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Record W7071289298

Sensory Filtering and Cognitive Function in a Valproic Acid Rat Model of Autism

2016· article· en· W7071289298 on OpenAlexaff

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsCognitionSensory systemAutismValproic AcidAnxietyAutism spectrum disorderElementary cognitive taskDevelopmental disorder
DOInot available

Abstract

fetched live from OpenAlex

Autistic individuals display sensory filtering impairments often correlated with cognitive dysfunction. Studies have shown that both these functions can be modulated by big potassium (BK) channels. Importantly, a subset of individuals with autism have shown BK channel mutations. We assessed sensory filtering and cognitive function through behavioural tests in a valproic acid (VPA) rat model of autism. We hypothesize that the model will display sensory filtering and cognitive impairments and that activation of BK channels may rescue observed cognitive deficits. Results revealed impairments in sensory filtering, hyper-locomotive activity and increased anxiety in VPA animals during adolescence. Although no significant impairments in cognitive function were observed, BK channel modulators were shown to facilitate normal cognitive function. We conclude that the VPA model is valid for displaying sensory filtering impairments associated with autism. However, no cognitive deficits were identified. Our results also provided further evidence for the importance of BK channels in cognition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.212
GPT teacher head0.320
Teacher spread0.108 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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