Grey matter differences in bipolar disorder: a meta-analysis of voxel-based morphometry studies

Identification of a common neurobiological substrate for mental illness

IMPORTANCE

Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness.

OBJECTIVE

To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret structural findings in the meta-analysis.

DATA SOURCES

PubMed was searched to identify voxel-based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta-analysis. The 3 parallel healthy participant data sets included resting-state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data.

DATA EXTRACTION AND SYNTHESIS

Studies were included in the meta-analysis if they reported voxel-based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses). The meta-analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach.

MAIN OUTCOMES AND MEASURES

We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow-up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta-analysis and the relationship of gray matter volume to cognition.

RESULTS

Based on the voxel-based morphometry meta-analysis of 193 studies comprising 15 892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety), we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis-specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow-up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning.

CONCLUSIONS AND REVELANCE

We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate-based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.

Epidemiological and clinical aspects will guide the neuroimaging research in bipolar disorder

Although neurobiological mechanisms of bipolar disorder (BD) are still unclear, neural models of the disease have recently been conceptualised thanks to neuroimaging. Indeed, magnetic resonance imaging (MRI) studies investigating structural and functional connectivity between different areas of the brain suggest an altered prefrontal-limbic coupling leading to disrupted emotional processing in BD, including uncinate fasciculus, amygdala, parahippocampal cortex, cingulate cortex as well corpus callosum. Specifically, these models assume an altered prefrontal control over a hyperactivity of the subcortical limbic structures implicated in automatic emotional processing. This impaired mechanism may finally trigger emotional hyper-reactivity and mood episodes. In this review, we first summarised some key neuroimaging studies on BD. In the second part of the work, we focused on the heterogeneity of the available studies. This variability is partly due to methodological factors (i.e., small sample size) and differences among studies (i.e., MRI acquisition and post-processing analyses) and partly to the clinical heterogeneity of BD. We finally outlined how epidemiological studies should indicate which risk factors and clinical dimensions of BD are relevant to be studied with neuroimaging in order to reduce heterogeneity and go beyond diagnostic categories.

Implicit motor learning in bipolar disorder

OBJECTIVES

A growing number of publications describe cerebellar abnormalities in patients with bipolar disorder (BD). The aim of the following paper was to examine the functional aspects of that issue by focusing on implicit learning - a cognitive function with significant cerebellar underpinnings.

METHODS

27 patients with BD and 26 healthy controls (HC), matched for age and sex took part in the study. Implicit motor learning was assessed by the serial reaction time task (SRTT), in which participants were unconsciously learning a sequence of motor reactions. The indicators of procedural learning were the decrease of reaction time (RT) across the repetition of the sequence and the rebound of RT when the sequence changed into a random set of stimuli.

RESULTS

BD patients did not present any indicators of the implicit learning, their RT increased across repetitions of the sequence and it decreased when the sequence changed to random. Contrary, in the control group RT decreased across the sequence repetitions and increased when the stimuli begun to appear randomly.

LIMITATIONS

A low subject count and a non-drug naïve patients group, medicated with atypical antipsychotic and mood stabilizers, are the most significant limitations of this study.

CONCLUSIONS

BD patients did not acquire procedural knowledge while performing the task, whereas HC did. To our knowledge this is the first study that shows the impairment of implicit motor learning in patients with BD. This indicates the possible cerebellar dysfunction in this disease and may provide a new neuropsychiatric approach to bipolar disorder.

Association between age of disease-onset, cognitive performance and cortical thickness in bipolar disorders

OBJECTIVES

Neuroimaging studies in patients with bipolar disorder (BD) have indicated a number of structural brain changes, including reduced cortical thickness. However, the effects of the course of illness, clinical and cognitive variables on cortical thickness in BD patients have not yet been evaluated.

METHODS

A total of 67 individuals (32 patients with euthymic BD and 35 healthy and age-matched controls) underwent 3D-anatomical magnetic resonance imaging (MRI). Whole-brain cortical thickness and group differences were assessed using the Freesurfer software. Course of disease variables, clinical and cognitive parameters were correlated with cortical thickness measures.

RESULTS

We found reduced cortical thickness in BD patients compared with controls in the frontal and temporal lobes and in several limbic areas. We also report significant associations between cortical thickness and age of disease-onset, speed of cognitive processing, executive function and depression severity in BD patients.

CONCLUSIONS

Cortical thickness reduction across frontal and limbic areas is a structural correlate of affective symptom severity and cognitive impairments in BD as well of age of disease-onset. We may assume that frontal lobe structural abnormalities are present in bipolar disorder, and might lead to dysfunctional cognitive functioning. The causality and functional relevance beyond mere correlation, however, is yet to be established. Our findings encourage further longitudinal studies in BD patients and in healthy at-risk subjects in order to discern the temporal order and development of morphological changes and clinical symptoms.

Sad mood induction has an opposite effect on amygdala response to emotional stimuli in euthymic patients with bipolar disorder and healthy controls

BACKGROUND

Aberrant amygdala reactivity to affective stimuli represents a candidate factor predisposing patients with bipolar disorder (BD) to relapse, but it is unclear to what extent amygdala reactivity is state-dependent. We evaluated the modulatory influence of mood on amygdala reactivity and functional connectivity in patients with remitted BD and healthy controls.

METHODS

Amygdala response to sad versus neutral faces was investigated using fMRI during periods of normal and sad mood induced by autobiographical scripts. We assessed the functional connectivity of the amygdala to characterize the influence of mood state on the network responsible for the amygdala response.

RESULTS

We included 20 patients with remitted BD and 20 controls in our study. The sad and normal mood exerted opposite effects on the amygdala response to emotional faces in patients compared with controls (F1,38 = 5.85, p = 0.020). Sad mood amplified the amygdala response to sad facial stimuli in controls but attenuated the amygdala response in patients. The groups differed in functional connectivity between the amygdala and the inferior prefrontal gyrus (p ≤ 0.05, family-wise error-corrected) of ventrolateral prefrontal cortex (vlPFC) corresponding to Brodmann area 47. The sad mood challenge increased connectivity during the period of processing sad faces in patients but decreased connectivity in controls.

LIMITATIONS

Limitations to our study included long-term medication use in the patient group and the fact that we mapped only depressive (not manic) reactivity.

CONCLUSION

Our results support the role of the amygdala-vlPFC as the system of dysfunctional contextual affective processing in patients with BD. Opposite amygdala reactivity unmasked by the mood challenge paradigm could represent a trait marker of altered mood regulation in patients with BD.

False positive rates in Voxel-based Morphometry studies of the human brain: should we be worried?

Voxel-based Morphometry (VBM) is a widely used automated technique for the analysis of neuroanatomical images. Despite its popularity within the neuroimaging community, there are outstanding concerns about its potential susceptibility to false positive findings. Here we review the main methodological factors that are known to influence the results of VBM studies comparing two groups of subjects. We then use two large, open-access data sets to empirically estimate false positive rates and how these depend on sample size, degree of smoothing and modulation. Our review and investigation provide three main results: (i) when groups of equal size are compared false positive rate is not higher than expected, i.e. about 5%; (ii) the sample size, degree of smoothing and modulation do not appear to influence false positive rate; (iii) when they exist, false positive findings are randomly distributed across the brain. These results provide reassurance that VBM studies comparing groups are not vulnerable to the higher than expected false positive rates that are evident in single case VBM.

