The psychological correlates of distinct neural states occurring during wakeful rest

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...

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Main Authors: Karapanagiotidis, T, Vidaurre, D, Quinn, A, Vatansever, D, Poerio, G, Turnbull, A, Siu Ping Ho, N, Leech, R, Bernhardt, B, Jefferies, E, Margulies, D, Nichols, T, Woolrich, M, Smallwood, S
Format: Journal article
Language:University of Oxford
Published: Springer Nature 2020
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author Karapanagiotidis, T
Vidaurre, D
Quinn, A
Vatansever, D
Poerio, G
Turnbull, A
Siu Ping Ho, N
Leech, R
Bernhardt, B
Jefferies, E
Margulies, D
Nichols, T
Woolrich, M
Smallwood, S
author_facet Karapanagiotidis, T
Vidaurre, D
Quinn, A
Vatansever, D
Poerio, G
Turnbull, A
Siu Ping Ho, N
Leech, R
Bernhardt, B
Jefferies, E
Margulies, D
Nichols, T
Woolrich, M
Smallwood, S
author_sort Karapanagiotidis, T
collection OXFORD
description 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.
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spelling oxford-uuid:51ffbb04-a24d-4672-a3b3-07b3ed5a790c2022-03-26T16:23:03ZThe psychological correlates of distinct neural states occurring during wakeful restJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:51ffbb04-a24d-4672-a3b3-07b3ed5a790cUniversity of OxfordSymplectic ElementsSpringer Nature2020Karapanagiotidis, TVidaurre, DQuinn, AVatansever, DPoerio, GTurnbull, ASiu Ping Ho, NLeech, RBernhardt, BJefferies, EMargulies, DNichols, TWoolrich, MSmallwood, SWhen 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.
spellingShingle Karapanagiotidis, T
Vidaurre, D
Quinn, A
Vatansever, D
Poerio, G
Turnbull, A
Siu Ping Ho, N
Leech, R
Bernhardt, B
Jefferies, E
Margulies, D
Nichols, T
Woolrich, M
Smallwood, S
The psychological correlates of distinct neural states occurring during wakeful rest
title The psychological correlates of distinct neural states occurring during wakeful rest
title_full The psychological correlates of distinct neural states occurring during wakeful rest
title_fullStr The psychological correlates of distinct neural states occurring during wakeful rest
title_full_unstemmed The psychological correlates of distinct neural states occurring during wakeful rest
title_short The psychological correlates of distinct neural states occurring during wakeful rest
title_sort psychological correlates of distinct neural states occurring during wakeful rest
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