Connectomic markers of disease expression, genetic risk and resilience in bipolar disorder

Brain Markers of Resilience to Psychosis in High-Risk Individuals: A Systematic Review and Label-Based Meta-Analysis of Multimodal MRI Studies

Background/Objectives: Most individuals who have a familial or clinical risk of developing psychosis remain free from psychopathology. Identifying neural markers of resilience in these at-risk individuals may help clarify underlying mechanisms and yield novel targets for early intervention. However, in contrast to studies on risk biomarkers, studies on neural markers of resilience to psychosis are scarce. The current study aimed to identify potential brain markers of resilience to psychosis. Methods: A systematic review of the literature yielded a total of 43 MRI studies that reported resilience-associated brain changes in individuals with an elevated risk for psychosis. Label-based meta-analysis was used to synthesize findings across MRI modalities. Results: Resilience-associated brain changes were significantly overreported in the default mode and language network, and among highly connected and central brain regions. Conclusions: These findings suggest that the DMN and language-associated areas and central brain hubs may be hotspots for resilience-associated brain changes. These neural systems are thus of key interest as targets of inquiry and, possibly, intervention in at-risk populations.

Inter-network Effective Connectivity During An Emotional Working Memory Task in Two Independent Samples of Young Adults

BACKGROUND

Effective connectivity (EC) analysis provides valuable insights into the directionality of neural interactions, which are crucial for understanding the mechanisms underlying cognitive and emotional regulation in depressive and anxiety disorders. In this study, we examined EC within key neural networks during working memory (WM) and emotional regulation (ER) tasks in young adults, both healthy individuals and those seeking help from mental health professionals for emotional distress.

METHODS

Dynamic causal modeling was used to analyze EC in 2 independent samples (n = 97 and n = 94). Participants performed an emotional n-back task to assess EC across the central executive network (CEN), default mode network (DMN), salience network (SN), and face processing network. Group-level parametric empirical Bayes analyses were conducted to examine EC patterns, with subanalyses comparing individuals with and without depression and anxiety.

RESULTS

Consistent patterns of positive (posterior probability > .95) DMN→CEN and DMN→SN EC were observed in both samples, predominantly in low and high WM conditions without ER. However, individuals without depressive or anxiety disorders exhibited a significantly greater number of preserved connections that were replicated across both samples.

CONCLUSIONS

This study highlights the different patterns of DMN→CEN EC in conditions with high and low WM loads with and without ER, suggesting that in higher WM loads with ER, the integration of the DMN with the CEN is reduced to facilitate successful cognitive task performance. The findings also suggest that DMN→CEN and DMN→SN EC are significantly reduced in depressive and anxiety disorders, highlighting this pattern of reduced EC as a potential neural marker of these disorders.

Causal mechanisms of quadruple networks in pediatric bipolar disorder

BACKGROUND

Pediatric bipolar disorder (PBD) is characterized by abnormal functional connectivity among distributed brain regions. Increasing evidence suggests a role for the limbic network (LN) and the triple network model in the pathophysiology of bipolar disorder (BD). However, the specific relationship between the LN and the triple network in PBD remains unclear. This study aimed to investigate the aberrant causal connections among these four core networks in PBD.

METHOD

Resting-state functional MRI scans from 92 PBD patients and 40 healthy controls (HCs) were analyzed. Dynamic Causal Modeling (DCM) was employed to assess effective connectivity (EC) among the four core networks. Parametric empirical Bayes (PEB) analysis was conducted to identify ECs associated with group differences, as well as depression and mania severity. Leave-one-out cross-validation (LOOCV) was used to test predictive accuracy.

RESULT

Compared to HCs, PBD patients exhibited primarily excitatory bottom-up connections from the LN to the salience network (SN) and bidirectional excitatory connections between the default mode network (DMN) and SN. In PBD, top-down connectivity from the triple network to the LN was excitatory in individuals with higher depression severity but inhibitory in those with higher mania severity. LOOCV identified dysconnectivity circuits involving the caudate and hippocampus as being associated with mania and depression severity, respectively.

CONCLUSIONS

Disrupted bottom-up connections from the LN to the triple network distinguish PBD patients from healthy controls, while top-down disruptions from the triple network to LN relate to mood state differences. These findings offer insight into the neural mechanisms of PBD.

Brain signatures of catastrophic events: Emotion, salience, and cognitive control

Anticipatory brain activity makes it possible to predict the occurrence of expected situations. However, events such as traffic accidents are statistically unpredictable and can generate catastrophic consequences. This study investigates the brain activity and effective connectivity associated with anticipating and processing such unexpected, unavoidable accidents. We asked 161 participants to ride a motorcycle simulator while recording their electroencephalographic activity. Of these, 90 participants experienced at least one accident while driving. We conducted both within-subjects and between-subjects comparisons. During the pre-accident period, the right inferior parietal lobe (IPL), left anterior cingulate cortex (ACC), and right insula showed higher activity in the accident condition. In the post-accident period, the bilateral orbitofrontal cortex, right IPL, bilateral ACC, and middle and superior frontal gyrus also showed increased activity in the accident condition. We observed greater effective connectivity within the nodes of the limbic network (LN) and between the nodes of the attentional networks in the pre-accident period. In the post-accident period, we also observed greater effective connectivity between networks, from the ventral attention network (VAN) to the somatomotor network and from nodes in the visual network, VAN, and default mode network to nodes in the frontoparietal network, LN, and attentional networks. This suggests that activating salience-related processes and emotional processing allows the anticipation of accidents. Once an accident has occurred, integration and valuation of the new information takes place, and control processes are initiated to adapt behavior to the new demands of the environment.

Longitudinal changes in resting-state functional connectivity as markers of vulnerability or resilience in first-degree relatives of patients with bipolar disorder

BACKGROUND

There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives.

METHODS

In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years.

RESULTS

At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker.

