Multiple routes of communication within the amygdala-mPFC network: A comparative approach in humans and macaques.

The network formed by the amygdala (AMG) and the medial Prefrontal Cortex (mPFC), at the interface between our internal and external environment, has been shown to support some important aspects of behavioral adaptation. Whether and how the anatomo-functional organization of this network evolved across primates remains unclear. Here, we compared AMG nuclei morphological characteristics and their functional connectivity with the mPFC in humans and macaques to identify potential homologies and differences between these species. Based on selected studies, we highlight two subsystems within the AMG-mPFC circuits, likely involved in distinct temporal dynamics of integration during behavioral adaptation. We also show that whereas the mPFC displays a large expansion but a preserved intrinsic anatomo-functional organization, the AMG displays a volume reduction and morphological changes related to specific nuclei. We discuss potential commonalities and differences in the dialogue between AMG nuclei and mPFC in humans and macaques based on available data.

Response selection versus feedback analysis in conditional visuo-motor learning.

Conditional associative sensori-motor learning (i.e. the acquisition of specific arbitrary sensori-motor mappings) involves several processes that depend upon the integrity of the fronto-striatal system. The specific role of the different components of the fronto-striatal system in this type of learning is still unclear and was examined in the present functional Magnetic Resonance Imaging (fMRI) study in humans. The subjects had to learn by trial and error arbitrary associations between visual stimuli and motor responses in an experimental paradigm designed to dissociate between the neuronal substrates specifically involved in the selection of the appropriate response and in the analysis of the feedback obtained during the learning and post-learning periods. First, the results demonstrate that the dorsal premotor (PMd) cortex is the critical structure for the acquisition and execution of arbitrary mappings of visual stimuli to motor responses. Second, they reveal an important shift in activation from the cognitive fronto-striatal network (involving the caudate nucleus, the dorsolateral prefrontal cortex, and the PMd) to the motor fronto-striatal network (involving the putamen and the PMd) as we move from initial learning of sensori-motor relations to the post-learning selection of the responses. Finally, they show that feedback processing, but not response selection, increased activity in the anterior cingulate and orbitofrontal cortical regions, demonstrating the selective involvement of these limbic frontal regions in the processing of the consequences of a given action. Altogether our data suggest that, in conditional visuo-motor learning, the associations are critically regulated by the dorsal premotor cortex and the striatum, with additional brain areas contributing to specific aspects of the learning and performance of such associations.

Reward encoding in the monkey anterior cingulate cortex.

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.

The effects of sequence structure and reward schedule on serial reaction time learning in the monkey.

This research tests the hypothesis that sequence learning performance in non-human primates will be modulated both by the structure of the sequences to be learned and by the schedule of reward applied during learning. Sequence learning in humans has been extensively explored with serial reaction time (SRT) protocols where learning is revealed by reduced reaction times for stimuli presented in repeating sequences vs. stimuli presented in random series. The SRT protocol has been used to demonstrate that different types of sequential structure may be learned under different awareness conditions. Here, we consider surface and abstract structure of sensorimotor sequences such that sequences ABCBAC and DEFEDF (where A to F correspond to spatial locations on a touch sensitive screen) have different serial order or surface structure, but share the same abstract structure 123213, and are thus considered isomorphic. In four experiments, we manipulated the type of sequential structure to be learned, and the schedule of reward in spatial sequence learning tasks. Both of the two monkeys tested demonstrated significant SRT learning for serial order or surface structure, while they failed to learn and transfer abstract structure. Their learning performance was also modulated by the schedule of reward. These results are in support of our hypothesis and are discussed in the context of existing models of sensorimotor sequence learning.