Neuronal population dynamics during motor plan cancellation in nonhuman primates.

To understand the cortical neuronal dynamics behind movement generation and control, most studies have focused on tasks where actions were planned and then executed using different instances of visuomotor transformations. However, to fully understand the dynamics related to movement control, one must also study how movements are actively inhibited. Inhibition, indeed, represents the first level of control both when different alternatives are available and only one solution could be adopted and when it is necessary to maintain the current position. We recorded neuronal activity from a multielectrode array in the dorsal premotor cortex (PMd) of monkeys performing a countermanding reaching task that requires, in a subset of trials, them to cancel a planned movement before its onset. In the analysis of the neuronal state space of PMd, we found a subspace in which activities conveying temporal information were confined during active inhibition and position holding. Movement execution required activities to escape from this subspace toward an orthogonal subspace and, furthermore, surpass a threshold associated with the maturation of the motor plan. These results revealed further details in the neuronal dynamics underlying movement control, extending the hypothesis that neuronal computation confined in an "output-null" subspace does not produce movements.

Attentional spatial cueing of the stop-signal affects the ability to suppress behavioural responses.

The ability to adapt to the environment is linked to the possibility of inhibiting inappropriate behaviours, and this ability can be enhanced by attention. Despite this premise, the scientific literature that assesses how attention can influence inhibition is still limited. This study contributes to this topic by evaluating whether spatial and moving attentional cueing can influence inhibitory control. We employed a task in which subjects viewed a vertical bar on the screen that, from a central position, moved either left or right where two circles were positioned. Subjects were asked to respond by pressing a key when the motion of the bar was interrupted close to the circle (go signal). In about 40% of the trials, following the go signal and after a variable delay, a visual target appeared in either one of the circles, requiring response inhibition (stop signal). In most of the trials the stop signal appeared on the same side as the go signal (valid condition), while in the others, it appeared on the opposite side (invalid condition). We found that spatial and moving cueing facilitates inhibitory control in the valid condition. This facilitation was observed especially for stop signals that appeared within 250ms of the presentation of the go signal, thus suggesting an involvement of exogenous attentional orienting. This work demonstrates that spatial and moving cueing can influence inhibitory control, providing a contribution to the investigation of the relationship between spatial attention and inhibitory control.

Neural Activity in Quarks Language: Lattice Field Theory for a Network of Real Neurons.

Brain-computer interfaces have seen extraordinary surges in developments in recent years, and a significant discrepancy now exists between the abundance of available data and the limited headway made in achieving a unified theoretical framework. This discrepancy becomes particularly pronounced when examining the collective neural activity at the micro and meso scale, where a coherent formalization that adequately describes neural interactions is still lacking. Here, we introduce a mathematical framework to analyze systems of natural neurons and interpret the related empirical observations in terms of lattice field theory, an established paradigm from theoretical particle physics and statistical mechanics. Our methods are tailored to interpret data from chronic neural interfaces, especially spike rasters from measurements of single neuron activity, and generalize the maximum entropy model for neural networks so that the time evolution of the system is also taken into account. This is obtained by bridging particle physics and neuroscience, paving the way for particle physics-inspired models of the neocortex.

Neuronal Activity in the Premotor Cortex of Monkeys Reflects Both Cue Salience and Motivation for Action Generation and Inhibition.