CONCLUSION

Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

Brain-based correlates of antidepressant response to ketamine: a comprehensive systematic review of neuroimaging studies

Ketamine is an effective antidepressant, but there is substantial variability in patient response and the precise mechanism of action is unclear. Neuroimaging can provide predictive and mechanistic insights, but findings are limited by small sample sizes. This systematic review covers neuroimaging studies investigating baseline (pre-treatment) and longitudinal (post-treatment) biomarkers of responses to ketamine. All modalities were included. We performed searches of five electronic databases (from inception to April 26, 2022). 69 studies were included (with 1751 participants). There was substantial methodological heterogeneity and no well replicated biomarker. However, we found convergence across some significant results, particularly in longitudinal biomarkers. Response to ketamine was associated with post-treatment increases in gamma power in frontoparietal regions in electrophysiological studies, post-treatment increases in functional connectivity within the prefrontal cortex, and post-treatment increases in the functional activation of the striatum. Although a well replicated neuroimaging biomarker of ketamine response was not identified, there are biomarkers that warrant further investigation.

Global hippocampus functional connectivity as a predictive neural marker for conversion to future mood disorder in unaffected offspring of bipolar disorder parents

OBJECTIVES

Hippocampus-related functional alteration in genetically at-risk individuals may reflect an endophenotype of a mood disorder. Herein, we performed a prospective study to investigate whether baseline hippocampus functional connectivity (FC) in offspring of patients with bipolar disorder (BD) would predict subsequent conversion to mood disorder.

METHODS

Eighty bipolar offspring and 40 matched normal controls (NC) underwent resting state functional MRI (rsfMRI) scanning on a 3.0 Tesla MR scanner. The offspring were subdivided into asymptomatic offspring (AO) (n = 41) and symptomatic offspring (SO) (n = 39) according to whether they manifested subthreshold mood symptoms. After identifying the different hippocampus FCs between the AO and SO, a logistic regression analysis was conducted to investigate whether the baseline hippocampus FCs predicted a future mood disorder during a 6-year follow-up.

RESULTS

We identified seven baseline para/hippocampus FCs that showed differences between AO and SO, which were entered as predictive features in the logistic regressive model. Of the 80 bipolar offspring entering the analysis, the FCs between left hippocampus and left precuneus, and between right hippocampus and left posterior cingulate, showed a discriminative capacity for predicting future mood disorder (area-under-curve, or AUC=75.76 % and 75.00 % respectively), and for predicting BD onset (AUC=77.46 % and 81.63 %, respectively).

CONCLUSIONS

The present findings revealed high predictive utility of the hippocampus resting state FCs for future mood disorder and BD onset in individuals at familial risk. These neural markers can potentially improve early detection of individuals carrying particularly high risk for future mood disorder.

Assessment of the validity and feasibility of a novel virtual reality test of emotion regulation in patients with bipolar disorder and their unaffected relatives

BACKGROUND

Emotion dysregulation has been suggested as an endophenotype of bipolar disorder (BD). Neuroimaging studies show aberrant neural activity during emotion regulation in remitted patients with BD and their unaffected first-degree relatives (UR) compared to healthy controls (HC). However, behavioural studies produce conflicting - generally negative findings - possibly due to limited sensitivity and ecological validity of current behavioural paradigms.

METHODS

This study aimed to explore emotion regulation in BD (n = 30) and UR (n = 26) relative to HC (n = 47) by using a novel emotion regulation task in virtual reality (VR). Participants were instructed to either react naturally to, or dampen, their emotional response to highly positive or highly negative scenarios presented in first-person 360-degree spherically camera-recorded VR environments. Participants also completed a more traditional computerised task of emotion regulation for comparison purposes.

RESULTS

Patients with BD exhibited difficulties with down-regulating their negative emotions in the VR paradigm compared to HC and UR (ps ≤ .04), whereas UR did not differ from HC (p = .97). There was no emotion regulation difference between groups in the more traditional computerised task (ps ≥ .40).

LIMITATIONS

The small sample size limits generalisability.

CONCLUSIONS

The results suggest trait-related reduced ability to down-regulate negative emotions in BD patients compared to HC in the VR paradigm, but not in the more traditional task of emotion regulation. This may indicate that VR provides a more sensitive measure relative to traditional paradigms. The findings provided no support for aberrant emotional regulation as an endophenotype of BD given the normal emotion regulation performance in UR.

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.

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.

Evidence From Imaging Resilience Genetics for a Protective Mechanism Against Schizophrenia in the Ventral Visual Pathway

INTRODUCTION

Illuminating neurobiological mechanisms underlying the protective effect of recently discovered common genetic resilience variants for schizophrenia is crucial for more effective prevention efforts. Current models implicate adaptive neuroplastic changes in the visual system and their pro-cognitive effects as a schizophrenia resilience mechanism. We investigated whether common genetic resilience variants might affect brain structure in similar neural circuits.

METHOD

Using structural magnetic resonance imaging, we measured the impact of an established schizophrenia polygenic resilience score (PRSResilience) on cortical volume, thickness, and surface area in 101 healthy subjects and in a replication sample of 33 224 healthy subjects (UK Biobank).

FINDING

We observed a significant positive whole-brain correlation between PRSResilience and cortical volume in the right fusiform gyrus (FFG) (r = 0.35; P = .0004). Post-hoc analyses in this cluster revealed an impact of PRSResilience on cortical surface area. The replication sample showed a positive correlation between PRSResilience and global cortical volume and surface area in the left FFG.

CONCLUSION

Our findings represent the first evidence of a neurobiological correlate of a genetic resilience factor for schizophrenia. They support the view that schizophrenia resilience emerges from strengthening neural circuits in the ventral visual pathway and an increased capacity for the disambiguation of social and nonsocial visual information. This may aid psychosocial functioning, ameliorate the detrimental effects of subtle perceptual and cognitive disturbances in at-risk individuals, and facilitate coping with the cognitive and psychosocial consequences of stressors. Our results thus provide a novel link between visual cognition, the vulnerability-stress concept, and schizophrenia resilience models.

Neural correlates of working memory function in euthymic people with bipolar disorder compared to healthy controls: A systematic review and meta-analysis

BACKGROUND

Bipolar disorders (BD) are serious mental health disorders that impacts on cognitive and social functioning. We aimed to systematically review and conduct a meta-analysis of fMRI correlates of working memory in euthymic people with BD compared to healthy participants.

