A comparison and evaluation of the predictions of relational and conjunctive accounts of hippocampal function
Bibliographic record
Abstract
Relational and conjunctive memory theory each postulate that the hippocampus participates in the formation of long-term memory representations comprised of associations between multiple elements. The goals of the current work were to clarify and contrast these theories by outlining the nature of the representations that are spared vs. impaired following hippocampal damage according to each theoretical perspective. Relational theory predicts that hippocampal lesions will impair performance on tasks that require the formation of new long-term representations in which distinct elements must be regarded in relation to all other elements. Representations that remain intact despite hippocampal damage include separate representations of distinct individual elements or multiple stimuli fused into a static "blend" such as several elements viewed from one vantage point. Additionally, the relational account predicts that rapid incidental online processing of the relations can be achieved through structures other than the hippocampus, but this information will not be stored. In contrast, conjunctive theory predicts that hippocampal damage will impair the rapid formation of unitary representations that contain features of elements and their relative relationships bound in an inflexible manner. Deficits in the rapid formation of these conjunctive representations result in impaired performance on tasks that require rapid incidental stimulus binding. However, intact formation of conjunctive representations can occur over multiple trials in the service of problem solving. Using these theoretical frameworks, recent findings from the human and nonhuman animal literature are reexamined in order to determine whether one theory better accounts for current findings. We discuss empirical studies that serve as "critical experiments" in addressing the relational vs. conjunctive debate, and find that the predictions of relational theory are supported by existing findings over those from the conjunctive account.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".