Diagnostic value of structural, functional and effective connectivity in bipolar disorder

INTRODUCTION

The aim of this systematic review is to assess the functional magnetic resonance imaging (fMRI) studies of bipolar disorder (BD) patients that characterize differences in terms of structural, functional, and effective connectivity between the patients with BD, patients with other psychiatric disorders and healthy controls as possible biomarkers for diagnosing the disorder using neuroimaging.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), guidelines a systematic search for recent (since 2015) original studies on connectivity in bipolar disorder was conducted in PUBMED and SCOPUS.

RESULTS

A total of 60 studies were included in this systematic review: 20 of the structural connectivity, 33 of the functional connectivity, and only 7 of the studies focused on effective connectivity complied with the inclusion and exclusion criteria.

DISCUSSION

Despite the great heterogeneity in the findings, there are several trends that emerge. In structural connectivity studies, the main abnormalities in bipolar disorder patients were in the frontal gyrus, anterior, as well as posterior cingulate cortex and differences in emotion and reward-related networks. Cerebellum (vermis) to cerebrum functional connectivity was found to be the most common finding in BD. Moreover, prefrontal cortex and amygdala connectivity as part of the rich-club hubs were often reported to be disrupted. The most common findings based on effective connectivity were alterations in salience network, default mode network and executive control network. Although more studies with larger sample sizes are needed to ascertain altered brain connectivity as diagnostic biomarker, there is a perspective that the method could be used as a single marker of diagnosis in the future, and the process of adoption could be accelerated by using approaches such as semiunsupervised machine learning.

Increased cortical surface area but not altered cortical thickness or gyrification in bipolar disorder following stabilisation from a first episode of mania

BACKGROUND

Despite reports of altered brain morphology in established bipolar disorder (BD), there is limited understanding of when these morphological abnormalities emerge. Assessment of patients during the early course of illness can help to address this gap, but few studies have examined surface-based brain morphology in patients at this illness stage.

METHODS

We completed a secondary analysis of baseline data from a randomised control trial of BD individuals stabilised after their first episode of mania (FEM). The magnetic resonance imaging scans of n = 35 FEM patients and n = 29 age-matched healthy controls were analysed. Group differences in cortical thickness, surface area and gyrification were assessed at each vertex of the cortical surface using general linear models. Significant results were identified at p < 0.05 using cluster-wise correction.

RESULTS

The FEM group did not differ from healthy controls with regards to cortical thickness or gyrification. However, there were two clusters of increased surface area in the left hemisphere of FEM patients, with peak coordinates falling within the lateral occipital cortex and pars triangularis.

CONCLUSIONS

Cortical thickness and gyrification appear to be intact in the aftermath of a first manic episode, whilst cortical surface area in the inferior/middle prefrontal and occipitoparietal cortex is increased compared to age-matched controls. It is possible that increased surface area in the FEM group is the outcome of abnormalities in a premorbidly occurring process. In contrast, the findings raise the hypothesis that cortical thickness reductions seen in past studies of individuals with more established BD may be more attributable to post-onset factors.

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.

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.

Dynamic Causal Modeling on the Identification of Interacting Networks in the Brain: A Systematic Review

Dynamic causal modeling (DCM) has long been used to characterize effective connectivity within networks of distributed neuronal responses. Previous reviews have highlighted the understanding of the conceptual basis behind DCM and its variants from different aspects. However, no detailed summary or classification research on the task-related effective connectivity of various brain regions has been made formally available so far, and there is also a lack of application analysis of DCM for hemodynamic and electrophysiological measurements. This review aims to analyze the effective connectivity of different brain regions using DCM for different measurement data. We found that, in general, most studies focused on the networks between different cortical regions, and the research on the networks between other deep subcortical nuclei or between them and the cerebral cortex are receiving increasing attention, but far from the same scale. Our analysis also reveals a clear bias towards some task types. Based on these results, we identify and discuss several promising research directions that may help the community to attain a clear understanding of the brain network interactions under different tasks.

