Evidence for Hierarchical Processing in Cat Auditory Cortex: Nonreciprocal Influence of Primary Auditory Cortex on the Posterior Auditory Field
Bibliographic record
Abstract
The auditory cortex of the cat is composed of 13 distinct fields that have been defined on the basis of anatomy, physiology, and behavior. Although an anatomically based hierarchical processing scheme has been proposed in auditory cortex, few functional studies have examined how these areas influence one another. The purpose of the present study was to examine the bidirectional processing contributions between primary auditory cortex (A1) and the nonprimary posterior auditory field (PAF). Multiunit acute recording techniques in eight mature cats were used to measure neuronal responses to tonal stimuli in A1 or PAF while synaptic activity from PAF or A1 was suppressed with reversible cooling deactivation techniques. Specifically, in four animals, electrophysiological recordings in A1 were conducted before, during, and after deactivation of PAF. Similarly, in the other four animals, PAF activity was measured before, during, and after deactivation of A1. The characteristic frequency, bandwidth, and neuronal threshold were calculated at each receptive field collected and the response strength and response latency measures were calculated from cumulative peristimulus time histograms. Two major changes in PAF response properties were observed during A1 deactivation: a decrease in response strength and a reduction in receptive field bandwidths. In comparison, we did not identify any significant changes in A1 neuronal responses during deactivation of PAF neurons. These findings support proposed models of hierarchal processing in cat auditory cortex.
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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 | 0.001 |
| 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".