Global brain connectivity alterations in patients with schizophrenia and bipolar spectrum disorders.

BACKGROUND: The human brain is organized into functionally distinct modules of which interactions constitute the human functional connectome. Accumulating evidence has implicated perturbations in the patterns of brain connectivity across a range of neurologic and neuropsychiatric disorders, but little is known about diagnostic specificity. Schizophrenia and bipolar disorders are severe mental disorders with partly overlapping symptomatology. Neuroimaging has demonstrated brain network disintegration in the pathophysiologies; however, to which degree the 2 diagnoses present with overlapping abnormalities remains unclear. METHODS: We collected resting-state fMRI data from patients with schizophrenia or bipolar disorder and from healthy controls. Aiming to characterize connectivity differences across 2 severe mental disorders, we derived global functional connectivity using eigenvector centrality mapping, which allows for regional inference of centrality or importance in the brain network. RESULTS: Seventy-one patients with schizophrenia, 43 with bipolar disorder and 196 healthy controls participated in our study. We found significant effects of diagnosis in 12 clusters, where pairwise comparisons showed decreased global connectivity in high-centrality clusters: sensory regions in patients with schizophrenia and subcortical regions in both patient groups. Increased connectivity occurred in frontal and parietal clusters in patients with schizophrenia, with intermediate effects in those with bipolar disorder. Patient groups differed in most cortical clusters, with the strongest effects in sensory regions. LIMITATIONS: Methodological concerns of in-scanner motion and the use of full correlation measures may make analyses more vulnerable to noise. CONCLUSION: Our results show decreased eigenvector centrality of limbic structures in both patient groups and in sensory regions in patients with schizophrenia as well as increased centrality in frontal and parietal regions in both groups, with stronger effects in patients with schizophrenia.

Functional connectivity indicates differential roles for the intraparietal sulcus and the superior parietal lobule in multiple object tracking.

Attentive tracking requires sustained object-based attention, rather than passive vigilance or rapid attentional shifts to brief events. Several theories of tracking suggest a mechanism of indexing objects that allows for attentional resources to be directed toward the moving targets. Imaging studies have shown that cortical areas belonging to the dorsal frontoparietal attention network increase BOLD-signal during multiple object tracking (MOT). Among these areas, some studies have assigned IPS a particular role in object indexing, but the neuroimaging evidence has been sparse. In the present study, we tested participants on a continuous version of the MOT task in order to investigate how cortical areas engage in functional networks during attentional tracking. Specifically, we analyzed the data using eigenvector centrality mapping (ECM) analysis, which provides estimates of individual voxels' connectedness with hub-like parts of the functional network. The results obtained using permutation based voxel-wise statistics support the proposed role for the IPS in object indexing as this region displayed increased centrality during tracking as well as increased functional connectivity with both prefrontal and visual perceptual cortices. In contrast, the opposite pattern was observed for the SPL, with decreasing centrality, as well as reduced functional connectivity with the visual and frontal cortices, in agreement with a hypothesized role for SPL in attentional shifts. These findings provide novel evidence that IPS and SPL serve different functional roles during MOT, while at the same time being highly engaged during tracking as measured by BOLD-signal changes.

Thalamo-cortical functional connectivity in schizophrenia and bipolar disorder.

The thalamus is a highly connected subcortical structure that relays and integrates sensory and cortical information, which is critical for coherent and accurate perceptual awareness and cognition. Thalamic dysfunction is a classical finding in schizophrenia (SZ), and resting-state functional MRI has implicated somatomotor and frontal lobe thalamic dysconnectivity. However, it remains unclear whether these findings generalize to different psychotic disorders, are confined to specific thalamic sub-regions, and how they relate to structural thalamic alterations. Within-thalamic and thalamo-cortical functional connectivity was assessed using resting-state functional MRI data obtained from patients with SZ (n = 96), bipolar disorder (BD, n = 57), and healthy controls (HC, n = 280). Further, we used thalamic sub-regions as seeds to investigate specific cortical connectivity patterns, and performed structural analyses of thalamic volume and shape. Results showed reduced within-thalamic connectivity and thalamo-frontoparietal coupling in SZ and increased thalamo-somatomotor connectivity in BD. One thalamic sub-region showed increased sensory connectivity in SZ and eight sub-regions showed reductions with frontal and posterior areas. Reduced gray matter and shape abnormalities were found in frontal-projecting regions in both SZ and BD, but did not seem to explain reduced functional connectivity. Aberrant thalamo-cortical connectivity patterns in SZ and BD supports the notion of the thalamus as a key structure in the functional connectome across the psychosis spectrum, and the frontal and somatomotor anatomical distribution is in line with the characteristic cognitive and perceptual symptoms in psychotic disorders.

Consistent Functional Connectivity Alterations in Schizophrenia Spectrum Disorder: A Multisite Study.