Conductance-based dynamic causal modeling: A mathematical review of its application to cross-power spectral densities

Dynamic Causal Modeling (DCM) is a Bayesian framework for inferring on hidden (latent) neuronal states, based on measurements of brain activity. Since its introduction in 2003 for functional magnetic resonance imaging data, DCM has been extended to electrophysiological data, and several variants have been developed. Their biophysically motivated formulations make these models promising candidates for providing a mechanistic understanding of human brain dynamics, both in health and disease. However, due to their complexity and reliance on concepts from several fields, fully understanding the mathematical and conceptual basis behind certain variants of DCM can be challenging. At the same time, a solid theoretical knowledge of the models is crucial to avoid pitfalls in the application of these models and interpretation of their results. In this paper, we focus on one of the most advanced formulations of DCM, i.e. conductance-based DCM for cross-spectral densities, whose components are described across multiple technical papers. The aim of the present article is to provide an accessible exposition of the mathematical background, together with an illustration of the model's behavior. To this end, we include step-by-step derivations of the model equations, point to important aspects in the software implementation of those models, and use simulations to provide an intuitive understanding of the type of responses that can be generated and the role that specific parameters play in the model. Furthermore, all code utilized for our simulations is made publicly available alongside the manuscript to allow readers an easy hands-on experience with conductance-based DCM.

Aberrant brain network topology in the frontoparietal-limbic circuit in bipolar disorder: a graph-theory study

Characterizing the properties of brain networks across mood states seen in bipolar disorder (BP) can provide a deeper insight into the mechanisms involved in this type of affective disorder. In this study, graph theoretical methods were used to examine global, modular and nodal brain network topology in the resting state using functional magnetic resonance imaging data acquired from 95 participants, including those with bipolar depression (BPD; n = 30) and bipolar mania (BPM; n = 39) and healthy control (HC) subjects (n = 26). The threshold value of the individual subjects' connectivity matrix varied from 0.15 to 0.30 with steps of 0.01. We found that: (1) at the global level, BP patients showed a significantly increased global efficiency and synchronization and a decreased path length; (2) at the nodal level, BP patients showed impaired nodal parameters, predominantly within the frontoparietal and limbic sub-network; (3) at the module level, BP patients were characterized by denser FCs (edges) between Module III (the front-parietal system) and Module V (limbic/paralimbic systems); (4) at the nodal level, the BPD and BPM groups showed state-specific differences in the orbital part of the left superior-frontal gyrus, right putamen, right parahippocampal gyrus and left fusiform gyrus. These results revealed abnormalities in topological organization in the whole brain, especially in the frontoparietal-limbic circuit in both BPD and BPM. These deficits may reflect the pathophysiological processes occurring in BP. In addition, state-specific regional nodal alterations in BP could potentially provide biomarkers of conversion across different mood states.

Individuals at increased risk for development of bipolar disorder display structural alterations similar to people with manifest disease

In psychiatry, there has been a growing focus on identifying at-risk populations. For schizophrenia, these efforts have led to the development of early recognition and intervention measures. Despite a similar disease burden, the populations at risk of bipolar disorder have not been sufficiently characterized. Within the BipoLife consortium, we used magnetic resonance imaging (MRI) data from a multicenter study to assess structural gray matter alterations in N = 263 help-seeking individuals from seven study sites. We defined the risk using the EPIbipolar assessment tool as no-risk, low-risk, and high-risk and used a region-of-interest approach (ROI) based on the results of two large-scale multicenter studies of bipolar disorder by the ENIGMA working group. We detected significant differences in the thickness of the left pars opercularis (Cohen's d = 0.47, p = 0.024) between groups. The cortex was significantly thinner in high-risk individuals compared to those in the no-risk group (p = 0.011). We detected no differences in the hippocampal volume. Exploratory analyses revealed no significant differences in other cortical or subcortical regions. The thinner cortex in help-seeking individuals at risk of bipolar disorder is in line with previous findings in patients with the established disorder and corresponds to the region of the highest effect size in the ENIGMA study of cortical alterations. Structural alterations in prefrontal cortex might be a trait marker of bipolar risk. This is the largest structural MRI study of help-seeking individuals at increased risk of bipolar disorder.

