Systems Consolidation in the Context of Schemas, Sleep, and Medial Temporal Lobe Damage
Bibliographic record
Abstract
In recent years, models of systems consolidation have become more complex as we consider the different factors that influence the establishment of long-lasting memories. This dissertation outlines a series of experiments that examines systems consolidation in two contexts: 1) in patients with temporal lobe epilepsy who evince a relatively selective long-term memory disorder, termed accelerated long-term forgetting (ALF), and 2) in the context of schematic congruency of new information with prior knowledge in the healthy brain, which has been shown to accelerate consolidation in rodents. In study 1, we present evidence that ALF is not a disorder of hippocampal binding and is instead associated with diminished hippocampal coupling with neocortical regions important for ultimately supporting the memory trace over time. In study 2, we report evidence that in the same patients, sleep-related consolidation mechanisms are disrupted. We found that time spent in slow wave sleep overnight was detrimental to subsequent memory, and present evidence that forgetting may be due to more numerous epileptic discharges during this sleep stage. In study 3, we investigated the influence of schematic congruency on memory in the healthy brain over time. Relative to incongruent information, content that was schema-congruent was remembered more coarsely over time, which was associated with increased post-encoding functional coupling between the hippocampus and medial prefrontal cortex (mPFC). There was also greater integration according to the congruent schematic context in the mPFC over time, as assessed via multivoxel pattern-similarity analyses. These findings are consistent with the idea that schemas act as a scaffold for the accelerated consolidation of congruent information. Finally, in study 4, we describe a schema benefit to long-term memory in patients with ALF, although that benefit is not as great as that which was observed for controls. While schematic congruency improved long-term retention in patients, there was some indication that these benefits may not be long-lasting. Together, these studies present evidence for altered timelines of systems consolidation, depending on hippocampal-neocortical interaction, sleep, and schema-congruency.
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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 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".