Reward prospect weighs on motor decision processes, enhancing the selection of appropriate actions and the inhibition of others. While many studies have investigated the neuronal basis of reward representations and of cortical control of actions, the neuronal correlates of the influences of reward prospect on motor decisions are less clear. We recorded from the dorsal premotor cortex (PMd) of 2 male macaque monkeys performing a modified version of the Stop-signal (countermanding) task. This task challenges motor decisions by requiring responding to a frequent Go stimulus, but to suppress this response when a rare Stop signal is presented during the reaction time. We unbalanced the motivation to respond or to suppress the response by presenting a cue informing on three different rewards schedules: in one case, Go trials were rewarded more than Stop trials; in another case, Stop trials were rewarded more than Go trials; in the last case, both types of trials were rewarded equally. Monkeys adopted different strategies according to reward information provided by the cue: the higher the reward for Stop trials, the higher their ability to suppress the response and the slower their response to Go stimuli. PMd neuronal activity evolved in time and correlated with the behavior: PMd signaled first the cue salience, representing the chance to earn the highest reward at stake, then reflected the shaping of the motor choice by the motivation to move or to stop. These findings represent a neuronal correlate of the influence of reward information on motor decision.SIGNIFICANCE STATEMENT The motivation to obtain rewards drives how animals act over their environment. To explore the involvement of motor cortices in motivated behaviors, we recorded high-resolution neuronal activity in the premotor cortex of monkeys performing a task that manipulated the motivation to generate/withhold a movement through different cued reward probabilities. Our results show the presence of neuronal signals dynamically reflecting the salience of the cue, in the time immediately following its presentation, and a motivation-related activity in performing (or cancelling) a motor program, while the behavioral response approached. The encoding of multiple reward-related signals in this region leads to consider an important role of premotor areas in the reward circuitry supporting action.

Response Preparation Affects Cognitive Motor Control.

OBJECTIVE: We investigated how the ability to control whether or not to inhibit an action is affected by the response preparation. BACKGROUND: The ability to control actions is a central skill to properly behave in complex environments. Increased levels of response preparation are associated with reduced response times, but how they directly affect the ability to control actions is not well explored. We investigated how the response preparation affects the ability to control the generation of actions in the context of a stop selective task. METHOD: Participants performed a visuo-motor stop selective task. RESULTS: We found that an increased level of response preparation reduced the ability to control actions. In the condition with high preparation, we observed shorter response times and increased probability of wrong responses to a request to stop, compared to a condition with a lower level of preparation. CONCLUSION: We demonstrated that high response preparation hinders action control. APPLICATION: Understanding the cognitive factors that affect the ability to properly control actions is crucial to develop devices that can be exploited in different contexts such as the aviation, industrial, and military. We demonstrated that subjects' response preparation is a key factor influencing their ability to flexibly control their reaction to different stimuli. This study offers a suitable paradigm that can be used to investigate which system features in a controlled task promote an optimal balance between response speed and error rate.

The small scale functional topology of movement control: Hierarchical organization of local activity anticipates movement generation in the premotor cortex of primates.

How neurons coordinate their collective activity for behavioural control is an open question in neuroscience. Several studies have progressively proven, on various scales, that the patterns of neural synchronization change accordingly with behavioural events. However, the topological features of the neural dynamics that underlie task-based cognitive decisions on the small scale level are not understood. We analysed the multiunit activity (MUA) from a multielectrode (96 channels) array of the dorsal premotor cortex (PMd) in rhesus monkeys during a countermanding reaching task. Within the framework of graph theory, we found that in the local PMd network motor execution is preceded by the emergence of hubs of anti-correlation that are organized in a hierarchical manner. Conversely, this organization is absent when monkeys correctly inhibit programmed movements. Thus, we interpret the presence of hubs as reflecting the readiness of the motor plan and the irrevocable signature of the onset of the incoming movement.

Modulation of Neural Variability in Premotor, Motor, and Posterior Parietal Cortex during Change of Motor Intention.