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.

Children with euthymic bipolar disorder during an emotional go/nogo task: Insights into the neural circuits of cognitive-emotional regulation

BACKGROUND

Pediatric bipolar disorder (PBD), manifested by alternating episodes of depression and mania, is more likely to relapse than adult BD and develop into chronic BD. Although it can be asymptomatic during the remission of PBD, subtle changes in the brain neural response can still exist. Abnormal activities in the neural circuits of cognitive-emotional regulation have been found in adult BD patients using fMRI. However, few fMRI studies focus on emotional regulation on cognitive function in euthymic PBD, especially during an emotional go/nogo task. Therefore, this study aims to compare differences in the activities of both emotional and cognitive circuits between euthymic BD children and healthy controls.

METHODS

18 euthymic PBD and 17 healthy subjects from 12 to 17 years of age were enrolled in our study. Simultaneous neural activity was recorded during the overall task and the effect of emotional factors on task performances was assessed.

RESULTS

There were no significant differences in behavioral performances between the PBD group and the control group. During a task with emotional versus neutral distractors, euthymic PBD patients showed increased activities in the DLPFC, inferior parietal lobule, superior/middle frontal gyrus, superior/middle temporal gyrus, insula, posterior cingulate gyrus and posterior cerebellum lobe relative to healthy controls. The insula and DLPFC activities in response to emotional versus neutral distractors were positively associated with the differences in false response errors.

CONCLUSIONS

This study confirms the enhanced neural activities in euthymic PBD during a task with emotional versus control distractors. These brain regions supporting the cognitive and emotional dysregulation of PBD mainly coincide with the salience and executive control networks. As neural responses are more sensitive than behavioral manifestations in euthymic PBD, our findings will inspire more clinical studies to unveil the characteristic neuromechanism of PBD.

Psychiatric and psychological features of children at high-risk for bipolar disorder

BACKGROUND

Psychological/psychiatric features of high risk children (HR) for bipolar disorder are majorly overlooked. We aimed to compare psychological profiles (eg. anger level/ management, attachment/stress-coping mechanisms and emotional regulation difficulties) of HR with healthy controls.

METHOD

Total of 60 children in HR and 55 children in control group were evaluated using Trait Anger Scale (TAS), Anger Expression Scale (AES), Inventory of Parent/Peer Attachment (IPPA), Coping Style Scale (CSS) and Difficulties in Emotion Regulation Scale (DERS).

RESULTS

AXE/In and AXE/Con subscales of AES, "trust" and "communication" facets of IPPA-Peer and "communication" facet of IPPA-Parent were significantly lower in HR. They scored higher in "helpless" and lower in "submissive" and "optimistic" subscales of CSS. HR scored higher only in "lack of emotional awareness" facet of DERS.

LIMITATIONS

Self-reported scales which we used, may be susceptible to subjective personal characteristics. Also cross-sectional design of our study may have captured only a fraction of rapidly changing developmental processes.

CONCLUSIONS

Lower AXE/In and AXE/Con scores of HR are similar to Type-A Behavior Pattern which is includes agressiveness and impulsiveness. Higher "helpless", and lower "submissive" and "optimistic" scores may reflect emotionally disregulated coping mechanisms which may lead to the risk of developing future depressive episodes. Lower "communication" in IPPA may show a disturbance in executive function of language. Lack of emotional awareness can be examined in line with alexithymia; but further studies are needed to explain these aspects.

Altered functional connectivity of right inferior frontal gyrus subregions in bipolar disorder: a resting state fMRI study

