Simultaneous oscillatory encoding of "hot" and "cold" information during social interactions in the monkey medial prefrontal cortex.

Social interactions in primates require social cognition abilities such as anticipating the partner's future choices as well as pure cognitive skills involving processing task-relevant information. The medial prefrontal cortex (mPFC) has been implicated in these cognitive processes. Here, we investigated the neural oscillations underlying the complex social behaviors involving the interplay of social roles (Actor vs. Observer) and interaction types (whether working with a "Good" or "Bad" partner). We found opposite power modulations of the beta and gamma bands by social roles, indicating dedicated processing for task-related information. Concurrently, the interaction type was conveyed by lower frequencies, which are commonly associated with neural circuits linked to performance and reward monitoring. Thus, the mPFC exhibits parallel coding of both "cold" processes (purely cognitive) and "hot" processes (reward and social-related). This allocation of neural resources gives the mPFC a key neural node, flexibly integrating multiple sources of information during social interactions.

Prefrontal Control of Proactive and Reactive Mechanisms of Visual Suppression.

In everyday life, we are continuously struggling at focusing on our current goals while at the same time avoiding distractions. Attention is the neuro-cognitive process devoted to the selection of behaviorally relevant sensory information while at the same time preventing distraction by irrelevant information. Distraction can be prevented proactively, by strategically prioritizing task-relevant information at the expense of irrelevant information, or reactively, by suppressing the ongoing processing of distractors. The distinctive neuronal signature of these suppressive mechanisms is still largely unknown. Thanks to machine-learning decoding methods applied to prefrontal cortical activity, we monitor the dynamic spatial attention with an unprecedented spatial and temporal resolution. We first identify independent behavioral and neuronal signatures for long-term (learning-based spatial prioritization) and short-term (dynamic spatial attention) mechanisms. We then identify distinct behavioral and neuronal signatures for proactive and reactive suppression mechanisms. We find that while distracting task-relevant information is suppressed proactively, task-irrelevant information is suppressed reactively. Critically, we show that distractor suppression, whether proactive or reactive, strongly depends on the implementation of both long-term and short-term mechanisms of selection. Overall, we provide a unified neuro-cognitive framework describing how the prefrontal cortex deals with distractors in order to flexibly optimize behavior in dynamic environments.

Prefrontal attentional saccades explore space rhythmically.

Recent studies suggest that attention samples space rhythmically through oscillatory interactions in the frontoparietal network. How these attentional fluctuations coincide with spatial exploration/displacement and exploitation/selection by a dynamic attentional spotlight under top-down control is unclear. Here, we show a direct contribution of prefrontal attention selection mechanisms to a continuous space exploration. Specifically, we provide a direct high spatio-temporal resolution prefrontal population decoding of the covert attentional spotlight. We show that it continuously explores space at a 7-12 Hz rhythm. Sensory encoding and behavioral reports are increased at a specific optimal phase w/ to this rhythm. We propose that this prefrontal neuronal rhythm reflects an alpha-clocked sampling of the visual environment in the absence of eye movements. These attentional explorations are highly flexible, how they spatially unfold depending both on within-trial and across-task contingencies. These results are discussed in the context of exploration-exploitation strategies and prefrontal top-down attentional control.

The Puzzling Relationship between Attention and Motivation: Do Motor Biases Matter?

The relationship between attention and incentive motivation has been mostly examined by administering Posner style cueing tasks in humans and varying monetary stakes. These studies found that higher incentives improved performance independently of spatial attention. However, the ability of the cueing task to measure actual attentional orienting has been debated by several groups that have highlighted the function of the motor system in affecting the behavioral features that are commonly attributed to spatial attention. To determine the impact of motor influences on the interplay between attention and motivation, we administered 2 reaching versions of a cueing task to monkeys in various motor scenarios. In both tasks, a central stimulus indicated the reward stake and predicted the stimulus target location in 80% of trials. In Experiment 1, subjects were requested to report the detection of a target stimulus in each trial. In Experiment 2, the task was modified to fit a paradigm of Go/NoGo target identification. We found that attention and motivation interacted exclusively in Experiment 2, wherein anticipated motor activation was discouraged and more demanding visual processing was imposed. Consequently, we suggest a protocol that provides novel insights into the study of the relationship between spatial attention and motivation and highlights the influence of the arm motor system in the estimation of the deployment of spatial attention.