The time course of neural variability was studied in three nodes of the parieto-frontal system: the dorsal premotor cortex (PMd, area 6), primary motor cortex (MI, area 4), and posterior parietal cortex (PPC, area 5) while monkeys made either direct reaches to visual targets or changed reach direction in response to an unexpected change of target location. These areas are crucial nodes in the distributed control of reaching and their lesion impairs trajectory formation and correction under different circumstances. During unperturbed reaches, neural variability declined before the onset of hand movement in both frontal and parietal cortex. When the original motor intention suddenly changed, neural variability displayed a complex and area-specific modulation because the perturbation of the motor state was signaled earlier in PMd than in MI and PPC. The comparison of perturbed versus unperturbed reaches revealed that, in the time between the onset of correction signal and trajectory change, identical hand movements were associated with different, therefore context-dependent, patterns of neural variability induced by the instruction to change hand movement direction. In PMd, neural variability was higher before the initiation of hand reach than before its correction, thus providing a neural underpinning to the phenomenon that it takes less time to correct than to initiate hand movement. Furthermore, neural variability was an excellent predictor of slow and fast reach corrections because it was lower during the latter than the former. We conclude that the analysis of neural variability can be an important tool for the study of complex forms of motor cognition. SIGNIFICANCE STATEMENT: No single study has been performed on neural variability during update of motor intention across monkey premotor, motor, and posterior parietal cortex. In perturbed reaches, target location changed unexpectedly during reaction time and the correction of hand trajectory required updating the original motor plan. Comparing unperturbed versus perturbed reaches revealed that neural variability displayed a complex context- and area-dependent pattern of modulation because, before trajectory correction, similar initial hand movements were associated with different patterns of variability depending on the instruction signal, and therefore on the future hand path and final destination. Furthermore, neural variability predicted both slow and fast hand movement corrections, also offering a neural underpinning to the phenomenon that it takes less time to correct than to initiate hand movement.

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.

Visual salience of the stop-signal affects movement suppression process.

We investigated how the ability to suppress an impending movement is affected by the visual salience of the stop-signal in a reaching countermanding task. We found that when the stop-signal was easy to detect, stop performance was better than when the stop-signal was difficult to detect. In an exploratory analysis, we also found that the change in salience of the stop-signal can have an effect on the speed of response in trials following the stop-signal. This effect occurred together with strategic slowing down after an error in inhibiting was committed and together with a repetition priming effect due to the stop-signal presented in the previous trial. Our results suggest the need to investigate more in depth the afferent processing stage of the inhibitory control of movement and how task demands can affect its functioning.

Atrophic degeneration of cerebellum impairs both the reactive and the proactive control of movement in the stop signal paradigm.

The cognitive control of movement suppression, including performance monitoring, is one of the core properties of the executive system. A complex cortical and subcortical network involving cerebral cortex, thalamus, subthalamus, and basal ganglia has been regarded as the neural substrate of inhibition of programmed movements. Using the countermanding task, a suitable tool to explore behavioral components of movement suppression, the contribution of the cerebellum in the proactive control and monitoring of voluntary action has been recently described in patients affected by focal lesions involving in particular the cerebellar dentate nucleus. Here, we evaluated the performance on the countermanding task in a group of patients with cerebellar degeneration, in which the cerebellar cortex was diffusely affected, and showed that they display additionally a longer latency in countermanding engaged movements. Overall, the present data confirm the role of the cerebellum in executive control of action inhibition by extending the contribution to reactive motor suppression.

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.

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.

Heterogeneous attractor cell assemblies for motor planning in premotor cortex.

Cognitive functions like motor planning rely on the concerted activity of multiple neuronal assemblies underlying still elusive computational strategies. During reaching tasks, we observed stereotyped sudden transitions (STs) between low and high multiunit activity of monkey dorsal premotor cortex (PMd) predicting forthcoming actions on a single-trial basis. Occurrence of STs was observed even when movement was delayed or successfully canceled after a stop signal, excluding a mere substrate of the motor execution. An attractor model accounts for upward STs and high-frequency modulations of field potentials, indicative of local synaptic reverberation. We found in vivo compelling evidence that motor plans in PMd emerge from the coactivation of such attractor modules, heterogeneous in the strength of local synaptic self-excitation. Modules with strong coupling early reacted with variable times to weak inputs, priming a chain reaction of both upward and downward STs in other modules. Such web of "flip-flops" rapidly converged to a stereotyped distributed representation of the motor program, as prescribed by the long-standing theory of associative networks.

Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network.

Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.

In this study, we investigated the dynamics of information transfer among functionally identified neural modules during cognitive motor control. Our focus was on mesoscopic neural activities in the dorsal premotor cortex of rhesus monkeys engaged in a Stop-signal task. Leveraging multivariate transfer entropy and graph theory, we uncovered insights on how behavioral control shapes the topology of information transmission in a local brain network. Task phases modulated the strength and hierarchy of information exchange between modules, revealing the nuanced interplay between neural populations during generated and canceled movements. Notably, during successful inhibition, the network displayed a distinctive configuration, unveiling a novel mechanism for motor inhibition in the premotor cortex: a topological reshuffle of information among neuronal ensembles.

