GSK-3β disrupts neural oscillatory function to inhibit learning and memory in rats
Bibliographic record
Abstract
Abstract Background. Alterations in glycogen synthase kinase-3β (GSK-3β) activity have been implicated in disorders of cognitive impairment including Alzheimer’s disease and schizophrenia. Another characteristic of cognitive impairment is the dysregulation of neural oscillatory activity, macroscopic electrical rhythms in brain critical to systems communication. A direct functional relationship between GSK-3β and neural oscillations has not been elucidated.Methods. In the present study, the impact of increasing GSK-3β activity in prefrontal cortex (PFC) or hippocampus (HIP) on the regulation of neural oscillations in rats was investigated using an adeno-associated viral vector containing a persistently active mutant of GSK-3β (S9A), and changes in learning and memory and tau phosphorylation assessed.Results. Increasing GSK-3β activity in either region had similar effects on oscillatory spectral power, enhancing theta and/or gamma oscillatory power recorded from one or both regions. Increasing PFC GSK-3β activity additionally suppressed high gamma PFC-HIP coherence. These oscillatory changes were accompanied by deficits in recognition memory, spatial learning and/or reversal learning. Increased pathogenic tau phosphorylation was also evident in regions where GSK-3β activity was elevated. Conclusions. These findings indicate that increased GSK-3β activity in PFC or HIP dysregulates neural oscillatory function in, and between, these regions. This suggests that GSK-3β may not only play an early role in cognitive decline in Alzheimer’s disease but may also play a more central role in disorders of cognitive dysfunction through the regulation of neurophysiological network function.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".