EEG studies of wakeful rest have shown that there are brief periods in which global electrical brain activity on the scalp remains semi-stable (so-called microstates). Topographical analyses of this activity have revealed that much of the variance is explained by four distinct microstates that occur in a repetitive sequence. A recent fMRI study showed that these four microstates correlated with four known functional systems, each of which is activated by specific cognitive functions and sensory inputs. The present study used high density EEG to examine the degree to which spatial and temporal properties of microstates may be altered by manipulating cognitive task (a serial subtraction task vs. wakeful rest) and the availability of visual information (eyes open vs. eyes closed conditions). The hypothesis was that parameters of microstate D would be altered during the serial subtraction task because it is correlated with regions that are part of the dorsal attention functional system. It was also expected that the sequence of microstates would preferentially transition from all other microstates to microstate D during the task as compared to rest. Finally, it was hypothesized that the eyes open condition would significantly increase one or more microstate parameters associated with microstate B, which is associated with the visual system. Topographical analyses indicated that the duration, coverage, and occurrence of microstate D were significantly higher during the cognitive task compared to wakeful rest; in addition, microstate C, which is associated with regions that are part of the default mode and cognitive control systems, was very sensitive to the task manipulation, showing significantly decreased duration, coverage, and occurrence during the task condition compared to rest. Moreover, microstate B was altered by manipulations of visual input, with increased occurrence and coverage in the eyes open condition. In addition, during the eyes open condition microstates A and D had significantly shorter durations, while C had increased occurrence. Microstate D had decreased coverage in the eyes open condition. Finally, at least 15 microstates (identified via k-means clustering) were required to explain a similar amount of variance of EEG activity as previously published values. These results support important aspects of our hypotheses and demonstrate that cognitive manipulation of microstates is possible, but the relationships between microstates and their corresponding functional systems are complex. Moreover, there may be more than four primary microstates.
Patients with bipolar disorder and schizophrenia often show decision-making deficits in everyday circumstances. A failure to appropriately weigh immediate versus future consequences of choices may contribute to these deficits. We used the delay discounting task in individuals with bipolar disorder (BD) or schizophrenia (SZ) to investigate their temporal decision-making. Twenty-two individuals with BD, 21 individuals with SZ and 31 healthy individuals completed the delay discounting task along with neuropsychological measures of working memory and cognitive function. Both BD and SZ groups discounted delayed rewards more steeply than the healthy group even after controlling for current substance use, age, gender, and employment. Hierarchical multiple regression analyses showed that discounting rate was associated both with diagnostic group and working memory/intelligence composite scores. In each group, working memory or intelligence scores negatively correlated with discounting rate. The results suggest that 1) both BD and SZ groups value smaller, immediate rewards more than larger, delayed rewards compared to the healthy group and 2) working memory or intelligence is related to temporal decision-making in individuals with BD or SZ as well as in healthy individuals.
Disruption of functional connectivity may be a key feature of bipolar disorder (BD) which reflects disturbances of synchronization and oscillations within brain networks. We investigated whether the resting electroencephalogram (EEG) in patients with BD showed altered synchronization or network properties. Resting-state EEG was recorded in 57 BD type-I patients and 87 healthy control subjects. Functional connectivity between pairs of EEG channels was measured using synchronization likelihood (SL) for 5 frequency bands (δ, θ, α, β, and γ). Graph-theoretic analysis was applied to SL over the electrode array to assess network properties. BD patients showed a decrease of mean synchronization in the alpha band, and the decreases were greatest in fronto-central and centro-parietal connections. In addition, the clustering coefficient and global efficiency were decreased in BD patients, whereas the characteristic path length increased. We also found that the normalized characteristic path length and small-worldness were significantly correlated with depression scores in BD patients. These results suggest that BD patients show impaired neural synchronization at rest and a disruption of resting-state functional connectivity.