Correlations between brain structure and symptom dimensions of psychosis in schizophrenia, schizoaffective, and psychotic bipolar I disorders

INTRODUCTION

Structural alterations may correlate with symptom severity in psychotic disorders, but the existing literature on this issue is heterogeneous. In addition, it is not known how cortical thickness and cortical surface area correlate with symptom dimensions of psychosis.

METHODS

Subjects included 455 individuals with schizophrenia, schizoaffective, or bipolar I disorders. Data were obtained as part of the Bipolar Schizophrenia Network for Intermediate Phenotypes study. Diagnosis was made through the Structured Clinical Interview for DSM-IV. Positive and negative symptom subscales were assessed using the Positive and Negative Syndrome Scale. Structural brain measurements were extracted from T1-weight structural MRIs using FreeSurfer v5.1 and were correlated with symptom subscales using partial correlations. Exploratory factor analysis was also used to identify factors among those regions correlating with symptom subscales.

RESULTS

The positive symptom subscale correlated inversely with gray matter volume (GMV) and cortical thickness in frontal and temporal regions, whereas the negative symptom subscale correlated inversely with right frontal cortical surface area. Among regions correlating with the positive subscale, factor analysis identified four factors, including a temporal cortical thickness factor and frontal GMV factor. Among regions correlating with the negative subscale, factor analysis identified a frontal GMV-cortical surface area factor. There was no significant diagnosis by structure interactions with symptom severity.

CONCLUSIONS

Structural measures correlate with positive and negative symptom severity in psychotic disorders. Cortical thickness demonstrated more associations with psychopathology than cortical surface area.

Genetic and environmental influences on cortical surface area and cortical thickness in bipolar disorder

BACKGROUND

The risk of developing bipolar disorder (BD) has been linked to structural brain abnormalities. The degree to which genes and environment influence the association of BD with cortical surface area remains to be elucidated. In this twin study, genetic and environmental contributions to the association between liability to develop BD and surface area, thickness and volume of the cortex were examined.

METHOD

The study cohort included 44 affected monozygotic (nine concordant, 12 discordant) and dizygotic (four concordant, 19 discordant) twin pairs, and seven twins from incomplete discordant monozygotic and dizygotic discordant twin pairs. In addition, 37 monozygotic and 24 dizygotic healthy control twin pairs, and six twins from incomplete monozygotic and dizygotic control pairs were included.

RESULTS

Genetic liability to develop BD was associated with a larger cortical surface in limbic and parietal regions, and a thicker cortex in central and parietal regions. Environmental factors related to BD were associated with larger medial frontal, parietal and limbic, and smaller orbitofrontal surfaces. Furthermore, thinner frontal, limbic and occipital cortex, and larger frontal and parietal, and smaller orbitofrontal volumes were also associated with environmental factors related to BD.

CONCLUSIONS

Our results suggest that unique environmental factors play a prominent role in driving the associations between liability to develop BD and cortical measures, particularly those involving cortical thickness. Further evaluation of their influence on the surface and thickness of the cortical mantle is recommended. In addition, cortical volume appeared to be primarily dependent on surface and not thickness.

Prophylactic lithium treatment and cognitive performance in patients with a long history of bipolar illness: no simple answers in complex disease-treatment interplay

Cognitive impairment in patients with bipolar disorder (BD) is not restricted to symptomatic phases. It is also present in euthymia. There is evidence of differences in the brain's structure between bipolar patients and healthy individuals, as well as changes over time in patients. Lithium constitutes the gold standard in long-term prophylactic treatment. Appropriate therapy that prevents new episodes improves the disease's course and reduces the frequency of harmful outcomes. Interestingly, preclinical data suggest that lithium has a (additional) neuroprotective effect. There is limited data on its related effects in humans and even less on its long-term application. In this multi-center cross-sectional study from the International Group for the Study of Lithium-treated Patients (IGSLi), we compared three groups: bipolar patients without long-term lithium treatment (non-Li group; <3 months cumulative lithium exposure, ≥24 months ago), bipolar patients with long-term lithium treatment (Li group, ongoing treatment ≥24 months), and healthy subjects (controls). Strict inclusion and exclusion criteria were defined; the inclusion criteria for patients were diagnosis of BD types I or II, duration of illness ≥10 years, ≥5 episodes in patient's history and a euthymic mood state. Neurocognitive functioning was assessed using the Wechsler Adult Intelligence Scale-Revised (WAIS-R), the California Verbal Learning Test (CVLT), and a visual backward masking (VBM) task. A total of 142 subjects were included, 31 in the non-Li and 58 in the Li group, as well as 53 healthy controls. Treated patients with long-standing BD and controls did not differ significantly in overall cognitive functioning and verbal learning, recall, and recognition; regardless of whether lithium had been part of the treatment. Patients, however, demonstrated poorer early visual information processing than healthy controls, with the lithium-treated patients performing worse than those without. Our data suggest that bipolar patients with a long illness history and effective prophylactic treatment do not reveal significantly impaired general cognitive functioning or verbal learning and memory. However, they are worse at processing early visual information. Accompanying volumetric and spectroscopic data suggest cell loss in patients not treated with lithium that may be counterbalanced by long-term lithium treatment.

When structure affects function--the need for partial volume effect correction in functional and resting state magnetic resonance imaging studies

Both functional and also more recently resting state magnetic resonance imaging have become established tools to investigate functional brain networks. Most studies use these tools to compare different populations without controlling for potential differences in underlying brain structure which might affect the functional measurements of interest. Here, we adapt a simulation approach combined with evaluation of real resting state magnetic resonance imaging data to investigate the potential impact of partial volume effects on established functional and resting state magnetic resonance imaging analyses. We demonstrate that differences in the underlying structure lead to a significant increase in detected functional differences in both types of analyses. Largest increases in functional differences are observed for highest signal-to-noise ratios and when signal with the lowest amount of partial volume effects is compared to any other partial volume effect constellation. In real data, structural information explains about 25% of within-subject variance observed in degree centrality – an established resting state connectivity measurement. Controlling this measurement for structural information can substantially alter correlational maps obtained in group analyses. Our results question current approaches of evaluating these measurements in diseased population with known structural changes without controlling for potential differences in these measurements.

Pituitary gland volumes in bipolar disorder

BACKGROUND

Bipolar disorder has been associated with increased Hypothalamic-Pituitary-Adrenal axis function. The mechanism is not well understood, but there may be associated increases in pituitary gland volume (PGV) and these small increases may be functionally significant. However, research investigating PGV in bipolar disorder reports mixed results. The aim of the current study was twofold. First, to assess PGV in two novel samples of patients with bipolar disorder and matched healthy controls. Second, to perform a meta-analysis comparing PGV across a larger sample of patients and matched controls.

