In Vitro Recordings of Human Neocortical Oscillations
Bibliographic record
Abstract
Electrophysiological oscillations are thought to create temporal windows of communication between brain regions. We show here that human cortical slices maintained in vitro can generate oscillations similar to those observed in vivo. We have characterized these oscillations using local field potential and whole-cell recordings obtained from neocortical slices acquired during epilepsy surgery. We confirmed that such neocortical slices maintain the necessary cellular and circuitry components, and in particular inhibitory mechanisms, to manifest oscillatory activity when exposed to glutamatergic and cholinergic agonists. The generation of oscillations was dependent on intact synaptic activity and muscarinic receptors. Such oscillations differed in electrographic and pharmacological properties from epileptiform activity. Two types of activity, theta oscillations and high gamma activity, uniquely characterized this model-activity not typically observed in animal cortical slices. We observed theta oscillations to be synchronous across cortical laminae suggesting a novel role of theta as a substrate for interlaminar communication. As well, we observed cross-frequency coupling (CFC) between theta phase and high gamma amplitude similar to that observed in vivo. The high gamma "bursts" generated by such CFC varied in their frequency content, suggesting that this variability may underlie the broadband nature of high gamma activity.
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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".