Epileptic scalp ripples are associated with corticothalamic <scp>BOLD</scp> changes
Bibliographic record
Abstract
OBJECTIVE: Interictal high frequency oscillations (HFOs) in the 40-200 Hz range have been identified in scalp electroencephalography (EEG) recordings of patients with focal epilepsy. HFOs usually co-occur with interictal epileptiform discharges (IEDs), and are specific and accurate markers for the epileptic focus, but the brain regions involved when HFOs are generated are unknown. We investigated this question with combined EEG-functional magnetic resonance imaging (fMRI), measuring the blood oxygenation level-dependent (BOLD) signal, and examined HFOs in the gamma (40-80 Hz) and ripple (80-200 Hz) bands. METHODS: Twenty-eight consecutive patients with focal epilepsy who underwent HFO and EEG-fMRI studies were selected; six were excluded because of negative EEG-fMRI. The remaining 22 patients were divided into two equal groups (11 patients each) based on the frequency of co-occurrence of gamma or ripples with IEDs: low versus high gamma (LG/HG) and low versus high ripples (LR/HR). RESULTS: No significant changes were found in the BOLD characteristics between the LG and HG groups. As a group, HR had a larger IED concordant BOLD cluster than the LR group, despite similar IED rates. In addition, the HR group had significantly more thalamic BOLD changes than the LR group (11/11 vs. 2/11). In HR, 5 of 11 patients had thalamic activation only, 4 of 11 had thalamic deactivation only, and 2 of 11 had activation and deactivation in different thalamic regions. In the LR group, 2 of 11 had thalamic activation. The lateralization of thalamic BOLD responses was concordant with the lateralization of cortical ripples in 12 of 13 patients. SIGNIFICANCE: Scalp IEDs, when frequently accompanied by HFOs in the ripple but not in the gamma band, are associated with larger cortical metabolic responses and with thalamic involvement lateralized to the side of cortical ripples. We propose that a high rate of epileptic ripples is associated with a more active pathologic cortical-thalamocortical network.
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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 | 0.001 |
| 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) | 0.002 | 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".