The right inferior frontal gyrus (rIFG) is a key cortical node in the circuits of emotion and cognitive control, and it has been frequently associated with bipolar disorder (BP); however, a reliable pattern of aberrant rIFG activation and connectivity in bipolar disorder has yet to be established. To further elucidate rIFG abnormalities in different states of bipolar disorder, we examined activation and functional connectivity (FC) in five subregions of rIFG in bipolar disorder. A total of 83 participants, including those with bipolar depression (BPD; n = 25) and bipolar mania (BPM; n = 37) along with healthy control (HC) subjects (n = 26), were examined by resting state functional magnetic resonance imaging (rs-fMRI). Both BPD and BPM groups showed higher values of amplitude of low-frequency fluctuations (ALFF) than healthy control in four of the five rIFG subregions except cluster 2(posterior-ventral rIFG). Using five subregions of rIFG as seeds, the decreased FC in bipolar disorder was mainly between posterior-ventral rIFG(cluster 2) and multiple brain regions including the postcentral gyrus, the precentral gyrus, paracentral lobule, lingual Gyrus, fusiform and cerebellum posterior lobe. These results indicated that local activity and FC were altered within specific subregions of the rIFG in BP. These findings may provide the distinct functional connectivity of rIFG subregions in BP and suggest that the cluster2 (posterior-ventral rIFG) circuitry plays a crucial role in BP. Also, such abnormalities might help define a more precise intervention targets.

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.

Neural correlates of emotion processing predict resilience in youth at familial risk for mood disorders

Aberrant face emotion processing has been demonstrated in youth with and at a familial risk for bipolar and major depressive disorders. However, the neurobiological factors related to emotion processing that underlie resilience from youth-onset mood disorders are not well understood. Functional magnetic resonance imaging data during an implicit emotion processing task were collected at baseline from a sample of 50 youth, ages 8-17, who were healthy but also familially at high risk for either bipolar disorder or major depressive disorder, and 24 healthy controls with no family history of psychopathology (HCL). Participants were reevaluated 3 years later and classified into three groups for analysis: high-risk youth who converted to a psychiatric diagnosis (CVT; N = 23), high-risk youth who were resilient from developing any psychopathology (RES; N = 27), and HCL youth (N = 24) who remained healthy at follow-up. For happy &gt; calm faces, the CVT and RES groups had significantly lower activation in the left inferior parietal lobe (IPL), while the RES group had lower activation in the right supramarginal gyrus. For fear &gt; calm faces, the RES group had lower activation in the right precuneus and inferior frontal gyrus (IFG) compared to the CVT group. Connectivity analyses revealed the RES group exhibited higher left IPL connectivity with visual cortical regions for happy &gt; calm faces, and higher IFG connectivity with frontal, temporal, and limbic regions for fear &gt; calm faces. These connectivities were correlated with improvements in prosocial behaviors and global functioning. Our findings suggest that differential activation and connectivity in the IPL, IFG, and precuneus in response to emotional stimuli may represent distinct resilience and risk markers for youth-onset mood disorders.

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".

Effective connectivity of the anterior hippocampus predicts recollection confidence during natural memory retrieval

Human interactions with the world are influenced by memories of recent events. This effect, often triggered by perceptual cues, occurs naturally and without conscious effort. However, the neuroscience of involuntary memory in a dynamic milieu has received much less attention than the mechanisms of voluntary retrieval with deliberate purpose. Here, we investigate the neural processes driven by naturalistic cues that relate to, and presumably trigger the retrieval of recent experiences. Viewing the continuation of recently viewed clips evokes greater bilateral activation in anterior hippocampus, precuneus and angular gyrus than naïve clips. While these regions manifest reciprocal connectivity, continued viewing specifically modulates the effective connectivity from the anterior hippocampus to the precuneus. The strength of this modulation predicts participants' confidence in later voluntary recall of news details. Our study reveals network mechanisms of dynamic, involuntary memory retrieval and its relevance to metacognition in a rich context resembling everyday life.

Abnormal intrinsic cerebro-cerebellar functional connectivity in un-medicated patients with bipolar disorder and major depressive disorder

OBJECTIVE

The cerebellum plays an important role in depression. Cerebro-cerebellar circuits have been found to show aberrance in bipolar disorder (BD) and major depressive disorder (MDD). However, whether the cerebro-cerebellar connectivity contributes equally to the pathologic mechanisms of BD and MDD remains unknown.

METHODS

We recruited 33 patients with MDD, 32 patients with BD, and 43 healthy controls (HC). We selected six seed regions (three per hemisphere) in the cerebrum, corresponding to the affective, cognitive control, and default mode networks, to establish cerebro-cerebellar functional connectivity maps.

