Aberrant Cerebellar Resting‐State Functional Connectivity Related to Reading Performance in Struggling Readers
Bibliographic record
Abstract
Reading is a critical neurodevelopmental skill for school-aged children, which requires a distributed network of brain regions including the cerebellum. However, we do not know how functional connectivity between the cerebellum and other brain regions contributes to reading. Here we used resting-state functional connectivity to understand the cerebellum's role in decoding, reading speed, and comprehension in a group of struggling readers (RD) and a group of adolescents and children with typical reading abilities (TD). We observed an increase in functional connectivity between the sensorimotor network and the left angular gyrus, left lateral occipital cortex, and right inferior frontal gyrus in the RD group relative to the TD group. Additionally, functional connectivity between the cerebellum network and the precentral gyrus was decreased and was related to reading fluency in the RD group. Seed-based analysis revealed increased functional connectivity between crus 1, lobule 6, and lobule 8 of the cerebellum and brain regions related to the default mode network and the motor system for the RD group. We also found associations between reading performance and the functional connectivity between lobule 8 of the cerebellum and the left angular gyrus for both groups, with stronger relationships in the TD group. Specifically, the RD group displayed a positive relationship between functional connectivity, whereas the TD group displayed the opposite relationship. These results suggest that the cerebellum is involved in multiple components of reading performance and that functional connectivity differences observed in the RD group may contribute to poor reading performance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".