Resting state electroencephalogram (EEG) abnormalities in schizophrenia and bipolar disorder patients suggest alterations in neural oscillatory activity. However, few studies directly compare these anomalies between patient groups, and none have examined EEG coherence. Therefore, this study investigated whether these electrophysiological characteristics differentiate clinical populations from one another, and from non-psychiatric controls. To address this question, resting EEG power and coherence were assessed in 76 bipolar patients (BP), 132 schizophrenia patients (SZ), and 136 non-psychiatric controls (NC). We conducted separate repeated-measures ANOVAs to examine group differences within seven frequency bands across several brain regions. BP showed significantly greater power relative to SZ at higher frequencies including Beta and Gamma across all regions. In terms of intra-hemispheric coherence, while SZ generally exhibited higher coherence at Delta compared to NC and BP, both SZ and BP showed higher coherence at Alpha1 and Alpha2. In contrast, BP and HC showed higher coherence within hemispheres compared to SZ at Beta 1. In terms of inter-hemispheric coherence, SZ displayed higher coherence compared to NC at temporal sites at both Alpha1 and Alpha2. Taken together, BP exhibited increased high frequency power with few disruptions in neural synchronization. In contrast, SZ generally exhibited enhanced synchronization within and across hemispheres. These findings suggest that resting EEG can be a sensitive measure for differentiating between clinical disorders.
Motor dysfunction is a consistently reported but understudied aspect of schizophrenia. Postural sway area was examined in individuals with schizophrenia under four conditions with different amounts of visual and proprioceptive feedback: eyes open or closed and feet together or shoulder width apart. The nonlinear complexity of postural sway was assessed by detrended fluctuation analysis (DFA). The schizophrenia group (n = 27) exhibited greater sway area compared to controls (n = 37). Participants with schizophrenia showed increased sway area following the removal of visual input, while this pattern was absent in controls. Examination of DFA revealed decreased complexity of postural sway and abnormal changes in complexity upon removal of visual input in individuals with schizophrenia. Additionally, less complex postural sway was associated with increased symptom severity in participants with schizophrenia. Given the critical involvement of the cerebellum and related circuits in postural stability and sensorimotor integration, these results are consistent with growing evidence of motor, cerebellar, and sensory integration dysfunction in the disorder, and with theoretical models that implicate cerebellar deficits and more general disconnection of function in schizophrenia.
Theoretical models suggest that symptoms of schizophrenia may be due to a dysfunctional modulatory system associated with the cerebellum. Although it has long been known that the cerebellum plays a critical role in associative learning and motor timing, recent evidence suggests that it also plays a role in nonmotor psychological processes. Indeed, cerebellar anomalies in schizophrenia have been linked to cognitive dysfunction and poor long-term outcome. To test the hypothesis that schizophrenia is associated with cerebellar dysfunction, cerebellar-dependent, delay eye-blink conditioning was examined in 62 individuals with schizophrenia and 62 age-matched nonpsychiatric comparison subjects. The conditioned stimulus was a 400 ms tone, which co-terminated with a 50 ms unconditioned stimulus air puff. A subset of participants (25 with schizophrenia and 29 controls) also completed the Wechsler Abbreviated Scale of Intelligence. Participants with schizophrenia exhibited lower rates of eye-blink conditioning, including earlier (less adaptively timed) conditioned response latencies. Cognitive functioning was correlated with the rate of conditioned responsing in the non-psychiatric comparison subjects but not among those with schizophrenia, and the magnitude of these correlations significantly differed between groups. These findings are consistent with models of schizophrenia in which disruptions within the corticocerebellar-thalamic-cortical (CCTC) brain circuit are postulated to underlie the cognitive fragmentation that characterizes the disorder.
A disturbance in the integration of information during mental processing has been implicated in schizophrenia, possibly due to faulty communication within and between brain regions. Graph theoretic measures allow quantification of functional brain networks. Functional networks are derived from correlations between time courses of brain regions. Group differences between SZ and control groups have been reported for functional network properties, but the potential of such measures to classify individual cases has been little explored. We tested whether the network measure of betweenness centrality could classify persons with schizophrenia and normal controls. Functional networks were constructed for 19 schizophrenic patients and 29 non-psychiatric controls based on resting state functional MRI scans. The betweenness centrality of each node, or fraction of shortest-paths that pass through it, was calculated in order to characterize the centrality of the different regions. The nodes with high betweenness centrality agreed well with hub nodes reported in previous studies of structural and functional networks. Using a linear support vector machine algorithm, the schizophrenia group was differentiated from non-psychiatric controls using the ten nodes with highest betweenness centrality. The classification accuracy was around 80%, and stable against connectivity thresholding. Better performance was achieved when using the ranks as feature space as opposed to the actual values of betweenness centrality. Overall, our findings suggest that changes in functional hubs are associated with schizophrenia, reflecting a variation of the underlying functional network and neuronal communications. In addition, a specific network property, betweenness centrality, can classify persons with SZ with a high level of accuracy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.