Functional Connectivity of the Medial Temporal Lobe Relates to Learning and Awareness
Bibliographic record
Abstract
Learning with awareness is believed to require the involvement of the medial temporal lobe (MTL). In this study, the hypothesis tested was that this involvement is best appreciated by the pattern of MTL functional connectivity with other brain areas. In a sensory learning paradigm, human subjects were classified as AWARE or UNAWARE, on the basis of whether they noted that one of two tones predicted a visual event. Only AWARE subjects acquired and reversed a differential response to the tones. However, learned facilitation was evident in both groups. MTL activity, indexed by blood flow changes measured with positron emission tomography, was correlated with facilitation in both groups but in opposite directions (greater MTL activity was related to less facilitation in AWARE subjects but more facilitation in UNAWARE subjects). Discrimination and reversal in AWARE subjects involved anterior medial, inferior prefrontal, and lateral occipital cortices. Furthermore, unique regional patterns of MTL functional connectivity were observed: AWARE subjects engaged dorsolateral prefrontal and lateral occipital cortices, whereas UNAWARE subjects showed a more spatially restricted network involving contralateral MTL regions and the thalamus. In the AWARE group, the MTL functional connectivity pattern overlapped with regions associated with facilitation and discrimination, but in UNAWARE subjects, the MTL pattern was related only to facilitation. These results suggest that the MTL and functional connected regions, including dorsolateral and medial prefrontal cortex, acted to link facilitation and discrimination patterns in AWARE subjects. Thus, the contribution of the MTL to learning and awareness is shaped by the pattern of interregional interactions, the neural context.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".