Genetic Effects on Cerebellar Structure Across Mouse Models of Autism Using a Magnetic Resonance Imaging Atlas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) of autism populations is confounded by the inherent heterogeneity in the individuals' genetics and environment, two factors difficult to control for. Imaging genetic animal models that recapitulate a mutation associated with autism quantify the impact of genetics on brain morphology and mitigate the confounding factors in human studies. Here, we used MRI to image three genetic mouse models with single mutations implicated in autism: Neuroligin-3 R451C knock-in, Methyl-CpG binding protein-2 (MECP2) 308-truncation and integrin β3 homozygous knockout. This study identified the morphological differences specific to the cerebellum, a structure repeatedly linked to autism in human neuroimaging and postmortem studies. To accomplish a comparative analysis, a segmented cerebellum template was created and used to segment each study image. This template delineated 39 different cerebellar structures. For Neuroligin-3 R451C male mutants, the gray (effect size (ES) = 1.94, FDR q = 0.03) and white (ES = 1.84, q = 0.037) matter of crus II lobule and the gray matter of the paraflocculus (ES = 1.45, q = 0.045) were larger in volume. The MECP2 mutant mice had cerebellar volume changes that increased in scope depending on the genotype: hemizygous males to homozygous females. The integrin β3 mutant mouse had a drastically smaller cerebellum than controls with 28 out of 39 cerebellar structures smaller. These imaging results are discussed in relation to repetitive behaviors, sociability, and learning in the context of autism. This work further illuminates the cerebellum's role in autism.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it