Structures involved at the time of temporal lobe spikes revealed by interindividual group analysis of EEG/fMRI data
Bibliographic record
Abstract
PURPOSE: We measured metabolic changes associated with temporal lobe (TL) spikes using combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). We selected 18 patients with temporal lobe epilepsy (TLE) who underwent a 2-h simultaneous EEG-fMRI and had unilateral or bilateral independent TL spikes for interindividual group analysis, in order to identify consistent blood oxygenation level dependent (BOLD) responses to TL spikes. METHODS: EEG was postprocessed and spikes were visually identified. fMRI data were preprocessed with motion correction, spatial smoothing, and removal of low frequency drifts. Spike timings were used as events for fMRI statistical analysis. Four hemodynamic response functions were used to account for variability in the BOLD response. RESULTS: Group analysis revealed common areas of BOLD activations and deactivations. The hemodynamic response function (HRF) peaking 3 s after the spike showed activation involving ipsilaterally the mesial temporal structures (presumably the hippocampus), putamen/globus pallidus, inferior insula, and superior temporal gyrus. The HRF peaking at 5 s showed activations involving ipsi- and contralaterally the superior temporal gyrus and inferior insula. Both HRFs showed bilateral posterior cingulate deactivations. DISCUSSION: We disclosed involvement of a network of activated areas during unilateral TL spikes, including ipsilateral mesial temporal structures, basal ganglia, and bilateral neocortical temporal regions. Despite the low temporal resolution of fMRI we demonstrated that contralateral temporal involvement occurred later than ipsilateral activation. This contralateral change took place in the absence of visible EEG changes. The posterior cingulate deactivation may reflect the interconnections between this region and other limbic structures. It may also partially correspond to a suspension of the default mode network, as previously described for TL spikes.
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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) | 0.001 | 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".