The influence of stimulus properties on multisensory processing in the awake primate superior colliculus.
Bibliographic record
Abstract
Multisensory integration is a process whereby information converges from different sensory modalities to produce a response that is different from that elicited by the individual modalities presented alone. A neural basis for multisensory integration has been identified within a variety of brain regions, but the most thoroughly examined model has been that of the superior colliculus (SC). Multisensory processing in the SC of anaesthetized animals has been shown to be dependent on the physical parameters of the individual stimuli presented (e.g., intensity, direction, velocity) as well as their spatial relationship. However, it is unknown whether these stimulus features are important, or evident, in the awake behaving animal. To address this question, we evaluated the influence of physical properties of sensory stimuli (visual intensity, direction, and velocity; auditory intensity and location) on sensory activity and multisensory integration of SC neurons in awake, behaving primates. Monkeys were trained to fixate a central visual fixation point while visual and/or auditory stimuli were presented in the periphery. Visual stimuli were always presented within the contralateral receptive field of the neuron whereas auditory stimuli were presented at either ipsi- or contralateral locations. Many of the SC neurons responsive to these sensory stimuli (n = 66/84; 76%) had stronger responses when the visual and auditory stimuli were combined at contralateral locations than when the auditory stimulus was located on the ipsilateral side. This trend was significant across the population of auditory-responsive neurons. In addition, some SC neurons (n = 31) were presented a battery of tests in which the quality of one stimulus of a pair was systematically manipulated. A small proportion of these neurons (n = 8/31; 26%) showed preferential responses to stimuli with specific physical properties, and these preferences were not significantly altered when multisensory stimulus combinations were presented. These data demonstrate that multisensory processing in the awake behaving primate is influenced by the spatial congruency of the stimuli as well as their individual physical properties.
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 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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".