Neurons in the monkey frontopolar cortex encode learning stage and goal during a fast learning task.

The frontopolar cortex (FPC) is, to date, one of the least understood regions of the prefrontal cortex. The current understanding of its function suggests that it plays a role in the control of exploratory behaviors by coordinating the activities of other prefrontal cortex areas involved in decision-making and exploiting actions based on their outcomes. Based on this hypothesis, FPC would drive fast-learning processes through a valuation of the different alternatives. In our study, we used a modified version of a well-known paradigm, the object-in-place (OIP) task, to test this hypothesis in electrophysiology. This paradigm is designed to maximize learning, enabling monkeys to learn in one trial, which is an ability specifically impaired after a lesion of the FPC. We showed that FPC neurons presented an extremely specific pattern of activity by representing the learning stage, exploration versus exploitation, and the goal of the action. However, our results do not support the hypothesis that neurons in the frontal pole compute an evaluation of different alternatives. Indeed, the position of the chosen target was strongly encoded at its acquisition, but the position of the unchosen target was not. Once learned, this representation was also found at the problem presentation, suggesting a monitoring activity of the synthetic goal preceding its acquisition. Our results highlight important features of FPC neurons in fast-learning processes without confirming their role in the disengagement of cognitive control from the current goals.

Effects of contraction bias on the decision process in the macaque prefrontal cortex.

Our representation of magnitudes such as time, distance, and size is not always veridical because it is affected by multiple biases. From a Bayesian perspective, estimation errors are considered to be the result of an optimization mechanism for the behavior in a noisy environment by integrating previous experience with the incoming sensory information. One influence of the distribution of past stimuli on perceptual decisions is represented by the regression toward the mean, a type of contraction bias. Using a spatial discrimination task with 2 stimuli presented sequentially at different distances from the center, we show that this bias is also present in macaques when comparing the magnitude of 2 distances. We found that the contraction of the first stimulus magnitude toward the center of the distribution accounted for some of the changes in performance, even more so than the effect of difficulty related to the ratio between stimulus magnitudes. At the neural level in the dorsolateral prefrontal cortex, the coding of the decision after the presentation of the second stimulus reflected the effect of the contraction bias on the discriminability of the stimuli at the behavioral level.

Neural representation of others during action observation in posterior medial prefrontal cortex.

Making decisions based on the actions of others is critical to daily interpersonal interactions. We investigated the representations of other's actions at single neural level in posterior medial prefrontal cortex (pmPFC) in two monkeys during the observation of actions of another agent, in a social interaction task. Each monkey separately interacted with a human partner. The monkey and the human alternated turns as actor and observer. The actor was required to reach one of two visual targets, avoiding the previously chosen target, while the observer monitored that action. pmPFC neurons decoupled in most cases self from others during both the execution and the observation of explicit actions. pmPFC neurons showed selective directional tuning specific for the agent who was executing the task. Moreover, we assessed the relationship of the response coding between the periods immediately before and after the action, by using a cross-modal decoding analysis. We found neural network stability from the action anticipation period to the observation of other's actions, suggesting a strong relationship between the anticipation and the execution of an action. When the monkey was the actor, the population coding appeared dynamic, possibly reflecting a goal-action transformation unique to the monkey's own action execution.

Dedicated Representation of Others in the Macaque Frontal Cortex: From Action Monitoring and Prediction to Outcome Evaluation.

Social neurophysiology has increasingly addressed how several aspects of self and other are distinctly represented in the brain. In social interactions, the self-other distinction is fundamental for discriminating one's own actions, intentions, and outcomes from those that originate in the external world. In this paper, we review neurophysiological experiments using nonhuman primates that shed light on the importance of the self-other distinction, focusing mainly on the frontal cortex. We start by examining how the findings are impacted by the experimental paradigms that are used, such as the type of social partner or whether a passive or active interaction is required. Next, we describe the 2 sociocognitive systems: mirror and mentalizing. Finally, we discuss how the self-other distinction can occur in different domains to process different aspects of social information: the observation and prediction of others' actions and the monitoring of others' rewards.

Low-dimensional dynamics for working memory and time encoding.

