Horizontal cortical connections shape intrinsic traveling waves into feature-selective motifs that regulate perceptual sensitivity
Bibliographic record
Abstract
Intrinsic cortical activity forms traveling waves that modulate sensory-evoked responses and perceptual sensitivity. These intrinsic traveling waves (iTWs) may arise from the coordination of synaptic activity through long-range feature-dependent horizontal connectivity within cortical areas. In a spiking network model that incorporates feature-selective patchy connections, we observe iTW motifs that result from shifts in excitatory/inhibitory balance as action potentials traverse these patchy connections. To test whether feature-selective motifs occur in vivo, we examined data recorded in the middle temporal visual area (Area MT) of marmosets performing a visual detection task. We find that some iTWs form motifs that are feature selective, exhibiting direction-selective modulations in spiking activity. Further, motifs modulate the gain of target-evoked responses and perceptual sensitivity if the target matches the preference of the motif. These results suggest that iTWs are shaped by the patchy horizontal fiber projections in the cortex and can regulate neural and perceptual sensitivity in a feature-selective manner.
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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 | 0.000 | 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".