Multisensory and unisensory neurons in ferret parietal cortex exhibit distinct functional properties
Bibliographic record
Abstract
Despite the fact that unisensory and multisensory neurons are comingled in every neural structure in which they have been identified, no systematic comparison of their response features has been conducted. Towards that goal, the present study was designed to examine and compare measures of response magnitude, latency, duration and spontaneous activity in unisensory and bimodal neurons from the ferret parietal cortex. Using multichannel single-unit recording, bimodal neurons were observed to demonstrate significantly higher response levels and spontaneous discharge rates than did their unisensory counterparts. These results suggest that, rather than merely reflect different connectional arrangements, unisensory and multisensory neurons are likely to differ at the cellular level. Thus, it can no longer be assumed that the different populations of bimodal and unisensory neurons within a neural region respond similarly to a given external stimulus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".