Effects of Spatial Congruity on Audio-Visual Multimodal Integration
Bibliographic record
Abstract
Spatial constraints on multisensory integration of auditory (A) and visual (V) stimuli were investigated in humans using behavioral and electrophysiological measures. The aim was to find out whether cross-modal interactions between A and V stimuli depend on their spatial congruity, as has been found for multisensory neurons in animal studies (Stein & Meredith, 1993). Randomized sequences of unimodal (A or V) and simultaneous bimodal (AV) stimuli were presented to right- or left-field locations while subjects made speeded responses to infrequent targets of greater intensity that occurred in either or both modalities. Behavioral responses to the bimodal stimuli were faster and more accurate than to the unimodal stimuli for both same-location and different-location AV pairings. The neural basis of this cross-modal facilitation was studied by comparing event-related potentials (ERPs) to the bimodal AV stimuli with the summed ERPs to the unimodal A and V stimuli. These comparisons revealed neural interactions localized to the ventral occipito-temporal cortex (at 190 msec) and to the superior temporal cortical areas (at 260 msec) for both same- and different-location AV pairings. In contrast, ERP interactions that differed according to spatial congruity included a phase and amplitude modulation of visual-evoked activity localized to the ventral occipito-temporal cortex at 100-400 msec and an amplitude modulation of activity localized to the superior temporal region at 260-280 msec. These results demonstrate overlapping but distinctive patterns of multisensory integration for spatially congruent and incongruent AV stimuli.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".