state of low-grade inflammation and corticostriatal circuitry alterations. Herein, we aimed to investigate whether plasma leptin, an adipokine that plays a key role in the interplay of metabolism and inflammation, is associated with corticostriatal connectivity in patients with BD. Twenty-eight BD I patients, 36 BD II patients and 66 healthy controls were enrolled and completed the Hamilton Depression Rating Scale, the Young Mania Rating Scale, and the Recent Life Change Questionnaire. Fasting plasma leptin and C-reactive protein (CRP) levels were measured, and corticostriatal connectivity was examined using functional magnetic resonance imaging (fMRI). The relationships between leptin, CRP and body mass index (BMI) identified in the controls and BD II patients were absent in the BD I patients. We did not find a significant group difference in the leptin level; nevertheless, the negative correlation between leptin level and corticostriatal connectivity (ventrolateral prefrontal cortex and inferior temporal gyrus) observed in the healthy controls was absent in the BD patients. The disproportionate increase in leptin level with increasing BMI in BD indicated a potential inflammatory role of white adipose tissue in BD. Furthermore, higher CRP levels in BD I patients might induce leptin resistance. Collectively, our results implied vulnerability to inflammatory and metabolic diseases in patients with BD, especially BD I.

A graph theory neuroimaging approach to distinguish the depression of bipolar disorder from major depressive disorder in adolescents and young adults

BACKGROUND

Markers to differentiate depressions of bipolar disorder (BD-Dep) from depressions of major depressive disorder (MDD-Dep), and for more targeted treatments, are critically needed to decrease current high rates of misdiagnosis that can lead to ineffective or potentially deleterious treatments. Distinguishing, and specifically treating the depressions, during the adolescent/young adult epoch is especially important to decrease illness progression and improve prognosis, and suicide, as it is the epoch when suicide thoughts and behaviors often emerge. With differences in functional connectivity patterns reported when BD-Dep and MDD-Dep have been studied separately, this study used a graph theory approach aimed to identify functional connectivity differences in their direct comparison.

METHODS

Functional magnetic resonance imaging whole-brain functional connectivity (Intrinsic Connectivity Distribution, ICD) measures were compared across adolescents/young adults with BD-Dep (n = 28), MDD-Dep (n = 20) and HC (n = 111). Follow-up seed-based connectivity was conducted on regions of significant ICD differences. Relationships with demographic and clinical measures were assessed.

RESULTS

Compared to the HC group, both the BD-Dep and MDD-Dep groups exhibited left-sided frontal, insular, and medial temporal ICD increases. The BD-Dep group had additional right-sided ICD increases in frontal, basal ganglia, and fusiform areas. In seed-based analyses, the BD-Dep group exhibited increased interhemispheric functional connectivity between frontal areas not seen in the MDD-Dep group.

LIMITATIONS

Modest sample size; medications not studied systematically.

CONCLUSIONS

This study supports bilateral and interhemispheric functional dysconnectivity as features of BD-Dep that may differentiate it from MDD-Dep in adolescents/young adults and serve as a target for early diagnosis and treatment strategies.

Axonal transport deficits in neuropsychiatric disorders

Axonal transport is a major cellular process that mediates bidirectional signaling between the soma and synapse, enabling both intracellular and intercellular communications. Cellular materials, such as proteins, RNAs, and organelles, are transported by molecular motor proteins along cytoskeletal highways in a highly regulated manner. Several studies have demonstrated that axonal transport is central to normal neuronal function, plasticity, and memory storage. Importantly, disruptions in axonal transport result in neuronal dysfunction and are associated with several neurodegenerative disorders. However, we do not know much about axonal transport deficits in neuropsychiatric disorders. Here, we briefly discuss our current understanding of the role of axonal transport in schizophrenia, bipolar and autism.

Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder

Predictive neurobiological markers for prognosis are essential but underemphasized for patients with bipolar disorder (BD), a neuroprogressive disorder. Hence, we developed models for predicting symptom and functioning changes. Sixty-one patients with BD were recruited and assessed using the Young Mania Rating Scale (YMRS), Montgomery−Åsberg Depression Rating Scale (MADRS), Positive and Negative Syndrome Scale (PANSS), UKU Side Effect Rating Scale (UKU), Personal and Social Performance Scale (PSP), and Global Assessment of Functioning scale both at baseline and after 1-year follow-up. The models for predicting the changes in symptom and functioning scores were trained using data on the brain morphology, functional connectivity, and cytokines collected at baseline. The correlation between the predicted and actual changes in the YMRS, MADRS, PANSS, and UKU scores was higher than 0.86 (q < 0.05). Connections from subcortical and cerebellar regions were considered for predicting the changes in the YMRS, MADRS, and UKU scores. Moreover, connections of the motor network were considered for predicting the changes in the YMRS and MADRS scores. The neurobiological markers for predicting treatment-response symptoms and functioning changes were consistent with the neuropathology of BD and with the differences found between treatment responders and nonresponders.

Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder

BACKGROUND

Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity.

METHODS

We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest.

RESULTS

Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD.

CONCLUSIONS

Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry.

Multi-omics analyses of serum metabolome, gut microbiome and brain function reveal dysregulated microbiota-gut-brain axis in bipolar depression

The intricate processes of microbiota-gut-brain communication in modulating human cognition and emotion, especially in the context of mood disorders, have remained elusive. Here we performed faecal metagenomic, serum metabolomics and neuroimaging studies on a cohort of 109 unmedicated patients with depressed bipolar disorder (BD) patients and 40 healthy controls (HCs) to characterise the microbial-gut-brain axis in BD. Across over 12,000 measured metabolic features, we observed a large discrepancy (73.54%) in the serum metabolome between BD patients and HCs, spotting differentially abundant microbial-derived neuroactive metabolites including multiple B-vitamins, kynurenic acid, gamma-aminobutyric acid and short-chain fatty acids. These metabolites could be linked to the abundance of gut microbiota presented with corresponding biosynthetic potentials, including Akkermansia muciniphila, Citrobacter spp. (Citrobacter freundii and Citrobacter werkmanii), Phascolarctobacterium spp., Yersinia spp. (Yersinia frederiksenii and Yersinia aleksiciae), Enterobacter spp. (Enterobacter cloacae and Enterobacter kobei) and Flavobacterium spp. Based on functional neuroimaging, BD-related neuroactive microbes and metabolites were discovered as potential markers associated with BD-typical features of functional connectivity of brain networks, hinting at aberrant cognitive function, emotion regulation, and interoception. Our study combines gut microbiota and neuroactive metabolites with brain functional connectivity, thereby revealing potential signalling pathways from the microbiota to the gut and the brain, which may have a role in the pathophysiology of BD.

Quantifying dynamic facial expressions under naturalistic conditions

Facial affect is expressed dynamically – a giggle, grimace, or an agitated frown. However, the characterisation of human affect has relied almost exclusively on static images. This approach cannot capture the nuances of human communication or support the naturalistic assessment of affective disorders. Using the latest in machine vision and systems modelling, we studied dynamic facial expressions of people viewing emotionally salient film clips. We found that the apparent complexity of dynamic facial expressions can be captured by a small number of simple spatiotemporal states – composites of distinct facial actions, each expressed with a unique spectral fingerprint. Sequential expression of these states is common across individuals viewing the same film stimuli but varies in those with the melancholic subtype of major depressive disorder. This approach provides a platform for translational research, capturing dynamic facial expressions under naturalistic conditions and enabling new quantitative tools for the study of affective disorders and related mental illnesses.

Development of Thalamocortical Structural Connectivity in Typically Developing and Psychosis Spectrum Youths

BACKGROUND

Thalamocortical white matter connectivity is disrupted in psychosis and is hypothesized to play a role in its etiology and associated cognitive impairment. Attenuated cognitive symptoms often begin in adolescence, during a critical phase of white matter and cognitive development. However, little is known about the development of thalamocortical white matter connectivity and its association with cognition.

METHODS

This study characterized effects of age, sex, psychosis symptomatology, and cognition in thalamocortical networks in a large sample of youths (N = 1144, ages 8-22 years, 46% male) from the Philadelphia Neurodevelopmental Cohort, which included 316 typically developing youths, 330 youths on the psychosis spectrum, and 498 youths with other psychopathology. Probabilistic tractography was used to quantify percent total connectivity between the thalamus and six cortical regions and assess microstructural properties (i.e., fractional anisotropy) of thalamocortical white matter tracts.