Our decisions often depend on multiple sensory experiences separated by time delays. The brain can remember these experiences and, simultaneously, estimate the timing between events. To understand the mechanisms underlying working memory and time encoding, we analyze neural activity recorded during delays in four experiments on nonhuman primates. To disambiguate potential mechanisms, we propose two analyses, namely, decoding the passage of time from neural data and computing the cumulative dimensionality of the neural trajectory over time. Time can be decoded with high precision in tasks where timing information is relevant and with lower precision when irrelevant for performing the task. Neural trajectories are always observed to be low-dimensional. In addition, our results further constrain the mechanisms underlying time encoding as we find that the linear "ramping" component of each neuron's firing rate strongly contributes to the slow timescale variations that make decoding time possible. These constraints rule out working memory models that rely on constant, sustained activity and neural networks with high-dimensional trajectories, like reservoir networks. Instead, recurrent networks trained with backpropagation capture the time-encoding properties and the dimensionality observed in the data.

The importance of urgency in decision making based on dynamic information.

A standard view in the literature is that decisions are the result of a process that accumulates evidence in favor of each alternative until such accumulation reaches a threshold and a decision is made. However, this view has been recently questioned by an alternative proposal that suggests that, instead of accumulated, evidence is combined with an urgency signal. Both theories have been mathematically formalized and supported by a variety of decision-making tasks with constant information. However, recently, tasks with changing information have shown to be more effective to study the dynamics of decision making. Recent research using one of such tasks, the tokens task, has shown that decisions are better described by an urgency mechanism than by an accumulation one. However, the results of that study could depend on a task where all fundamental information was noiseless and always present, favoring a mechanism of non-integration, such as the urgency one. Here, we wanted to address whether the same conclusions were also supported by an experimental paradigm in which sensory evidence was removed shortly after it was provided, making working memory necessary to properly perform the task. Here, we show that, under such condition, participants' behavior could be explained by an urgency-gating mechanism that low-pass filters the mnemonic information and combines it with an urgency signal that grows with time but not by an accumulation process that integrates the same mnemonic information. Thus, our study supports the idea that, under certain situations with dynamic sensory information, decisions are better explained by an urgency-gating mechanism than by an accumulation one.

Neural Correlates of Strategy Switching in the Macaque Orbital Prefrontal Cortex.

We can adapt flexibly to environment changes and search for the most appropriate rule to a context. The orbital prefrontal cortex (PFo) has been associated with decision making, rule generation and maintenance, and more generally has been considered important for behavioral flexibility. To better understand the neural mechanisms underlying the flexible behavior, we studied the ability to generate a switching signal in monkey PFo when a strategy is changed. In the strategy task, we used a visual cue to instruct two male rhesus monkeys either to repeat their most recent choice (i.e., stay strategy) or to change it (i.e., shift strategy). To identify the strategy switching-related signal, we compared nonswitch and switch trials, which cued the same or a different strategy from the previous trial, respectively. We found that the switching-related signal emerged during the cue presentation and it was combined with the strategy signal in a subpopulation of cells. Moreover, the error analysis showed that the activity of the switch-related cells reflected whether the monkeys erroneously switched or not the strategy, rather than what was required for that trial. The function of the switching signal could be to prompt the use of different strategies when older strategies are no longer appropriate, conferring the ability to adapt flexibly to environmental changes. In our task, the switching signal might contribute to the implementation of the strategy cued, overcoming potential interference effects from the strategy previously cued. Our results support the idea that ascribes to PFo an important role for behavioral flexibility.SIGNIFICANCE STATEMENT We can flexibly adapt our behavior to a changing environment. One of the prefrontal areas traditionally associated with the ability to adapt to new contingencies is the orbital prefrontal cortex (PFo). We analyzed the switching related activity using a strategy task in which two rhesus monkeys were instructed by a visual cue either to repeat or change their most recent choice, respectively using a stay or a shift strategy. We found that PFo neurons were modulated by the strategy switching signal, pointing to the importance of PFo in behavioral flexibility by generating control over the switching of strategies.

Autocorrelation Structure in the Macaque Dorsolateral, But not Orbital or Polar, Prefrontal Cortex Predicts Response-Coding Strength in a Visually Cued Strategy Task.

In previous work, we studied the activity of neurons in the dorsolateral (PFdl), orbital (PFo), and polar (PFp) prefrontal cortex while monkeys performed a strategy task with 2 spatial goals. A cue instructed 1 of 2 strategies in each trial: stay with the previous goal or shift to the alternative goal. Each trial started with a fixation period, followed by a cue. Subsequently, a delay period was followed by a "go" signal that instructed the monkeys to choose one goal. After each choice, feedback was provided. In this study, we focused on the temporal receptive fields of the neurons, as measured by the decay in autocorrelation (time constant) during the fixation period, and examined the relationship with response and strategy coding. The temporal receptive field in PFdl correlated with the response-related but not with the strategy-related modulation in the delay and the feedback periods: neurons with longer time constants in PFdl tended to show stronger and more prolonged response coding. No such correlation was found in PFp or PFo. These findings demonstrate that the temporal specialization of neurons for temporally extended computations is predictive of response coding, and neurons in PFdl, but not PFp or PFo, develop such predictive properties.