RESULTS

Relative to the HC, both the BD and MDD patients exhibited weaker negative connectivity between the right subgenual anterior cingulate cortex and the cerebellar vermis IV_V (p_BD = 0.03, p_MDD = 0.001) and weaker positive connectivity between the left precuneus and the left cerebellar lobule IX (p_BD = 0.043, p_MDD = 0.000). Moreover, the MDD patients showed weaker positive connectivity in the left precuneus-left cerebellar lobule IX circuit than the BD patients (p = 0.049). In addition, the BD patients showed weaker positive connectivity in the right dorsolateral prefrontal cortex-left cerebellar lobule Crus Ι circuit compared to the HC (p = 0.002) or the MDD patients (p = 0.013). Receiver operating characteristic curves analyses showed that the altered cerebro-cerebellar connectivities could be used to distinguish the patients from the HC with relatively high accuracy.

CONCLUSIONS

Our findings suggested that differences in connectivity of cerebro-cerebellar circuits, which are involved in affective or cognitive functioning, significantly contributed to BD and MDD.

Clinical predictors of conversion to bipolar disorder in a prospective longitudinal familial high-risk sample: focus on depressive features

BACKGROUND

Identifying clinical features that predict conversion to bipolar disorder (BD) in those at high familial risk (HR) would assist in identifying a more focused population for early intervention.

METHOD

In total 287 participants aged 12-30 (163 HR with a first-degree relative with BD and 124 controls (CONs)) were followed annually for a median of 5 years. We used the baseline presence of DSM-IV depressive, anxiety, behavioural and substance use disorders, as well as a constellation of specific depressive symptoms (as identified by the Probabilistic Approach to Bipolar Depression) to predict the subsequent development of hypo/manic episodes.

RESULTS

At baseline, HR participants were significantly more likely to report ⩾4 Probabilistic features (40.4%) when depressed than CONs (6.7%; p < .05). Nineteen HR subjects later developed either threshold (n = 8; 4.9%) or subthreshold (n = 11; 6.7%) hypo/mania. The presence of ⩾4 Probabilistic features was associated with a seven-fold increase in the risk of 'conversion' to threshold BD (hazard ratio = 6.9, p < .05) above and beyond the fourteen-fold increase in risk related to major depressive episodes (MDEs) per se (hazard ratio = 13.9, p < .05). Individual depressive features predicting conversion were psychomotor retardation and ⩾5 MDEs. Behavioural disorders only predicted conversion to subthreshold BD (hazard ratio = 5.23, p < .01), while anxiety and substance disorders did not predict either threshold or subthreshold hypo/mania.

CONCLUSIONS

This study suggests that specific depressive characteristics substantially increase the risk of young people at familial risk of BD going on to develop future hypo/manic episodes and may identify a more targeted HR population for the development of early intervention programs.

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.

Generative models for clinical applications in computational psychiatry

Despite the success of modern neuroimaging techniques in furthering our understanding of cognitive and pathophysiological processes, translation of these advances into clinically relevant tools has been virtually absent until now. Neuromodeling represents a powerful framework for overcoming this translational deadlock, and the development of computational models to solve clinical problems has become a major scientific goal over the last decade, as reflected by the emergence of clinically oriented neuromodeling fields like Computational Psychiatry, Computational Neurology, and Computational Psychosomatics. Generative models of brain physiology and connectivity in the human brain play a key role in this endeavor, striving for computational assays that can be applied to neuroimaging data from individual patients for differential diagnosis and treatment prediction. In this review, we focus on dynamic causal modeling (DCM) and its use for Computational Psychiatry. DCM is a widely used generative modeling framework for functional magnetic resonance imaging (fMRI) and magneto-/electroencephalography (M/EEG) data. This article reviews the basic concepts of DCM, revisits examples where it has proven valuable for addressing clinically relevant questions, and critically discusses methodological challenges and recent methodological advances. We conclude this review with a more general discussion of the promises and pitfalls of generative models in Computational Psychiatry and highlight the path that lies ahead of us. This article is categorized under: Neuroscience > Computation Neuroscience > Clinical Neuroscience.

