Hemisphere-specific Episodic Memory Networks in the Human Brain: A Correlation Study between Intracarotid Amobarbital Test and [18F]FDG-PET
Bibliographic record
Abstract
The purpose of the present study was to explore the brain regions involved in human episodic memory by correlating unilateral memory performance estimated by the intracarotid amobarbital test (IAT) and interictal cerebral metabolism measured by [(18)F]fluorodeoxyglucose positron emission tomography ([(18)F]FDG-PET). Using this method, regional alterations of cerebral metabolism associated with epilepsy pathophysiology are used to predict hemisphere-specific episodic memory function, hence, investigate the differential distribution of memory in each hemisphere. Sixty-two patients with unilateral temporal lobe epilepsy (35 left and 27 right) were studied using [(18)F]FDG-PET with complementary voxel-based statistical parametric mapping (SPM) and region-of-interest (ROI) methods of analysis. Positive regression was analyzed in SPM with a series of different thresholds (p = .001, .01 or .05) with a correction to 100 voxels. IAT memory performance in which left hemisphere was tested by right-sided injection of amobarbital correlated with [(18)F]FDG uptake in left lateral and medial temporal regions, and in the left ventrolateral frontal cortex. Right IAT memory performance correlated with [(18)F]FDG uptake in the right inferior parietal lobule, right dorsolateral frontal cortex, right precentral gyrus, and caudal portion of the right anterior cingulate cortex. ROI analysis corroborated these results. Analyses carried out separately in patients with left (n = 50) and nonleft (n = 12) dominance for language showed that in the nonleft dominant group, right IAT scores correlated with right fronto-temporal regions, whereas left total memory scores correlated with left lateral and medial temporal regions. The findings indicate that (i) episodic memory is subserved by more widespread cortical regions beyond the core mesiotemporal lobe memory structures; (ii) there are different networks functional in the two hemispheres; and (iii) areas involved in memory may be different between patients with left and nonleft dominance for language, particularly in the right hemisphere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".