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Record W1858851078 · doi:10.1152/jn.2002.88.1.438

Auditory-Visual Interactions Subserving Goal-Directed Saccades in a Complex Scene

2002· article· en· W1858851078 on OpenAlexaff
Brian D. Corneil, Marc M. van Wanrooij, Douglas P. Munoz, A. John Van Opstal

Bibliographic record

VenueJournal of Neurophysiology · 2002
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsQueen's University
Fundersnot available
KeywordsSaccadic maskingSaccadeEye movementStimulus (psychology)PsychologySaccadic suppression of image displacementVisual perceptionNeuroscienceAudiologyPerceptionCommunicationCognitive psychologyMedicine

Abstract

fetched live from OpenAlex

This study addresses the integration of auditory and visual stimuli subserving the generation of saccades in a complex scene. Previous studies have shown that saccadic reaction times (SRTs) to combined auditory-visual stimuli are reduced when compared with SRTs to either stimulus alone. However, these results have been typically obtained with high-intensity stimuli distributed over a limited number of positions in the horizontal plane. It is less clear how auditory-visual interactions influence saccades under more complex but arguably more natural conditions, when low-intensity stimuli are embedded in complex backgrounds and distributed throughout two-dimensional (2-D) space. To study this problem, human subjects made saccades to visual-only (V-saccades), auditory-only (A-saccades), or spatially coincident auditory-visual (AV-saccades) targets. In each trial, the low-intensity target was embedded within a complex auditory-visual background, and subjects were allowed over 3 s to search for and foveate the target at 1 of 24 possible locations within the 2-D oculomotor range. We varied systematically the onset times of the targets and the intensity of the auditory target relative to background [i.e., the signal-to-noise (S/N) ratio] to examine their effects on both SRT and saccadic accuracy. Subjects were often able to localize the target within one or two saccades, but in about 15% of the trials they generated scanning patterns that consisted of many saccades. The present study reports only the SRT and accuracy of the first saccade in each trial. In all subjects, A-saccades had shorter SRTs than V-saccades, but were more inaccurate than V-saccades when generated to auditory targets presented at low S/N ratios. AV-saccades were at least as accurate as V-saccades but were generated at SRTs typical of A-saccades. The properties of AV-saccades depended systematically on both stimulus timing and S/N ratio of the auditory target. Compared with unimodal A- and V-saccades, the improvements in SRT and accuracy of AV-saccades were greatest when the visual target was synchronous with or leading the auditory target, and when the S/N ratio of the auditory target was lowest. Further, the improvements in saccade accuracy were greater in elevation than in azimuth. A control experiment demonstrated that a portion of the improvements in SRT could be attributable to a warning-cue mechanism, but that the improvements in saccade accuracy depended on the spatial register of the stimuli. These results agree well with earlier electrophysiological results obtained from the midbrain superior colliculus (SC) of anesthetized preparations, and we argue that they demonstrate multisensory integration of auditory and visual signals in a complex, quasi-natural environment. A conceptual model incorporating the SC is presented to explain the observed data.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.107
GPT teacher head0.378
Teacher spread0.270 · 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 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

Citations177
Published2002
Admission routes1
Has abstractyes

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