Behavioral and Neural Sustained Attention Deficits in Bipolar Disorder and Familial Risk of Bipolar Disorder

BACKGROUND

Few neuroimaging studies compare individuals affected with bipolar disorder (BP), at high familial risk of BP, and at low risk to identify endophenotypes for BP. None have examined variability in attention, despite promising behavioral work in this area. We used functional magnetic resonance imaging (fMRI) methods uniquely powered to compare the neural correlates of attention variability in these three groups.

METHODS

The present study examined 8- to 25-year-old individuals (n = 106) who completed an fMRI attention task: 24 with BP, 29 at risk based on a first-degree relative with BP, and 53 healthy, low-risk individuals. Group differences in intrasubject variability in reaction time were examined, and a sophisticated fMRI analytic approach was used to quantify precisely trialwise associations between reaction time and brain activity. The latter has not been examined previously in BP or risk of BP.

RESULTS

Relative to healthy individuals, those with BP or at risk for BP exhibited increased reaction time variability (F_2,102 = 4.26, p = .02, η_p² = .08). Importantly, we identified blunted relationships between trialwise variation in reaction time and brain activity in the inferior and middle frontal gyri, precuneus, cingulate cortex, caudate, and postcentral gyrus (all regions: p < .001, η_p² > .06) in both at-risk and BP individuals compared with healthy, low-risk individuals. This blunting partially mediated group differences in reaction time variability (β = .010, 95% confidence interval 0.002 to 0.020, Sobel Z = 2.08, p = .038).

CONCLUSIONS

Blunting in key frontal, cingulate, and striatal areas was evident in unaffected, at-risk individuals and in euthymic BP patients. Elucidating such novel neural endophenotypes can facilitate new approaches to BP prediction, diagnosis, and prevention.

Impaired cognitive control over emotional material in euthymic bipolar disorder

BACKGROUND

Previous research suggests that bipolar disorder (BD) is characterized by deficits in cognitive control (CC). Impaired CC has been found in high-risk samples and is associated with the maintenance of BD symptoms. It remains unclear, however, whether BD is characterized by a general deficit in CC or by a deficit that is specifically related to the processing of emotional material.

METHODS

The sample consisted of 42 remitted bipolar patients and 39 healthy controls (HC). We examined whether BD individuals display impaired CC when confronted with negative as well as positive material using an arithmetic inhibition task that required inhibition of pictorial stimulus material.

RESULTS

Whereas both groups showed difficulties in exerting CC over negative material, only BD individuals exhibited deficient CC over positive material.

LIMITATIONS

Even though we intended the negative and positive pictures in the arithmetic inhibition task to be similarly arousing, participants in the current study rated the negative compared to the positive pictures as more arousing.

CONCLUSIONS

BD is associated with impaired CC when processing emotional - especially positive - stimuli even when patients are in remission. Possible implications of this deficit especially for emotion regulation are discussed.

Functional Dysconnection of the Inferior Frontal Gyrus in Young People With Bipolar Disorder or at Genetic High Risk

BACKGROUND

Bipolar disorder (BD) is characterized by a dysregulation of affect and impaired integration of emotion with cognition. These traits are also expressed in probands at high genetic risk of BD. The inferior frontal gyrus (IFG) is a key cortical hub in the circuits of emotion and cognitive control, and it has been frequently associated with BD. Here, we studied resting-state functional connectivity of the left IFG in participants with BD and in those at increased genetic risk.

METHODS

Using resting-state functional magnetic resonance imaging we compared 49 young BD participants, 71 individuals with at least one first-degree relative with BD (at-risk), and 80 control subjects. We performed between-group analyses of the functional connectivity of the left IFG and used graph theory to study its local functional network topology. We also used machine learning to study classification based solely on the functional connectivity of the IFG.

