The statistics of the vestibular input experienced during natural self‐motion differ between rodents and primates
Bibliographic record
Abstract
KEY POINTS: In order to understand how the brain's coding strategies are adapted to the statistics of the sensory stimuli experienced during everyday life, the use of animal models is essential. Mice and non-human primates have become common models for furthering our knowledge of the neuronal coding of natural stimuli, but differences in their natural environments and behavioural repertoire may impact optimal coding strategies. Here we investigated the structure and statistics of the vestibular input experienced by mice versus non-human primates during natural behaviours, and found important differences. Our data establish that the structure and statistics of natural signals in non-human primates more closely resemble those observed previously in humans, suggesting similar coding strategies for incoming vestibular input. These results help us understand how the effects of active sensing and biomechanics will differentially shape the statistics of vestibular stimuli across species, and have important implications for sensory coding in other systems. ABSTRACT: It is widely believed that sensory systems are adapted to the statistical structure of natural stimuli, thereby optimizing coding. Recent evidence suggests that this is also the case for the vestibular system, which senses self-motion and in turn contributes to essential brain functions ranging from the most automatic reflexes to spatial perception and motor coordination. However, little is known about the statistics of self-motion stimuli actually experienced by freely moving animals in their natural environments. Accordingly, here we examined the natural self-motion signals experienced by mice and monkeys: two species commonly used to study vestibular neural coding. First, we found that probability distributions for all six dimensions of motion (three rotations, three translations) in both species deviated from normality due to long tails. Interestingly, the power spectra of natural rotational stimuli displayed similar structure for both species and were not well fitted by power laws. This result contrasts with reports that the natural spectra of other sensory modalities (i.e. vision, auditory and tactile) instead show a power-law relationship with frequency, which indicates scale invariance. Analysis of natural translational stimuli revealed important species differences as power spectra deviated from scale invariance for monkeys but not for mice. By comparing our results to previously published data for humans, we found the statistical structure of natural self-motion stimuli in monkeys and humans more closely resemble one another. Our results thus predict that, overall, neural coding strategies used by vestibular pathways to encode natural self-motion stimuli are fundamentally different in rodents and primates.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".