Closing the species gap: Translational approaches to studying sensory processing differences relevant for autism spectrum disorder
Bibliographic record
Abstract
The study of sensory phenotypes has great potential for increasing research translation between species, a necessity to decipher the neural mechanisms that contribute to higher-order differences in neurological conditions such as autism spectrum disorder (ASD). Over the past decade, despite separate advances in our understanding of the structural and functional differences within the brain of autistic and non-autistic individuals and in rodent models for ASD, researchers have had difficulty translating the findings in murine species to humans, mostly due to incompatibility in experimental methodologies used to screen for ASD phenotypes. Focusing on sensory phenotypes offers an avenue to close the species gap because sensory pathways are highly conserved across species and are affected by the same risk-factors as the higher-order brain areas mostly responsible for the diagnostic criteria for ASD. By first reviewing how sensory processing has been studied to date, we direct our focus to electrophysiological and behavioral techniques that can be used to study sensory phenotypes consistently across species. Using auditory sensory phenotypes as a template, we seek to improve the accessibility of translational methods by providing a framework for collecting cohesive data in both rodents and humans. Specifically, evoked-potentials, acoustic startle paradigms, and psychophysical detection/discrimination paradigms can be created and implemented in a coordinated and systematic fashion across species. Through careful protocol design and collaboration, sensory processing phenotypes can be harnessed to bridge the gap that exists between preclinical animal studies and human testing, so that mutually held questions in autism research can be answered. LAY SUMMARY: It has always been difficult to relate results from animal research to humans. We try to close this gap by studying changes in sensory processing using careful protocol design and collaboration between clinicians and researchers. Sensory pathways are comparable between animals and humans, and are affected in the same way as the rest of the brain in ASD. Using changes in hearing as a template, we point the field in an innovative direction by providing a framework for collecting cohesive data in rodents and humans.
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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 | 0.011 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".