Cognitive mechanisms of learning in sequential decision-making under uncertainty: an experimental and theoretical approach.

Learning to make adaptive decisions involves making choices, assessing their consequence, and leveraging this assessment to attain higher rewarding states. Despite vast literature on value-based decision-making, relatively little is known about the cognitive processes underlying decisions in highly uncertain contexts. Real world decisions are rarely accompanied by immediate feedback, explicit rewards, or complete knowledge of the environment. Being able to make informed decisions in such contexts requires significant knowledge about the environment, which can only be gained via exploration. Here we aim at understanding and formalizing the brain mechanisms underlying these processes. To this end, we first designed and performed an experimental task. Human participants had to learn to maximize reward while making sequences of decisions with only basic knowledge of the environment, and in the absence of explicit performance cues. Participants had to rely on their own internal assessment of performance to reveal a covert relationship between their choices and their subsequent consequences to find a strategy leading to the highest cumulative reward. Our results show that the participants' reaction times were longer whenever the decision involved a future consequence, suggesting greater introspection whenever a delayed value had to be considered. The learning time varied significantly across participants. Second, we formalized the neurocognitive processes underlying decision-making within this task, combining mean-field representations of competing neural populations with a reinforcement learning mechanism. This model provided a plausible characterization of the brain dynamics underlying these processes, and reproduced each aspect of the participants' behavior, from their reaction times and choices to their learning rates. In summary, both the experimental results and the model provide a principled explanation to how delayed value may be computed and incorporated into the neural dynamics of decision-making, and to how learning occurs in these uncertain scenarios.

Restart errors reaction time of a two-step inhibition process account for the violation of the race model's independence in multi-effector selective stop signal task.

Goal-oriented actions often require the coordinated movement of two or more effectors. Sometimes multi-effector movements need to be adjusted according to a continuously changing environment, requiring stopping an effector without interrupting the movement of the others. This form of control has been investigated by the selective Stop Signal Task (SST), requiring the inhibition of an effector of a multicomponent action. This form of selective inhibition has been hypothesized to act through a two-step process, where a temporary global inhibition deactivating all the ongoing motor responses is followed by a restarting process that reactivates only the moving effector. When this form of inhibition takes place, the reaction time (RT) of the moving effector pays the cost of the previous global inhibition. However, it is poorly investigated if and how this cost delays the RT of the effector that was required to be stopped but was erroneously moved (Stop Error trials). Here we measure the Stop Error RT in a group of participants instructed to simultaneously rotate the wrist and lift the foot when a Go Signal occurred, and interrupt both movements (non-selective Stop version) or only one of them (selective Stop version) when a Stop Signal was presented. We presented this task in two experimental conditions to evaluate how different contexts can influence a possible proactive inhibition on the RT of the moving effector in the selective Stop versions. In one context, we provided the foreknowledge of the effector to be inhibited by presenting the same selective or non-selective Stop versions in the same block of trials. In a different context, while providing no foreknowledge of the effector(s) to be stopped, the selective and non-selective Stop versions were intermingled, and the information on the effector to be stopped was delivered at the time of the Stop Signal presentation. We detected a cost in both Correct and Error selective Stop RTs that was influenced by the different task conditions. Results are discussed within the framework of the race model related to the SST, and its relationship with a restart model developed for selective versions of this paradigm.

Reward prospect affects strategic adjustments in stop signal task.

