Synaptic Strength Modulation after Cortical Trauma: A Role in Epileptogenesis
Bibliographic record
Abstract
Traumatic brain injuries are often followed by abnormal hyperexcitability, leading to acute seizures and epilepsy. Previous studies documented the rewiring capacity of neocortical neurons in response to various cortical and subcortical lesions. However, little information is available on the functional consequences of these anatomical changes after cortical trauma and the adaptation of synaptic connectivity to a decreased input produced by chronic deafferentation. In this study, we recorded intracellular (IC) activities of cortical neurons simultaneously with extracellular (EC) unit activities and field potentials of neighboring cells in cat cortex, after a large transection of the white matter underneath the suprasylvian gyrus, in acute and chronic conditions (at 2, 4, and 6 weeks) in ketamine-xylazine-anesthetized cats. Using EC spikes to compute the spike-triggered averages of IC membrane potential, we found an increased connection probability and efficacy between cortical neurons weeks after cortical trauma. Inhibitory interactions showed no significant changes in the traumatized cortex compared with control. The increased synaptic efficacy was accompanied by enhanced input resistance and intrinsic excitability of cortical neurons, as well as by increased duration of silent network periods. Our electrophysiological data revealed functional consequences of previously reported anatomical changes in the injured cortex. We suggest that homeostatic synaptic plasticity compensating the decreased activity in the undercut cortex leads to an uncontrollable cortical hyperexcitability and seizure generation.
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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".