RESULTS

Overall, percent total connectivity of the thalamus was weakly associated with age and was not associated with psychopathology or cognition. In contrast, fractional anisotropy of all thalamocortical tracts increased significantly with age, was generally higher in males than females, and was lowest in youths on the psychosis spectrum. Fractional anisotropy of tracts linking the thalamus to prefrontal and posterior parietal cortices was related to better cognitive function across subjects.

CONCLUSIONS

By characterizing the pattern of typical development and alterations in those at risk for psychotic disorders, this study provides a foundation for further conceptualization of thalamocortical white matter microstructure as a marker of neurodevelopment supporting cognition and an important risk marker for psychosis.

Pretreatment Alterations and Acute Medication Treatment Effects on Brain Task-Related Functional Connectivity in Youth With Bipolar Disorder: A Neuroimaging Randomized Clinical Trial

OBJECTIVE

Disruptions in cognition are a clinically significant feature of bipolar disorder (BD). The effects of different treatments on these deficits and the brain systems that support them remain to be established.

METHOD

A continuous performance test was administered to 55 healthy controls and 71 acutely ill youths with mixed/manic BD to assess vigilance and working memory during task-based functional magnetic resonance imaging studies. Patients, who were untreated for at least 7 days at baseline, and controls were scanned at pretreatment baseline and at weeks 1 and 6. After baseline testing, patients (n = 71) were randomly assigned to 6-week double-blind treatment with lithium (n = 26; 1.0-1.2 mEq/L) or quetiapine (n = 45; 400-600 mg). Weighted seed-based connectivity (wSBC) was used to assess regional brain interactions during the attention task compared with the control condition.

RESULTS

At baseline, youths with BD showed reduced connectivity between bilateral anterior cingulate cortex and both left ventral lateral prefrontal cortex and left insula and increased connectivity between left ventral lateral prefrontal cortex and left temporal pole, left orbital frontal cortex and right postcentral gyrus, and right amygdala and right occipital pole compared with controls. At 1-week follow-up, quetiapine, but not lithium, treatment led to a significant shift of connectivity patterns toward those of the controls. At week 6, compared with baseline, there was no difference between treatment conditions, at which time both patient groups showed significant normalization of brain connectivity toward that of controls.

CONCLUSION

Functional alterations in several brain regions associated with cognitive processing and the integration of cognitive and affective processing were demonstrated in untreated youths with BD before treatment. Treatment reduced several of these alterations, with significant effects at week 1 only in the quetiapine treatment group. Normalization of functional connectivity might represent a promising biomarker for early target engagement in youth with BD.

CLINICAL TRIAL REGISTRATION INFORMATION

Multimodal Neuroimaging of Treatment Effects in Adolescent Mania; https://clinicaltrials.gov/; NCT00893581.

Normalization of impaired emotion inhibition in bipolar disorder mediated by cholinergic neurotransmission in the cingulate cortex

The muscarinic-cholinergic system is involved in the pathophysiology of bipolar disorder (BD), and contributes to attention and the top-down and bottom-up cognitive and affective mechanisms of emotional processing, functionally altered in BD. Emotion processing can be assessed by the ability to inhibit a response when the content of the image is emotional. Impaired regulatory capacity of cholinergic neurotransmission conferred by reduced M₂-autoreceptor availability is hypothesized to play a role in elevated salience of negative emotional distractors in euthymic BD relative to individuals with no history of mood instability. Thirty-three euthymic BD type-I (DSM-V-TR) and 50 psychiatrically-healthy controls underwent functional magnetic resonance imaging (fMRI) and an emotion-inhibition paradigm before and after intravenous cholinergic challenge using the acetylcholinesterase inhibitor, physostigmine (1 mg), or placebo. Mood, accuracy, and reaction time on either recognizing or inhibiting a response associated with an image involving emotion and regional functional activation were examined for effects of cholinergic challenge physostigmine relative to placebo, prioritizing any interaction with the diagnostic group. Analyses revealed that (1) at baseline, impaired behavioral performance was associated with lower activation in the anterior cingulate cortex in BD relative to controls during emotion processing; (2) physostigmine (vs. placebo) affected behavioral performance during the inhibition of negative emotions, without altering mood, and increased activation in the posterior cingulate cortex in BD (vs. controls); (3) In BD, lower accuracy observed during emotion inhibition of negative emotions was remediated by physostigmine and was associated with cingulate cortex overactivation. Our findings implicate abnormal regulation of cholinergic neurotransmission in the cingulate cortices in BD, which may mediate exaggerated emotional salience processing, a core feature of BD.

