Involvement of the hippocampus in implicit learning of supra-span sequences: The case of JS
Bibliographic record
Abstract
Learning of supra-span sequences was assessed in a densely amnesic individual (SJ) who suffers from a substantial circumscribed bilateral lesion to the hippocampus. SJ’s ability to lay down information originating from repetitive memory recall episodes was assessed using Hebb’s supra-span procedure. After assessment of short-term memory span, 25 sequences of span +1 items were presented to SJ for immediate serial recall (ISR), one sequence being presented repeatedly eight times. Learning was deduced by the comparison of ISR scores on the repeated versus nonrepeated sequences of span +1 items. SJ’s learning capacity was examined using four different types of stimuli: digits, spatial locations (Corsi block tapping test), words, and pseudowords. Implicit learning of sensorimotor sequences was also assessed in SJ using a serial reaction time (SRT) paradigm. Findings with the supra-span ISR task revealed evidence of learning in SJ with all four types of stimuli. The learning magnitude, as well as learning rate, observed in SJ were comparable to those observed in matched control participants. SJ showed evidence of implicit learning on the SRT paradigm. We conclude that the hippocampus is not required to learn certain types of recurrent information, and that the supra-span ISR task can be considered as an implicit-based learning paradigm. These findings have significant implications for our conceptualisation of implicit learning, and for understanding of the role of the hippocampus in learning.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".