METHODS

Sample 1 consisted of 23 established patients and 32 matched controls. Sample 2 consisted of 39 medication-naïve patients and 42 matched controls. PGV was measured on structural MRI scans. Seven further studies were identified comparing PGV between patients and matched controls (total n; 244 patients, 308 controls).

RESULTS

Both novel samples showed a small (approximately 20mm(3) or 4%), but non-significant, increase in PGV in patients. Combining the two novel samples showed a significant association of age and PGV. Meta-analysis showed a trend towards a larger pituitary gland in patients (effect size: .23, CI: -.14, .59).

LIMITATIONS

While results suggest a possible small difference in pituitary gland volume between patients and matched controls, larger mega-analyses with sample sizes greater even than those used in the current meta-analysis are still required.

CONCLUSIONS

There is a small but potentially functionally significant increase in PGV in patients with bipolar disorder compared to controls. Results demonstrate the difficulty of finding potentially important but small effects in functional brain disorders.

Voxel-based morphometry study of the insular cortex in bipolar depression

Bipolar depression (BD) is a common psychiatric illness characterized by deficits in emotional and cognitive processing. Abnormalities in the subregions of the insula are common findings in neuroanatomical studies of patients with bipolar disorder. However, the specific relationships between morphometric changes in specific insular subregions and the pathogenesis of BD are not clear. In this study, structural magnetic resonance imaging (MRI) was used to investigate gray matter volume abnormalities in the insular subregion in 27 patients with BD and in 27 age and sex-matched controls. Using DARTEL (diffeomorphic anatomical registration through exponentiated lie algebra) for voxel-based morphometry (VBM), we examined changes in regional gray matter volumes of the insula in patients with BD. As compared with healthy controls, the BD patients showed decreased gray matter volumes in the right posterior insula and left ventral anterior insula and increased gray matter volumes in the left dorsal anterior insula. Consistent with the emerging theory of insular interference as a contributor to emotional-cognitive dysregulation, the current findings suggest that the insular cortex may be involved in the neural substrates of BD.

A case study in connectomics: the history, mapping, and connectivity of the claustrum

The claustrum seems to have been waiting for the science of connectomics. Due to its tiny size, the structure has remained remarkably difficult to study until modern technological and mathematical advancements like graph theory, connectomics, diffusion tensor imaging, HARDI, and excitotoxic lesioning. That does not mean, however, that early methods allowed researchers to assess micro-connectomics. In fact, the claustrum is such an enigma that the only things known for certain about it are its histology, and that it is extraordinarily well connected. In this literature review, we provide background details on the claustrum and the history of its study in the human and in other animal species. By providing an explanation of the neuroimaging and histology methods have been undertaken to study the claustrum thus far—and the conclusions these studies have drawn—we illustrate this example of how the shift from micro-connectomics to macro-connectomics advances the field of neuroscience and improves our capacity to understand the brain.

Brain morphometric biomarkers distinguishing unipolar and bipolar depression. A voxel-based morphometry-pattern classification approach

IMPORTANCE

The structural abnormalities in the brain that accurately differentiate unipolar depression (UD) and bipolar depression (BD) remain unidentified.

OBJECTIVES

First, to investigate and compare morphometric changes in UD and BD, and to replicate the findings at 2 independent neuroimaging sites; second, to differentiate UD and BD using multivariate pattern classification techniques.

DESIGN, SETTING, AND PARTICIPANTS

In a 2-center cross-sectional study, structural gray matter data were obtained at 2 independent sites (Pittsburgh, Pennsylvania, and Münster, Germany) using 3-T magnetic resonance imaging. Voxel-based morphometry was used to compare local gray and white matter volumes, and a novel pattern classification approach was used to discriminate between UD and BD, while training the classifier at one imaging site and testing in an independent sample at the other site. The Pittsburgh sample of participants was recruited from the Western Psychiatric Institute and Clinic at the University of Pittsburgh from 2008 to 2012. The Münster sample was recruited from the Department of Psychiatry at the University of Münster from 2010 to 2012. Equally divided between the 2 sites were 58 currently depressed patients with bipolar I disorder, 58 age- and sex-matched unipolar depressed patients, and 58 matched healthy controls.

MAIN OUTCOMES AND MEASURES

Magnetic resonance imaging was used to detect structural differences between groups. Morphometric analyses were applied using voxel-based morphometry. Pattern classification techniques were used for a multivariate approach.

RESULTS

At both sites, individuals with BD showed reduced gray matter volumes in the hippocampal formation and the amygdala relative to individuals with UD (Montreal Neurological Institute coordinates x = -22, y = -1, z = 20; k = 1938 voxels; t = 4.75), whereas individuals with UD showed reduced gray matter volumes in the anterior cingulate gyrus compared with individuals with BD (Montreal Neurological Institute coordinates x = -8, y = 32, z = 3; k = 979 voxels; t = 6.37; all corrected P < .05). Reductions in white matter volume within the cerebellum and hippocampus were found in individuals with BD. Pattern classification yielded up to 79.3% accuracy (P < .001) by differentiating the 2 depressed groups, training and testing the classifier at one site, and up to 69.0% accuracy (P < .001), training the classifier at one imaging site (Pittsburgh) and testing it at the other independent sample (Münster). Medication load did not alter the pattern of results.

CONCLUSIONS AND RELEVANCE

Individuals with UD and those with BD are differentiated by structural abnormalities in neural regions supporting emotion processing. Neuroimaging and multivariate pattern classification techniques are promising tools to differentiate UD from BD and show promise as future diagnostic aids.

Insulin resistance, diabetes mellitus, and brain structure in bipolar disorders

Type 2 diabetes mellitus (T2DM) damages the brain, especially the hippocampus, and frequently co-occurs with bipolar disorders (BD). Reduced hippocampal volumes are found only in some studies of BD subjects and may thus be secondary to the presence of certain clinical variables. Studying BD patients with abnormal glucose metabolism could help identify preventable risk factors for hippocampal atrophy in BD. We compared brain structure using optimized voxel-based morphometry of 1.5T MRI scans in 33 BD subjects with impaired glucose metabolism (19 with insulin resistance/glucose intolerance (IR/GI), 14 with T2DM), 15 euglycemic BD participants and 11 euglycemic, nonpsychiatric controls. The group of BD patients with IR, GI or T2DM had significantly smaller hippocampal volumes than the euglycemic BD participants (corrected p=0.02) or euglycemic, nonpsychiatric controls (corrected p=0.004). Already the BD subjects with IR/GI had smaller hippocampal volumes than euglycemic BD participants (t(32)=-3.15, p=0.004). Age was significantly more negatively associated with hippocampal volumes in BD subjects with IR/GI/T2DM than in the euglycemic BD participants (F(2, 44)=9.96, p=0.0003). The gray matter reductions in dysglycemic subjects extended to the cerebral cortex, including the insula. In conclusion, this is the first study demonstrating that T2DM or even prediabetes may be risk factors for smaller hippocampal and cortical volumes in BD. Abnormal glucose metabolism may accelerate the age-related decline in hippocampal volumes in BD. These findings raise the possibility that improving diabetes care among BD subjects and intervening already at the level of prediabetes could slow brain aging in BD.