Altered effective connectivity among core brain networks in patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is increasingly being regarded as a dysconnection syndrome. Functional integration among the three core brain networks - executive control network (ECN), salience network (SN), and default mode network (DMN) - is abnormal in patients with BD; however, the causal relationship among the three networks in BD is largely unknown. It is also unclear whether patients with BD in different mood states show distinct effective connectivity patterns during rest.

METHODS

Resting-state fMRI data were collected from 65 patients with BD and 85 healthy controls. Spectral dynamic causal modeling was applied to investigate the effective connectivity difference of the three brain networks between all patients with BD and healthy controls and between patients who were in euthymic mood state (euthymic BD) and depressed mood state (depressed BD).

RESULTS

Compared with healthy controls, all patients with BD showed altered effective connectivity within and between the ECN and SN and from these two networks to the DMN. Compared with patients with depressed BD, patients with euthymic BD showed increased excitatory effects within the ECN and decreased inhibitory effects from the SN to the ECN and DMN.

CONCLUSION

These results further confirmed that patients with BD show abnormal functional integration within and among the three core brain networks, and exhibit similar and different effective connectivity patterns in different mood states. Abnormal effective connectivity has the potential to be a critical index for diagnosing BD and differentiating between BD patients with different mood states.

A graph theory-based whole brain approach to assess mood state differences in adolescents and young adults with bipolar disorder

OBJECTIVES

Identifying hubs of brain dysfunction in adolescents and young adults with Bipolar I Disorder (BD_AYA ) could provide targets for early detection, prevention, and treatment. Previous neuroimaging studies across mood states of BD_AYA are scarce and often examined limited brain regions potentially prohibiting detection of other important regions. We used a data-driven whole-brain Intrinsic Connectivity Distribution (ICD) approach to investigate dysconnectivity hubs across mood states in BD_AYA .

METHODS

Functional magnetic resonance imaging whole-brain ICD data were investigated for differences across four groups: BD_AYA -depressed (n = 22), BD_AYA -euthymic (n = 45), BD_AYA -elevated (n = 24), and healthy controls (HC, n = 111). Clusters of ICD differences were assessed for regional dysconnectivity and mood symptom relationships. Analyses were also performed for BD_AYA overall (vs. HC) ICD differences persisting across mood states.

RESULTS

ICD was higher in the BD_AYA- depressed group than other groups in bilateral ventral/rostral/dorsal prefrontal cortex (PFC) and right lenticular nucleus (LN) (p_corrected  <0.05). In BD_AYA -depressed, functional connectivity (FC) was increased between these regions with their contralateral homologues and PFC-medial temporal FC was more negative (p < 0.005). PFC-related findings correlated with depression scores (p < 0.05). The overall BD_AYA group showed ICD increases in more ventral left PFC and right cerebellum, present across euthymia and acute mood states.

CONCLUSIONS

This ICD approach supports a PFC hub of inter- and intra-hemispheric frontotemporal dysconnectivity in BD_AYA with potential trait features and disturbances of higher magnitude during depression. Hubs were also revealed in LN and cerebellum, less common foci of BD research. The hubs are potential targets for early interventions to detect, prevent, and treat BD.

Longitudinal Changes in Structural Connectivity in Young People at High Genetic Risk for Bipolar Disorder

OBJECTIVE

Recent studies of patients with bipolar disorder or at high genetic risk reveal structural dysconnections among key brain networks supporting cognitive and affective processes. Understanding the longitudinal trajectories of these networks across the peak age range of bipolar disorder onset could inform mechanisms of illness onset or resilience.

METHODS

Longitudinal diffusion-weighted MRI and phenotypic data were acquired at baseline and after 2 years in 183 individuals ages 12-30 years in two cohorts: 97 unaffected individuals with a first-degree relative with bipolar disorder (the high-risk group) and 86 individuals with no family history of mental illness (the control group). Whole-brain structural networks were derived using tractography, and longitudinal changes in these networks were studied using network-based statistics and mixed linear models.

