Sensory Over-responsivity and Aberrant Plasticity in Cerebellar Cortex in a Mouse Model of Syndromic Autism
Bibliographic record
Abstract
Background: Patients with autism spectrum disorder often show altered responses to sensory stimuli as well as motor deficits, including an impairment of delay eyeblink conditioning, which involves integration of sensory signals in the cerebellum. Here, we identify abnormalities in parallel fiber (PF) and climbing fiber (CF) signaling in the mouse cerebellar cortex that may contribute to these pathologies. Methods: We used a mouse model for the human 15q11-13 duplication (patDp/+) and studied responses to sensory stimuli in Purkinje cells from awake mice using two-photon imaging of GCaMP6f signals. Moreover, we examined synaptic transmission and plasticity using in vitro electrophysiological, immunohistochemical, and confocal microscopic techniques. Results: We found that spontaneous and sensory-evoked CF-calcium transients are enhanced in patDp/+ Purkinje cells, and aversive movements are more severe across sensory modalities. We observed increased expression of the synaptic organizer NRXN1 at CF synapses and ectopic spread of these synapses to fine dendrites. CF-excitatory postsynaptic currents recorded from Purkinje cells are enlarged in patDp/+ mice, while responses to PF stimulation are reduced. Confocal measurements show reduced PF+CF-evoked spine calcium transients, a key trigger for PF long-term depression, one of several plasticity types required for eyeblink conditioning learning. Long-term depression is impaired in patDp/+ mice but is rescued on pharmacological enhancement of calcium signaling. Conclusions: Our findings suggest that this genetic abnormality causes a pathological inflation of CF signaling, possibly resulting from enhanced NRXN1 expression, with consequences for the representation of sensory stimuli by the CF input and for PF synaptic organization and plasticity.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".