Default mode network connectivity indicates episodic memory capacity in mesial temporal lobe epilepsy
Bibliographic record
Abstract
PURPOSE: The clinical relevance of resting state functional connectivity in neurologic disorders, including mesial temporal lobe epilepsy (mTLE), remains unclear. This study investigated how connectivity in the default mode network changes with unilateral damage to one of its nodes, the hippocampus (HC), and how such connectivity can be exploited clinically to characterize memory deficits and indicate postsurgical memory change. METHODS: Functional magnetic resonance imaging (fMRI) resting state scans and neuropsychological memory assessments (Warrington Recognition Tests for Words and Faces) were performed on 19 healthy controls, 20 patients with right mTLE, and 18 patients with left mTLE. In addition, postsurgical fMRI resting state and memory change (postsurgical memory performance-presurgical memory performance) data were available for half of these patients. KEY FINDINGS: Patients with mTLE showed reduced connectivity from the posterior cingulate cortex (PCC) to the epileptogenic HC and increased PCC connectivity to the contralateral HC. Stronger PCC connectivity to the epileptogenic HC was associated with better presurgical memory and with greater postsurgical memory decline. Stronger PCC connectivity to the contralateral HC was associated with less postsurgical memory decline. Following surgery, PCC connectivity to the remaining HC increased from presurgical values and showed enhanced correlation with postsurgical memory function. It is notable that this index was superior to others (hippocampal volume, preoperative memory scores) in explaining variance in memory change following surgery. SIGNIFICANCE: Our results demonstrate the striking clinical significance of the brain's intrinsic connectivity in evaluating cognitive capacity and indicating the potential of postsurgical cognitive morbidity in patients with mTLE.
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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".