RESULTS

Both groups showed widespread longitudinal changes, comprising both increases and decreases in structural connectivity, consistent with a shared neurodevelopmental process. On top of these shared changes, high-risk participants showed weakening of connectivity in a network encompassing the left inferior and middle frontal areas, left striatal and thalamic structures, the left fusiform, and right parietal and occipital regions. Connections among these regions strengthened in the control group, whereas they weakened in the high-risk group, shifting toward a cohort with established bipolar disorder. There was marginal evidence for even greater network weakening in those who had their first manic or hypomanic episode before follow-up.

CONCLUSIONS

Neurodevelopment from adolescence into early adulthood is associated with a substantial reorganization of structural brain networks. Differences in these maturational processes occur in a multisystem network in individuals at high genetic risk of bipolar disorder. This may represent a novel candidate to understand resilience and predict conversion to bipolar disorder.

Prefrontal modulation of frustration-related physiology in preschool children ranging from low to severe irritability

Limbic-prefrontal connectivity during negative emotional challenges underpins a wide range of psychiatric disorders, yet the early development of this system is largely unknown due to difficulties imaging young children. Functional Near-Infrared Spectroscopy (fNIRS) has advanced an understanding of early emotion-related prefrontal activation and psychopathology, but cannot detect activation below the outer cortex. Galvanic skin response (GSR) is a sensitive index of autonomic arousal strongly influenced by numerous limbic structures. We recorded simultaneous lateral prefrontal cortex (lPFC) activation via fNIRS and GSR in 73 3- to 5-year-old children, who ranged from low to severe levels of irritability, during a frustration task. The goal of the study was to test how frustration-related PFC activation modulated psychophysiology in preschool children, and whether associations were moderated by irritability severity. Results showed lPFC activation significantly increased, and GSR levels significantly decreased, as children moved from frustration to rest, such that preschoolers with the highest activation had the steepest recovery. Further, this relation was moderated by irritability such that children with severe irritability showed no association between lPFC activation and GSR. Results suggest functional connections between prefrontal and autonomic nervous systems are in place early in life, with evidence of lPFC down-regulation of frustration-based stress that is altered in early psychopathology. Combining fNIRS and GSR may be a promising novel approach for inferring limbic-PFC processes that drive early emotion regulation and psychopathology.

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Low to high irritable preschoolers tolerated simultaneous fNIRS and GSR recording.

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Frustration-related lPFC activation predicted steeper GSR recovery.

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Irritability moderated the association between lPFC activation and GSR recovery.

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Preschoolers with high irritability showed no lPFC-GSR association.

Altered task-modulated functional connectivity during emotional face processing in euthymic bipolar patients: A whole-brain psychophysiological interaction study

BACKGROUND

Patients with bipolar disorder (BD) show deficits of facial emotion processing even in the euthymic phase. However, the large-scale functional brain network mechanism underlying the emotional deficit of BD remains unclear. Specifically, it is of importance to understand how the task-modulated functional connectivity (FC) was alternated over distributed brain networks in BD.

METHODS

In this study, we analyzed functional MRI data of a face-matching task from 29 euthymic BD patients and 29 healthy controls (HC), and performed whole-brain psychophysiological interaction (PPI) analysis to obtain task-modulated FC. Abnormal FC patterns were identified through support vector machine-based classification. The topological organization of task-modulated FC networks was estimated by the graph theoretical analysis and compared between BD and HC.

RESULTS

BD exhibited widely distributed aberrant task-modulated FC patterns not only in core neurocognitive intrinsic brain networks (the fronto-parietal, cingulo-opercular, and default mode networks), but also in the cerebellum and primary processing networks (sensorimotor and visual). Furthermore, the local efficiency of the frontal-parietal network was significantly increased in BD.

LIMITATIONS

The modest sample size. Only face pictures with negative emotion were used. Only unidirectional task-modulated FC was investigated.

CONCLUSIONS

BD patients showed a widely distributed aberrant task-modulated FC pattern. Particularly, the fronto-parietal network, as one of the core neurocognitive intrinsic brain networks, was the primary network that demonstrated changes of both FC strength and local efficiency in BD. These findings on the task-modulated FC between these intrinsic brain networks might be considered an endophenotype of the BD condition persistent in the euthymic state.