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.

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.

Firing Variability of Frontal Pole Neurons during a Cued Strategy Task.

In previous reports, we described neuronal activity in the polar (PFp), dorsolateral (PFdl), and orbital (PFo) PFC as monkeys performed a cued strategy task with two spatial goals. On each trial, a cue instructed one of two strategies: Stay with the previous goal or shift to the alternative. A delay period followed each cue, and feedback followed each choice, also at a delay. Our initial analysis showed that the mean firing rate of a population of PFp cells encoded the goal chosen on a trial, but only near the time of feedback, not earlier in the trial. In contrast, PFdl cells encoded goals and strategies during the cue and delay periods, and PFo cells encoded strategies in those task periods. Both areas also signaled goals near feedback time. Here we analyzed trial-to-trial variability of neuronal firing, as measured by the Fano factor (FF): the ratio of variance to the mean. Goal-selective PFp neurons had two properties: (1) a lower FF from the beginning of the trial compared with PFp cells that did not encode goals and (2) a weak but significant inverse correlation between FF throughout a trial and the degree of goal selectivity at feedback time. Cells in PFdl and PFo showed neither of these properties. Our findings indicate that goal-selective PFp neurons were engaged in the task throughout a trial, although they only encoded goals near feedback time. Their lower FF could improve the ability of other cortical areas to decode its selected-goal signal.

Independent coding of absolute duration and distance magnitudes in the prefrontal cortex.

The estimation of space and time can interfere with each other, and neuroimaging studies have shown overlapping activation in the parietal and prefrontal cortical areas. We used duration and distance discrimination tasks to determine whether space and time share resources in prefrontal cortex (PF) neurons. Monkeys were required to report which of two stimuli, a red circle or blue square, presented sequentially, were longer and farther, respectively, in the duration and distance tasks. In a previous study, we showed that relative duration and distance are coded by different populations of neurons and that the only common representation is related to goal coding. Here, we examined the coding of absolute duration and distance. Our results support a model of independent coding of absolute duration and distance metrics by demonstrating that not only relative magnitude but also absolute magnitude are independently coded in the PF. NEW & NOTEWORTHY: Human behavioral studies have shown that spatial and duration judgments can interfere with each other. We investigated the neural representation of such magnitudes in the prefrontal cortex. We found that the two magnitudes are independently coded by prefrontal neurons. We suggest that the interference among magnitude judgments might depend on the goal rather than the perceptual resource sharing.

Neural Encoding of Self and Another Agent's Goal in the Primate Prefrontal Cortex: Human-Monkey Interactions.

The primate prefrontal cortex represents both past and future goals. To investigate its role in representing the goals of other agents, we designed a nonmatch-to-goal task that involved a human-monkey (H-M) interaction. During each trial, 2 of 4 potential goal objects were presented randomly to the left or right part of a display screen, and the monkey's (or human's) task was to choose the one that did not match the object goal previously chosen. Human and monkey trials were intermixed, and each agent, when acting as observer, was required to monitor the other actor's choice to switch the object goal choice in case it became the actor on the subsequent trial. We found neurons encoding the actor, either the monkey itself or the human, neurons encoding the agent future goal position and neurons encoding the agent previous goal position. In the category of neurons encoding the human future goal, we differentiated between those encoding the future goal of both agents and those encoding only the human agent future goal. While the first one might represent a covert mental simulation in the human trials, the other one could represent a prediction signal of the other's agent choice.

Context-Dependent Duration Signals in the Primate Prefrontal Cortex.

The activity of some prefrontal (PF) cortex neurons distinguishes short from long time intervals. Here, we examined whether this property reflected a general timing mechanism or one dependent on behavioral context. In one task, monkeys discriminated the relative duration of 2 stimuli; in the other, they discriminated the relative distance of 2 stimuli from a fixed reference point. Both tasks had a pre-cue period (interval 1) and a delay period (interval 2) with no discriminant stimulus. Interval 1 elapsed before the presentation of the first discriminant stimulus, and interval 2 began after that stimulus. Both intervals had durations of either 400 or 800 ms. Most PF neurons distinguished short from long durations in one task or interval, but not in the others. When neurons did signal something about duration for both intervals, they did so in an uncorrelated or weakly correlated manner. These results demonstrate a high degree of context dependency in PF time processing. The PF, therefore, does not appear to signal durations abstractedly, as would be expected of a general temporal encoder, but instead does so in a highly context-dependent manner, both within and between tasks.