METHOD

Web of Science, Embase and PubMed databases were systematically searched to identify studies which examined the fMRI correlates of working memory function in euthymic people with BD and healthy participants. Relevant demographic, behavioral and functional MRI (fMRI) data was qualitatively and quantitatively assessed, and the quality of the included studies evaluated. Comparable studies which used the same working memory task were included in a meta-analysis using Seed-Based D Mapping software (SDM).

RESULTS

Twenty-four studies were included in this systematic review. Consistent brain fMRI activity differences were found in key brain areas of the working memory network in euthymic people with BD compared to healthy participants including the ventromedial and dorsolateral prefrontal cortices. Cognitive performance was not significantly different between the two groups. Six studies were suitable to be included in the meta-analysis. There was no significant overlap in areas of brain activation after family-wise correction for multiple comparisons.

LIMITATIONS

Heterogeneity of task paradigms, small sample sizes and inherent difficulty in the interpretation of functional brain activity due to variations between studies were all limitations.

CONCLUSION

The differences in working memory related fMRI activity identified by this study between people with BD and healthy participants are consistent with existing literature reporting impaired working memory performance in BD. This was not accompanied by significant differences in cognitive performance in the reviewed studies, likely due to small sample sizes. Further studies are needed to investigate the relationship between differential brain activity and working memory performance in people with BD.

Increased functional interaction within frontoparietal network during working memory task in major depressive disorder

Abnormal fronto-parietal activation has been suggested as a neural underpinning of the working memory (WM) deficits in major depressive disorder (MDD). However, the potential interaction within the frontoparietal network during WM processing in MDD remains unclear. This study aimed to examine the role of abnormal functional interactions within frontoparietal network in the neuropathological mechanisms of WM deficits in MDD. A total of 40 MDD patients and 47 demographic matched healthy controls (HCs) were included. Functional magnetic resonance imaging and behavioral data were collected during numeric n-back tasks. The psychophysiological interaction and dynamic causal modelling methods were applied to investigate the connectivity within the frontoparietal network in MDD during n-back tasks. The psychophysiological interaction analysis revealed that MDD patients showed increased functional connectivity between the right inferior parietal lobule (IPL) and the right dorsolateral prefrontal cortex (dlPFC) compared with HCs during the 2-back task. The dynamic causal modelling analysis revealed that MDD patients had significantly increased forward modulation connectivity from the right IPL to the right dlPFC than HCs during the 2-back task. Partial correlation was used to calculate the relationship between connective parameters and psychological variables in the MDD group, which showed that the effective connectivity from right IPL to right dlPFC was correlated negatively with the sensitivity index d' of WM performances and positively with the depressive severity in MDD group. In conclusion, the abnormal functional and effective connectivity between frontal and parietal regions might contribute to explain the neuropathological mechanism of working memory deficits in major depressive disorder.

Dynamic Causal Modeling Self-Connectivity Findings in the Functional Magnetic Resonance Imaging Neuropsychiatric Literature

Dynamic causal modeling (DCM) is a method for analyzing functional magnetic resonance imaging (fMRI) and other functional neuroimaging data that provides information about directionality of connectivity between brain regions. A review of the neuropsychiatric fMRI DCM literature suggests that there may be a historical trend to under-report self-connectivity (within brain regions) compared to between brain region connectivity findings. These findings are an integral part of the neurologic model represented by DCM and serve an important neurobiological function in regulating excitatory and inhibitory activity between regions. We reviewed the literature on the topic as well as the past 13 years of available neuropsychiatric DCM literature to find an increasing (but still, perhaps, and inadequate) trend in reporting these results. The focus of this review is fMRI as the majority of published DCM studies utilized fMRI and the interpretation of the self-connectivity findings may vary across imaging methodologies. About 25% of articles published between 2007 and 2019 made any mention of self-connectivity findings. We recommend increased attention toward the inclusion and interpretation of self-connectivity findings in DCM analyses in the neuropsychiatric literature, particularly in forthcoming effective connectivity studies of substance use disorders.

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.

Anterior cingulate cortex neuro-metabolic changes underlying lithium-induced euthymia in bipolar depression: A longitudinal 1H-MRS study

The diagnosis and treatment of bipolar depression (BDep) poses complex clinical challenges for psychiatry. Proton magnetic resonance spectroscopy (¹H-MRS) is a useful imaging tool for investigating in vivo levels of brain neuro-metabolites, critical to understanding the process of mood dysregulation in Bipolar Disorder. Few studies have evaluated longitudinal clinical outcomes in BDep associated with ¹H-MRS metabolic changes. This study aimed to longitudinally assess brain ¹H-MRS metabolites in the anterior cingulate cortex (ACC) correlated with improvement in depression (from BDep to euthymia) after lithium treatment in BDep patients versus matched healthy controls (HC). Twenty-eight medication-free BDep patients and 28 HC, matched for age and gender, were included in this study. All subjects were submitted to a 3-Tesla brain ¹H-MRS scan in the ACC using a single-voxel (8cm³) PRESS sequence at baseline. At follow-up (6 weeks), 14 BDep patients repeated the exam in euthymia. Patients with current BDep had higher baseline Myo-inositol/Cr (mI/Cr) and Choline/Cr (Cho/Cr) compared to HC. After six weeks, mI/Cr or Cho/Cr levels in subjects that achieved euthymia no longer differed to levels in HC, while high Cho/Cr levels persisted in non-responders . Elevated ACC mI/Cr and Cho/Cr in BDep might indicate increased abnormal membrane phospholipid metabolism and phosphatidylinositol (PI) cycle activity. Return of mI/Cr and Cho/Cr to normal levels after lithium-induced euthymia suggests a critical regulatory effect of lithium targeting the PI cycle involved in mood regulation.

Evaluating endophenotypes for bipolar disorder

BACKGROUND

Phenotypic heterogeneity is a major impediment to the elucidation of the neurobiology and genetics of bipolar disorder. Endophenotype could help in reducing heterogeneity by defining biological traits that are more direct expressions of gene effects. The aim of this review is to examine the recent literature on clinical, epidemiological, neurobiological, and genetic findings and to select and evaluate candidate endophenotypes for bipolar disorder. Evaluating putative endophenotype could be helpful in better understanding the neurobiology of bipolar disorder by improving the definition of bipolar-related phenotypes in genetic studies. In this manner, research on endophenotypes could be useful to improve psychopathological diagnostics in the long-run by dissecting psychiatric macro phenotypes into biologically valid components.