Modular-Level Functional Connectome Alterations in Individuals With Hallucinations Across the Psychosis Continuum

Functional connectome alterations, including modular network organization, have been related to the experience of hallucinations. It remains to be determined whether individuals with hallucinations across the psychosis continuum exhibit similar alterations in modular brain network organization. This study assessed functional connectivity matrices of 465 individuals with and without hallucinations, including patients with schizophrenia and bipolar disorder, nonclinical individuals with hallucinations, and healthy controls. Modular brain network organization was examined at different scales of network resolution, including (1) global modularity measured as Qmax and Normalised Mutual Information (NMI) scores, and (2) within- and between-module connectivity. Global modular organization was not significantly altered across groups. However, alterations in within- and between-module connectivity were observed for higher-order cognitive (e.g., central-executive salience, memory, default mode), and sensory modules in patients with schizophrenia and nonclinical individuals with hallucinations relative to controls. Dissimilar patterns of altered within- and between-module connectivity were found bipolar disorder patients with hallucinations relative to controls, including the visual, default mode, and memory network, while connectivity patterns between visual, salience, and cognitive control modules were unaltered. Bipolar disorder patients without hallucinations did not show significant alterations relative to controls. This study provides evidence for alterations in the modular organization of the functional connectome in individuals prone to hallucinations, with schizophrenia patients and nonclinical individuals showing similar alterations in sensory and higher-order cognitive modules. Other higher-order cognitive modules were found to relate to hallucinations in bipolar disorder patients, suggesting differential neural mechanisms may underlie hallucinations across the psychosis continuum.

Compromised mammillary body connectivity and psychotic symptoms in mice with di- and mesencephalic ablation of ST8SIA2

Altered long-range connectivity is a common finding across neurodevelopmental psychiatric disorders, but causes and consequences are not well understood. Genetic variation in ST8SIA2 has been associated with schizophrenia, autism, and bipolar disorder, and St8sia2^-/- mice show a number of related neurodevelopmental and behavioral phenotypes. In the present study, we use conditional knockout (cKO) to dissect neurodevelopmental defects and behavioral consequences of St8sia2 deficiency in cortical interneurons, their cortical environment, or in the di- and mesencephalon. Neither separate nor combined cortical and diencephalic ablation of St8sia2 caused the disturbed thalamus-cortex connectivity observed in St8sia2^-/- mice. However, cortical ablation reproduced hypoplasia of corpus callosum and fornix and mice with di- and mesencephalic ablation displayed smaller mammillary bodies with a prominent loss of parvalbumin-positive projection neurons and size reductions of the mammillothalamic tract. In addition, the mammillotegmental tract and the mammillary peduncle, forming the reciprocal connections between mammillary bodies and Gudden's tegmental nuclei, as well as the size of Gudden's ventral tegmental nucleus were affected. Only mice with these mammillary deficits displayed enhanced MK-801-induced locomotor activity, exacerbated impairment of prepulse inhibition in response to apomorphine, and hypoanxiety in the elevated plus maze. We therefore propose that compromised mammillary body connectivity, independent from hippocampal input, leads to these psychotic-like responses of St8sia2-deficient mice.

Altered striatal functional connectivity and structural dysconnectivity in individuals with bipolar disorder: A resting state magnetic resonance imaging study

OBJECTIVE

Bipolar disorder (BD) is a mood swing illness characterized by episodes ranging from depressive lows to manic highs. Although the specific origin of BD is unknown, genetics, environment, and changes in brain structure and chemistry may all have a role. Through magnetic resonance imaging (MRI) evaluations, this study looked into functional abnormalities involving the striatum between BD group and healthy controls (HC), compared the whole-brain gray matter (GM) morphological patterns between the groups and see whether functional connectivity has its underlying structural basis.

MATERIALS AND METHODS

We applied sliding windows to functional magnetic resonance imaging (fMRI) data from 49 BD patients and 44 HCs to generate temporal correlations maps to determine strength and variability of the striatum-to-whole-brain-network functional connectivity (FC) in each window whilst also employing voxel-based morphometry (VBM) to high-resolution structural MRI data to uncover structural differences between the groups.

RESULTS

Our analyses revealed increased striatal connectivity in three consecutive windows 69, 70, and 71 (180, 182, and 184 s) in individuals with BD (p < 0.05; Bonferroni corrected) in fMRI images. Moreover, the VBM findings of structural images showed gray matter (GM) deficits in the left precentral gyrus and middle frontal gyrus of the BD patients (p = 0.001, uncorrected) when compared to HCs. Variability of striatal connectivity did not reveal significant differences between the groups.

CONCLUSION

These findings revealed that BD was associated with a weakening of the precentral gyrus and middle frontal gyrus, also implying that bipolar illness may be linked to striatal functional brain alterations.

