MétaCan
Menu
Back to cohort
Record W1974819199 · doi:10.1089/109493103769710514

Spatial Navigation in Virtual Reality Environments: An EEG Analysis

2003· article· en· W1974819199 on OpenAlexaff
Walter F. Bischof, Pierre Boulanger

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations83
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueCyberPsychology & BehaviorSame topicMemory and Neural MechanismsFrench-language works237,207