Revealing hidden states in visual working memory using electroencephalography

It is often assumed that information in visual working memory (vWM) is maintained via persistent activity. However, recent evidence indicates that information in vWM could be maintained in an effectively ‘activity-silent’ neural state. Silent vWM is consistent with recent cognitive and neural models...

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Main Authors: Michael J. Wolff, Jacqueline eDing, Nicholas E. Myers, Mark G. Stokes
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-09-01
Series:Frontiers in Systems Neuroscience
Subjects:
EEG
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnsys.2015.00123/full
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spelling doaj-07a42f277e7f4214b400b85a7cef0b372020-11-24T23:38:19ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372015-09-01910.3389/fnsys.2015.00123150772Revealing hidden states in visual working memory using electroencephalographyMichael J. Wolff0Michael J. Wolff1Jacqueline eDing2Nicholas E. Myers3Nicholas E. Myers4Mark G. Stokes5Mark G. Stokes6University of GroningenUniversity of OxfordUniversity of OxfordUniversity of OxfordUniversity of OxfordUniversity of OxfordUniversity of OxfordIt is often assumed that information in visual working memory (vWM) is maintained via persistent activity. However, recent evidence indicates that information in vWM could be maintained in an effectively ‘activity-silent’ neural state. Silent vWM is consistent with recent cognitive and neural models, but poses an important experimental problem: how can we study these silent states using conventional measures of brain activity? We propose a novel approach that is analogous to echolocation: using a high-contrast visual stimulus, it may be possible to drive brain activity during vWM maintenance and measure the vWM-dependent impulse response. We recorded electroencephalography (EEG) while participants performed a vWM task in which a randomly oriented grating was remembered. Crucially, a high-contrast, task-irrelevant stimulus was shown in the maintenance period in half of the trials. The electrophysiological response from posterior channels was used to decode the orientations of the gratings. While orientations could be decoded during and shortly after stimulus presentation, decoding accuracy dropped back close to baseline in the delay. However, the visual evoked response from the task-irrelevant stimulus resulted in a clear re-emergence in decodability. This result provides important proof-of-concept for a promising and relatively simple approach to decode ‘activity-silent’ vWM content using non-invasive EEG.http://journal.frontiersin.org/Journal/10.3389/fnsys.2015.00123/fullEEGmultivariate pattern analysisvisual working memoryHidden stateDynamic coding
collection DOAJ
language English
format Article
sources DOAJ
author Michael J. Wolff
Michael J. Wolff
Jacqueline eDing
Nicholas E. Myers
Nicholas E. Myers
Mark G. Stokes
Mark G. Stokes
spellingShingle Michael J. Wolff
Michael J. Wolff
Jacqueline eDing
Nicholas E. Myers
Nicholas E. Myers
Mark G. Stokes
Mark G. Stokes
Revealing hidden states in visual working memory using electroencephalography
Frontiers in Systems Neuroscience
EEG
multivariate pattern analysis
visual working memory
Hidden state
Dynamic coding
author_facet Michael J. Wolff
Michael J. Wolff
Jacqueline eDing
Nicholas E. Myers
Nicholas E. Myers
Mark G. Stokes
Mark G. Stokes
author_sort Michael J. Wolff
title Revealing hidden states in visual working memory using electroencephalography
title_short Revealing hidden states in visual working memory using electroencephalography
title_full Revealing hidden states in visual working memory using electroencephalography
title_fullStr Revealing hidden states in visual working memory using electroencephalography
title_full_unstemmed Revealing hidden states in visual working memory using electroencephalography
title_sort revealing hidden states in visual working memory using electroencephalography
publisher Frontiers Media S.A.
series Frontiers in Systems Neuroscience
issn 1662-5137
publishDate 2015-09-01
description It is often assumed that information in visual working memory (vWM) is maintained via persistent activity. However, recent evidence indicates that information in vWM could be maintained in an effectively ‘activity-silent’ neural state. Silent vWM is consistent with recent cognitive and neural models, but poses an important experimental problem: how can we study these silent states using conventional measures of brain activity? We propose a novel approach that is analogous to echolocation: using a high-contrast visual stimulus, it may be possible to drive brain activity during vWM maintenance and measure the vWM-dependent impulse response. We recorded electroencephalography (EEG) while participants performed a vWM task in which a randomly oriented grating was remembered. Crucially, a high-contrast, task-irrelevant stimulus was shown in the maintenance period in half of the trials. The electrophysiological response from posterior channels was used to decode the orientations of the gratings. While orientations could be decoded during and shortly after stimulus presentation, decoding accuracy dropped back close to baseline in the delay. However, the visual evoked response from the task-irrelevant stimulus resulted in a clear re-emergence in decodability. This result provides important proof-of-concept for a promising and relatively simple approach to decode ‘activity-silent’ vWM content using non-invasive EEG.
topic EEG
multivariate pattern analysis
visual working memory
Hidden state
Dynamic coding
url http://journal.frontiersin.org/Journal/10.3389/fnsys.2015.00123/full
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