No group differences in Traditional Economics Measures of loss aversion and framing effects in bipolar I disorder

Bipolar disorder (BD) is associated with impaired decision making, yet few studies have adopted paradigms from behavioral economics to decompose which, if any, aspects of decision making may be impacted. This may be particularly relevant for decision-making processes relevant to known difficulties with emotive dysfunction and corresponding reward dysregulation in BD. Participants with bipolar I disorder (BD; n = 44) and non-psychiatric healthy controls (CTL; n = 28) completed three well-validated behavioral economics decision making tasks via a remote-based survey, including loss aversion and framing effects, that examined sensitivity to probabilities and potential gains and losses in monetary and non-monetary domains. Consistent with past work, we found evidence of moderate loss aversion and framing effects across all participants. No group differences were found in any of the measures of loss aversion or framing effects. We report no group differences between bipolar and non-psychiatric groups with respect to loss aversion and framing effects using a remote-based survey approach. These results provide a framework future studies to explore similar tasks in clinical populations and suggest the context and degree to which decision making is altered in BD may be rooted in a more complex cognitive mechanism that warrants future research.

Shaping the Trans-Scale Properties of Schizophrenia via Cerebral Alterations on Magnetic Resonance Imaging and Single-Nucleotide Polymorphisms of Coding and Non-Coding Regions

Schizophrenia is a complex mental illness with genetic heterogeneity, which is often accompanied by alterations in brain structure and function. The neurobiological mechanism of schizophrenia associated with heredity remains unknown. Recently, the development of trans-scale and multi-omics methods that integrate gene and imaging information sheds new light on the nature of schizophrenia. In this article, we summarized the results of brain structural and functional changes related to the specific single-nucleotide polymorphisms (SNPs) in the past decade, and the SNPs were divided into non-coding regions and coding regions, respectively. It is hoped that the relationship between SNPs and cerebral alterations can be displayed more clearly and intuitively, so as to provide fresh approaches for the discovery of potential biomarkers and the development of clinical accurate individualized treatment decision-making.

Anterior Cingulate Cortex Ablation Disrupts Affective Vigor and Vigilance

Despite many observations of anterior cingulate cortex (ACC) activity related to cognition and affect in humans and nonhuman animals, little is known about the causal role of the ACC in psychological processes. Here, we investigate the causal role of the ACC in affective responding to threat in rhesus monkeys (Macaca mulatta), a species with an ACC largely homologous to humans in structure and connectivity. Male adult monkeys received bilateral ibotenate axon-sparing lesions to the ACC (sulcus and gyrus of areas 24, 32, and 25) and were tested in two classic tasks of monkey threat processing: the human intruder and object responsiveness tasks. Monkeys with ACC lesions did not significantly differ from controls in their overall mean reactivity toward threatening or novel stimuli. However, while control monkeys maintained their reactivity across test days, monkeys with ACC lesions reduced their reactivity toward stimuli as days advanced. Critically, this attenuated reactivity was found even when the stimuli presented each day were novel, suggesting that ACC lesions did not simply cause accelerated adaptation to stimuli as they became less novel over repeated presentations. Rather, these results imply that the primate ACC is necessary for maintaining appropriate affective responses toward potentially harmful and/or novel stimuli. These findings therefore have implications for mood disorders in which responding to threat and novelty is disrupted.SIGNIFICANCE STATEMENT Decades of research in humans and nonhuman animals have investigated the role of the anterior cingulate cortex in a huge number and variety of psychological processes spanning cognition and affect, as well as in psychological and neurologic diseases. The structure is broadly implicated in psychological processes and mental and neurologic health, yet its causal role in these processes has largely gone untested, particularly in primates. Here we demonstrate that when anterior cingulate cortex is completely eliminated, rhesus monkeys are initially responsive to threats, but these responses attenuate rather than persist, resembling a pattern of behavior commonly seen in patients diagnosed with mood disorders.

Exploring Signatures of Neurodegeneration in Early-Onset Older-Age Bipolar Disorder and Behavioral Variant Frontotemporal Dementia

Introduction: Older-age bipolar disorder (OABD) may involve neurocognitive decline and behavioral disturbances that could share features with the behavioral variant of frontotemporal dementia (bvFTD), making the differential diagnosis difficult in cases of suspected dementia.

