Familiarity impairments after anterior temporal-lobe resection with hippocampal sparing: Lessons learned from case NB
Bibliographic record
Abstract
We review evidence from an extensive single case study in an individual (NB) who underwent a rare left-sided anterior temporal-lobe resection with sparing of the hippocampus. Our study aimed to determine whether memory functions of perirhinal cortex, which was largely removed in the resection, can be impaired against a background of preserved hippocampus-dependent memory processing. This research was guided by the proposal that item-based familiarity assessment relies on contributions of perirhinal cortex, and that the hippocampus plays a unique role in the relational binding of items to episodic contexts, which is critical for recollection. Seven sets of findings have emerged from this research in NB and from follow-up work in other patients: (i) Familiarity impairments can be selective and be revealed with multiple methods; (ii) selective familiarity and selective recollection impairments can be double dissociated; (iii) selective familiarity impairments show material specificity; (iv) selective familiarity impairments extend to assessment of cumulative lifetime experience; (v) selective familiarity impairments are sensitive to degree of feature overlap between object concepts; (vi) selective familiarity impairments are associated with preserved task-related fMRI signals in the hippocampus; (vii) selective familiarity impairments can be observed in other lesion cases. Despite our main focus on the dual-process framework, we also discuss implications for the functional organization of the medial temporal lobes in broader terms. We argue that our findings shed light on this organization even if the functional specialization of different medial temporal structures is ultimately not fully captured with reference to the cognitive distinction between familiarity and recollection.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".