Monkeys share the neurophysiological basis for encoding sound periodicities captured by the frequency-following response with humans
Bibliographic record
Abstract
The extraction and encoding of acoustical temporal regularities are fundamental for human cognitive auditory abilities such as speech or beat entrainment. Because the comparison of the neural sensitivity to temporal regularities between human and animals is fundamental to relate non-invasive measures of auditory processing to their neuronal basis, here we compared the neural representation of auditory periodicities between human and non-human primates by measuring scalp-recorded frequency-following response (FFR). We found that rhesus monkeys can resolve the spectrotemporal structure of periodic stimuli to a similar extent as humans by exhibiting a homologous FFR potential to the speech syllable /da/. The FFR in both species is robust and phase-locked to the fundamental frequency of the sound, reflecting an effective neural processing of the fast-periodic information of subsyllabic cues. Our results thus reveal a conserved neural ability to track acoustical regularities within the primate order. These findings open the possibility to study the neurophysiology of complex sound temporal processing in the macaque subcortical and cortical areas, as well as the associated experience-dependent plasticity across the auditory pathway in behaving monkeys.
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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 | 0.001 |
| 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".