MAIN BODY

The associations among the psychopathological and biological endophenotypes are discussed with respect to specificity, temporal stability, heritability, familiarity, and clinical and biological plausibility. Numerous findings regarding brain function, brain structure, neuropsychology and altered neurochemical pathways in patients with bipolar disorder and their relatives deserve further investigation. Overall, major findings suggest a developmental origin of this disorder as all the candidate endophenotypes that we have been able to select are present both in the early stages of the disorder as well as in subjects at risk.

CONCLUSIONS

Among the stronger candidate endophenotypes, we suggest circadian rhythm instability, dysmodulation of emotion and reward, altered neuroimmune state, attention and executive dysfunctions, anterior cingulate cortex thickness and early white matter abnormalities. In particular, early white matter abnormalities could be the result of a vulnerable brain on which new stressors are added in young adulthood which favours the onset of the disorder. Possible pathways that lead to a vulnerable brain are discussed starting from the data about molecular and imaging endophenotypes of bipolar disorder.

The activity and connectivity of the facial emotion processing neural circuitry in bipolar disorder: a systematic review

BACKGROUND

Facial emotion processing abnormalities may be a trait feature of bipolar disorder (BD). These social cognitive impairments may be due to alterations in the neural processing of facial affective information in visual ("core"), and limbic and prefrontal ("extended") networks, however, the precise neurobiological mechanism(s) underlying these symptoms are unclear.

METHODS

We conducted a systematic review to appraise the literature on the activity and connectivity of the facial emotion processing neural circuitry in BD. Two reviewers undertook a search of the electronic databases PubMed, Scopus and PsycINFO, to identify relevant literature published since inception up until September 2019. Study eligibility criteria included; BD participants, neuroimaging, and facial emotion processing tasks.

RESULTS

Out of an initial yield of 6121 articles, 66 were eligible for inclusion in this review. We identified differences in neural activity and connectivity within and between occipitotemporal, limbic, and prefrontal regions, in response to facial affective stimuli, in BD compared to healthy controls.

LIMITATIONS

The methodologies used across studies varied considerably.

CONCLUSIONS

The findings from this review suggest abnormalities in both the activity and connectivity of facial emotion processing neural circuitry in BD. It is recommended that future research aims to further define the connectivity and spatiotemporal course of neural events within and between occipitotemporal, limbic, and prefrontal regions.

Aberrant cognition in newly diagnosed patients with bipolar disorder and their unaffected relatives

BACKGROUND

Patients with bipolar disorder (BD) experience persistent impairments in both affective and non-affective cognitive function, which is associated with a worse course of illness and poor functional outcomes. Nevertheless, the temporal progression of cognitive dysfunction in BD remains unclear and the identification of objective endophenotypes can inform the aetiology of BD.

METHODS

The present study is a cross-sectional investigation of cognitive baseline data from the longitudinal Bipolar Illness Onset-study. One hundred seventy-two remitted patients newly diagnosed with BD, 52 of their unaffected relatives (UR), and 110 healthy controls (HC) were compared on a large battery of behavioural cognitive tasks tapping into non-affective (i.e. neurocognitive) and affective (i.e. emotion processing and regulation) cognition.

RESULTS

Relative to HCs, patients with BD exhibited global neurocognitive deficits (ps < 0.001), as well as aberrant emotion processing and regulation (ps ⩽ 0.011); including decreased emotional reactivity to positive social scenarios, impaired ability to down-regulate positive emotion, as well as a specific deficit in the ability to recognise surprised facial expressions. Their URs also showed a trend towards difficulties identifying surprised faces (p = 0.075). No other differences in cognitive function were found for URs compared to HCs.

CONCLUSIONS

Neurocognitive deficits and impairments within emotion processing and regulation may be illness-related deficits of BD that present after illness-onset, whereas processing of emotional faces may represent an early risk marker of BD. However, longitudinal studies are needed to examine the association between cognitive impairments and illness progression in BD.

The role of altered brain structural connectivity in resilience, vulnerability, and disease expression to schizophrenia

BACKGROUND

Schizophrenia (SCZ) is a highly heritable disorder associated with brain connectivity changes. Although the mechanism of disease expression and vulnerability of SCZ have been reported by previous studies, the mechanism of resilience to SCZ based on the brain structural connectivity is poorly understood. The goal of the present study was to identify the structural brain connectivity related with the resilience to SCZ, which is defined here as the capacity to avoid or delay the onset of SCZ in unaffected siblings of SCZ probands.

METHOD

We collected diffusion tensor imaging (DTI) data of 49 medication-naive, first-episode SCZ (FE-SCZ) patients, 56 unaffected siblings of SCZ probands (SIB-SCZ), and 90 healthy controls. Then we used graph theoretical approach to calculate the topological properties of the brain structural network, including global, subnetwork, and regional parameters. Finally, we compared the parameters between the three groups, and identified the brain structural network related to the resilience, vulnerability and disease expression to SCZ.

RESULTS

With respect to resilience, only the SIB-SCZ showed significantly increased connectivity in the subnetworks of the left cuneus-precuneus and left posterior cingulate gyrus-precuneus, and in brain areas of right supramarginal gyrus and right inferior temporal gyrus. With respect to vulnerability, both the FE-SCZ and SIB-SCZ had decreased cluster coefficients and local efficiency, and decreased nodal efficiency in the right medial superior frontal gyrus and right medial orbital superior frontal gyrus compared with the healthy controls. With respect to disease expression, only the FE-SCZ group showed decreased or increased global, subnetwork, and nodal connectivity in broader brain regions compared with the healthy controls.

CONCLUSION

Difference in the topological properties of brain structural connectivity not only reflect the underlying mechanism of vulnerability but also that of resilience to schizophrenia. Alteration in the brain structural connectivity associating with resilience and disease expression may contribute to the onset of SCZ.

