Contribution of the subthalamic nucleus to motor, cognitive and limbic processes: an electrophysiological and stimulation study in monkeys.

Deep brain stimulation of the subthalamic nucleus (STN) has become the gold standard surgical treatment for Parkinson's disease and is being investigated for obsessive compulsive disorders. Even if the role of the STN in the behavior is well documented, its organization and especially its division into several functional territories is still debated. A better characterization of these territories and a better knowledge of the impact of stimulation would address this issue. We aimed to find specific electrophysiological markers of motor, cognitive and limbic functions within the STN and to specifically modulate these components. Two healthy non-human primates (Macaca fascicularis) performed a behavioral task allowing the assessment of motor, cognitive and limbic reward-related behavioral components. During the task, four contacts in the STN allowed recordings and stimulations, using low frequency stimulation (LFS) and high frequency stimulation (HFS). Specific electrophysiological functional markers were found in the STN with beta band activity for the motor component of behavior, theta band activity for the cognitive component, and, gamma and theta activity bands for the limbic component. For both monkeys, dorsolateral HFS and LFS of the STN significantly modulated motor performances, whereas only ventromedial HFS modulated cognitive performances. Our results validated the functional overlap of dorsal motor and ventral cognitive subthalamic territories, and, provide information that tends toward a diffuse limbic territory sensitive to the reward within the STN.

The Differential Weights of Motivational and Task Performance Measures on Medial and Lateral Frontal Neural Activity.

Behavioral adaptations are triggered by different constraints given by rules, and are informed by outcomes, or motivational changes. Neural activity in multiple frontal areas is modulated during behavioral adaptations, but the source of these modulations and the nature of the mechanisms involved are unclear. Here we tested how different variables related to changes in task performance and to behavioral adaptation impact the amplitude of event-related local field potentials (LFPs) in the lateral prefrontal and midcingulate cortex of male rhesus macaques. We found that the behavioral task used induced consistently different types of performance modulation: in relation to task difficulty (imposed by the experimental setup), to successes and errors, and to the time spent in the task. Difficulty had a significant effect on monkeys' accuracy and reaction times. Interestingly, there is also a strong interaction between difficulty and trial success on the reaction times variation. However, LFP modulations were mostly related to reaction times, touch position, feedback valence and time-in-session, with little, if any, effect of difficulty. Hence, difficulty modulated performance but not LFP activity. This suggests that, in our experimental design, execution, regulation, and motivation-related factors are the main factors influencing medial and lateral frontal activity.SIGNIFICANCE STATEMENT Adapting decisions might be determined by several mechanisms and might be driven by motivational factors and/or factors inherent to the task at hand. Multiple frontal areas contribute to behavioral adaptations. One current challenge is to understand which information they process contributes to behavioral changes. Diverging views have emerged on whether task demands, like the decision difficulty, or factors linked to incentives to adapt, are driving frontal activity. Here we show that task difficulty had a strong effect on performance (accuracy and reaction times) but little effect on LFP recorded in monkey lateral prefrontal and midcingulate cortex. However, information related to actions, outcome valence, and time-in-session had major influences. Thus, task difficulty modulated performance but not LFP activity in frontal areas.

Inhibitory control of frontal metastability sets the temporal signature of cognition.

Cortical dynamics are organized over multiple anatomical and temporal scales. The mechanistic origin of the temporal organization and its contribution to cognition remain unknown. Here, we demonstrate the cause of this organization by studying a specific temporal signature (time constant and latency) of neural activity. In monkey frontal areas, recorded during flexible decisions, temporal signatures display specific area-dependent ranges, as well as anatomical and cell-type distributions. Moreover, temporal signatures are functionally adapted to behaviourally relevant timescales. Fine-grained biophysical network models, constrained to account for experimentally observed temporal signatures, reveal that after-hyperpolarization potassium and inhibitory GABA-B conductances critically determine areas' specificity. They mechanistically account for temporal signatures by organizing activity into metastable states, with inhibition controlling state stability and transitions. As predicted by models, state durations non-linearly scale with temporal signatures in monkey, matching behavioural timescales. Thus, local inhibitory-controlled metastability constitutes the dynamical core specifying the temporal organization of cognitive functions in frontal areas.

The midcingulate cortex and temporal integration.

The ability to integrate information across time at multiple timescales is a vital element of adaptive behavior, because it provides the capacity to link events separated in time, extract useful information from previous events and actions, and to construct plans for behavior over time. Here we make the argument that this information integration capacity is a central function of the midcingulate cortex (MCC), by reviewing the anatomical, intrinsic network, neurophysiological, and behavioral properties of MCC. The MCC is the region of the medial wall situated dorsal to the corpus callosum and sometimes referred to as dACC. It is positioned within the densely connected core network of the primate brain, with a rich diversity of cognitive, somatomotor and autonomic connections. Furthermore, the MCC shows strong local network inhibition which appears to control the metastability of the region-an established feature of many cortical networks in which the neural dynamics move through a series of quasi-stationary states. We propose that the strong local inhibition in MCC leads to particularly long dynamic state durations, and so less frequent transitions. Apparently as a result of these anatomical features and synaptic and ionic determinants, the MCC cells display the longest neuronal timescales among a range of recorded cortical areas. We conclude that the anatomical position, intrinsic properties, and local network interactions of MCC make it a uniquely positioned cortical area to perform the integration of diverse information over time that is necessary for behavioral adaptation.

Specific frontal neural dynamics contribute to decisions to check.

Curiosity and information seeking potently shapes our behaviour and are thought to rely on the frontal cortex. Yet, the frontal regions and neural dynamics that control the drive to check for information remain unknown. Here we trained monkeys in a task where they had the opportunity to gain information about the potential delivery of a large bonus reward or continue with a default instructed decision task. Single-unit recordings in behaving monkeys reveal that decisions to check for additional information first engage midcingulate cortex and then lateral prefrontal cortex. The opposite is true for instructed decisions. Importantly, deciding to check engages neurons also involved in performance monitoring. Further, specific midcingulate activity could be discerned several trials before the monkeys actually choose to check the environment. Our data show that deciding to seek information on the current state of the environment is characterized by specific dynamics of neural activity within the prefrontal cortex.