UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Clinical Applications of Stochastic Dynamic Models of the Brain, Part II: A Review

Roberts, JA; Friston, KJ; Breakspear, M; (2017) Clinical Applications of Stochastic Dynamic Models of the Brain, Part II: A Review. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging , 2 (3) pp. 225-234. 10.1016/j.bpsc.2016.12.009. Green open access

[thumbnail of Friston_SDMs_ms2nofigs_part2_161107.pdf]
Preview
Text
Friston_SDMs_ms2nofigs_part2_161107.pdf - Accepted Version

Download (671kB) | Preview

Abstract

Brain activity derives from intrinsic dynamics (due to neurophysiology and anatomical connectivity) in concert with stochastic effects that arise from sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random fluctuations can be studied with stochastic dynamic models (SDMs). This article, Part II of a two-part series, reviews applications of SDMs to large-scale neural systems in health and disease. Stochastic models have already elucidated a number of pathophysiological phenomena, such as epilepsy and hypoxic ischemic encephalopathy, although their use in biological psychiatry remains rather nascent. Emerging research in this field includes phenomenological models of mood fluctuations in bipolar disorder and biophysical models of functional imaging data in psychotic and affective disorders. Together with deeper theoretical considerations, this work suggests that SDMs will play a unique and influential role in computational psychiatry, unifying empirical observations with models of perception and behavior.

Type: Article
Title: Clinical Applications of Stochastic Dynamic Models of the Brain, Part II: A Review
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.bpsc.2016.12.009
Publisher version: http://dx.doi.org/10.1016/j.bpsc.2016.12.009
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Computational neuroscience, Computational psychiatry, Epilepsy, Mathematical modeling, Melancholia, Stochastic
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10057807
Downloads since deposit
423Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item