Outcome Modulation Across Tasks in the Primate Dorsolateral Prefrontal Cortex

Methylphenidate affects task-switching and neural signaling in non-human primates

RATIONALE

Low doses of psychostimulants such as methylphenidate (MPH), which increase extracellular dopamine and norepinephrine by inhibiting their reuptake, are the most commonly used treatment for attention deficit hyperactivity disorder (ADHD). Therapeutic doses of these drugs may improve focused attention at the expense of hindering other cognitive functions, including the ability to adapt behavior in response to changing circumstances-cognitive flexibility. Cognitive flexibility is thought to depend on proper operation of the prefrontal cortex (PFC) and is also linked to reward processing, which is dopamine-dependent. Additionally, reward outcome signals have been recorded from the PFC.

OBJECTIVES

This study tested the hypothesis that therapeutic doses of MPH impair cognitive flexibility and that this impairment in performance resulted from interference in reward signals within the PFC.

METHODS

Four rhesus monkeys were given therapeutically relevant doses of oral MPH (0, 3, and 6 mg/kg) while performing an oculomotor switching task to evaluate its effect on task performance. Single-unit recordings in the PFC of two monkeys were taken before and after MPH administration during task performance.

RESULTS

The results show that MPH does hinder switching task performance, an effect that was correlated with a reduction in the amplitude of outcome signals found in the discharges of some neurons in the PFC.

CONCLUSIONS

Methylphenidate impaired task-switching performance, which can be used as a measure of cognitive flexibility. This detriment may result from degraded outcome signaling within the PFC. This study has implications for the use of MPH in the treatment of ADHD.

Hidden Markov Models Predict the Future Choice Better Than a PSTH-Based Method

Beyond average firing rate, other measurable signals of neuronal activity are fundamental to an understanding of behavior. Recently, hidden Markov models (HMMs) have been applied to neural recordings and have described how neuronal ensembles process information by going through sequences of different states. Such collective dynamics are impossible to capture by just looking at the average firing rate. To estimate how well HMMs can decode information contained in single trials, we compared HMMs with a recently developed classification method based on the peristimulus time histogram (PSTH). The accuracy of the two methods was tested by using the activity of prefrontal neurons recorded while two monkeys were engaged in a strategy task. In this task, the monkeys had to select one of three spatial targets based on an instruction cue and on their previous choice. We show that by using the single trial's neural activity in a period preceding action execution, both models were able to classify the monkeys' choice with an accuracy higher than by chance. Moreover, the HMM was significantly more accurate than the PSTH-based method, even in cases in which the HMM performance was low, although always above chance. Furthermore, the accuracy of both methods was related to the number of neurons exhibiting spatial selectivity within an experimental session. Overall, our study shows that neural activity is better described when not only the mean activity of individual neurons is considered and that therefore, the study of other signals rather than only the average firing rate is fundamental to an understanding of the dynamics of neuronal ensembles.

Effects of reward size and context on learning in macaque monkeys

The outcome of an action plays a crucial role in decision-making and reinforcement learning processes. Indeed, both human and animal behavioural studies have shown that different expected reward values, either quantitatively or qualitatively, modulate the motivation of subjects to perform an action and, as a consequence, affect their behavioural performance. Here, we investigated the effect of different amounts of reward on the learning of macaque monkeys using a modified version of the object-in-place task. This task offers the opportunity to shape rapid learning based on a set of external stimuli that enhance an animal's accuracy in terms of solving a problem. We compared the learning of three monkeys among three different reward conditions. Our results demonstrate that the larger the reward, the better the monkey's ability to learn the associations starting with the second presentation of the problem. Moreover, we compared the present results with those of our previous work using the same monkeys in the same task but with a unique reward condition, the intermediate one. Interestingly, the performance of our animals in our previous work matched with their performance in the largest and not intermediate reward condition of the present study These results suggest that learning is mostly influenced by the reward context and not by its absolute value.