Forgetting as an Active Process: An fMRI Investigation of Item-Method-Directed Forgetting
Bibliographic record
Abstract
Using event-related functional magnetic resonance imaging (fMRI), we examined the blood oxygen level-dependent response associated with intentional remembering and forgetting. In an item-method directed forgetting paradigm, participants were presented with words, one at a time, each of which was followed after a brief delay by an instruction to Remember or Forget. Behavioral data revealed a directed forgetting effect: greater recognition of to-be-remembered than to-be-forgotten words. We used this behavioral recognition data to sort the fMRI data into 4 conditions based on the combination of memory instruction and behavioral outcome. When contrasted with unintentional forgetting, intentional forgetting was associated with increased activity in hippocampus (Broadmann area [BA] 35) and superior frontal gyrus (BA10/11); when contrasted with intentional remembering, intentional forgetting was associated with activity in medial frontal gyrus (BA10), middle temporal gyrus (BA21), parahippocampal gyrus (BA34 and 35), and cingulate gyrus (BA31). Thus, intentional forgetting depends on neural structures distinct from those involved in unintentional forgetting and intentional remembering. These results challenge the standard selective rehearsal account of item-method directed forgetting and suggest that frontal control processes may be critical for directed forgetting.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".