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Record W4407850755 · doi:10.1080/13875868.2025.2467624

Exploring human spatial orientation and navigation with electroencephalography: a scoping review

2025· review· en· W4407850755 on OpenAlex
Michael McLaren-Gradinaru, Ford Burles, Kelsey Cnudde, Alia Damji, Lila Berger, Nicole Betts, Hessan Hanif, Andrea B. Protzner, Giuseppe Iaria

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSpatial Cognition and Computation · 2025
Typereview
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectroencephalographyOrientation (vector space)Computer scienceHuman–computer interactionArtificial intelligenceComputer visionPsychologyNeuroscience

Abstract

fetched live from OpenAlex

This scoping review explores and describes how electroencephalography (EEG) has been used to study higher-order spatial orientation and navigation in healthy adults. 22 studies were included, where key findings highlighted the presence of theta (especially frontal-midline) during spatial memory encoding and alpha desynchronization during complex wayfinding. Event-related potentials revealed rapid changes in neural processing tied to path decisions, reward feedback, and navigation errors. Source localization findings suggest regions such as the retrosplenial complex and posterior parietal cortex are involved in egocentric and allocentric strategies. These results reinforce the value of EEG in capturing unique neural activity underlying spatial navigation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.333
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it