The course of neuropsychological impairment and brain structure abnormalities in psychotic disorders

Neuropsychological impairment and abnormalities in brain structure are commonly observed in psychotic disorders, including schizophrenia and bipolar disorder. Shared deficits in neuropsychological functioning and abnormalities in brain structure suggest overlapping neuropathology between schizophrenia and bipolar disorder which has important implications for psychiatric nosology, treatment, and our understanding of the etiology of psychotic illnesses. However, the emergence and trajectory of brain dysfunction in psychotic disorders is less well understood. Differences in the course and progression of neuropsychological impairment and brain abnormalities among psychotic disorders may point to unique neuropathological processes. This article reviews the course of neuropsychological impairment and brain structure abnormalities in schizophrenia and bipolar disorder.

Bipolar or borderline: a clinical overview

OBJECTIVE

To examine the empirical literature on diagnostic validators in borderline personality and bipolar illness.

METHOD

Using principles of evidence-based medicine, the highest levels of evidence were emphasized in interpretation of similarities or differences between bipolar illness and borderline personality on the five standard diagnostic validators in psychiatric nosology: symptoms, course, genetics, treatment response, and neurobiology.

RESULTS

Bipolar illness and borderline personality were found to be similar in the nosological validator of symptoms of mood lability and impulsivity, but differed notably on all other diagnostic validators, especially the course validator of past sexual abuse and the genetic validator of a bipolar family history. They also differ notably in the symptom validator of parasuicidal self-harm. Treatment response and neurobiological differences were also present and consistent.

CONCLUSION

This review of the literature indicates that these two conditions, bipolar illness and borderline personality, are different and can be distinguished. The much stronger biological and genetic evidence for bipolar illness in particular suggests that the two conditions can be reasonably seen as different kinds of clinical entities, namely a biological disease versus a psychosocially caused clinical picture. If this interpretation is correct, similarities between the two conditions, such as mood lability and impulsivity, are superficial, while differences are profound. Further, true comorbidity may be much less common than often presumed.

A critical appraisal of neuroimaging studies of bipolar disorder: toward a new conceptualization of underlying neural circuitry and a road map for future research

OBJECTIVE

In this critical review, the authors appraise neuroimaging findings in bipolar disorder in emotion-processing, emotion-regulation, and reward-processing neural circuitry in order to synthesize the current knowledge of the neural underpinnings of bipolar disorder and provide a neuroimaging research road map for future studies.

METHOD

The authors examined findings from all major studies in bipolar disorder that used functional MRI, volumetric analysis, diffusion imaging, and resting-state techniques, integrating findings to provide a better understanding of larger-scale neural circuitry abnormalities in bipolar disorder.

RESULTS

Bipolar disorder can be conceptualized, in neural circuitry terms, as parallel dysfunction in prefrontal cortical (especially ventrolateral prefrontal cortical)-hippocampal-amygdala emotion-processing and emotion-regulation circuits bilaterally, together with an "overactive" left-sided ventral striatal-ventrolateral and orbitofrontal cortical reward-processing circuitry, resulting in characteristic behavioral abnormalities associated with bipolar disorder: emotional lability, emotional dysregulation, and heightened reward sensitivity. A potential structural basis for these functional abnormalities is gray matter volume decreases in the prefrontal and temporal cortices, the amygdala, and the hippocampus and fractional anisotropy decreases in white matter tracts connecting prefrontal and subcortical regions.

CONCLUSIONS

Neuroimaging studies of bipolar disorder clearly demonstrate abnormalities in neural circuits supporting emotion processing, emotion regulation, and reward processing, although there are several limitations to these studies. Future neuroimaging research in bipolar disorder should include studies adopting dimensional approaches; larger studies examining neurodevelopmental trajectories in youths with bipolar disorder or at risk for bipolar disorder; multimodal neuroimaging studies using integrated systems approaches; and studies using pattern recognition approaches to provide clinically useful individual-level data. Such studies will help identify clinically relevant biomarkers to guide diagnosis and treatment decision making for individuals with bipolar disorder.

Body mass index-related regional gray and white matter volume reductions in first-episode mania patients

BACKGROUND

We previously reported that overweight/obese first-episode mania patients had reduced white matter (WM) and temporal lobe volumes compared with normal-weight patients. WM reductions are characteristic of early-stage bipolar disorder (BD), whereas temporal lobe reductions are frequently reported later in the illness. These findings thus suggested a testable hypothesis: that the neuropathology of BD is exacerbated with elevated body mass index (BMI).

METHODS

We used voxel-based morphometry to examine the relationship between BMI and regional gray matter (GM) and WM volumes in our sample of 57 euthymic first-episode mania patients and 55 healthy subjects. We hypothesized that elevated BMI in patients, but not healthy subjects, would be associated with volume reductions in frontal, temporal, and subcortical limbic brain regions implicated in the pathophysiology of BD.

RESULTS

At recovery from their first manic episode, patients with higher BMI had GM and WM reductions in the predicted emotion-generating and -regulating regions. In contrast, healthy subjects with higher BMI had reduced occipital lobe GM only. Factorial analyses confirmed significant BMI × diagnosis interactions for the WM reductions. Approximately three-quarters of patients with elevated BMI were overweight rather than obese; thus, weight-related volume reductions were detectable in patients with modestly elevated BMI.

CONCLUSIONS

This is the first hypothesis-driven test of, and supporting evidence for, our theory that elevated BMI is associated with unique brain changes in BD that have a negative impact on regions believed to be vulnerable in the illness. Our results suggest a neurobiological mechanism to explain the well-validated link between obesity and illness severity in BD.

Comparative organization of the claustrum: what does structure tell us about function?

The claustrum is a subcortical nucleus present in all placental mammals. Many anatomical studies have shown that its inputs are predominantly from the cerebral cortex and its outputs are back to the cortex. This connectivity thus suggests that the claustrum serves to amplify or facilitate information processing in the cerebral cortex. The size and the complexity of the cerebral cortex varies dramatically across species. Some species have lissencephalic brains, with few cortical areas, while others have a greatly expanded cortex and many cortical areas. This evolutionary diversity in the cerebral cortex raises several questions about the claustrum. Does its volume expand in coordination with the expansion of cortex and does it acquire new functions related to the new cortical functions? Here we survey the organization of the claustrum in animals with large brains, including great apes and cetaceans. Our data suggest that the claustrum is not always a continuous structure. In monkeys and gorillas there are a few isolated islands of cells near the main body of the nucleus. In cetaceans, however, there are many isolated cell islands. These data suggest constraints on the possible function of the claustrum. Some authors propose that the claustrum has a more global role in perception or consciousness that requires intraclaustral integration of information. These theories postulate mechanisms like gap junctions between claustral cells or a “syncytium” to mediate intraclaustral processing. The presence of discontinuities in the structure of the claustrum, present but minimal in some primates, but dramatically clear in cetaceans, argues against the proposed mechanisms of intraclaustral processing of information. The best interpretation of function, then, is that each functional subdivision of the claustrum simply contributes to the function of its cortical partner.

