Responses of Neurons in Chinchilla Auditory Cortex to Frequency-Modulated Tones
Bibliographic record
Abstract
Frequency-modulated (FM) stimuli have been used to explore the behavior of neurons in the auditory cortex of several animal models; however, the properties of FM-sensitive auditory cortical neurons in the chinchilla are still unknown. Single-unit responses to FM stimulation were obtained from the auditory cortex of anesthetized adult chinchillas (Chinchilla laniger). Upward and downward linear FM sweeps spanning frequencies from 0.1 to 20 kHz were presented at speeds of 0.05 to 0.82 kHz/ms. Results indicated that >90% of sampled neurons were responsive to FM sweeps. The population preference was for upward FM sweeps and for medium to fast speeds (> or =0.3 kHz/ms). Few units (3%) were selective for downward FM sweeps, whereas <22% of units preferred slow speeds (< or =0.1 kHz/ms). Velocity preference and direction sensitivity were positively correlated for upward sweeps only (r = 0.40, P = 0.0021, t-test). Three types of firing rate patterns were observed in the FM response peristimulus time histograms: a single peak at sweep onset/offset ("onset") and a single peak ("late") or multiple peaks ("burst") during the sweep. "Late" units expressed the highest mean values for direction sensitivity and speed selectivity; "onset" units were selective only for direction and "burst" units were not selective for either direction or speed. The robust responsiveness of these neurons to FM sweeps suggests a functional role for FM detection such as the identification of FM sweeps present in vocalizations of other organisms within the chinchilla's natural environment.
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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".