Neuronal Modulation in the Prefrontal Cortex in a Transitive Inference Task: Evidence of Neuronal Correlates of Mental Schema Management.

When informed that A > B and B > C, humans and other animals can easily conclude that A > C. This remarkable trait of advanced animals, which allows them to manipulate knowledge flexibly to infer logical relations, has only recently garnered interest in mainstream neuroscience. How the brain controls these logical processes remains an unanswered question that has been merely superficially addressed in neuroimaging and lesion studies, which are unable to identify the underlying neuronal computations. We observed that the activation pattern of neurons in the prefrontal cortex (PFC) during pair comparisons in a highly demanding transitive inference task fully supports the behavioral performance of the two monkeys that we tested. Our results indicate that the PFC contributes to the construction and use of a mental schema to represent premises. This evidence provides a novel framework for understanding the function of various areas of brain in logic processes and impairments to them in degenerative, traumatic, and psychiatric pathologies. SIGNIFICANCE STATEMENT: In cognitive neuroscience, it is unknown how information that leads to inferential deductions are encoded and manipulated at the neuronal level. We addressed this question by recording single-unit activity from the dorsolateral prefrontal cortex of monkeys that were performing a transitive inference (TI) task. The TI required one to choose the higher ranked of two items, based on previous, indirect experience. Our results demonstrated that single-neuron activity supports the construction of an abstract, mental schema of ordered items in solving the task and that this representation is independent of the reward value that is experienced for the single items. These findings identify the neural substrates of abstract mental representations that support inferential thinking.

Alpha- and beta-band oscillations subserve different processes in reactive control of limb movements.

The capacity to rapidly suppress a behavioral act in response to sudden instruction to stop is a key cognitive function. This function, called reactive control, is tested in experimental settings using the stop signal task, which requires subjects to generate a movement in response to a go signal or suppress it when a stop signal appears. The ability to inhibit this movement fluctuates over time: sometimes, subjects can stop their response, and at other times, they can not. To determine the neural basis of this fluctuation, we recorded local field potentials (LFPs) in the alpha (6-12 Hz) and beta (13-35 Hz) bands from the dorsal premotor cortex of two nonhuman primates that were performing the task. The ability to countermand a movement after a stop signal was predicted by the activity of both bands, each purportedly representing a distinct neural process. The beta band represents the level of movement preparation; higher beta power corresponds to a lower level of movement preparation, whereas the alpha band supports a proper phasic, reactive inhibitory response: movements are inhibited when alpha band power increases immediately after a stop signal. Our findings support the function of LFP bands in generating the signatures of various neural computations that are multiplexed in the brain.

The NMDAr antagonist ketamine interferes with manipulation of information for transitive inference reasoning in non-human primates.

One of the most remarkable traits of highly encephalized animals is their ability to manipulate knowledge flexibly to infer logical relationships. Operationally, the corresponding cognitive process can be defined as reasoning. One hypothesis is that this process relies on the reverberating activity of glutamate neural circuits, sustained by NMDA receptor (NMDAr) mediated synaptic transmission, in both parietal and prefrontal areas. We trained two macaque monkeys to perform a form of deductive reasoning - the transitive inference task - in which they were required to learn the relationship between six adjacent items in a single session and then deduct the relationship between nonadjacent items that had not been paired in the learning phase. When the animals had learned the sequence, we administered systemically a subanaesthetic dose of ketamine (a NMDAr antagonist) and measured their performance on learned and novel problems. We observed impairments in determining the relationship between novel pairs of items. Our results are consistent with the hypothesis that transitive inference premises are integrated during learning in a unified representation and that reducing NMDAr activity interferes with the use of this mental model, when decisions are required in comparing pairs of items that have not been learned.