Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation

Anne L. Collins, Venuz Y. Greenfield, Jeffrey K. Bye, Kay E. Linker, Alice S. Wang, Kate M. Wassum

Research output: Contribution to journalArticlepeer-review

56 Scopus citations


Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation.

Original languageEnglish (US)
Article number20231
JournalScientific reports
StatePublished - Feb 12 2016
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by a Hellman Foundation Fellowship, a UCLA Faculty Career Development award, and grant DA035443 from NIDA to KMW. The authors would like to thank Dr. Rick Laughlin for his preliminary intellectual and technical contributions to this work and Dr. Sean Ostlund for his helpful comments on an earlier version of this manuscript. Lastly, the authors would like to thank Dr. Scott Ng-Evans for his hardware and software assistance.


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