The AudioMaze: An EEG and motion capture study of human spatial navigation in sparse augmented reality.


Journal

The European journal of neuroscience
ISSN: 1460-9568
Titre abrégé: Eur J Neurosci
Pays: France
ID NLM: 8918110

Informations de publication

Date de publication:
12 2021
Historique:
revised: 21 12 2020
received: 22 07 2020
accepted: 19 01 2021
pubmed: 27 1 2021
medline: 9 4 2022
entrez: 26 1 2021
Statut: ppublish

Résumé

Spatial navigation is one of the fundamental cognitive functions central to survival in most animals. Studies in humans investigating the neural foundations of spatial navigation traditionally use stationary, desk-top protocols revealing the hippocampus, parahippocampal place area (PPA), and retrosplenial complex to be involved in navigation. However, brain dynamics, while freely navigating the real world remain poorly understood. To address this issue, we developed a novel paradigm, the AudioMaze, in which participants freely explore a room-sized virtual maze, while EEG is recorded synchronized to motion capture. Participants (n = 16) were blindfolded and explored different mazes, each in three successive trials, using their right hand as a probe to "feel" for virtual maze walls. When their hand "neared" a virtual wall, they received directional noise feedback. Evidence for spatial learning include shortening of time spent and an increase of movement velocity as the same maze was repeatedly explored. Theta-band EEG power in or near the right lingual gyrus, the posterior portion of the PPA, decreased across trials, potentially reflecting the spatial learning. Effective connectivity analysis revealed directed information flow from the lingual gyrus to the midcingulate cortex, which may indicate an updating process that integrates spatial information with future action. To conclude, we found behavioral evidence of navigational learning in a sparse-AR environment, and a neural correlate of navigational learning was found near the lingual gyrus.

Identifiants

pubmed: 33497490
doi: 10.1111/ejn.15131
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

8283-8307

Informations de copyright

© 2021 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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Auteurs

Makoto Miyakoshi (M)

Swartz Center for Neural Computation, Institute for Neural Computation, University of California San Diego, CA, USA.

Lukas Gehrke (L)

FG Biopsychologie und Neuroergonomie, Technische Universität Berlin, Berlin, Germany.

Klaus Gramann (K)

FG Biopsychologie und Neuroergonomie, Technische Universität Berlin, Berlin, Germany.
School of Computer Science, University of Technology Sydney, Sydney, Australia.

Scott Makeig (S)

Swartz Center for Neural Computation, Institute for Neural Computation, University of California San Diego, CA, USA.

John Iversen (J)

Swartz Center for Neural Computation, Institute for Neural Computation, University of California San Diego, CA, USA.

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