In previous reports, we described neuronal activity in the polar (PFp), dorsolateral (PFdl), and orbital (PFo) PFC as monkeys performed a cued strategy task with two spatial goals. On each trial, a cue instructed one of two strategies: Stay with the previous goal or shift to the alternative. A delay period followed each cue, and feedback followed each choice, also at a delay. Our initial analysis showed that the mean firing rate of a population of PFp cells encoded the goal chosen on a trial, but only near the time of feedback, not earlier in the trial. In contrast, PFdl cells encoded goals and strategies during the cue and delay periods, and PFo cells encoded strategies in those task periods. Both areas also signaled goals near feedback time. Here we analyzed trial-to-trial variability of neuronal firing, as measured by the Fano factor (FF): the ratio of variance to the mean. Goal-selective PFp neurons had two properties: (1) a lower FF from the beginning of the trial compared with PFp cells that did not encode goals and (2) a weak but significant inverse correlation between FF throughout a trial and the degree of goal selectivity at feedback time. Cells in PFdl and PFo showed neither of these properties. Our findings indicate that goal-selective PFp neurons were engaged in the task throughout a trial, although they only encoded goals near feedback time. Their lower FF could improve the ability of other cortical areas to decode its selected-goal signal.

Reaching movements require the integration of both somatic and visual information. These signals can have different relevance, depending on whether reaches are performed toward visual or memorized targets. We tested the hypothesis that under such conditions, therefore depending on target visibility, posterior parietal neurons integrate differently somatic and visual signals. Monkeys were trained to execute both types of reaches from different hand resting positions and in total darkness. Neural activity was recorded in Area 5 (PE) and analyzed by focusing on the preparatory epoch, that is, before movement initiation. Many neurons were influenced by the initial hand position, and most of them were further modulated by the target visibility. For the same starting position, we found a prevalence of neurons with activity that differed depending on whether hand movement was performed toward memorized or visual targets. This result suggests that posterior parietal cortex integrates available signals in a flexible way based on contextual demands.

The prefrontal cortex (PFC) supports goal-directed actions and exerts cognitive control over behavior, but the underlying coding and mechanism are heavily debated. We present evidence for the role of goal coding in PFC from two converging perspectives: computational modeling and neuronal-level analysis of monkey data. We show that neural representations of prospective goals emerge by combining a categorization process that extracts relevant behavioral abstractions from the input data and a reward-driven process that selects candidate categories depending on their adaptive value; both forms of learning have a plausible neural implementation in PFC. Our analyses demonstrate a fundamental principle: goal coding represents an efficient solution to cognitive control problems, analogous to efficient coding principles in other (e.g., visual) brain areas. The novel analytical–computational approach is of general interest because it applies to a variety of neurophysiological studies.