Initial Evidence for Brain Plasticity Following a Digital Therapeutic Intervention for Depression

Background

Digital therapeutics such as cognitive-emotional training have begun to show promise for the treatment of major depressive disorder. Available clinical trial data suggest that monotherapy with cognitive-emotional training using the Emotional Faces Memory Task is beneficial in reducing depressive symptoms in patients with major depressive disorder. The aim of this study was to investigate whether Emotional Faces Memory Task training for major depressive disorder is associated with changes in brain connectivity and whether changes in connectivity parameters are related to symptomatic improvement.

Methods

Fourteen major depressive disorder patients received Emotional Faces Memory Task training as monotherapy over a six-week period. Patients were scanned at baseline and posttreatment to identify changes in resting-state functional connectivity and effective connectivity during emotional working memory processing.

Results

Compared to baseline, patients showed posttreatment reduced connectivity within resting-state networks involved in self-referential and salience processing and greater integration across the functional connectome at rest. Moreover, we observed a posttreatment increase in the Emotional Faces Memory Task-induced modulation of connectivity between cortical control and limbic brain regions, which was associated with clinical improvement.

Discussion

These findings provide initial evidence that cognitive-emotional training may be associated with changes in short-term plasticity of brain networks implicated in major depressive disorder.

Conclusion

Our findings pave the way for the principled design of large clinical and neuroimaging studies.

The impact of familial risk and early life adversity on emotion and reward processing networks in youth at-risk for bipolar disorder

A recently developed risk calculator for bipolar disorder (BD) accounts for clinical and parental psychopathology. Yet, it is understood that both familial predisposition and early life adversity contribute to the development of BD. How the interplay between these two factors influence emotion and reward processing networks in youth at risk for BD remains unclear. In this exploratory analysis, offspring of BD parents performed emotion and reward processing tasks while undergoing a fMRI scan. Risk calculator score was used to assess risk for developing BD in the next 5 years. Environmental risk was tabulated using the Stressful Life Events Schedule (SLES). Emotion and reward processing networks were investigated for genetic and/or environment interactions. Interaction effects were found between risk calculator scores, negative SLES score and activity in right amygdala and bilateral fusiform gyri during the emotion processing task, as well as activity in the fronto-, striatal, and parietal regions during the reward processing task. Our findings are preliminary; however, they support the unique and interactive contributions of both familial and environmental risk factors on emotion and reward processing within OBP. They also identify potential neural targets to guide development of interventions for youth at greatest risk for psychiatric disorders.

Multiscale Neuroscience of Psychiatric Disorders

The human brain comprises a multiscale network with multiple levels of organization. Neurons with dendritic and axonal connections form the microscale fabric of brain circuitry, and macroscale brain regions and white matter connections form the infrastructure for system-level brain communication and information integration. In this review, we discuss the emerging trend of multiscale neuroscience, the multidisciplinary field that brings together data from these different levels of nervous system organization to form a better understanding of between-scale relationships of brain structure, function, and behavior in health and disease. We provide a broad overview of this developing field and discuss recent findings of exemplary multiscale neuroscience studies that illustrate the importance of studying cross-scale interactions among the genetic, molecular, cellular, and macroscale levels of brain circuitry and connectivity and behavior. We particularly consider a central, overarching goal of these multiscale neuroscience studies of human brain connectivity: to obtain insight into how disease-related alterations at one level of organization may underlie alterations observed at other scales of brain network organization in mental disorders. We conclude by discussing the current limitations, challenges, and future directions of the field.

Resilience as a multimodal dynamic process

AIM

Resilience is rapidly gaining momentum in mental health literature. It provides a new understanding of the highly variable trajectories of mental illness, and has consistently been linked with improved mental health outcomes. The present review aims to clarify the definition of resilience and to discuss new directions for the field.

METHODS

After discussing the definition of resilience, this narrative review synthesizes evidence that identifies the specific protective factors involved in this process. This review also addresses the mechanisms that underlie resilience.

RESULTS

Recent literature has clarified the three core components of resilience, which are the presence of an adversity or specific risk for mental illness; the influence of protective factors that supersede this risk; and finally, a subsequently more positive outcome than expected. Now that these are largely agreed upon, the field should move on to addressing other topics. Resilience is a dynamic process by which individuals utilize protective factors and resources to their benefit. It can vary within one individual across time and circumstance. It can also refer to good functional outcomes in the context of diagnosable illness. While previous research has focused on psychological resilience, it is essential that resilience is conceptualized across modalities.

CONCLUSIONS

The field should move towards the development of a multimodal model of resilience. Researchers should now focus on producing empirical research which clarifies the specific protective factors and mechanisms of the process, aligning with the core concepts of resilience. This growing, more homogeneous evidence base, can then inform new intervention strategies.

Neuroimaging Markers of Risk, Disease Expression, and Resilience to Bipolar Disorder

PURPOSE OF REVIEW

Familial predisposition to bipolar disorder is associated with increased risk of affective morbidity in the first-degree relatives of patients. Nevertheless, a substantial proportion of relatives remain free of psychopathology throughout their lifetime. A series of studies reviewed here were designed to test whether resilience in these high-risk individuals is associated with adaptive brain plasticity.

RECENT FINDINGS

The findings presented here derive from structural and functional magnetic resonance imaging data obtained from patients, their resilient first-degree relatives, and healthy individuals. Patients and relatives showed similar abnormalities in activation and connectivity while performing tasks of interference control and facial affect recognition and in the resting-state connectivity of sensory and motor regions. Resilient relatives manifested unique neuroimaging features that differentiated them from patients and healthy individuals. Specifically, they had larger cerebellar vermis volume, enhanced prefrontal connectivity during task performance, and enhanced functional integration of the default mode network in task-free conditions. Resilience to bipolar disorder is not the reverse of risk but is associated with adaptive brain changes indicative of increased neural reserve. This line of research may open new avenues in preventing and treating bipolar disorder.