Objective: To compare the neuropsychological profile, brain morphometry, and structural connectivity patterns between patients diagnosed with bvFTD, patients classified as OABD with an early onset of the disease (EO-OABD), and healthy controls (HC).

Methods: bvFTD patients (n = 25, age: 66 ± 7, female: 64%, disease duration: 6 ± 4 years), EO-OABD patients (n = 17, age: 65 ± 9, female: 71%, disease duration: 38 ± 8 years), and HC (n = 28, age: 62 ± 7, female: 64%) were evaluated through neuropsychological tests concerning attention, memory, executive function, praxis, and language. Brain morphometry was analyzed through surface-based morphometry (SBM), while structural brain connectivity was assessed through diffusion tensor imaging (DTI).

Results: Both bvFTD and EO-OABD patients showed lower performance in neuropsychological tests of attention, verbal fluency, working memory, verbal memory, and praxis than HC. Comparisons between EO-OABD and bvFTD showed differences limited to cognitive flexibility delayed recall and intrusion errors in the memory test. SBM analysis demonstrated that several frontal, temporal, and parietal regions were altered in both bvFTD and EO-OABD compared to HC. In contrast, comparisons between bvFTD and EO-OABD evidenced differences exclusively in the right temporal pole and the left entorhinal cortex. DTI analysis showed alterations in association and projection fibers in both EO-OABD and bvFTD patients compared to HC. Commissural fibers were found to be particularly affected in EO-OABD. The middle cerebellar peduncle and the pontine crossing tract were exclusively altered in bvFTD. There were no significant differences in DTI analysis between EO-OABD and bvFTD.

Discussion: EO-OABD and bvFTD may share an overlap in cognitive, brain morphometry, and structural connectivity profiles that could reflect common underlying mechanisms, even though the etiology of each disease can be different and multifactorial.

Networks underpinning emotion: A systematic review and synthesis of functional and effective connectivity

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We reviewed 33 studies of functional connectivity of emotion in healthy participants.

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Our results challenge a hierarchical model of emotion processing.

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Causal connectivity analyze identify dynamic modulatory relationships between regions.

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We derive a quality tool to make recommendations addressing variability in study design.

Existing models of emotion processing are based almost exclusively on brain activation data, yet make assumptions about network connectivity. There is a need to integrate connectivity findings into these models.

We systematically reviewed all studies of functional and effective connectivity employing tasks to investigate negative emotion processing and regulation in healthy participants. Thirty-three studies met inclusion criteria. A quality assessment tool was derived from prominent neuroimaging papers. The evidence supports existing models, with primarily limbic regions for salience and identification, and frontal areas important for emotion regulation. There was mixed support for the assumption that regulatory influences on limbic and sensory areas come predominantly from prefrontal areas. Rather, studies quantifying effective connectivity reveal context-dependent dynamic modulatory relationships between occipital, subcortical, and frontal regions, arguing against purely top-down regulatory theoretical models. Our quality assessment tool found considerable variability in study design and tasks employed.

The findings support and extend those of previous syntheses focused on activation studies, and provide evidence for a more nuanced view of connectivity in networks of human emotion processing and regulation.

Identifying subtypes of bipolar disorder based on clinical and neurobiological characteristics

The ability to classify patients with bipolar disorder (BD) is restricted by their heterogeneity, which limits the understanding of their neuropathology. Therefore, we aimed to investigate clinically discernible and neurobiologically distinguishable BD subtypes. T1-weighted and resting-state functional magnetic resonance images of 112 patients with BD were obtained, and patients were segregated according to diagnostic subtype (i.e., types I and II) and clinical patterns, including the number of episodes and hospitalizations and history of suicide and psychosis. For each clinical pattern, fewer and more occurrences subgroups and types I and II were classified through nested cross-validation for robust performance, with minimum redundancy and maximum relevance, in feature selection. To assess the proportion of variance in cognitive performance explained by the neurobiological markers, multiple linear regression between verbal memory and the selected features was conducted. Satisfactory performance (mean accuracy, 73.60%) in classifying patients with a high or low number of episodes was attained through functional connectivity, mostly from default-mode and motor networks. Moreover, these neurobiological markers explained 62% of the variance in verbal memory. The number of episodes is a potentially critical aspect of the neuropathology of BD. Neurobiological markers can help identify BD neuroprogression.