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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
Peak alpha frequency and electroencephalographic microstates are correlated with aggression in schizophrenia
Michael Murphy1, Ricardo E Carrión2, Jose Rubio2
1McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA.
Abstract:
Large scale retrospective studies have shown an association between schizophrenia and risk of violence. Overall, this increase in risk is small and does not justify or support stigmatizing public perceptions or media depictions of people with schizophrenia. Nonetheless, in some situations, some symptoms of schizophrenia can increase the risk of violent behavior. Prediction of this behavior would allow high impact preventive interventions. However, to date the neurobiological correlates of violent behavior in schizophrenia are not well understood, precluding the development of prognostic biomarkers. We used electroencephalography to measure alpha activity and microstates from 31 patients with schizophrenia and 18 age matched controls. Participants also completed multiple assessments of current aggressive tendencies and their lifetime history of aggressive acts. We found that individual alpha peak frequency was negatively correlated with aggression scores in both patients and controls (largest Spearman's r = -0.45). Furthermore, this result could be replicated in data taken from a single frontal channel suggesting that this may be possible to obtain in routine clinical settings (largest Spearman's r = -0.40). We also found that transitions between microstates corresponding to auditory and visual networks were inversely correlated with aggression scores. Finally, we found that, within patients, aggression was correlated with the degree of randomness between microstate transitions. This suggests that aggression is related to inappropriate switching between large scale brain networks and subsequent failure to appropriately integrate complicated environmental and internal stimuli. By elucidating some of the electrophysiological correlates of aggression, these data facilitate the development of prognostic biomarkers.
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