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Record W1974819199 · doi:10.1089/109493103769710514

Spatial Navigation in Virtual Reality Environments: An EEG Analysis

2003· article· en· W1974819199 on OpenAlex

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.

Bibliographic record

VenueCyberPsychology & Behavior · 2003
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEncoding (memory)ElectroencephalographySpatial memoryVirtual realitySpatial analysisPsychologySpatial learningComputer scienceNeuroscienceArtificial intelligenceCommunicationCognitive psychologyGeographyHippocampusCognitionWorking memory

Abstract

fetched live from OpenAlex

Past research has linked theta oscillations (electroencephalographic activity in the 4-8-Hz range) to spatial navigation in rodents and humans, and to the encoding and retrieval of spatial information in rodents. In the present study, electroencephalographic activity was measured while humans navigated through virtual mazes. Results confirmed previous findings that the frequency of theta episodes is directly related to the difficulty of maze navigation. We were also able to show that theta episodes occur most likely at points in a maze where new hallways come into view, or after navigational mistakes have been realized and are being corrected. This indicates that, just as in rodents, theta episodes in humans are related to the encoding and retrieval of spatial information.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.083
GPT teacher head0.367
Teacher spread0.284 · 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