Schizophrenia (SZ) is a severe mental illness with high heritability and complex etiology. Mounting evidence from neuroimaging has implicated disrupted brain network connectivity in the pathophysiology. However, previous findings are inconsistent, likely due to a combination of methodological and clinical variability and relatively small sample sizes. Few studies have used a data-driven approach for characterizing pathological interactions between regions in the whole brain and evaluated the generalizability across independent samples. To overcome this issue, we collected resting-state functional magnetic resonance imaging data from 3 independent samples (1 from Norway and 2 from Sweden) consisting of 182 persons with a SZ spectrum diagnosis and 348 healthy controls. We used a whole-brain data-driven definition of network nodes and regularized partial correlations to evaluate and compare putatively direct brain network node interactions between groups. The clinical utility of the functional connectivity features and the generalizability of effects across samples were evaluated by training and testing multivariate classifiers in the independent samples using machine learning. Univariate analyses revealed 14 network edges with consistent reductions in functional connectivity encompassing frontal, somatomotor, visual, auditory, and subcortical brain nodes in patients with SZ. We found a high overall accuracy in classifying patients and controls (up to 80%) using independent training and test samples, strongly supporting the generalizability of connectivity alterations across different scanners and heterogeneous samples. Overall, our findings demonstrate robust reductions in functional connectivity in SZ spectrum disorders, indicating disrupted information flow in sensory, subcortical, and frontal brain regions.

Cognitive Effort and Schizophrenia Modulate Large-Scale Functional Brain Connectivity.

Schizophrenia (SZ) is characterized by cognitive dysfunction and disorganized thought, in addition to hallucinations and delusions, and is regarded a disorder of brain connectivity. Recent efforts have been made to characterize the underlying brain network organization and interactions. However, to which degree connectivity alterations in SZ vary across different levels of cognitive effort is unknown. Utilizing independent component analysis (ICA) and methods for delineating functional connectivity measures from functional magnetic resonance imaging (fMRI) data, we investigated the effects of cognitive effort, SZ and their interactions on between-network functional connectivity during 2 levels of cognitive load in a large and well-characterized sample of SZ patients (n = 99) and healthy individuals (n = 143). Cognitive load influenced a majority of the functional connections, including but not limited to fronto-parietal and default-mode networks, reflecting both decreases and increases in between-network synchronization. Reduced connectivity in SZ was identified in 2 large-scale functional connections across load conditions, with a particular involvement of an insular network. The results document an important role of interactions between insular, default-mode, and visual networks in SZ pathophysiology. The interplay between brain networks was robustly modulated by cognitive effort, but the reduced functional connectivity in SZ, primarily related to an insular network, was independent of cognitive load, indicating a relatively general brain network-level dysfunction.

Disintegration of Sensorimotor Brain Networks in Schizophrenia.

BACKGROUND: Schizophrenia is a severe mental disorder associated with derogated function across various domains, including perception, language, motor, emotional, and social behavior. Due to its complex symptomatology, schizophrenia is often regarded a disorder of cognitive processes. Yet due to the frequent involvement of sensory and perceptual symptoms, it has been hypothesized that functional disintegration between sensory and cognitive processes mediates the heterogeneous and comprehensive schizophrenia symptomatology. METHODS: Here, using resting-state functional magnetic resonance imaging in 71 patients and 196 healthy controls, we characterized the standard deviation in BOLD (blood-oxygen-level-dependent) signal amplitude and the functional connectivity across a range of functional brain networks. We investigated connectivity on the edge and node level using network modeling based on independent component analysis and utilized the brain network features in cross-validated classification procedures. RESULTS: Both amplitude and connectivity were significantly altered in patients, largely involving sensory networks. Reduced standard deviation in amplitude was observed in a range of visual, sensorimotor, and auditory nodes in patients. The strongest differences in connectivity implicated within-sensorimotor and sensorimotor-thalamic connections. Furthermore, sensory nodes displayed widespread alterations in the connectivity with higher-order nodes. We demonstrated robustness of effects across subjects by significantly classifying diagnostic group on the individual level based on cross-validated multivariate connectivity features. CONCLUSION: Taken together, the findings support the hypothesis of disintegrated sensory and cognitive processes in schizophrenia, and the foci of effects emphasize that targeting the sensory and perceptual domains may be key to enhance our understanding of schizophrenia pathophysiology.

CACNA1C risk variant and amygdala activity in bipolar disorder, schizophrenia and healthy controls.

OBJECTIVES: Several genetic studies have implicated the CACNA1C SNP rs1006737 in bipolar disorder (BD) and schizophrenia (SZ) pathology. This polymorphism was recently found associated with increased amygdala activity in healthy controls and patients with BD. We performed a functional Magnetic Resonance Imaging (fMRI) study in a sample of BD and SZ cases and healthy controls to test for altered amygdala activity in carriers of the rs1006737 risk allele (AA/AG), and to investigate if there were differences across the diagnostic groups. METHODS: Rs1006737 was genotyped in 250 individuals (N = 66 BD, 61 SZ and 123 healthy controls), all of Northern European origin, who underwent an fMRI negative faces matching task. Statistical tests were performed with a model correcting for sex, age, diagnostic category and medication status in the total sample, and then in each diagnostic group. RESULTS: In the total sample, carriers of the risk allele had increased activation in the left amygdala. Group-wise analyses showed that this effect was significant in the BD group, but not in the other diagnostic groups. However, there was no significant interaction effect for the risk allele between BD and the other groups. CONCLUSIONS: These results indicate that CACNA1C SNP rs1006737 affects amygdala activity during emotional processing across all diagnostic groups. The current findings add to the growing body of knowledge of the pleiotropic effect of this polymorphism, and further support that ion channel dysregulation is involved in the underlying mechanisms of BD and SZ.