Whole brain expression of bipolar disorder associated genes: structural and genetic analyses

Studies of bipolar disorder (BD) suggest a genetic basis of the illness that alters brain function and morphology. In recent years, a number of genetic variants associated with BD have been identified. However, little is known about the associated genes, or brain circuits that rely upon their function. Using an anatomically comprehensive survey of the human transcriptome (The Allen Brain Atlas), we mapped the expression of 58 genes with suspected involvement in BD based upon their relationship to SNPs identified in genome wide association studies (GWAS). We then conducted a meta-analysis of structural MRI studies to identify brain regions that are abnormal in BD. Of 58 BD associated genes, 22 had anatomically distinct expression patterns that could be categorized into one of three clusters (C1–C3). Brain regions with the highest and lowest expression of these genes did not overlap strongly with anatomical sites identified as abnormal by structural MRI except in the parahippocampal gyrus, the inferior/superior temporal gyrus and the cerebellar vermis, regions where overlap was significant. Using the 22 genes in C1–C3 as reference points, additional genes with correlated expression patterns were identified and organized into sets based on similarity. Further analysis revealed that five of these gene sets were significantly associated with BD, suggesting that anatomical expression profile is correlated with genetic susceptibility to BD, particularly for genes in C2. Our data suggest that expression profiles of BD-associated genes do not explain the majority of structural abnormalities observed in BD, but may be useful in identifying new candidate genes. Our results highlight the complex neuroanatomical basis of BD, and reinforce illness models that emphasize impaired brain connectivity.

Cortical thickness differences between bipolar depression and major depressive disorder

OBJECTIVES

Bipolar disorder (BD) is a psychiatric disorder with high morbidity and mortality that cannot be distinguished from major depressive disorder (MDD) until the first manic episode. A biomarker able to differentiate BD and MDD could help clinicians avoid risks of treating BD with antidepressants without mood stabilizers.

METHODS

Cortical thickness differences were assessed using magnetic resonance imaging in BD depressed patients (n = 18), MDD depressed patients (n = 56), and healthy volunteers (HVs) (n = 54). A general linear model identified clusters of cortical thickness difference between diagnostic groups.

RESULTS

Compared to the HV group, the BD group had decreased cortical thickness in six regions, after controlling for age and sex, located within the frontal and parietal lobes, and the posterior cingulate cortex. Mean cortical thickness changes in clusters ranged from 7.6 to 9.6% (cluster-wise p-values from 1.0 e-4 to 0.037). When compared to MDD, three clusters of lower cortical thickness in BD were identified that overlapped with clusters that differentiated the BD and HV groups. Mean cortical thickness changes in the clusters ranged from 7.5 to 8.2% (cluster-wise p-values from 1.0 e-4 to 0.023). The difference in cortical thickness was more pronounced when the subgroup of subjects with bipolar I disorder (BD-I) was compared to the MDD group.

CONCLUSIONS

Cortical thickness patterns were distinct between BD and MDD. These results are a step toward developing an imaging test to differentiate the two disorders.

Common variants in psychiatric risk genes predict brain structure at birth

Studies in adolescents and adults have demonstrated that polymorphisms in putative psychiatric risk genes are associated with differences in brain structure, but cannot address when in development these relationships arise. To determine if common genetic variants in disrupted-in-schizophrenia-1 (DISC1; rs821616 and rs6675281), catechol-O-methyltransferase (COMT; rs4680), neuregulin 1 (NRG1; rs35753505 and rs6994992), apolipoprotein E (APOE; ε3ε4 vs. ε3ε3), estrogen receptor alpha (ESR1; rs9340799 and rs2234693), brain-derived neurotrophic factor (BDNF; rs6265), and glutamate decarboxylase 1 (GAD1; rs2270335) are associated with individual differences in brain tissue volumes in neonates, we applied both automated region-of-interest volumetry and tensor-based morphometry to a sample of 272 neonates who had received high-resolution magnetic resonance imaging scans. ESR1 (rs9340799) predicted intracranial volume. Local variation in gray matter (GM) volume was significantly associated with polymorphisms in DISC1 (rs821616), COMT, NRG1, APOE, ESR1 (rs9340799), and BDNF. No associations were identified for DISC1 (rs6675281), ESR1 (rs2234693), or GAD1. Of note, neonates homozygous for the DISC1 (rs821616) serine allele exhibited numerous large clusters of reduced GM in the frontal lobes, and neonates homozygous for the COMT valine allele exhibited reduced GM in the temporal cortex and hippocampus, mirroring findings in adults. The results highlight the importance of prenatal brain development in mediating psychiatric risk.

Vertex-based morphometry in euthymic bipolar disorder implicates striatal regions involved in psychomotor function

We hypothesized that psychomotor disturbances in patients with bipolar disorder are associated with morphometric changes in functionally specific regions of the basal ganglia and thalamus. We used structural magnetic resonance imaging and vertex-based morphometry to investigate whether psychomotor performance is associated with changes in volume and shape in euthymic subjects with bipolar disorder (n=27) compared with matched healthy controls (n=27). We saw no significant differences between age- and sex-matched groups in motor performance. We found a statistically significant group difference in the shape of the right putamen in the absence of psychomotor disturbances. There was an association between shape and motor performance in controls that was lacking in patients. We conclude that euthymic subjects with bipolar disorder without psychomotor disturbances show shape changes in regions of the right putamen that contribute to executive functions and motor function. It may be that other brain regions sustain the psychomotor functions that produce nearly identical motor performance in both groups.

Neuropsychological deficits in bipolar depression persist after successful antidepressant treatment

BACKGROUND

Bipolar disorder is a common disabling illness with a lifetime morbid risk of approximately 4%. Neuropsychological deficits constitute enduring trait-like features in bipolar disorder, are associated with each phase of the illness and persist also in euthymia. Total sleep deprivation (TSD) has been shown to cause rapid and sustained antidepressant effects in bipolar depression and to revert the biased self description and speed of information processing present in these patients. The aim of the study was to assess neuropsychological performances first in a sample of bipolar patients during a depressive episode compared to healthy controls and secondly to investigate if TSD treatment would change cognitive performances.

METHODS

One-hundred bipolar patients and 100 healthy controls were evaluated through the Brief Assessment of Cognition in Schizophrenia, 42 patients were assessed before and after TSD treatment.

RESULTS

Bipolar patients obtained significantly lower domain scores across the entire battery compared to healthy subjects. Cognitive deficits persisted in each function despite a clinical improvement of depressive symptomatology.

LIMITATIONS

Limitations of the study include issues such as generalizability, possible undetected past comorbidities, population stratification and ongoing medication.

CONCLUSIONS

This is the first study of the effect of TSD treatment on cognitive performance. TSD treatment improved clinical symptoms but not cognitive deficits however bipolar patients did not experience the well known worsening of performance observed in healthy controls after sleep loss.

