Abstract

Prior expectations of movement instructions can promote preliminary action planning and influence choices. We investigated how action priors affect action-goal encoding in premotor and parietal cortices and if they bias subsequent free choice. Monkeys planned reaches according to visual cues that indicated relative probabilities of two possible goals. On instructed trials, the reach goal was determined by a secondary cue respecting these probabilities. On rarely interspersed free-choice trials without instruction, both goals offered equal reward. Action priors induced graded free-choice biases and graded frontoparietal motor-goal activity, complementarily in two subclasses of neurons. Down-regulating neurons co-encoded both possible goals and decreased opposite-to-preferred responses with decreasing prior, possibly supporting a process of choice by elimination. Up-regulating neurons showed increased preferred-direction responses with increasing prior, likely supporting a process of computing net likelihood. Action-selection signals emerged earliest in down-regulating neurons of premotor cortex, arguing for an initiation of selection in the frontal lobe.

Highlights

  • We are often faced with probabilistic information guiding our decisions and actions, for example, asking ourselves which way to aim a penalty kick when the goalkeeper seems prepared to jump to the right

  • While the pre-cue was indicated in every trial, the associated probabilities only applied to the instructed trials, in which a later rule-cue indicated the single valid goal that would be rewarded upon selection

  • On interspersed free-choice trials, the rule-cue was neutral, indicating that both reach goals would be rewarded with equal probability, independent of the pre-cue at trial start

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Summary

Introduction

We are often faced with probabilistic information guiding our decisions and actions, for example, asking ourselves which way to aim a penalty kick when the goalkeeper seems prepared to jump to the right. These kinds of prior probabilities allow us to prepare the action mostly likely to become relevant, thereby helping us economize reaction times and improve accuracy (Dorris and Munoz, 1998; Basso and Wurtz, 1998; Gold et al, 2008; Suriya-Arunroj and Gail, 2015).

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