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Curr Biol. 2018 Mar 5;28(5):795-802.e6. doi: 10.1016/j.cub.2018.01.071. Epub 2018 Feb 15.

Dynamic Interplay of Value and Sensory Information in High-Speed Decision Making.

Author information

1
Department of Biomedical Engineering, The City College of The City University of New York, New York, NY 10031, USA.
2
Department of Biomedical Engineering, The City College of The City University of New York, New York, NY 10031, USA; Zuckerman Mind, Brain, and Behavior Institute, Columbia University, New York, NY 10027, USA.
3
Department of Biomedical Engineering, The City College of The City University of New York, New York, NY 10031, USA; OCTO Technology, Paris, France.
4
Department of Biomedical Engineering, The City College of The City University of New York, New York, NY 10031, USA; School of Electrical and Electronic Engineering, University College Dublin, Ireland. Electronic address: simon.kelly@ucd.ie.

Abstract

In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively [1-6], but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases are affected by starting the integrator closer to the more valuable bound. Here, we show significant departures from this account for humans making rapid sensory-instructed action choices. Behavior was best explained by a simple model in which the evidence representation-and hence, rate of accumulation-is itself biased by value and is non-stationary, increasing over the short decision time frame. Because the value bias initially dominates, the model uniquely predicts a dynamic "turn-around" effect on low-value cues, where the accumulator first launches toward the incorrect action but is then re-routed to the correct one. This was clearly exhibited in electrophysiological signals reflecting motor preparation and evidence accumulation. Finally, we construct an extended model that implements this dynamic effect through plausible sensory neural response modulations and demonstrate the correspondence between decision signal dynamics simulated from a behavioral fit of that model and the empirical decision signals. Our findings suggest that value and sensory information can exert simultaneous and dynamically countervailing influences on the trajectory of the accumulation-to-bound process, driving rapid, sensory-guided actions.

PMID:
29456147
PMCID:
PMC5841252
DOI:
10.1016/j.cub.2018.01.071
[Indexed for MEDLINE]
Free PMC Article

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