RESULTS

In BD, the left IFG was functionally dysconnected from a network of regions, including bilateral insulae, ventrolateral prefrontal gyri, superior temporal gyri, and the putamen (p < .001). A small network incorporating neighboring insular regions and the anterior cingulate cortex showed weaker functional connectivity in at-risk than control participants (p < .006). These constellations of regions overlapped with frontolimbic regions that a machine learning classifier selected as predicting group membership with an accuracy significantly greater than chance.

CONCLUSIONS

Functional dysconnectivity of the IFG from regions involved in emotional regulation may represent a trait abnormality for BD and could potentially aid clinical diagnosis.

Summaries of plenary and selected symposia sessions at the XXIV World Congress of Psychiatric Genetics; Jerusalem, Israel; 30 October 2016-3 November 2016

The XXII World Congress of Psychiatric Genetics, sponsored by the International Society of Psychiatric Genetics, took place in Jerusalem, Israel, from 30 October 2016 to 3 November 2016. A total of 372 participants gathered to discuss the latest findings in the field. The following report was written by early career investigator travel awardees, and student and postdoctoral attendees. Each was assigned one or more sessions as a rapporteur. This manuscript represents topics covered in most, but not all of the presentations during the conference, and contains some of the major notable new findings reported.

Neural Markers in Pediatric Bipolar Disorder and Familial Risk for Bipolar Disorder

OBJECTIVE

Bipolar disorder (BD) is highly heritable. Neuroimaging studies comparing unaffected youth at high familial risk for BD (i.e., those with a first-degree relative with the disorder; termed "high-risk" [HR]) to "low-risk" (LR) youth (i.e., those without a first-degree relative with BD) and to patients with BD may help identify potential brain-based markers associated with risk (i.e., regions where HR+BD≠LR), resilience (HR≠BD+LR), or illness (BD≠HR+LR).

METHOD

During functional magnetic resonance imaging (fMRI), 99 youths (i.e., adolescents and young adults) aged 9.8 to 24.8 years (36 BD, 22 HR, 41 LR) performed a task probing face emotion labeling, previously shown to be impaired behaviorally in youth with BD and HR youth.

RESULTS

We found three patterns of results. Candidate risk endophenotypes (i.e., where BD and HR shared deficits) included dysfunction in higher-order face processing regions (e.g., middle temporal gyrus, dorsolateral prefrontal cortex). Candidate resilience markers and disorder sequelae (where HR and BD, respectively, show unique alterations relative to the other two groups) included different patterns of neural responses across other regions mediating face processing (e.g., fusiform), executive function (e.g., inferior frontal gyrus), and social cognition (e.g., default network, superior temporal sulcus, temporo-parietal junction).

CONCLUSION

If replicated in longitudinal studies and with additional populations, neural patterns suggesting risk endophenotypes could be used to identify individuals at risk for BD who may benefit from prevention measures. Moreover, information about risk and resilience markers could be used to develop novel treatments that recruit neural markers of resilience and attenuate neural patterns associated with risk. Clinical trial registration information-Studies of Brain Function and Course of Illness in Pediatric Bipolar Disorder and Child and Adolescent Bipolar Disorder Brain Imaging and Treatment Study; http://clinicaltrials.gov/; NCT00025935 and NCT00006177.

Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future.

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.

Interhemispheric white matter integrity in young people with bipolar disorder and at high genetic risk

BACKGROUND

White matter (WM) impairments have been reported in patients with bipolar disorder (BD) and those at high familial risk of developing BD. However, the distribution of these impairments has not been well characterized. Few studies have examined WM integrity in young people early in the course of illness and in individuals at familial risk who have not yet passed the peak age of onset.

METHOD

WM integrity was examined in 63 BD subjects, 150 high-risk (HR) individuals and 111 participants with no family history of mental illness (CON). All subjects were aged 12 to 30 years.

RESULTS

This young BD group had significantly lower fractional anisotropy within the genu of the corpus callosum (CC) compared with the CON and HR groups. Moreover, the abnormality in the genu of the CC was also present in HR participants with recurrent major depressive disorder (MDD) (n = 16) compared with CON participants.

