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Identifying Objective EEG Based Markers of Linear Vection in Depth

This proof-of-concept study investigated whether a time-frequency EEG approach could be used to examine vection (i.e., illusions of self-motion). In the main experiment, we compared the event-related spectral perturbation (ERSP) data of 10 observers during and directly after repeated exposures to tw...

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Autores principales: Palmisano, Stephen, Barry, Robert J., De Blasio, Frances M., Fogarty, Jack S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979253/
https://www.ncbi.nlm.nih.gov/pubmed/27559328
http://dx.doi.org/10.3389/fpsyg.2016.01205
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author Palmisano, Stephen
Barry, Robert J.
De Blasio, Frances M.
Fogarty, Jack S.
author_facet Palmisano, Stephen
Barry, Robert J.
De Blasio, Frances M.
Fogarty, Jack S.
author_sort Palmisano, Stephen
collection PubMed
description This proof-of-concept study investigated whether a time-frequency EEG approach could be used to examine vection (i.e., illusions of self-motion). In the main experiment, we compared the event-related spectral perturbation (ERSP) data of 10 observers during and directly after repeated exposures to two different types of optic flow display (each was 35° wide by 29° high and provided 20 s of motion stimulation). Displays consisted of either a vection display (which simulated constant velocity forward self-motion in depth) or a control display (a spatially scrambled version of the vection display). ERSP data were decomposed using time-frequency Principal Components Analysis (t–f PCA). We found an increase in 10 Hz alpha activity, peaking some 14 s after display motion commenced, which was positively associated with stronger vection ratings. This followed decreases in beta activity, and was also followed by a decrease in delta activity; these decreases in EEG amplitudes were negatively related to the intensity of the vection experience. After display motion ceased, a series of increases in the alpha band also correlated with vection intensity, and appear to reflect vection- and/or motion-aftereffects, as well as later cognitive preparation for reporting the strength of the vection experience. Overall, these findings provide support for the notion that EEG can be used to provide objective markers of changes in both vection status (i.e., “vection/no vection”) and vection strength.
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spelling pubmed-49792532016-08-24 Identifying Objective EEG Based Markers of Linear Vection in Depth Palmisano, Stephen Barry, Robert J. De Blasio, Frances M. Fogarty, Jack S. Front Psychol Psychology This proof-of-concept study investigated whether a time-frequency EEG approach could be used to examine vection (i.e., illusions of self-motion). In the main experiment, we compared the event-related spectral perturbation (ERSP) data of 10 observers during and directly after repeated exposures to two different types of optic flow display (each was 35° wide by 29° high and provided 20 s of motion stimulation). Displays consisted of either a vection display (which simulated constant velocity forward self-motion in depth) or a control display (a spatially scrambled version of the vection display). ERSP data were decomposed using time-frequency Principal Components Analysis (t–f PCA). We found an increase in 10 Hz alpha activity, peaking some 14 s after display motion commenced, which was positively associated with stronger vection ratings. This followed decreases in beta activity, and was also followed by a decrease in delta activity; these decreases in EEG amplitudes were negatively related to the intensity of the vection experience. After display motion ceased, a series of increases in the alpha band also correlated with vection intensity, and appear to reflect vection- and/or motion-aftereffects, as well as later cognitive preparation for reporting the strength of the vection experience. Overall, these findings provide support for the notion that EEG can be used to provide objective markers of changes in both vection status (i.e., “vection/no vection”) and vection strength. Frontiers Media S.A. 2016-08-10 /pmc/articles/PMC4979253/ /pubmed/27559328 http://dx.doi.org/10.3389/fpsyg.2016.01205 Text en Copyright © 2016 Palmisano, Barry, De Blasio and Fogarty. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Palmisano, Stephen
Barry, Robert J.
De Blasio, Frances M.
Fogarty, Jack S.
Identifying Objective EEG Based Markers of Linear Vection in Depth
title Identifying Objective EEG Based Markers of Linear Vection in Depth
title_full Identifying Objective EEG Based Markers of Linear Vection in Depth
title_fullStr Identifying Objective EEG Based Markers of Linear Vection in Depth
title_full_unstemmed Identifying Objective EEG Based Markers of Linear Vection in Depth
title_short Identifying Objective EEG Based Markers of Linear Vection in Depth
title_sort identifying objective eeg based markers of linear vection in depth
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979253/
https://www.ncbi.nlm.nih.gov/pubmed/27559328
http://dx.doi.org/10.3389/fpsyg.2016.01205
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