Case studies continue to illuminate the cognitive neuroscience of memory
Bibliographic record
Abstract
The current ubiquity of functional neuroimaging studies, and the importance they have had in elucidating brain function, obscures the fact that much of what we know about brain-behavior relationships derives largely from the study of single- and multiple-patient cases. A major goal of the present review is to describe how single cases continue to uniquely and critically contribute to cognitive neuroscience theory. With several recent examples from the literature, we demonstrate that single cases can both challenge accepted dogma and generate hypotheses and theories that steer the field in new directions. We discuss recent findings from case studies that specify critical functions of the hippocampus in episodic memory and recollection, and clarify its role in nonmnemonic abilities. Although we focus on the hippocampus, we discuss other regions and the occurrence of new associative learning, as well as the involvement of the ventromedial prefrontal and parietal cortices in memory encoding and retrieval. We also describe ways of dealing with the shortcomings of case studies, and emphasize the partnership of patient and neuroimaging methods in constraining neurocognitive models of memory.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".