Olfactory learning: convergent findings from lesion and brain imaging studies in humans
Bibliographic record
Abstract
The role of temporal lobe structures in olfactory memory was investigated by (i) the examination of odour learning and memory in patients who had undergone resection from a temporal lobe (including primary olfactory regions) for the treatment of intractable epilepsy; and (ii) the examination of brain function during odour memory tasks as assessed via PET imaging of healthy individuals. In order to study different stages of odour memory, recognition of a 'list' of odours was tested after a first exposure, again after four exposures and once more after a 24 h delay interval. Patients with resection from a temporal lobe performed significantly less well than control subjects on all trials, and no significant differences were noted as a function of side of resection, indicating that there is not a strong hemispheric superiority for this task. The PET data yielded different levels of activity in piriform cortex (primary olfactory cortex), in relation to the 'no-odour' baseline scan, depending on the type of processing: no increase in activity noted during odour encoding, a small increase bilaterally during short-term recognition and a larger increase bilaterally during long-term recognition. These findings, together with findings in animal studies, suggest that piriform cortex may have an active role in odour memory processing, not simply in odour perception. Taken together, the findings from the lesion study and functional brain imaging of healthy subjects suggest that olfactory memory requires input from left and right temporal lobe regions for optimal odour recognition, and that, unlike with verbal or non-verbal visual material, there is not a strong functional lateralization for olfactory 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".