Interaction with the environment requires us to predict the potential reward that will follow our choices. Rewards could change depending on the context and our behavior adapts accordingly. Previous studies have shown that, depending on reward regimes, actions can be facilitated (i.e., increasing the reward for response) or interfered (i.e., increasing the reward for suppression). Here we studied how the change in reward perspective can influence subjects' adaptation strategy. Students were asked to perform a modified version of the Stop-Signal task. Specifically, at the beginning of each trial, a Cue Signal informed subjects of the value of the reward they would receive; in one condition, Go Trials were rewarded more than Stop Trials, in another, Stop Trials were rewarded more than Go Trials, and in the last, both trials were rewarded equally. Subjects participated in a virtual competition, and the reward consisted of points to be earned to climb the leaderboard and win (as in a video game contest). The sum of points earned was updated with each trial. After a learning phase in which the three conditions were presented separately, each subject performed 600 trials testing phase in which the three conditions were randomly mixed. Based on the previous studies, we hypothesized that subjects could employ different strategies to perform the task, including modulating inhibition efficiency, adjusting response speed, or employing a constant behavior across contexts. We found that to perform the task, subjects preferentially employed a strategy-related speed of response adjustment, while the duration of the inhibition process did not change significantly across the conditions. The investigation of strategic motor adjustments to reward's prospect is relevant not only to understanding how action control is typically regulated, but also to work on various groups of patients who exhibit cognitive control deficits, suggesting that the ability to inhibit can be modulated by employing reward prospects as motivational factors.

The transitive inference task to study the neuronal correlates of memory-driven decision making: A monkey neurophysiology perspective.

A vast amount of literature agrees that rank-ordered information as A>B>C>D>E>F is mentally represented in spatially organized schemas after learning. This organization significantly influences the process of decision-making, using the acquired premises, i.e. deciding if B is higher than D is equivalent to comparing their position in this space. The implementation of non-verbal versions of the transitive inference task has provided the basis for ascertaining that different animal species explore a mental space when deciding among hierarchically organized memories. In the present work, we reviewed several studies of transitive inference that highlighted this ability in animals and, consequently, the animal models developed to study the underlying cognitive processes and the main neural structures supporting this ability. Further, we present the literature investigating which are the underlying neuronal mechanisms. Then we discuss how non-human primates represent an excellent model for future studies, providing ideal resources for better understanding the neuronal correlates of decision-making through transitive inference tasks.

Decision time and response accuracy in a conditional motor learning task are impaired independently in unilateral temporal lobe-resected patients.

Learning and memory of declarative knowledge and relational information are dependent on the integrity of medial temporal lobe (MTL). Numerous studies suggest that left lobectomy impairs verbal memory while right lobectomy impairs non-verbal memory. In order to instrumentally quantify material-specific memory impairment after temporal lobe excision, we compared, using a computerized conditional motor associative learning task, patients with surgically treated drug-resistant temporal lobe epilepsy to age-matched controls. We enrolled seven epileptic patients with left (LTR), seven with right (RTR) temporal lobe resection and fourteen controls. During the task, abstract visual stimuli had to be associated, by trial and error, with a spatially oriented joystick motor response. Response and decision time were analyzed. Statistical analysis disclosed that the learning curve slopes of both RTR and LTR patients were significantly shallower compared to controls, LTR patients needed a number of test trials significantly increased compared to RTR patients and controls, the average probability of success in the test trials was significantly lower in LTR patients compared to RTR patients and controls, and RTR patients' decision times were significantly longer than LTR patients and controls. The results suggest that RTR patients, using the preserved verbalization strategy, achieved higher learning scores than LTR patients, which were forced to use a visuo-spatial representation of the stimuli-response association. Accordingly, RTR patients were significantly slower, compared to LTR patients and controls, indicating that processes involving recall were partially impaired, and non-canonical networks for executing a non-verbal task could be in action.

Gaze orientation interferes with mental numerical representation.

Number comparison tasks are characterized by distance and size effects. The distance effect reveals that the higher the distance is between two numbers, the easier their magnitude comparison is. Accordingly, people are thought to represent numbers on a spatial dimension, the mental number line, on which any given number corresponds to a location on the line. The size effect, instead, states that at any given distance, comparing two small numbers is easier than comparing two large numbers, thus suggesting that larger numbers are more vaguely represented than smaller ones. In the present work we first tested whether the participants were adopting a spatial strategy to solve a very simple numbers comparison task, by assessing the presence of the distance and the magnitude effect. Secondarily, we focused on the influence of gaze position on their performance. The present results provide evidence that gaze direction interferes with number comparisons, worsening the vague representation of larger numbers and further supporting the hypothesis of the overlapping between physical and mental spaces.