Frontal Lobe Epilepsy Alters Functional Connections Within the Brain's Motor Network: A Resting-State fMRI Study
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Bibliographic record
Abstract
Patients with frontal lobe epilepsy (FLE) often experience motor deficits, yet little is known of the impact of FLE on the activity of motor networks in the brain. Resting-state functional magnetic resonance imaging (rs-fMRI) has previously demonstrated an association between cognitive deficits in temporal lobe epilepsy patients and disruption of activity within pertinent brain networks. Hence, in the present study, rs-fMRI was used to determine whether FLE is associated with motor network disruption. Seven right-hemisphere FLE patients, six left-hemisphere FLE patients, and nine control subjects underwent rs-fMRI. Functional connectivity was computed between the sensorimotor cortex contralateral to the seizure focus and each voxel in the brain, and then compared voxel-by-voxel between patient groups and controls. A laterality index (LI) of connectivity between contralateral and ipsilateral sensorimotor cortices was calculated to investigate its association with epilepsy duration and seizure frequency. Positive laterality indices indicate reduced connectivity, and zero values indicate strong connectivity. Connectivity between the left and right sensorimotor cortices was significantly reduced in FLE patients compared with controls (p<0.05), and LI was positively correlated with the number of lifetime seizures (left FLE: rs=0.89, right FLE: rs=1.00). Patients with FLE exhibit decreased connectivity within the motor network, in correlation with the number of lifetime seizures, thus demonstrating a potential relationship between seizure activity and changes in motor network organization. These findings suggest that motor network disturbances may in part be responsible for the motor deficits observed in FLE patients.
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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 | 0.003 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 it