The psychological correlates of distinct neural states occurring during wakeful rest.

Autor: Karapanagiotidis T; Department of Psychology, York Neuroimaging Centre, University of York, York, YO10 5DD, UK. theodoros.karapanagiotidis@york.ac.uk., Vidaurre D; Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK.; Department of Clinical Medicine, Center of Functionally Integrative Neuroscience, Aarhus University, 8000, Aarhus, Denmark., Quinn AJ; Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK., Vatansever D; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, People's Republic of China., Poerio GL; Department of Psychology, University of Essex, Colchester, Essex, CO4 3SQ, UK., Turnbull A; Department of Psychology, York Neuroimaging Centre, University of York, York, YO10 5DD, UK., Ho NSP; Department of Psychology, York Neuroimaging Centre, University of York, York, YO10 5DD, UK., Leech R; Centre for Neuroimaging Science, Kings College, London, SE5 8AF, UK., Bernhardt BC; McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, H3A 2B4, Canada., Jefferies E; Department of Psychology, York Neuroimaging Centre, University of York, York, YO10 5DD, UK., Margulies DS; Brain and Spine Institute (ICM), National Center for Scientific Research, Paris, 75013, France., Nichols TE; Oxford Centre for Functional MRI of the Brain, Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK., Woolrich MW; Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK., Smallwood J; Department of Psychology, York Neuroimaging Centre, University of York, York, YO10 5DD, UK.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2020 Dec 03; Vol. 10 (1), pp. 21121. Date of Electronic Publication: 2020 Dec 03.
DOI: 10.1038/s41598-020-77336-z
Abstrakt: When unoccupied by an explicit external task, humans engage in a wide range of different types of self-generated thinking. These are often unrelated to the immediate environment and have unique psychological features. Although contemporary perspectives on ongoing thought recognise the heterogeneity of these self-generated states, we lack both a clear understanding of how to classify the specific states, and how they can be mapped empirically. In the current study, we capitalise on advances in machine learning that allow continuous neural data to be divided into a set of distinct temporally re-occurring patterns, or states. We applied this technique to a large set of resting state data in which we also acquired retrospective descriptions of the participants' experiences during the scan. We found that two of the identified states were predictive of patterns of thinking at rest. One state highlighted a pattern of neural activity commonly seen during demanding tasks, and the time individuals spent in this state was associated with descriptions of experience focused on problem solving in the future. A second state was associated with patterns of activity that are commonly seen under less demanding conditions, and the time spent in it was linked to reports of intrusive thoughts about the past. Finally, we found that these two neural states tended to fall at either end of a neural hierarchy that is thought to reflect the brain's response to cognitive demands. Together, these results demonstrate that approaches which take advantage of time-varying changes in neural function can play an important role in understanding the repertoire of self-generated states. Moreover, they establish that important features of self-generated ongoing experience are related to variation along a similar vein to those seen when the brain responds to cognitive task demands.
Databáze: MEDLINE
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