CONCLUSIONS

Our findings provide important validation of interhemispheric abnormalities in BD patients. The novel finding in HR subjects with recurrent MDD - a group at particular risk of future hypo/manic episodes - suggests that this may potentially represent a trait marker for BD, though this will need to be confirmed in longitudinal follow-up studies.

Abnormalities in left inferior frontal gyral thickness and parahippocampal gyral volume in young people at high genetic risk for bipolar disorder

BACKGROUND

Fronto-limbic structural brain abnormalities have been reported in patients with bipolar disorder (BD), but findings in individuals at increased genetic risk of developing BD have been inconsistent. We conducted a study in adolescents and young adults (12-30 years) comparing measures of fronto-limbic cortical and subcortical brain structure between individuals at increased familial risk of BD (at risk; AR), subjects with BD and controls (CON). We separately examined cortical volume, thickness and surface area as these have distinct neurodevelopmental origins and thus may reflect differential effects of genetic risk.

METHOD

We compared fronto-limbic measures of grey and white matter volume, cortical thickness and surface area in 72 unaffected-risk individuals with at least one first-degree relative with bipolar disorder (AR), 38 BD subjects and 72 participants with no family history of mental illness (CON).

RESULTS

The AR group had significantly reduced cortical thickness in the left pars orbitalis of the inferior frontal gyrus (IFG) compared with the CON group, and significantly increased left parahippocampal gyral volume compared with those with BD.

CONCLUSIONS

The finding of reduced cortical thickness of the left pars orbitalis in AR subjects is consistent with other evidence supporting the IFG as a key region associated with genetic liability for BD. The greater volume of the left parahippocampal gyrus in those at high risk is in line with some prior reports of regional increases in grey matter volume in at-risk subjects. Assessing multiple complementary morphometric measures may assist in the better understanding of abnormal developmental processes in BD.

Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools

The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website.

Computational neuroimaging strategies for single patient predictions

Neuroimaging increasingly exploits machine learning techniques in an attempt to achieve clinically relevant single-subject predictions. An alternative to machine learning, which tries to establish predictive links between features of the observed data and clinical variables, is the deployment of computational models for inferring on the (patho)physiological and cognitive mechanisms that generate behavioural and neuroimaging responses. This paper discusses the rationale behind a computational approach to neuroimaging-based single-subject inference, focusing on its potential for characterising disease mechanisms in individual subjects and mapping these characterisations to clinical predictions. Following an overview of two main approaches - Bayesian model selection and generative embedding - which can link computational models to individual predictions, we review how these methods accommodate heterogeneity in psychiatric and neurological spectrum disorders, help avoid erroneous interpretations of neuroimaging data, and establish a link between a mechanistic, model-based approach and the statistical perspectives afforded by machine learning.

Elucidating neural network functional connectivity abnormalities in bipolar disorder: toward a harmonized methodological approach

Bipolar disorder (BD), a mood disorder characterized by emotional lability and dysregulation, is associated with alterations in functional connectivity, particularly as assessed using functional MRI. Here, we provide an overview of the extant literature, and themes that have emerged within it. We identified published research describing functional connectivity in BD using PubMed and follow-up searches. The most consistent evidence favors abnormally heightened functional connectivity between the amygdala and the lateral regions of the ventral prefrontal cortex (PFC), both during rest or emotional processing. Altered interactions between the amygdala and more medial PFC regions have been implicated in BD, but are less consistently related to core symptoms and are sometimes associated with mood state or psychosis. Interactions between medial and lateral ventral PFC have also been reported to be altered in BD, and may mediate estimates of amygdala/vlPFC connectivity. We also describe other themes, including an emerging literature examining reward circuitry, which has highlighted abnormal functional interactions between the ventral striatum and medial prefrontal cortex, as well as the advent of examining global network abnormalities in BD. Functional connectivity studies in BD have established altered interactions between PFC and the amygdala. To address the inconsistencies in the literature, we suggest avenues for the adoption of large scale, and network-based analysis of connectivity, the integration of structural connectivity and the acknowledgement of dynamic and context-related shifts in functional connectivity as a means of clarifying the abnormal neural circuitry in the disorder.