Rapid neocortical acquisition of long-term arbitrary associations independent of the hippocampus
Bibliographic record
Abstract
Anterograde amnesia following hippocampal damage involves the loss of the capacity to form new declarative memories but leaves nondeclarative memory processes intact. Current theories of declarative memory suggest the existence of two complementary memory systems: a hippocampal-based system that specializes in rapid acquisition of specific events and a neocortical system that slowly learns through environmental statistical regularities and requires the initial support of the hippocampal system. Contrary to this notion, we demonstrate a neurocognitive mechanism that enables rapid acquisition of novel arbitrary associations independently of the hippocampus. This mechanism has been dubbed "fast mapping" (FM) and is believed to support the rapid acquisition of vocabulary in children as young as 16 mo of age. We used FM to teach novel word-picture associations to four profoundly amnesic patients with hippocampal system damage. Patients were able to acquire arbitrary associations through FM normally, despite profound impairment on a matched standard associative memory task. Most importantly, they retained what they learned through FM after a week's delay, when they were around chance level on the standard task. By contrast, two patients with unilateral damage to the left polar temporal neocortex were impaired on FM, suggesting that this cortical region is critical for associative learning through FM. Left perirhinal and entorhinal cortices might also play a role in learning through FM. Contrary to current theories, these findings indicate that rapid acquisition of declarative-like (relational) memory can be accomplished independently of the hippocampus and that neocortical plasticity can be induced rapidly to support novel arbitrary associations.
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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 | 0.000 |
| 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) | 0.001 | 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".