Intracranial Electroencephalography Reveals Selective Responses to Cognitive Stimuli in the Periventricular Heterotopias
Bibliographic record
Abstract
Our recent work suggests that non-lesional epileptic brain tissue is capable of generating normal neurophysiological responses during cognitive tasks, which are then seized by ongoing pathologic epileptic activity. Here, we aim to extend the scope of our work to epileptic periventricular heterotopias (PVH) and examine whether the PVH tissue also exhibits normal neurophysiological responses and network-level integration with other non-lesional cortical regions. As part of routine clinical assessment, three adult patients with PVH underwent implantation of intracranial electrodes and participated in experimental cognitive tasks. We obtained simultaneous recordings from PVH and remote cortical sites during rest as well as controlled experimental conditions. In all three subjects (two females), cognitive experimental conditions evoked significant electrophysiological responses in discrete locations within the PVH tissue that were correlated with responses seen in non-epileptic cortical sites. Moreover, the responsive PVH sites exhibited correlated electrophysiological activity with responsive, non-lesional cortical sites during rest conditions. Taken together, our work clearly demonstrates that the PVH tissue may be functionally organized and it may be functionally integrated within cognitively engaged cortical networks despite its anatomic displacement during neurodevelopment. SIGNIFICANCE STATEMENTPeriventricular heterotopias (PVH) are developmentally abnormal brain tissues that frequently cause epileptic seizures. In a rare opportunity to obtain direct electrophysiological recordings from PVH, we were able to show that, contrary to common assumptions, PVH functional activity is similar to healthy cortical sites during a well-established cognitive task and exhibits clear resting state connectivity with the responsive cortical regions.
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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".