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Kalman-filter model of rats’ reversal learning under LSD

Clara Elizabeth
University of Colorado, Boulder ~ Psychology & Neuroscience
Matt Jones
University of Colorado Boulder

Recent work on the cognitive effects of psychedelics proposes these substances act to weaken the impact of prior expectations, thus increasing the subject’s ability to flexibly accommodate patterns in new experiential data (RElaxed Beliefs Under pSychedelics [REBUS]; Carhart-Harris & Friston, 2019, doi 10.1124/pr.118.017160). Whereas this theory has previously been applied to perception and belief, here we apply it to learning. We develop a Bayesian model of reinforcement learning based on the Kalman filter, in which psychedelics increase the variance of the random walk or equivalently decrease observation noise. Thus as dosage increases, the impact of new observations increases relative to previous experience. The model is applied to data on reversal learning in rats (King et al., 1974, doi 10.1111/j.1476-5381.1974.tb08611.x) and is found to provide a good account for the positive effects of LSD on learning rates following reversal.


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Cite this as:

Elizabeth, C., & Jones, M. (2021, November). Kalman-filter model of rats’ reversal learning under LSD. Paper presented at MathPsych at Virtual Psychonomics 2021. Via