55 results match your criteria: "BM-SCIENCE-Brain and Mind Technologies Research Centre[Affiliation]"

Recent reports on functional brain imaging in major depression have lead to an assumption that observed psychopathology might be related to an altered brain functional connectivity. Our hypothesis was that an increase in brain functional connectivity occurs in major depression. As a measure of functional connectivity, the electroencephalogram (EEG) structural synchrony approach was used in 12 medication-free depressive outpatients and 10 control subjects.

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Objective: In the present experimental study, we examined topographic variability of composition of brain oscillations and their temporal behavior in frequencies from 0.5 to 30 Hz of interictal EEG without epileptiform abnormalities and healthy EEG.

Methods: Spatio-temporal variability of brain oscillations (indexed by short-term EEG spectral patterns (SPs)) was assessed by the probability-classification analysis of SPs.

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Recent research emphasizes that majority of brain disorders and psychiatric problems are accompanied by disruption in the temporal structure of brain activity. From this perspective, disruption is viewed as a disorder of the metastable balance between large-scale integration and independent processing in the brain, in favor of either independent or hyper-ordered processing. This paper proposes that the future of psychopharmacology lies in its ability to design the psychotropic drugs which can restore the normal temporal structure and metastable structure of brain activity.

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Even though functional brain connectivity is an influential concept in modern cognitive neuroscience, it is a very controversial notion. This is why further theoretical and methodological clarification are needed to help define precisely what is meant by functional connectivity and to help frame-associated issues. In this review we present the neurophysiological concept of functional connectivity, which utilizes in a plausible manner the notion of neural assemblies, as well as local and large-scale levels of description.

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The current paper focuses on a relatively new and promising area of the study of EEG transformations during brain information processing based on the reduction of the signal to the discrete quasi-stationary segment sequences which may reflect individual brain microstates or discrete operations. In this framework, the complex brain functions require integration of several operations throughout the whole neocortex. However, the role of inhibitory brain systems in such processes is still unsettled.

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