Recruitment of the left precentral gyrus in reading epilepsy: A multimodal neuroimaging study
Bibliographic record
Abstract
PURPOSE: In a previous study, we investigated a 42-year-old male patient with primary reading epilepsy using continuous video-electroencephalography (EEG). Reading tasks induced left parasagittal spikes with a higher spike frequency when the phonological reading pathway was recruited compared to the lexical one. Here, we seek to localize the epileptogenic focus in the same patient as a function of reading pathway using multimodal neuroimaging. METHODS AND RESULTS: The participant read irregular words and nonwords presented in a block-design paradigm during magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) recordings, all combined with EEG. Spike analyses from MEG, fNIRS, and fMRI-EEGs data revealed an epileptic focus in the left precentral gyrus, and spike localization did not differ in lexical and phonological reading. CONCLUSION: This study is the first to investigate ictogenesis in reading epilepsy during both lexical and phonological reading while using three different multimodal neuroimaging techniques. The somatosensory and motor control functions of the left precentral gyrus that are congruently involved in lexical as well as phonological reading can explain the identical spike localization in both reading pathways. The concurrence between our findings in this study and those from our previous one supports the role of the left precentral gyrus in phonological output computation as well as seizure activity in a case of reading epilepsy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| 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) | 0.000 | 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 teacher head, 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".