The impact of fornix lesions in rats on spatial learning tasks sensitive to anterior thalamic and hippocampal damage
Bibliographic record
Abstract
The present study sought to understand how the hippocampus and anterior thalamic nuclei are conjointly required for spatial learning by examining the impact of cutting a major tract (the fornix) that interconnects these two sites. The initial experiments examined the consequences of fornix lesions in rats on spatial biconditional discrimination learning. The rationale arose from previous findings showing that fornix lesions spare the learning of spatial biconditional tasks, despite the same task being highly sensitive to both hippocampal and anterior thalamic nuclei lesions. In the present study, fornix lesions only delayed acquisition of the spatial biconditional task, pointing to additional contributions from non-fornical routes linking the hippocampus with the anterior thalamic nuclei. The same fornix lesions spared the learning of an analogous nonspatial biconditional task that used local contextual cues. Subsequent tests, including T-maze place alternation, place learning in a cross-maze, and a go/no-go place discrimination, highlighted the impact of fornix lesions when distal spatial information is used flexibly to guide behaviour. The final experiment examined the ability to learn incidentally the spatial features of a square water-maze that had differently patterned walls. Fornix lesions disrupted performance but did not stop the rats from distinguishing the various corners of the maze. Overall, the results indicate that interconnections between the hippocampus and anterior thalamus, via the fornix, help to resolve problems with flexible spatial and temporal cues, but the results also signal the importance of additional, non-fornical contributions to hippocampal-anterior thalamic spatial processing, particularly for problems with more stable spatial solutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".