Examination of the predictive value of structural magnetic resonance scans in bipolar disorder: a pattern classification approach

BACKGROUND

Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD.

METHOD

GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls.

RESULTS

The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD.

CONCLUSIONS

Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

Frontal white matter alterations are associated with executive cognitive function in euthymic bipolar patients

BACKGROUND

Bipolar affective disorder (BD) is often associated with cognitive dysfunction in executive domains. However the biological underpinnings of cognitive deficits in BD are not sufficiently understood. A growing body of evidence indicates a loss of microstructural integrity in various white matter (WM) fiber tracts in BD. The aim of the current study was to assess potential links between WM structural abnormalities and cognitive performance in euthymic middle-aged BD patients (n=30) and matched healthy controls (n=32).

METHODS

Diffusion tensor imaging (DTI) data was carried out with both voxelwise (tract based spatial statistics, TBSS) and region-of-interest (ROI) based analysis. We compared multiple indices of diffusion including fractional anisotropy (FA), radial (DR), axial (DA) and mean diffusivities (MD).

RESULTS

Increased mean diffusivity was found in the fornix, anterior thalamic radiation, splenium and the truncus of the corpus callosum in BD patients compared with controls. These diffusion changes were significantly associated with poorer performance in executive tasks in BD patients.

CONCLUSIONS

Our results indicate a direct link between executive cognitive functioning and abnormal WM microstructural integrity of fronto-limbic tracts in remitted BD patients, and add evidence to the neuronal disruption that underlies the residual symptomatology of BD.

Neuroanatomical classification in a population-based sample of psychotic major depression and bipolar I disorder with 1 year of diagnostic stability

The presence of psychotic features in the course of a depressive disorder is known to increase the risk for bipolarity, but the early identification of such cases remains challenging in clinical practice. In the present study, we evaluated the diagnostic performance of a neuroanatomical pattern classification method in the discrimination between psychotic major depressive disorder (MDD), bipolar I disorder (BD-I), and healthy controls (HC) using a homogenous sample of patients at an early course of their illness. Twenty-three cases of first-episode psychotic mania (BD-I) and 19 individuals with a first episode of psychotic MDD whose diagnosis remained stable during 1 year of followup underwent 1.5 T MRI at baseline. A previously validated multivariate classifier based on support vector machine (SVM) was employed and measures of diagnostic performance were obtained for the discrimination between each diagnostic group and subsamples of age- and gender-matched controls recruited in the same neighborhood of the patients. Based on T1-weighted images only, the SVM-classifier afforded poor discrimination in all 3 pairwise comparisons: BD-I versus HC; MDD versus HC; and BD-I versus MDD. Thus, at the population level and using structural MRI only, we failed to achieve good discrimination between BD-I, psychotic MDD, and HC in this proof of concept study.

Cerebral gray matter volumes and low-frequency fluctuation of BOLD signals in cocaine dependence: duration of use and gender difference

BACKGROUND

Magnetic resonance imaging has provided a wealth of information on altered brain activations and structures in individuals addicted to cocaine. However, few studies have considered the influence of age and alcohol use on these changes.

METHODS

We examined gray matter volume with voxel based morphometry (VBM) and low frequency fluctuation (LFF) of BOLD signals as a measure of cerebral activity of 84 cocaine dependent (CD) and 86 healthy control (HC) subjects. We performed a covariance analysis to account for the effects of age and years of alcohol use.

RESULTS

Compared to HC, CD individuals showed decreased gray matter (GM) volumes in frontal and temporal cortices, middle/posterior cingulate cortex, and the cerebellum, at p<0.05, corrected for multiple comparisons. The GM volume of the bilateral superior frontal gyri (SFG) and cingulate cortices were negatively correlated with years of cocaine use, with women showing a steeper loss in the right SFG in association with duration of use. In contrast, the right ventral putamen showed increased GM volume in CD as compared to HC individuals. Compared to HC, CD individuals showed increased fractional amplitude of LFF (fALFF) in the thalamus, with no significant overlap with regions showing GM volume loss.

CONCLUSIONS

These results suggested that chronic cocaine use is associated with distinct changes in cerebral structure and activity that can be captured by GM volume and fALFF of BOLD signals.

The spectrum of borderline personality disorder: a neurophysiological view

Borderline Personality Disorder (BPD) has been defined as a personality disorder in all editions of DSM since 1980; namely, DSM III through V. The criteria are a mixture of symptoms and traits; the etiology, a heterogeneous array of genetic, constitutional, and environmental factors. Until recently the diagnosis relied on clinical descriptions. In the last two decades, neurophysiological data, including MRI and fMRI, have established correlates in various brain regions, particularly those involving the frontal lobes and various limbic structures, that show promise of providing a more substantial basis for diagnosis-relying primarily on (internal) brain changes, rather than on (external) clinical observation. Some of the changes in BPD consist of decreased volume in the orbitofrontal and dorsolateral prefrontal cortices and smaller volume in both the amygdala and hippocampus, though with heightened reactivity in the amygdala. Similar abnormalities have been noted in bipolar disorders (BDs) and in ADHD, both of which often accompany BPD and share certain clinical features. Persons with strong genetic predisposition to BDs can develop BPD even in the absence of adverse environmental factors; those with extreme adverse environmental factors (chiefly, early sexual molestation) can develop BPD in the absence of bipolar vulnerability. In some BPD patients, both sets of factors are present. As ideal treatment depends on careful analysis of these factors, neurophysiological testing may permit both more rational, brain-based diagnostic decisions and more appropriate therapeutic strategies.

Laterality interacts with sex across the schizophrenia/bipolarity continuum: an interpretation of meta-analyses of structural MRI

Review of the first comprehensive meta-analysis of VBM (voxel-based morphometry) studies in schizophrenia indicates asymmetrical reductions of anterior cingulate gyrus to the right, and medial temporal lobe (including the uncus) and para-hippocampal gyrus to the left. In subsequent meta-analyses of schizophrenia and bipolar disorder change in these limbic structures is systematically related to change in the insula. Deficits in insula (and para-hippocampal gyrus) to the left, and dorsal anterior cingulate gyrus to the right are greater in schizophrenic psychoses whereas deficits in anterior cingulate to the left and insula to the right are greater in bipolar illness. Thus (1) brain structures implicated in schizophrenia include those implicated in bipolar disorder, (2) the variation that separates the prototypical psychoses may be a subset of that relating to the structural asymmetry (the "torque") characteristic of the human brain, and (3) the meta-analysis of Bora et al. (2012) indicates that laterality of involvement of the insula and cingulate gyrus across the spectrum of bipolar and schizophrenic psychoses is critically dependent upon the sex ratio. Thus structural change underlying the continuum of psychosis relates to the interaction of laterality and sex.

