Successive-signal biasing for a learned sound sequence
Bibliographic record
Abstract
Adult rats were trained to detect the occurrence of a two-element sound sequence in a background of nine other nontarget sound pairs. Training resulted in a modest, enduring, static expansion of the cortical areas of representation of both target stimulus sounds. More importantly, once the initial stimulus A in the target A-B sequence was presented, the cortical "map" changed dynamically, specifically to exaggerate further the representation of the "anticipated" stimulus B. If B occurred, it was represented over a larger cortical area by more strongly excited, more coordinated, and more selectively responding neurons. This biasing peaked at the expected time of B onset with respect to A onset. No dynamic biasing of responses was recorded for any sound presented in a nontarget pair. Responses to nontarget frequencies flanking the representation of B were reduced in area and in response strength only after the presentation of A at the expected time of B onset. This study shows that cortical areas are not representationally static but, to the contrary, can be biased moment by moment in time as a function of behavioral context.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".