Dopamine D2 agonist affects visuospatial working memory distractor interference depending on individual differences in baseline working memory span
The interplay of dopaminergic striatal D1–D2 circuits is thought to support working memory (WM) by selectively filtering information that is to be remembered versus information to be ignored. To test this theory, we conducted an experiment in which healthy participants performed a visuospatial working memory (VSWM) task after ingesting the D2-receptor agonist cabergoline (or placebo), in a randomized, double-blinded, crossover design. Results showed greater interference from distractors under cabergoline, particularly for individuals with higher baseline dopamine (indicated by WM span). These findings support computational theories of striatal D1–D2 function during WM encoding and distractor-filtering, and provide new evidence for interactive cortico-striatal systems that support VSWM capacity and their dependence on WM span.
KeywordsAgonist Basal ganglia Cabergoline Capacity Dopamine D2 Individual differences Prefrontal cortex Striatum Visuospatial working memory Working memory
This study was supported by National Science Foundation (NSF) 1125788 and National Institute of General Medical Sciences (NIGMS) 1P20GM109089-01A1.
- Abi-Dargham, A., Rodenhiser, J., Printz, D., Zea-Ponce, Y.,… & Laruelle, M. (2000). Increased baseline occupancy of D2 receptors by dopamine in schizophrenia. Proceedings of the National Academy of Sciences, 14, 8104–8109.Google Scholar
- Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. A. Bower (Ed.), The psychology of learning and motivation (Vol. 8, pp. 47–89). New York, NY: Academic Press.Google Scholar
- Biller, B. M., Molitch, M. E., Vance, M. L., Cannistraro, K. B., Davis, K. R., Simons, J.,… Klibanski, A. (1996). Treatment of prolactin-secreting macroadenomas with the once-weekly dopamine agonist cabergoline. Journal of Clinical Endocrinology and Metabolism: Clinical and Experimental, 81, 2338–2343.Google Scholar
- Cavanagh, J. F., Masters, S. E., Bath, K., & Frank M. J. (2014). Conflict acts as an implicit cost in reinforcement learning. Nature Communications, 5. https://doi.org/10.1038/ncomms6394
- Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analyses for the behavioral sciences. Mahwah, NJ: Erlbaum.Google Scholar
- Hazy, T. E., Frank, M. J., & O’Reilly, R. C. (2007). Towards an executive without a homunculus: Computational models of the prefrontal cortex/basal ganglia system. Philosophical Transactions of the Royal Society B. https://doi.org/10.1098/rstb.2007.2055
- Millan, M. J., Maoffiss, L., Didra, C., Audino, V., Bontin, J., & Newman-Tancredi, A. (2002). Differential actions of antiparkinson agents at multiple classes of monoaminergic receptor: I. A multivariate analysis of the binding profiles of 14 drugs at 21 native and cloned human receptor subtypes. The Journal of Pharmacology and Experimental Therapeutics, 303, 791–804.CrossRefPubMedGoogle Scholar
- Nassar, M. R., Helmers, J., & Frank, M. J. (2017). Chunking as a rational strategy for lossy data compression in visual working memory tasks. Retrieved from http://biorxiv.org/content/early/2017/01/06/098939
- Redick, T. S., Broadway, J. M., Meier, M. E., Kuriakose, P. S., Unsworth, N., Kane, M. J., & Engle, R. W. (2012). Measuring working memory capacity with automated complex span tasks. European Journal of Psychological Assessment, 28, 164–171. https://doi.org/10.1027/1015-5759/a000123 CrossRefGoogle Scholar
- Schneider, W., Eschman, A., & Zuccolotto, A. (2002). E-Prime user’s guide. Pittsburgh, PA: Psychology Software Tools.Google Scholar