Reward Anticipation Dynamics during Cognitive Control and Episodic Encoding: Implications for Dopamine
Bibliographic record
Abstract
Dopamine (DA) modulatory activity critically supports motivated behavior. This modulation operates at multiple timescales, but the functional roles of these distinct dynamics on cognition are still being characterized. Reward processing has been robustly linked to DA activity; thus, examining behavioral effects of reward anticipation at different timing intervals, corresponding to different putative dopaminergic dynamics, may help in characterizing the functional role of these dynamics. Towards this end, we present two research studies investigating reward motivation effects on cognitive control and episodic memory, converging in their manipulation of rapid vs. multi-second reward anticipation (consistent with timing profiles of phasic vs. ramping DA, respectively) on performance. Under prolonged reward anticipation, both control and memory performances were enhanced, specifically when combined with other experimental factors: task-informative cues (control task) and reward uncertainty (memory task). Given observations of ramping DA under uncertainty (Fiorillo et al., 2003) and arguments that uncertainty may act as a control signal increasing environmental monitoring (Mushtaq et al., 2011), we suggest that task information and reward uncertainty can both serve as "need for control" signals that facilitate learning via enhanced monitoring, and that this activity may be supported by a ramping profile of dopaminergic activity. Observations of rapid (i.e., phasic) reward on control and memory performance can be interpreted in line with prior evidence, but review indicates that contributions of different dopaminergic timescales in these processes are not well-understood. Future experimental work to clarify these dynamics and characterize a cross-domain role for reward motivation and DA in goal-directed behavior is suggested.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".