Consequences of hippocampal damage across the autobiographical memory network in left temporal lobe epilepsy
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Bibliographic record
Abstract
Lesion and neuroimaging evidence suggests the hippocampus (HC) is a crucial node in the neural network supporting autobiographical memory (AM) retrieval, and thus focal damage to the HC may have functional consequences for structures throughout the network. Using fMRI, we examined the impact of hippocampal damage on the engagement and connectivity of the AM network in 11 patients with left temporal lobe epilepsy (mean age of onset of seizures, 24 years) with significant left hippocampal atrophy and a mild AM deficit. All investigations were completed pre-surgically. The fMRI paradigm comprised three conditions: (i) retrieving specific AMs in response to personalized cues obtained during a pre-scan interview; (ii) a sentence completion control task; and (iii) a size discrimination control task. AM-related activity (relative to the control tasks) was significantly reduced in patients compared to controls, in residual hippocampal tissue and across the AM network, including the medial prefrontal cortex, temporal poles, retrosplenial and lateral parietal cortex. Furthermore, the strength of connections involving the left HC was also reduced in patients. In contrast, connections between extra-hippocampal nodes, such as left retrosplenial and medial prefrontal cortex, were strengthened in patients, possibly reflecting a compensatory mechanism. Our findings confirm that the left HC is a crucial node in the AM network, possibly playing a dominant role in initiating the engagement of other network nodes, and its damage has significant consequences for the functional organization and connectivity of the neural network supporting AM retrieval.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it