The Critical Roles of Localization and Physiology for Understanding Parietal Contributions to Memory Retrieval
Bibliographic record
Abstract
Functional magnetic resonance imaging (fMRI) studies of recognition memory ubiquitously demonstrate retrieval-related activity in left lateral parietal cortex (LLPC) when contrasting studied ("old") items with unstudied ("new") items. Recent work demonstrates that there is considerable functional-anatomical heterogeneity in LLPC. One implication of this observation is that single- or dual-process models fall short of characterizing LLPC contributions to memory retrieval. Instead of considering LLPC as a single entity, functional accounts must be given for each of the distinct regions that show retrieval-related effects; we posit there are a minimum of four such regions and very likely more. Identification of these LLPC regions requires careful analysis to map the boundaries and the extent of the regions precisely. In addition, characterizing the functional responses as activations or deactivations relative to baseline will be crucial in understanding the underlying cognitive processes. Considering LLPC in both memory and "nonmemory" domains will also illuminate the contribution of these regions, because it is certainly unlikely they serve only the domain of memory retrieval.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".