Abstract
Dopaminergic neurons (DANs) exhibit complex dynamics across a variety of behavioral contexts, often in ways that seem task-specific and even incompatible with results across different paradigms. Dopaminergic signaling during timing tasks has been a prime example. In behavioral timing, dopaminergic dynamics predict the initiation of self-timed movement via a seconds-long ramp up of activity prior to movement onset, similar to ramping seen in visuospatial reward approach and multi-step, goal-directed behaviors. By contrast, in perceptual timing, DANs exhibit more complex dynamics whose direction of modulation seems to be the opposite of that observed in behavioral timing. Mikhael et al. (2022) recently proposed a formal model in which dopaminergic dynamics encode reward expectation in the form of an “ongoing” reward-prediction error (RPE) that arises from resolving uncertainty of one’s position in the value landscape (i.e., one’s spatial-temporal distance to reward delivery/omission). Here, we show that application of this framework recapitulates and reconciles the seemingly contradictory dopaminergic dynamics observed in behavioral vs perceptual timing. These results suggest a common neural mechanism that broadly underlies timing behavior: trial-by-trial variation in the rate of the internal “pacemaker,” manifested in DAN signals that reflect stretching or compression of the derivative of the subjective value function relative to veridical time. In this view, faster pacemaking is associated with relatively high amplitude dopaminergic signaling, whereas slower pacemaking is associated with relatively low levels of dopaminergic signaling, consistent with findings from pharmacological and lesion studies.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Author note. This work was supported by NIH grants UF-NS109177 and U19-NS113201, and NIH core grant EY-12196. A.E.H. was supported by a Harvard Lefler Predoctoral Fellowship, a Harvard Quan Predoctoral Fellowship, and a Harvard-MIT MD-PhD Program Scholarship. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
We have expanded upon behavioral timing models from the first paper, including new data. We have crested a GitHub repository with the behavioral timing models. We have added a methods section and extended discussion.





