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Record W4387564486 · doi:10.1097/wnr.0000000000001958

Effects of virtual reality working memory task difficulty on the passive processing of irrelevant auditory stimuli

2023· article· en· W4387564486 on OpenAlexaff
Farooq Kamal, Melanie Segado, Vincent Gagnon Shaigetz, Maxime Perron, Brian Lau, Claude Alain, Nusrat Choudhury

Bibliographic record

VenueNeuroreport · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsBaycrest HospitalUniversity of TorontoNational Research Council Canada
Fundersnot available
KeywordsP3aTask (project management)Working memoryPsychologyCognitionCognitive psychologyVirtual realityEvent-related potentialAudiologyComputer scienceNeuroscienceHuman–computer interaction

Abstract

fetched live from OpenAlex

The virtual reality (VR) environment is claimed to be highly immersive. Participants may thus be potentially unaware of their real, external world. The present study presented irrelevant auditory stimuli while participants were engaged in an easy or difficult visual working memory (WM) task within the VR environment. The difficult WM task should be immersive and require many cognitive resources, thus few will be available for the processing of task-irrelevant auditory stimuli. Sixteen young adults wore a 3D head-mounted VR device. In the easy WM task, the stimuli were nameable objects. In the difficult WM task, the stimuli were abstract objects that could not be easily named. A novel paradigm using event-related potentials (ERPs) was implemented to examine the feasibility of quantifying the extent of processing of task-irrelevant stimuli occurring outside of the VR environment. Auditory stimuli irrelevant to the WM task were presented concurrently at every 1.5 or 12 s in separate conditions. Performance on the WM task varied with task difficulty, with accuracy significantly lower during the difficult task. The auditory ERPs consisted of N1 and a later P2/P3a deflection which were larger when the auditory stimuli were presented slowly. ERPs were unaffected by task difficulty, but significant correlations were found. N1 and P2/P3a amplitudes were smallest when performance on the Easy WM task was highest. It is possible that even the easy WM task was so immersive and required many processing resources that few were available for the co-processing of the task-irrelevant auditory stimuli.

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 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)0.001
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 score0.190
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.146
GPT teacher head0.367
Teacher spread0.221 · 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 teacher head, 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

Citations3
Published2023
Admission routes1
Has abstractyes

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