Top-Down and Bottom-Up Attention to Memory Are Dissociated in Posterior Parietal Cortex: Neuroimaging and Neuropsychological Evidence
Bibliographic record
Abstract
Posterior parietal cortex is active during episodic memory retrieval, yet its role remains unclear. According to a recent proposal, dorsal parietal cortex (DPC) allocates top-down attention to memory retrieval, whereas ventral parietal cortex (VPC) mediates the bottom-up attentional capture by retrieved contents, i.e., the Attention-to-Memory (AtoM) hypothesis. Here, for the first time, functional magnetic resonance imaging (fMRI) and lesion techniques were combined in a single study to test the role of parietal cortex in episodic retrieval. Participants studied word pairs and then detected studied (target) words among new words. In some conditions, a studied word cued the upcoming target word, facilitating recognition performance. In line with the AtoM hypothesis, left DPC was engaged when participants searched for/anticipated memory targets upon presentation of relevant memory cues and predicted the ensuing behavioral advantage. In contrast, left VPC predicted efficacy and speed of target detection on noncued trials and was largest for memory targets that were invalidly cued. Consistent with fMRI evidence, patients with lesions in DPC did not benefit from memory cueing, whereas patients with lesions in VPC had problems recognizing unexpected memory targets. These results support the AtoM hypothesis that DPC and VPC mediate top-down and bottom-up attention to memory retrieval, respectively.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".