State-dependent changes in hippocampal grey matter in depression

Reduced hippocampal volume has been reported in depression and may be involved in the aetiology of depressive symptoms and vulnerability to depressive relapse. Neuroplasticity following antidepressant drug treatment in the hippocampus has been demonstrated in animal models but adaptive changes after such treatment have not been shown in humans. In this study, we determined whether grey matter loss in the hippocampus in depression (1) is present in medication-free depressed (2) changes in response to antidepressant treatment and (3) is present as a stable trait in medication-free remitted patients. Sixty-four medication-free unipolar depressed patients: 39 currently depressed and 25 in remission, and 66 healthy controls (HC) underwent structural magnetic resonance imaging in a cross-sectional and longitudinal design. Thirty-two currently depressed participants were then treated with the antidepressant citalopram for 8 weeks. Adherence to treatment was evaluated by measuring plasma citalopram concentration. We measured regional variation in grey matter concentration by using voxel-based morphometry-Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra. Patients with current depression had bilaterally reduced grey matter in the hippocampus compared with HC and untreated patients in stable remission with the latter groups not differing. An increase in grey matter was observed in the hippocampus following treatment with citalopram in currently depressed patients. Grey matter reduction in the hippocampus appears specific to the depressed state and is a potential biomarker for a depressive episode.

Gray matter volume as an intermediate phenotype for psychosis: Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP)

OBJECTIVE

The study examined gray matter volume across psychosis diagnoses organized by dimensional and DSM-IV categories from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) sample.

METHOD

In total, 351 probands with psychosis (146 with schizophrenia, 90 with schizoaffective disorder, and 115 with psychotic bipolar I disorder), 369 of their first-degree relatives (134 were relatives of individuals with schizophrenia, 106 of individuals with schizoaffective disorder, and 129 of individuals with psychotic bipolar I disorder), and 200 healthy comparison subjects were assessed. Gray matter volumes from 3-T T1-weighted images were analyzed using the VBM8 toolbox for SPM8, and outcomes were determined at a false discovery rate-corrected threshold of p<0.005.

RESULTS

Across the psychosis dimension, probands (N=351) and relatives with psychosis spectrum disorders (N=34) showed substantial overlapping gray matter reductions throughout the neocortex, whereas relatives without psychosis spectrum (N=332) had normal gray matter volumes relative to comparison subjects. Across DSM-IV diagnoses, schizophrenia and schizoaffective probands showed overlapping gray matter reductions in numerous cortical and subcortical regions, whereas psychotic bipolar probands showed limited gray matter reductions localized to the frontotemporal cortex relative to comparison subjects. All relative groups had gray matter volumes that did not differ from comparison subjects.

CONCLUSIONS

Across the dimensional psychosis categories, these findings indicate extensive neocortical gray matter reductions in psychosis probands and relatives with psychosis spectrum disorders, possibly reflecting lifetime psychosis burden, but normal gray matter in nonpsychotic relatives. Traditional DSM-IV psychosis grouping revealed partially divergent gray matter phenotypes for probands with schizophrenia or schizoaffective disorder (extensive neocortical or subcortical gray matter reductions) relative to those with psychotic bipolar disorder (smaller reductions were limited to frontotemporal regions). The dimensional conceptualization of psychosis appears useful in defining more homogenous disease categories that may help identify underlying psychosis biomarkers and develop a biologically driven diagnostic system and targeted treatments.

The brain in overdrive: a new look at borderline and related disorders

Borderline personality disorder (BPD) has been recognized as heterogeneous, etiologically, stemming from many combinations of genetic and environmental factors BPD never occurs alone: it is always accompanied by traits of other personality disorders and by various symptom-conditions, especially mood disorders. The controversy about linkage between BPD and bipolar disorder could not be resolved when the debate relied only on clinical description. Some twin-studies suggested modest overlap between BPD and bipolar disorder. Current neuroimaging research points to similarities in brain changes among several conditions characterized by emotional over-reactivity to stress: bipolar disorder, certain cases of BPD and attention-deficit hyperactivity (ADHD). These include alterations in the limbic system (e.g., amygdala and hippocampus) and neocortex (especially the prefrontal cortex). An important subset of BPD exists in which brain changes are essentially identical with those of bipolar disorder. Relevant brain-change findings and treatment implications are summarized in this article.

Structural brain alterations in bipolar disorder II: a combined voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) study

BACKGROUND

Brain structural changes have been described in bipolar disorder (BP), but usually studies focused on both I and II subtypes indiscriminately and investigated changes in either brain volume or white matter (WM) integrity. We used combined voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analysis to track changes in the grey matter (GM) and WM in the brains of patients affected by BPII, as compared to healthy controls.

METHODS

Using VBM and DTI, we scanned 20 DSM-IV-TR BPII patients in their euthymic phase and 21 healthy, age- and gender-matched volunteers with no psychiatric history.

RESULTS

VBM showed decreases in GM of BPII patients, compared to controls, which were diffuse in nature and most prominent in the right middle frontal gyrus and in the right superior temporal gurus. DTI showed significant and widespread FA reduction in BPII patients in all major WM tracts, including cortico-cortical association tracts.

LIMITATIONS

The small sample size limits the generalisability of our findings.

CONCLUSIONS

Reduced GM volumes and WM integrity changes in BPII patients are not prominent like those previously reported in bipolar disorder type-I and involve cortical structures and their related association tracts.

Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects

Although structural magnetic resonance imaging (MRI) has revealed partly non-overlapping brain abnormalities in schizophrenia and bipolar disorder, it is unknown whether structural MRI scans can be used to separate individuals with schizophrenia from those with bipolar disorder. An algorithm capable of discriminating between these two disorders could become a diagnostic aid for psychiatrists. Here, we scanned 66 schizophrenia patients, 66 patients with bipolar disorder and 66 healthy subjects on a 1.5T MRI scanner. Three support vector machines were trained to separate patients with schizophrenia from healthy subjects, patients with schizophrenia from those with bipolar disorder, and patients with bipolar disorder from healthy subjects, respectively, based on their gray matter density images. The predictive power of the models was tested using cross-validation and in an independent validation set of 46 schizophrenia patients, 47 patients with bipolar disorder and 43 healthy subjects scanned on a 3T MRI scanner. Schizophrenia patients could be separated from healthy subjects with an average accuracy of 90%. Additionally, schizophrenia patients and patients with bipolar disorder could be distinguished with an average accuracy of 88%.The model delineating bipolar patients from healthy subjects was less accurate, correctly classifying 67% of the healthy subjects and only 53% of the patients with bipolar disorder. In the latter group, lithium and antipsychotics use had no influence on the classification results. Application of the 1.5T models on the 3T validation set yielded average classification accuracies of 76% (healthy vs schizophrenia), 66% (bipolar vs schizophrenia) and 61% (healthy vs bipolar). In conclusion, the accurate separation of schizophrenia from bipolar patients on the basis of structural MRI scans, as demonstrated here, could be of added value in the differential diagnosis of these two disorders. The results also suggest that gray matter pathology in schizophrenia and bipolar disorder differs to such an extent that they can be reliably differentiated using machine learning paradigms.

