Application of amplitude of low-frequency fluctuation in non-lesional epilepsy: a blood oxygenation level dependent functional MRI study
Bibliographic record
Abstract
Objective To study the changes of amplitude of low-frequency fluctuation (ALFF) in blood oxygenation level dependent functional MRI (BOLD-fMPI) in non-lesional epilepsy (NLE),and discuss its underlying neurophysiological mechanism. Methods The BOLD-fMRI data of 16 patients with NLE and 15 normal volunteers were analyzed by ALFF. The amplitude of the blood oxygenation level dependent activation of the resting state brain was investigated. The brain structures showing increased and decreased ALFF in NLE patients were demonstrated by comparing to normal subjects with 2-sample t-test with threshold of P＜0.05. Results As compared with those in normal subjects,the regions showing increased ALFF in NLE patients were distributed in the right temporal lobe (Montreal Neurological Institute [MNI] coordinates:x=15,y=90,z=21),medial frontal lobe (MNI coordinates:0,24,-24),ventral anterior cingulated (MNI coordinates:-12,30,27) and right cerebellar hemisphere (MNI coordinates:-51,-57,-4); while the regions showing decreased ALFF covered the areas of the left cerebellar hemisphere (MNI coordinates:-48,-15,39),posterior cingulum gyrus (MNI coordinates:60,-21,33) and precuneus (MNI coordinates:-6,-54,66). Conclusion NLE patients show abnormal brain functional organization in resting state; the increased ALFF is considered to be the facilitation such as epileptic activity generation and propagation,while the decreased ALFF might be considered as the functional inhibition in these regions. Key words: Epilepsy; Functional magnetic resonance imaging; Amplitude of low-frequency fluctuation
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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".