Spatially segregated responses to visuo-tactile stimuli in mouse neocortex during active sensation
Bibliographic record
Abstract
ABSTRACT Multisensory integration is key for perception and animal survival yet how information from separate senses is integrated has been debated for decades. In the cortex, information from each sense is first processed in primary sensory areas and then combined in association areas. An alternative hypothesis to this hierarchical model is that primary sensory cortices partake in multisensory encoding. We probed tactile and visual responses in primary somatosensory and visual cortices in awake behaving animals using two-photon calcium imaging from layer 2/3 excitatory neurons. In support of an hierarchical model we found segregation of visual and tactile responses. Tactile stimuli evoked responses in S1 neurons. In striking contrast, V1 neurons failed to respond to tactile stimuli. This was true for passive whisker stimulation and for stimulation during active whisking. Furthermore, responses of V1 neurons to congruent visuo-tactile cues during active exploration, a condition where vision precedes touch, were completely abolished in darkness. The rostro-lateral area of the visual cortex responded to both visual and tactile aspects of the stimuli and may form a substrate for encoding multisensory signals during active exploration. Our results indicate that primary sensory areas mainly encode their primary sense and that the impact of other modalities may be restricted to modulatory effects.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".