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Spatiotemporal precision of neuroimaging in psychiatry

McFadyen, Jessica; Dolan, Raymond J; (2022) Spatiotemporal precision of neuroimaging in psychiatry. Biological Psychiatry 10.1016/j.biopsych.2022.08.016. (In press). Green open access

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Abstract

Aberrant patterns of cognition, perception, and behaviour seen in psychiatric disorders are thought to be driven by a complex interplay of neural processes that evolve at a rapid temporal scale. Understanding these dynamic processes in vivo in humans has been hampered by a trade-off between the spatial and temporal resolution inherent to current neuroimaging technology. A recent trend in psychiatric research has been the use of high temporal resolution imaging, particularly magnetoencephalography (MEG), often in conjunction with sophisticated machine learning decoding techniques. Developments here promise novel insights into the spatiotemporal dynamics of cognitive phenomena, including domains relevant to psychiatric illness such as reward and avoidance learning, memory, and planning. This review considers recent advances afforded by exploiting this increased spatiotemporal precision, with specific reference to applications the seek to drive a mechanistic understanding of psychopathology and the realisation of preclinical translation.

Type: Article
Title: Spatiotemporal precision of neuroimaging in psychiatry
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.biopsych.2022.08.016
Publisher version: https://doi.org/10.1016/j.biopsych.2022.08.016
Language: English
Additional information: © 2022 Published by Elsevier Inc on behalf of Society of Biological Psychiatry under a Creative Commons license (https://creativecommons.org/licenses/by/4.0/).
Keywords: MEG, decoding, replay, machine learning, representations, neuroimaging
UCL classification: 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 > Imaging Neuroscience
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
URI: https://discovery.ucl.ac.uk/id/eprint/10154683
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