Scale-Invariant Adaptation in Response to Second-Order Electro-Sensory Stimuli in Weakly Electric Fish
Bibliographic record
Abstract
Background: Natural stimuli can range orders of magnitude, and their encoding by the brain remains a central issue in neuroscience. An efficient way of encoding a natural stimulus is by changing a neuron’s cod- ing rule in tandem with changes in the stimulus. This phenomenon is called sensory adaptation. However, sensory adaptation creates ambiguity in the neural code, as different stimuli can produce the same neural response.
 Methods: One way to resolve this ambiguity is to encode additional stimulus information through parallel channels. We performed in vivo extracellular recordings from pyramidal cells in two parallel maps, the lateral segment (LS) and the centro-medial segment (CMS), within the hindbrain of the weakly electric fish Aptero- notus leptorhynchus, in response to stimuli that resemble the presence of another conspecific.
 Results: We found that CMS pyramidal cells generally adapted less strongly than LS cells (p<0.05). Signal detection theory confirms that the lesser degree of adaptation leads to a stronger ability to disambiguate between two input stimuli (p<0.05). In addition, the time course of adaptation in LS strictly followed a power law while that of CMS followed a power law only for a certain set of stimuli.
 Limitations: The design of our study allowed for a stimulus that oscillated only between two distributions. Further studies into the hindbrain’s ability to disambiguate the adaptive code will require confusion analysis of a stimulus that changes between more distributions. For confusion studies, cells in different areas can be compared as long as they have receptive fields in similar areas.
 Conclusions: Through recording from two parallel segments of the electro-sensory system in the hindbrain, we observed that different segments adapted with different strengths to similar stimuli. Different amounts of adaptation allude to a balance between the need to preserve absolute stimulus information while simul- taneously encoding a stimulus efficiently through adaptation.
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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 | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".