Neural mechanisms underlying the reward‐related enhancement of motivation when remembering episodic memories with high difficulty
Bibliographic record
Abstract
The motivation to receive rewards enhances episodic memories, and the motivation is modulated by task difficulty. In episodic retrieval, however, functional neuroimaging evidence regarding the motivation that mediates interactions between reward and task difficulty is scarce. The present fMRI study investigated this issue. During encoding performed without fMRI, participants encoded Japanese words using either deep or shallow strategies, which led to variation in difficulty level during subsequent retrieval. During retrieval with fMRI, participants recognized the target words in either high or low monetary reward conditions. In the behavioral results, a reward-related enhancement of memory was found only when the memory retrieval was difficult, and the rewarding effect on subjective motivation was greater in the retrieval of memories with high difficulty than those with low difficulty. The fMRI data showed that reward-related increases in the activation of the substantia nigra/ventral tegmental area (SN/VTA), medial temporal lobe (MTL), dorsomedial prefrontal cortex (dmPFC), and dorsolateral prefrontal cortex (dlPFC) were greater during the retrieval of memories with high difficulty than those with low difficulty. Furthermore, reward-related enhancement of functional connectivity between the SN/VTA and MTL and between the SN/VTA and dmPFC during the retrieval of memories with high difficulty was significantly correlated with reward-related increases of retrieval accuracy and subjective motivation. The reward-related enhancement of episodic retrieval and retrieval-related motivation could be most effective when the level of retrieval difficulty is optimized. Such reward-related enhancement of memory and motivation could be modulated by a network including the reward-related SN/VTA, motivation-related dmPFC, and memory-related MTL. Hum Brain Mapp 38:3428-3443, 2017. © 2017 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".