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Record W3005198380 · doi:10.3389/fpsyg.2020.00079

Audiovisual Integration During Joint Action: No Effects for Motion Discrimination and Temporal Order Judgment Tasks

2020· article· en· W3005198380 on OpenAlexaff
Basil Wahn, Jill A. Dosso, Alan Kingstone

Bibliographic record

VenueFrontiers in Psychology · 2020
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCrossmodalPsychologyMultisensory integrationTask (project management)Stimulus modalityCognitive psychologyPerceptionModality (human–computer interaction)ModalitiesMotion (physics)Process (computing)Action (physics)Visual perceptionSensory systemComputer scienceNeuroscienceArtificial intelligence

Abstract

fetched live from OpenAlex

In daily life, humans constantly process information from multiple sensory modalities (e.g., visual and auditory). Information across sensory modalities may (or may not) be combined to form the perception of a single event via the process of multisensory integration. Recent research has suggested that performing a spatial crossmodal congruency task jointly with a partner affects multisensory integration. To date, it has not been investigated whether multisensory integration in other crossmodal tasks is also affected by performing a task jointly. To address this point, we investigated whether joint task performance also affects perceptual judgments in a crossmodal motion discrimination task and a temporal order judgment task. In both tasks, pairs of participants were presented with auditory and visual stimuli that might or might not be perceived as belonging to a single event. Each participant in a pair was required to respond to stimuli from one sensory modality only (e.g., visual stimuli only). Participants performed both individual and joint conditions. Replicating earlier multisensory integration effects, we found that participants' perceptual judgments were significantly affected by stimuli in the other modality for both tasks. However, we did not find that performing a task jointly modulated these crossmodal effects. Taking this together with earlier findings, we suggest that joint task performance affects crossmodal results in a manner dependent on how these effects are quantified (i.e., via responses time or accuracy) and the specific task demands (i.e., whether tasks require processing stimuli in terms of location, motion, or timing).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

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

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 head0.075
GPT teacher head0.375
Teacher spread0.301 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

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