Is aberrant affective cognition an endophenotype for affective disorders? - A monozygotic twin study

BACKGROUND

Identification of endophenotypes can improve prevention, detection and development of new treatments. We therefore investigated whether aberrant affective cognition constitutes an endophenotype for affective disorders by being present in monozygotic (MZ) twins with unipolar or bipolar disorder in partial remission (i.e. affected) and their unaffected co-twins (i.e. high-risk) relative to twins with no family history of affective disorder (i.e. low-risk).

METHODS

We conducted an assessor blind cross-sectional study from 2014 to 2017 of MZ twins using Danish population-based registers in recruitment. Twins attended one test session involving neurocognitive testing, clinical ratings and questionnaires. Main outcomes were attention to and recognition of emotional facial expressions, the memory of emotional self-referential words, emotion regulation and coping strategies.

RESULTS

Participants were 103 affected, 44 high-risk and 36 low-risk MZ twins. Groups were demographically well-balanced and showed comparable non-affective cognitive performance. We observed no aberrant affective cognition in affected and high-risk relative to low-risk twins. However, high-risk twins displayed attentional avoidance of emotional faces (ps ⩽ 0.009) and more use of task-oriented coping strategies (p = 0.01) compared with affected twins. In contrast did affected twins show more emotion-oriented coping than high- and low-risk twins (ps ⩽ 0.004).

CONCLUSIONS

Our findings provide no support of aberrant affective cognition as an endophenotype for affective disorders. High-risk twins' attentional avoidance of emotional faces and greater use of task-oriented coping strategies may reflect compensatory mechanisms.

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

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

Cortico-limbic connectivity as a possible biomarker for bipolar disorder: where are we now?

INTRODUCTION

The fronto-limbic network has been suggested as a key circuitry in the pathophysiology and maintenance of bipolar disorder. In the past decade, a disrupted connectivity within prefrontal-limbic structures was identified as a promising candidate biomarker for the disorder. Areas Covered: In this review, the authors examine current literature in terms of the structural, functional and effective connectivity in bipolar disorder, integrating recent findings of imaging genetics and machine learning. This paper profiles the current knowledge and identifies future perspectives to provide reliable and usable neuroimaging biomarkers for bipolar psychopathology in clinical practice. Expert Opinion: The replication and the translation of acquired knowledge into useful and usable tools represents one of the current greatest challenges in biomarker research applied to psychiatry.

Telomere length as a predictor of emotional processing in the brain

Shorter telomere length (TL) has been associated with the development of mood disorders as well as abnormalities in brain morphology. However, so far, no studies have considered the role TL may have on brain function during tasks relevant to mood disorders. In this study, we examine the relationship between TL and functional brain activation and connectivity, while participants (n = 112) perform a functional magnetic resonance imaging (fMRI) facial affect recognition task. Additionally, because variation in TL has a substantial genetic component we calculated polygenic risk scores for TL to test if they predict face‐related functional brain activation. First, our results showed that TL was positively associated with increased activation in the amygdala and cuneus, as well as increased connectivity from posterior regions of the face network to the ventral prefrontal cortex. Second, polygenic risk scores for TL show a positive association with medial prefrontal cortex activation. The data support the view that TL and genetic loading for shorter telomeres, influence the function of brain regions known to be involved in emotional processing.

Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition

Psychiatric illnesses are complex and polygenic. They are associated with widespread alterations in the brain, which are partly influenced by genetic factors. There have been some attempts to relate polygenic risk scores (PRS) - a measure of the overall genetic risk an individual carries for a disorder - to brain structure using univariate methods. However, PRS are likely associated with distributed and covarying effects across the brain. We therefore used multivariate machine learning in this proof-of-principle study to investigate associations between brain structure and PRS for four psychiatric disorders; attention deficit-hyperactivity disorder (ADHD), autism, bipolar disorder and schizophrenia. The sample included 213 individuals comprising patients with depression (69), bipolar disorder (33), and healthy controls (111). The five psychiatric PRSs were calculated based on summary data from the Psychiatric Genomics Consortium. T1-weighted magnetic resonance images were obtained and voxel-based morphometry was implemented in SPM12. Multivariate relevance vector regression was implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo). Across the whole sample, a multivariate pattern of grey matter significantly predicted the PRS for autism (r = 0.20, pFDR = 0.03; MSE = 4.20 × 10-5, pFDR = 0.02). For the schizophrenia PRS, the MSE was significant (MSE = 1.30 × 10-5, pFDR = 0.02) although the correlation was not (r = 0.15, pFDR = 0.06). These results lend support to the hypothesis that polygenic liability for autism and schizophrenia is associated with widespread changes in grey matter concentrations. These associations were seen in individuals not affected by these disorders, indicating that this is not driven by the expression of the disease, but by the genetic risk captured by the PRSs.

An integrated brain-behavior model for working memory

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network.

Fronto-limbic dysconnectivity leads to impaired brain network controllability in young people with bipolar disorder and those at high genetic risk

Recent investigations have used diffusion-weighted imaging to reveal disturbances in the neurocircuitry that underlie cognitive-emotional control in bipolar disorder (BD) and in unaffected siblings or children at high genetic risk (HR). It has been difficult to quantify the mechanism by which structural changes disrupt the superimposed brain dynamics, leading to the emotional lability that is characteristic of BD. Average controllability is a concept from network control theory that extends structural connectivity data to estimate the manner in which local neuronal fluctuations spread from a node or subnetwork to alter the state of the rest of the brain. We used this theory to ask whether structural connectivity deficits previously observed in HR individuals (n = 84, mean age 22.4), patients with BD (n = 38, mean age 23.9), and age- and gender-matched controls (n = 96, mean age 22.6) translate to differences in the ability of brain systems to be manipulated between states. Localized impairments in network controllability were seen in the left parahippocampal, left middle occipital, left superior frontal, right inferior frontal, and right precentral gyri in BD and HR groups. Subjects with BD had distributed deficits in a subnetwork containing the left superior and inferior frontal gyri, postcentral gyrus, and insula (p = 0.004). HR participants had controllability deficits in a right-lateralized subnetwork involving connections between the dorsomedial and ventrolateral prefrontal cortex, the superior temporal pole, putamen, and caudate nucleus (p = 0.008). Between-group controllability differences were attenuated after removal of topological factors by network randomization. Some previously reported differences in network connectivity were not associated with controllability-differences, likely reflecting the contribution of more complex brain network properties. These analyses highlight the potential functional consequences of altered brain networks in BD, and may guide future clinical interventions.

