Rapid optimization of behavior requires decisions about when to explore and when to exploit discovered resources. The mechanisms that lead to fast adaptations and their interaction with action valuation are a central issue. We show here that the anterior cingulate cortex (ACC) encodes multiple feedbacks devoted to exploration and its immediate termination. In a task that alternates exploration and exploitation periods, the ACC monitored negative and positive outcomes relevant for different adaptations. In particular, it produced signals specific of the first reward, i.e., the end of exploration. Those signals disappeared in exploitation periods but immediately transferred to the initiation of trials-a transfer comparable to learning phenomena observed for dopaminergic neurons. Importantly, these were also observed for high gamma oscillations of local field potentials shown to correlate with brain imaging signal. Thus, mechanisms of action valuation and monitoring of events/actions are combined for rapid behavioral regulation.

The anterior cingulate cortex (ACC) is known to play a crucial role in the fast adaptations of behavior based on immediate reward values. What is less certain is whether the ACC is also involved in long-term adaptations to situations with uncertain outcomes. To study this issue, we placed macaque monkeys in a probabilistic context in which the appropriate strategy to maximize reward was to identify the stimulus with the highest reward value (optimal stimulus). Only knowledge of the theoretical average reward value associated with this stimulus--referred to as 'the task value'--was available. Remarkably, in each trial, ACC pre-reward activity correlated with the task value. Importantly, this neuronal activity was observed prior to the discovery of the optimal stimulus. We hypothesize that the received rewards and the task value, constructed a priori through learning, are used to guide behavior and identify the optimal stimulus. We tested this hypothesis by muscimol deactivation of the ACC. As predicted, this inactivation impaired the search for the optimal stimulus. We propose that ACC participates in long-term adaptation of voluntary reward-based behaviors by encoding general task values and received rewards.

SummaryNon-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.