Using EEG movement tagging to isolate brain responses coupled to biological movements

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Using EEG movement tagging to isolate brain responses coupled to biological movements. / Cracco, Emiel; Oomen, Danna; Papeo, Liuba et al.
In: Neuropsychologia, Vol. 177, 108395, 15.12.2022.

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Cracco E, Oomen D, Papeo L, Wiersema JR. Using EEG movement tagging to isolate brain responses coupled to biological movements. Neuropsychologia. 2022 Dec 15;177:108395. doi: 10.1016/j.neuropsychologia.2022.108395

Bibtex

@article{d898d9a75e16483f85ff6cbf3823da6e,
title = "Using EEG movement tagging to isolate brain responses coupled to biological movements",
abstract = "Detecting biological motion is essential for adaptive social behavior. Previous research has revealed the brain processes underlying this ability. However, brain activity during biological motion perception captures a multitude of processes. As a result, it is often unclear which processes reflect movement processing and which processes reflect secondary processes that build on movement processing. To address this issue, we developed a new approach to measure brain responses directly coupled to observed movements. Specifically, we showed 30 male and female adults a point-light walker moving at a pace of 2.4 Hz and used EEG frequency tagging to measure the brain response coupled to that pace ({\textquoteleft}movement tagging{\textquoteright}). The results revealed a reliable response at the walking frequency that was reduced by two manipulations known to disrupt biological motion perception: phase scrambling and inversion. Interestingly, we also identified a brain response at half the walking frequency (i.e., 1.2 Hz), corresponding to the rate at which the individual dots completed a cycle. In contrast to the 2.4 Hz response, the response at 1.2 Hz was increased for scrambled (vs. unscrambled) walkers. These results show that frequency tagging can be used to capture the visual processing of biological movements and can dissociate between global (2.4 Hz) and local (1.2 Hz) processes involved in biological motion perception, at different frequencies of the brain signal.",
keywords = "Biological motion perception, EEG, Frequency tagging, Global processing, Local processing, Sustainability Governance, Biology",
author = "Emiel Cracco and Danna Oomen and Liuba Papeo and Wiersema, {Jan R.}",
note = "Publisher Copyright: {\textcopyright} 2022 The Authors",
year = "2022",
month = dec,
day = "15",
doi = "10.1016/j.neuropsychologia.2022.108395",
language = "English",
volume = "177",
journal = "Neuropsychologia",
issn = "0028-3932",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Using EEG movement tagging to isolate brain responses coupled to biological movements

AU - Cracco, Emiel

AU - Oomen, Danna

AU - Papeo, Liuba

AU - Wiersema, Jan R.

N1 - Publisher Copyright: © 2022 The Authors

PY - 2022/12/15

Y1 - 2022/12/15

N2 - Detecting biological motion is essential for adaptive social behavior. Previous research has revealed the brain processes underlying this ability. However, brain activity during biological motion perception captures a multitude of processes. As a result, it is often unclear which processes reflect movement processing and which processes reflect secondary processes that build on movement processing. To address this issue, we developed a new approach to measure brain responses directly coupled to observed movements. Specifically, we showed 30 male and female adults a point-light walker moving at a pace of 2.4 Hz and used EEG frequency tagging to measure the brain response coupled to that pace (‘movement tagging’). The results revealed a reliable response at the walking frequency that was reduced by two manipulations known to disrupt biological motion perception: phase scrambling and inversion. Interestingly, we also identified a brain response at half the walking frequency (i.e., 1.2 Hz), corresponding to the rate at which the individual dots completed a cycle. In contrast to the 2.4 Hz response, the response at 1.2 Hz was increased for scrambled (vs. unscrambled) walkers. These results show that frequency tagging can be used to capture the visual processing of biological movements and can dissociate between global (2.4 Hz) and local (1.2 Hz) processes involved in biological motion perception, at different frequencies of the brain signal.

AB - Detecting biological motion is essential for adaptive social behavior. Previous research has revealed the brain processes underlying this ability. However, brain activity during biological motion perception captures a multitude of processes. As a result, it is often unclear which processes reflect movement processing and which processes reflect secondary processes that build on movement processing. To address this issue, we developed a new approach to measure brain responses directly coupled to observed movements. Specifically, we showed 30 male and female adults a point-light walker moving at a pace of 2.4 Hz and used EEG frequency tagging to measure the brain response coupled to that pace (‘movement tagging’). The results revealed a reliable response at the walking frequency that was reduced by two manipulations known to disrupt biological motion perception: phase scrambling and inversion. Interestingly, we also identified a brain response at half the walking frequency (i.e., 1.2 Hz), corresponding to the rate at which the individual dots completed a cycle. In contrast to the 2.4 Hz response, the response at 1.2 Hz was increased for scrambled (vs. unscrambled) walkers. These results show that frequency tagging can be used to capture the visual processing of biological movements and can dissociate between global (2.4 Hz) and local (1.2 Hz) processes involved in biological motion perception, at different frequencies of the brain signal.

KW - Biological motion perception

KW - EEG

KW - Frequency tagging

KW - Global processing

KW - Local processing

KW - Sustainability Governance

KW - Biology

UR - http://www.scopus.com/inward/record.url?scp=85140930841&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/72c9f994-d37e-30e1-90c9-7686b4284ff0/

U2 - 10.1016/j.neuropsychologia.2022.108395

DO - 10.1016/j.neuropsychologia.2022.108395

M3 - Journal articles

C2 - 36272677

AN - SCOPUS:85140930841

VL - 177

JO - Neuropsychologia

JF - Neuropsychologia

SN - 0028-3932

M1 - 108395

ER -

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