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Control theory estimates how neuronal fluctuations spread from local networks.

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We compare brain controllability in bipolar disorder and their high-risk relatives.

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These groups have impaired controllability in networks supporting cognitive and emotional control.

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Weaker connectivity as well as topological alterations contribute to these changes.

Structural dysconnectivity of key cognitive and emotional hubs in young people at high genetic risk for bipolar disorder

Emerging evidence suggests that psychiatric disorders are associated with disturbances in structural brain networks. Little is known, however, about brain networks in those at high risk (HR) of bipolar disorder (BD), with such disturbances carrying substantial predictive and etiological value. Whole-brain tractography was performed on diffusion-weighted images acquired from 84 unaffected HR individuals with at least one first-degree relative with BD, 38 young patients with BD and 96 matched controls (CNs) with no family history of mental illness. We studied structural connectivity differences between these groups, with a focus on highly connected hubs and networks involving emotional centres. HR participants showed lower structural connectivity in two lateralised sub-networks centred on bilateral inferior frontal gyri and left insular cortex, as well as increased connectivity in a right lateralised limbic sub-network compared with CN subjects. BD was associated with weaker connectivity in a small right-sided sub-network involving connections between fronto-temporal and temporal areas. Although these sub-networks preferentially involved structural hubs, the integrity of the highly connected structural backbone was preserved in both groups. Weaker structural brain networks involving key emotional centres occur in young people at genetic risk of BD and those with established BD. In contrast to other psychiatric disorders such as schizophrenia, the structural core of the brain remains intact, despite the local involvement of network hubs. These results add to our understanding of the neurobiological correlates of BD and provide predictions for outcomes in young people at high genetic risk for BD.

The 5-HTTLPR Polymorphism Affects Network-Based Functional Connectivity in the Visual-Limbic System in Healthy Adults

The serotonin transporter-linked polymorphic region 5-HTTLPR is a key genetic regulator of 5-HTT expression in the human brain where the short allele S has been implicated in emotion dysregulation. However, the neural mechanism underlying the association between this variant and emotion processing is still unclear. Earlier studies suggested an effect of 5-HTTLPR on amygdala activation during emotional face processing. However, this association has been questioned in recent studies employing larger sample sizes and meta-analyses. Here, we examined a sample of 223 healthy subjects with a well-established fMRI emotional face processing task to (1) re-evaluate the association between 5-HTTLPR and amygdala activation, (2) explore potential network-based functional connectivity phenotypes for associations with 5-HTTLPR, and (3) probe the reliability, behavioral significance and potential structural confounds of the identified network phenotype. Our results revealed no significant effect of 5-HTTLPR on amygdala activation (P>0.79). However, the number of S alleles was significantly correlated with functional connectivity of a visual-limbic subnetwork (P_FWE=0.03). The subnetwork cluster included brain regions that are pivotal to emotion regulation such as the hippocampus, orbitofrontal cortex, anterior cingulate gyrus, fusiform gyrus, and subcortex. Notably, individuals with lower subnetwork connectivity had significantly higher emotion suppression scores (P=0.01). Further, the connectivity metrics were test-retest reliable and independent from subnetwork gray matter volume and white matter anisotropy. Our data provide evidence for a functional network-based phenotype linking genetic variation in 5-HTTLPR to emotion regulation, and suggest that further critical evaluations of the association between 5-HTTLPR and amygdala activation are warranted.

Telomere Length and Bipolar Disorder

Variation in telomere length is heritable and is currently considered a promising biomarker of susceptibility for neuropsychiatric disorders, particularly because of its association with memory function and hippocampal morphology. Here, we investigate telomere length in connection to familial risk and disease expression in bipolar disorder (BD). We used quantitative PCRs and a telomere-sequence to single-copy-gene-sequence ratio method to determine telomere length in genomic DNA extracted from buccal smears from 63 patients with BD, 74 first-degree relatives (49 relatives had no lifetime psychopathology and 25 had a non-BD mood disorder), and 80 unrelated healthy individuals. Participants also underwent magnetic resonance imaging to determine hippocampal volumes and cognitive assessment to evaluate episodic memory using the verbal paired associates test. Telomere length was shorter in psychiatrically well relatives (p=0.007) compared with unrelated healthy participants. Telomere length was also shorter in relatives (regardless of psychiatric status; p<0.01) and patients with BD not on lithium (p=0.02) compared with lithium-treated patients with BD. In the entire sample, telomere length was positively associated with left and right hippocampal volume and with delayed recall. This study provides evidence that shortened telomere length is associated with familial risk for BD. Lithium may have neuroprotective properties that require further investigation using prospective designs.

The Role of Intrinsic Brain Functional Connectivity in Vulnerability and Resilience to Bipolar Disorder

OBJECTIVE

Bipolar disorder is a heritable disorder characterized by mood dysregulation associated with brain functional dysconnectivity. Previous research has focused on the detection of risk- and disease-associated dysconnectivity in individuals with bipolar disorder and their first-degree relatives. The present study seeks to identify adaptive brain connectivity features associated with resilience, defined here as avoidance of illness or delayed illness onset in unaffected siblings of patients with bipolar disorder.

METHOD

Graph theoretical methods were used to examine global and regional brain network topology in head-motion-corrected resting-state functional MRI data acquired from 78 patients with bipolar disorder, 64 unaffected siblings, and 41 healthy volunteers.

RESULTS

Global network properties were preserved in patients and their siblings while both groups showed reductions in the cohesiveness of the sensorimotor network. In the patient group, these sensorimotor network abnormalities were coupled with reduced integration of core default mode network regions in the ventromedial cortex and hippocampus. Conversely, integration of the default mode network was increased in the sibling group compared with both the patient group and the healthy volunteer group.

CONCLUSIONS

The authors found that trait-related vulnerability to bipolar disorder was associated with reduced resting-state cohesiveness of the sensorimotor network in patients with bipolar disorder. However, integration of the default mode network emerged as a key feature differentiating disease expression and resilience between the patients and their siblings. This is indicative of the presence of neural mechanisms that may promote resilience, or at least delay illness onset.

