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Record W2344232951 · doi:10.3389/fpsyg.2016.00595

Age Differences in Visual-Auditory Self-Motion Perception during a Simulated Driving Task

2016· article· en· W2344232951 on OpenAlexaff
Robert Ramkhalawansingh, Behrang Keshavarz, Bruce Haycock, Saba Shahab, Jennifer L. Campos

Bibliographic record

VenueFrontiers in Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversity of TorontoToronto Rehabilitation Institute
Fundersnot available
KeywordsPsychologyMultisensory integrationSensory cuePerceptionSensory systemCognitive psychologyStimulus (psychology)AudiologyContext (archaeology)Visual perceptionTask (project management)Neuroscience

Abstract

fetched live from OpenAlex

Recent evidence suggests that visual-auditory cue integration may change as a function of age such that integration is heightened among older adults. Our goal was to determine whether these changes in multisensory integration are also observed in the context of self-motion perception under realistic task constraints. Thus, we developed a simulated driving paradigm in which we provided older and younger adults with visual motion cues (i.e., optic flow) and systematically manipulated the presence or absence of congruent auditory cues to self-motion (i.e., engine, tire, and wind sounds). Results demonstrated that the presence or absence of congruent auditory input had different effects on older and younger adults. Both age groups demonstrated a reduction in speed variability when auditory cues were present compared to when they were absent, but older adults demonstrated a proportionally greater reduction in speed variability under combined sensory conditions. These results are consistent with evidence indicating that multisensory integration is heightened in older adults. Importantly, this study is the first to provide evidence to suggest that age differences in multisensory integration may generalize from simple stimulus detection tasks to the integration of the more complex and dynamic visual and auditory cues that are experienced during self-motion.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.335
Teacher spread0.312 · 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.

Study designObservational
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

Citations26
Published2016
Admission routes1
Has abstractyes

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