Structural brain features of borderline personality and bipolar disorders

A potential overlap between bipolar disorder (BD) and borderline personality disorder (BPD) has been recently proposed. We aimed to assess similarities and differences of brain structural features in BD and BPD. Structural magnetic resonance imaging (MRI) was performed in 26 inpatients with BPD, 14 with BD, and 40 age-and sex-matched healthycontrols (HC). Voxel-based morphometry analysis with Statistical Parametric Mapping (SPM) was used to localize and quantify gray (GM) and white matter (WM) abnormalities in BD and BPD compared to HC and to identify those specifically affected in each patient group. Region of interest (ROI)-based analyses were also performed for confirmation. GM density changes in BD are significantly more diffuse and severe than in BPD, as demonstrated in both SPM- and ROI-based analyses. The topography of GM alterations showed some regions of overlap, but each disorder had specific regions of abnormality (involving both cortical and subcortical structures in BD, confined mainly to fronto-limbic regions in BPD). WM density changes were less pronounced in both conditions and involved completely different regions. Although BPD and BD show a considerable overlap of GM changes, the topography of alterations is more consistent with the separate conditions hypothesis and with the vulnerability of separate neural systems.

White matter alterations in antipsychotic- and mood stabilizer-naïve individuals with bipolar II/NOS disorder

Structural magnetic resonance imaging (MRI) studies using voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) have been inconsistent in demonstrating impairments in gray matter (GM) and white matter (WM) structures in bipolar disorder (BD). This may be a consequence of significant confounding effects of medication, illness history and selection of controls in existing studies. Study of bipolar II or not-otherwise-specified (BD II/NOS) disorder provides a solution to these confounds and a bridge to unipolar cases across the affective spectrum. Thirty-eight euthymic, antipsychotic- and mood stabilizer-naïve young adults (mean age = 20.9 years) with BD II/NOS and 37 age-, cognitive ability- and gender-matched healthy controls (HCs) underwent MRI. Voxel-wise and regional gray matter volume comparisons were conducted using voxel-based morphometry (VBM). Tract-based spatial statistics (TBSS) were used to assess whole-brain WM, as indexed using fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusion values. No between-group differences were observed for whole-brain VBM comparisons. By contrast, in comparison to HCs, participants with BD II/NOS had significant widespread reductions in FA and increased MD and perpendicular diffusion values in virtually all the major cortical white matter tracts. These data suggest pathophysiological involvement of WM microstructures - but not GM macrostructures - in high functioning BD II/NOS patients at an early age and before significant clinical adversity has been recorded. We propose that white matter development is a valid candidate target for understanding genetic and environmental antecedents to bipolar disorder and mood disorder more generally.

Brain characterization using normalized quantitative magnetic resonance imaging

Objectives

To present a method for generating reference maps of typical brain characteristics of groups of subjects using a novel combination of rapid quantitative Magnetic Resonance Imaging (qMRI) and brain normalization. The reference maps can be used to detect significant tissue differences in patients, both locally and globally.

Materials and Methods

A rapid qMRI method was used to obtain the longitudinal relaxation rate (R₁), the transverse relaxation rate (R₂) and the proton density (PD). These three tissue properties were measured in the brains of 32 healthy subjects and in one patient diagnosed with Multiple Sclerosis (MS). The maps were normalized to a standard brain template using a linear affine registration. The differences of the mean value ofR₁, R₂ and PD of 31 healthy subjects in comparison to the oldest healthy subject and in comparison to an MS patient were calculated. Larger anatomical structures were characterized using a standard atlas. The vector sum of the normalized differences was used to show significant tissue differences.

Results

The coefficient of variation of the reference maps was high at the edges of the brain and the ventricles, moderate in the cortical grey matter and low in white matter and the deep grey matter structures. The elderly subject mainly showed significantly lower R₁ and R₂ and higher PD values along all sulci. The MS patient showed significantly lower R₁ and R₂ and higher PD values at the edges of the ventricular system as well as throughout the periventricular white matter, at the internal and external capsules and at each of the MS lesions.

Conclusion

Brain normalization of rapid qMRI is a promising new method to generate reference maps of typical brain characteristics and to automatically detect deviating tissue properties in the brain.

Decreased gray matter volume of the medial orbitofrontal cortex in panic disorder with agoraphobia: a preliminary study

BACKGROUND

Patients with panic disorder with agoraphobia (PDA) have clinical symptoms such as the fear of being outside or of open spaces from which escape would be difficult. Although recent neurobiological studies have suggested that fear conditioning and extinction are associated with PDA, no study has examined the possible structural abnormalities in patients with PDA.

METHODS

This preliminary study compares the gray matter volume among patients with PDA, those with panic disorder without agoraphobia (PDW), and healthy controls (HC) using high-resolution 3.0 T magnetic resonance imaging (MRI) with voxel-based morphometry (VBM).

RESULTS

Compared with HC, patients with PDA showed decreased gray matter volume in their left medial orbitofrontal gyrus. However, differences were not found in the gray matter volumes of patients with PDW and whole panic disorder compared with HC.

CONCLUSIONS

These findings suggest that the phobic avoidance found in patients with PDA arise from abnormalities in the medial orbitofrontal cortex, which plays an important role in fear extinction. Future studies should investigate the neuroanatomical substrates of PDA and distinguish them from those of PDW.

Simultaneous EEG-fMRI acquisition at low, high and ultra-high magnetic fields up to 9.4 T: perspectives and challenges

In this perspectives article we highlight the advantages of simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). As MRI moves towards using ultra-high magnetic fields in the quest for increased signal-to-noise, the question arises whether combined EEG-fMRI measurements are feasible at magnetic fields of 7 T and higher. We describe the challenges of MRI-EEG at 1.5, 3, 7 and 9.4 T and review the proposed solutions. In an outlook, we discuss further developments such as simultaneous trimodal imaging using MR, positron emission tomography (PET) and EEG under the same physiological conditions in the same subject.

Statistical analysis of brain tissue images in the wavelet domain: wavelet-based morphometry

Wavelet-based methods have been developed for statistical analysis of functional MRI and PET data, where the wavelet transformation is employed as a tool for efficient signal representation. A number of studies using these approaches have reported better estimation capabilities, in terms of increased sensitivity and specificity, than the standard statistical analyses in the spatial domain. In line with these previous studies, the present report proposes a statistical analysis in the wavelet domain for the estimation of inter-group differences from structural MRI data. The procedure, called wavelet-based morphometry (WBM), was implemented under a voxel-based morphometry (VBM) style analysis. It was evaluated by comparing the gray-matter images of a group of 32 healthy subjects whose images were artificially altered to induce thinning of the cortex, with a different group of 32 healthy subjects whose images were unaltered. In order to quantify the performance of the reconstruction from a practical perspective, the same comparison was also conducted with standard VBM using SPM's Gaussian random fields and FSL's cluster-based statistics, family-wise error corrected, for datasets spatially-normalized via two different registration methods (i.e., SyN and FNIRT). The effect of using different amounts of smoothing, Battle-Lemarié filters and resolution levels in the wavelet transform was also investigated. Results support the proposed approach as a different and promising methodology to assess the structural morphometric differences between different populations of subjects.