Persistent enhancement of functional MRI responsiveness to sensory stimulation following repeated seizures
Bibliographic record
Abstract
PURPOSE: Neural reorganization and interictal behavioral anomalies have been documented in people with epilepsy and in animal seizure models. Alterations in behavior could be due to somatosensory dysfunction. This study was designed to determine whether seizures can lead to changes in somatosensory representations and whether those changes are persistent. METHODS: Twice-daily seizures were elicited by delivering 1 s of electrical stimulation through carbon fiber electrodes implanted in both the corpus callosum and sensorimotor neocortex of young adult male Long-Evans rats until a total of 20 seizures were elicited. Either 1-3 days or 3-5 weeks following the last seizure, functional magnetic resonance imaging (MRI) was used to image the brain during electrical stimulation of each forepaw independently. KEY FINDINGS: Forepaw stimulation in control rats resulted in a focused and contralateral fMRI signal in the somatosensory neocortex. Rats that had repeated seizures had a 151% increase in the number of voxels activated in the contralateral hemisphere 1-3 days after the last seizure and a 166% increase at 3-5 weeks after the last seizure. The number of voxels activated in response to forepaw stimulation was positively correlated with the duration of the longest seizure experienced by each rat. The intensity of the activated voxels was not significantly increased at either time interval from the last seizure. SIGNIFICANCE: The increased area of activation in somatosensory cortex, which is persistent at 3-5 weeks, is consistent with previous observations of larger motor maps following seizures. Seizure-induced changes in the functioning of sensory cortex may also contribute to interictal behavioral anomalies.
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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) | 0.000 | 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) | 0.001 | 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".