Prefrontal Goal Codes Emerge as Latent States in Probabilistic Value Learning.

The prefrontal cortex (PFC) supports goal-directed actions and exerts cognitive control over behavior, but the underlying coding and mechanism are heavily debated. We present evidence for the role of goal coding in PFC from two converging perspectives: computational modeling and neuronal-level analysis of monkey data. We show that neural representations of prospective goals emerge by combining a categorization process that extracts relevant behavioral abstractions from the input data and a reward-driven process that selects candidate categories depending on their adaptive value; both forms of learning have a plausible neural implementation in PFC. Our analyses demonstrate a fundamental principle: goal coding represents an efficient solution to cognitive control problems, analogous to efficient coding principles in other (e.g., visual) brain areas. The novel analytical-computational approach is of general interest because it applies to a variety of neurophysiological studies.

Reaching-related Neurons in Superior Parietal Area 5: Influence of the Target Visibility.

Reaching movements require the integration of both somatic and visual information. These signals can have different relevance, depending on whether reaches are performed toward visual or memorized targets. We tested the hypothesis that under such conditions, therefore depending on target visibility, posterior parietal neurons integrate differently somatic and visual signals. Monkeys were trained to execute both types of reaches from different hand resting positions and in total darkness. Neural activity was recorded in Area 5 (PE) and analyzed by focusing on the preparatory epoch, that is, before movement initiation. Many neurons were influenced by the initial hand position, and most of them were further modulated by the target visibility. For the same starting position, we found a prevalence of neurons with activity that differed depending on whether hand movement was performed toward memorized or visual targets. This result suggests that posterior parietal cortex integrates available signals in a flexible way based on contextual demands.

Autonomous encoding of irrelevant goals and outcomes by prefrontal cortex neurons.

Two rhesus monkeys performed a distance discrimination task in which they reported whether a red square or a blue circle had appeared farther from a fixed reference point. Because a new pair of distances was chosen randomly on each trial, and because the monkeys had no opportunity to correct errors, no information from the previous trial was relevant to a current one. Nevertheless, many prefrontal cortex neurons encoded the outcome of the previous trial on current trials. A smaller, intermingled population of cells encoded the spatial goal on the previous trial or the features of the chosen stimuli, such as color or shape. The coding of previous outcomes and goals began at various times during a current trial, and it was selective in that prefrontal cells did not encode other information from the previous trial. The monitoring of previous goals and outcomes often contributes to problem solving, and it can support exploratory behavior. The present results show that such monitoring occurs autonomously and selectively, even when irrelevant to the task at hand.

Automatic comparison of stimulus durations in the primate prefrontal cortex: the neural basis of across-task interference.

Rhesus monkeys performed two tasks, both requiring a choice between a red square and a blue circle. In the duration task, the two stimuli appeared sequentially on each trial, for varying durations, and, later, during the choice phase of the task, the monkeys needed to choose the one that had lasted longer. In the matching-to-sample task, one of the two stimuli appeared twice as a sample, with durations matching those in the duration task, and the monkey needed to choose that stimulus during the choice phase. Although stimulus duration was irrelevant in the matching-to-sample task, the monkeys made twice as many errors when the second stimulus was shorter. This across-task interference supports an order-dependent model of the monkeys' choice and reveals something about their strategy in the duration task. The monkeys tended to choose the second stimulus when its duration exceeded the first and to choose the alternative stimulus otherwise. For the duration task, this strategy obviated the need to store stimulus-duration conjunctions for both stimuli, but it generated errors on the matching-to-sample task. We examined duration coding in prefrontal neurons and confirmed that a population of cells encoded relative duration during the matching-to-sample task, as expected from the order-dependent errors.

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.

Disentangling the identity of the zona incerta: a review of the known connections and latest implications.

The zona incerta (ZI) is a subthalamic region composed by loosely packed neurochemically mixed neurons, juxtaposed to the main ascending and descending bundles. The extreme neurochemical diversity that characterizes this area, together with the diffuseness of its connections with the entire neuraxis and its hard-to-reach positioning in the brain caused the ZI to keep its halo of mystery for over a century. However, in the last decades, a rich albeit fragmentary body of knowledge regarding both the incertal anatomical connections and functional implications has been built mostly based on rodent studies and its lack of cohesion makes difficult to depict an integrated, exhaustive picture regarding the ZI and its roles. This review aims to provide a unified resource that summarizes the current knowledge regarding the anatomical profile of interactions of the ZI in rodents and non-human primates and the functional significance of its connections, highlighting the aspects still unbeknown to research.