Response outcomes gate the impact of expectations on perceptual decisions

• Published in: Nature communications Vol. 11; no. 1; p. 1057
• Main Authors: Hermoso-Mendizabal, Ainhoa, Hyafil, Alexandre, Rueda-Orozco, Pavel E., Jaramillo, Santiago, Robbe, David, de la Rocha, Jaime
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 26.02.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 631/378/116/2396; 631/378/2649/1409; 631/378/2649/1723; 64/86; Acoustic Stimulation; Animals; Auditory tasks; Behavior, Animal - physiology; Bias; Brain Mapping; Computer applications; Decision making; Decision Making - physiology; Discrimination, Psychological - physiology; Humanities and Social Sciences; Life Sciences; Male; Motivation; multidisciplinary; Neurons and Cognition; Psychology and behavior; Rats; Rats, Long-Evans; Reaction Time - physiology; Reinforcement; Reward; Science; Science (multidisciplinary); Sensory Gating - physiology
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-14824-w

Perceptual decisions are based on sensory information but can also be influenced by expectations built from recent experiences. Can the impact of expectations be flexibly modulated based on the outcome of previous decisions? Here, rats perform an auditory task where the probability to repeat the previous stimulus category is varied in trial-blocks. All rats capitalize on these sequence correlations by exploiting a transition bias: a tendency to repeat or alternate their previous response using an internal estimate of the sequence repeating probability. Surprisingly, this bias is null after error trials. The internal estimate however is not reset and it becomes effective again after the next correct response. This behavior is captured by a generative model, whereby a reward-driven modulatory signal gates the impact of the latent model of the environment on the current decision. These results demonstrate that, based on previous outcomes, rats flexibly modulate how expectations influence their decisions. The authors use a combination of perceptual decision making in rats and computational modeling to explore the interplay of priors and sensory cues. They find that rats can learn to either alternate or repeat their actions based on reward likelihood and the influence of bias on their actions disappears after making an error.