Multimodal evaluation of the amygdala's functional connectivity

The amygdala is one of the most extensively studied human brain regions and undisputedly plays a central role in many psychiatric disorders. However, an outstanding question is whether connectivity of amygdala subregions, specifically the centromedial (CM), laterobasal (LB) and superficial (SF) nuclei, are modulated by brain state (i.e., task vs. rest). Here, using a multimodal approach, we directly compared meta-analytic connectivity modeling (MACM) and specific co-activation likelihood estimation (SCALE)-derived estimates of CM, LB and SF task-based co-activation to the functional connectivity of these nuclei as assessed by resting state fmri (rs-fmri). Finally, using a preexisting resting state functional connectivity-derived cortical parcellation, we examined both MACM and rs-fmri amygdala subregion connectivity with 17 large-scale networks, to explicitly address how the amygdala interacts with other large-scale neural networks. Analyses revealed strong differentiation of CM, LB and SF connectivity patterns with other brain regions, both in task-dependent and task-independent contexts. All three regions, however, showed convergent connectivity with the right ventrolateral prefrontal cortex (VLPFC) that was not driven by high base rate levels of activation. Similar patterns of connectivity across rs-fmri and MACM were observed for each subregion, suggesting a similar network architecture of amygdala connectivity with the rest of the brain across tasks and resting state for each subregion, that may be modified in the context of specific task demands. These findings support animal models that posit a parallel model of amygdala functioning, but importantly, also modify this position to suggest integrative processing in the amygdala.

The polygenic risk for bipolar disorder influences brain regional function relating to visual and default state processing of emotional information

Genome-wise association studies have identified a number of common single-nucleotide polymorphisms (SNPs), each of small effect, associated with risk to bipolar disorder (BD). Several risk-conferring SNPs have been individually shown to influence regional brain activation thus linking genetic risk for BD to altered brain function. The current study examined whether the polygenic risk score method, which models the cumulative load of all known risk-conferring SNPs, may be useful in the identification of brain regions whose function may be related to the polygenic architecture of BD. We calculated the individual polygenic risk score for BD (PGR-BD) in forty-one patients with the disorder, twenty-five unaffected first-degree relatives and forty-six unrelated healthy controls using the most recent Psychiatric Genomics Consortium data. Functional magnetic resonance imaging was used to define task-related brain activation patterns in response to facial affect and working memory processing. We found significant effects of the PGR-BD score on task-related activation irrespective of diagnostic group. There was a negative association between the PGR-BD score and activation in the visual association cortex during facial affect processing. In contrast, the PGR-BD score was associated with failure to deactivate the ventromedial prefrontal region of the default mode network during working memory processing. These results are consistent with the threshold-liability model of BD, and demonstrate the usefulness of the PGR-BD score in identifying brain functional alternations associated with vulnerability to BD. Additionally, our findings suggest that the polygenic architecture of BD is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions.

Neurobiology of Risk for Bipolar Disorder

Bipolar disorder (BD) is a chronic mental illness which follows a relapsing and remitting course and requires lifetime treatment. The lack of biological markers for BD is a major difficulty in clinical practice. Exploring multiple endophenotypes to fit in multivariate genetic models for BD is an important element in the process of finding tools to facilitate early diagnosis, early intervention, prevention of new episodes, and follow-up of treatment response in BD. Reviewing of studies on neuroimaging, neurocognition, and biochemical parameters in populations with high genetic risk for the illness can yield an integrative perspective on the neurobiology of risk for BD. The most up-to-date data reveals consistent deficits in executive function, response inhibition, verbal memory/learning, verbal fluency, and processing speed in risk groups for BD. Functional magnetic resonance imaging (fMRI) studies report alterations in the activity of the inferior frontal gyrus, medial prefrontal cortex, and limbic areas, particularly in the amygdala in unaffected first-degree relatives (FDR) of BD compared to healthy controls. Risk groups for BD also present altered immune and neurochemical modulation. Despite inconsistencies, accumulating data reveals cognitive and imaging markers for risk and to a less extent resilience of BD. Findings on neural modulation markers are preliminary and require further studies. Although the knowledge on the neurobiology of risk for BD has been inadequate to provide benefits for clinical practice, further studies on structural and functional changes in the brain, neurocognitive functioning, and neurochemical modulation have a potential to reveal biomarkers for risk and resilience for BD. Multimodal, multicenter, population-based studies with large sample size allowing for homogeneous subgroup analyses will immensely contribute to the elucidation of biological markers for risk for BD in an integrative model.

Multimodal Neuroimaging-Informed Clinical Applications in Neuropsychiatric Disorders

Recent advances in neuroimaging data acquisition and analysis hold the promise to enhance the ability to make diagnostic and prognostic predictions and perform treatment planning in neuropsychiatric disorders. Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits. We first discuss current challenges associated with the identification of reliable neuroimaging markers for diagnosis and prognosis in mood disorders and for neurosurgical treatment planning for deep brain stimulation (DBS). We then present data on the use of neuroimaging for the diagnosis and prognosis of mood disorders and for DBS treatment planning. We demonstrate how multivariate analyses of functional activation and connectivity parameters can be used to differentiate patients with bipolar disorder from those with major depressive disorder and non-affective psychosis. We also present data on connectivity parameters that mediate acute treatment response in affective and non-affective psychosis. We then focus on precision mapping of functional connectivity in native space. We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain. We discuss how this approach may be particularly promising in psychiatry, given the clinical and etiological heterogeneity of the disorders, and particularly in treatment response prediction and planning. Precision mapping of connectivity is essential for DBS. In DBS, treatment electrodes are inserted into positions near key gray matter nodes within the circuits considered relevant to disease expression. However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant for effective treatment. We demonstrate how this approach can be validated in the treatment of Parkinson's disease by identifying connectivity patterns that can be used as biomarkers for treatment planning and thus refine the traditional approach of DBS planning that uses only gray matter landmarks. Finally, we describe how this approach could be used in planning DBS treatment of psychiatric disorders.