Feature selectivity of corticocortical feedback along the primate dorsal visual pathway
Bibliographic record
Abstract
Abstract Anatomical studies have revealed a prominent role for feedback projections in the primate visual cortex. Theoretical models suggest that these projections support important brain functions, like attention, prediction, and learning. However, these models make different predictions about the relationship between feedback connectivity and neuronal stimulus selectivity. We have therefore performed simultaneous recordings in different regions of the primate dorsal visual pathway. Specifically, we recorded neural activity from the medial superior temporal (MST) area, and one of its main feedback targets, the middle temporal (MT) area. We estimated functional connectivity from correlations in the single-neuron spike trains and performed electrical microstimulation in MST to determine its causal influence on MT. Both methods revealed that inhibitory feedback occurred more commonly when the source and target neurons had very different stimulus preferences. At the same time, the strength of feedback suppression was greater for neurons with similar preferences. Excitatory feedback projections, in contrast, showed no consistent relationship with stimulus preferences. These results suggest that corticocortical feedback could play a role in shaping sensory responses according to behavioral or environmental context.
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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 | 0.001 |
| 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".