Dissociation of recognition and recency memory judgments after anterior thalamic nuclei lesions in rats.
Bibliographic record
Abstract
The anterior thalamic nuclei form part of a network for episodic memory in humans. The importance of these nuclei for recognition and recency judgments remains, however, unclear. Rats with anterior thalamic nuclei lesions and their controls were tested on object recognition, along with two types of recency judgment. The spontaneous discrimination of a novel object or a novel odor from a familiar counterpart (recognition memory) was not affected by anterior thalamic lesions when tested after retention delays of 1 and 60 min. To measure recency memory, rats were shown two familiar objects, one of which had been explored more recently. In one condition, rats were presented with two lists (List A, List B) of objects separated by a delay, thereby creating two distinct blocks of stimuli. After an additional delay, rats were presented with pairs of objects, one from List A and one from List B (between-block recency). No lesion-induced deficit was apparent for recency discriminations between objects from different lists, despite using three different levels of task difficulty. In contrast, rats with anterior thalamic lesions were significantly impaired when presented with a continuous list of objects and then tested on their ability to distinguish between those items early and late in the same list (within-block recency). The contrasting effects on recognition and recency support the notion that interlinked hippocampal-anterior thalamic interconnections support aspects of both spatial and nonspatial learning, although the role of the anterior thalamic nuclei may be restricted to a subclass of recency judgments (within-block).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".