Do Cross-Modal Projections Always Result in Multisensory Integration?
Bibliographic record
Abstract
Convergence of afferents from different sensory modalities has generally been thought to produce bimodal (and trimodal) neurons (i.e., exhibit suprathreshold excitation to more than 1 sensory modality). Consequently, studies identifying cross-modal connections assume that such convergence results in bimodal (or trimodal) neurons that produce familiar forms of multisensory integration: response enhancement or depression. The present study questioned that assumption by anatomically identifying a projection from ferret auditory to visual cortex Area 21. However, electrophysiological recording within Area 21 not only failed to identify a single bimodal neuron but also familiar forms of multisensory integration were not observed either. Instead, a small proportion of neurons (9%; 27/296) showed subthreshold multisensory integration, in which visual responses were significantly modulated by auditory inputs. Such subthreshold multisensory effects were enhanced by gamma-aminobutyric acid antagonism, whereby a majority of neurons (87%; 20/23) now participated in a significant, multisensory population effect. Thus, multisensory convergence does not de facto result in bimodal (or trimodal) neurons or the traditional forms of multisensory integration. However, the fact that unimodal neurons exhibited a subthreshold form of multisensory integration not only affirms the relationship between convergence and integration but also expands our understanding of the functional repertoire of multisensory processing itself.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".