039 Sleep Preferentially Supports Problem-Solving Skills via Greater Functional Connectivity Between the Caudate and Cerebral Cortex
Bibliographic record
Abstract
Abstract Introduction Sleep consolidates memory, including newly acquired procedural skills. One putative systems-level mechanism for this function of sleep is via sleep-dependent strengthening of functional connectivity between the putamen and the cortico-hippocampal-striatal-cerebellar network, which supports procedural motor skills. For procedural motor skills that also require problem solving and rule-learning, sleep preferentially benefits the cognitively complex aspects over the motor skills required to execute the solution itself. The caudate is implicated in higher-order cognitive components of skill learning, which include error monitoring and automizing new information. In the current study, we investigated how sleep alters functional connectivity in higher-order learning networks that support problem solving and rule learning-related procedural skills. Methods Participants (n = 38) were trained on a procedural skills task; the Tower of Hanoi (ToH), that requires the acquisition of a novel cognitive strategy (e.g., recursive logic), while undergoing functional magnetic resonance imaging (fMRI). After either a full night of sleep (n=19) or a full day of wakefulness (n=19), participants were retested on the same task in the fMRI. Resting state activity was acquired before (R1) and after the training session (R2), and before the retest session (R3). Results Behavioral performance on the ToH improved following sleep compared to wake (reduced number of errors: t(38)=2.92, p=0.006, d=1.24). Regions associated with higher-order learning and cognitive complexity (i.e., the caudate) and regions typically implicated in sequence learning (i.e., the putamen, hippocampus, cerebellum) were selected as regions of interest (ROI). Increased functional connectivity across the retention interval (R3-R2) was observed in the sleep vs. wake condition between the caudate and the motor cortex (t(36)=3.32, p=0.042, FWE). By contrast, changes in functional connectivity were not observed between the putamen and other ROIs. Conclusion These results suggest that sleep supports improved consolidation of motor skills that involve the acquisition of a novel cognitive strategy. Sleep enhanced functional connectivity in brain areas associated with higher-order cognitive skills (i.e., the caudate), but not regions typically associated with motor skills (i.e., the putamen) that are required to execute the solution to the cognitive procedural skill. Support (if any) Natural Science and Engineering Research Council of Canada
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".