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.

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.

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.

Coding of shape features in the macaque anterior intraparietal area.

The exquisite ability of primates to grasp and manipulate objects relies on the transformation of visual information into motor commands. To this end, the visual system extracts object affordances that can be used to program and execute the appropriate grip. The macaque anterior intraparietal (AIP) area has been implicated in the extraction of affordances for the purpose of grasping. Neurons in the AIP area respond during visually guided grasping and to the visual presentation of objects. A subset of AIP neurons is also activated by two-dimensional images of objects and even by outline contours defining the object shape, but it is unknown how AIP neurons actually represent object shape. In this study, we used a stimulus reduction approach to determine the minimum effective shape feature evoking AIP responses. AIP neurons responding to outline shapes also responded selectively to very small fragment stimuli measuring only 1-2°. This fragment selectivity could not be explained by differences in eye movements or simple orientation selectivity, but proved to be highly dependent on the relative position of the stimulus in the receptive field. Our findings challenge the current understanding of the AIP area as a critical stage in the dorsal stream for the extraction of object affordances.

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.

Grasping execution and grasping observation activity of single neurons in the macaque anterior intraparietal area.

Primates use vision to guide their actions in everyday life. Visually guided object grasping is known to rely on a network of cortical areas located in the parietal and premotor cortex. We recorded in the anterior intraparietal area (AIP), an area in the dorsal visual stream that is critical for object grasping and densely connected with the premotor cortex, while monkeys were grasping objects under visual guidance and during passive fixation of videos of grasping actions from the first-person perspective. All AIP neurons in this study responded during grasping execution in the light, that is, became more active after the hand had started to move toward the object and during grasping in the dark. More than half of these AIP neurons responded during the observation of a video of the same grasping actions on a display. Furthermore, these AIP neurons responded as strongly during passive fixation of movements of a hand on a scrambled background and to a lesser extent to a shape appearing within the visual field near the object. Therefore, AIP neurons responding during grasping execution also respond during passive observation of grasping actions and most of them even during passive observation of movements of a simple shape in the visual field.

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.

The increasing authorship trend in neuroscience: A scientometric analysis across 11 countries.

Previous studies have demonstrated an increasing trend of the number of authors across various fields over the years. This trend has been attributed to the necessity for larger collaborations and, at times, to ethical issues regarding authorship attribution. Our study focuses on the evolution of authorship trends in the field of Neuroscience. We conducted our analysis based on a dataset containing 580,782 neuroscience publications produced from 2000 to 2022, focusing on the publications within the Group of ten (G10) countries. Using a matrix-based methodology, we extracted and analyzed the average number of authors per country. Our findings reveal a consistent rise in authorship across all G10 countries over the past two decades. Italy emerged with the highest average number of authors, while France stood out for experiencing the most significant increase, particularly in the last decade. The countries with the lowest number of authors per publication were the USA, UK and Canada. Differences between countries could result from variations in the size of collaboration between researchers in different countries. Additionally, these differences may depend on utilitarian considerations aimed at receiving higher scores in the individual evaluation of their own work. We propose that a normalization procedure for the number of authors should be implemented to ensure a fair evaluation of researchers.

Selectivity for three-dimensional shape and grasping-related activity in the macaque ventral premotor cortex.

Anatomical studies indicate that area F5 in the macaque ventral premotor cortex consists of three different sectors. One of these is F5a in the posterior bank of the inferior arcuate sulcus, but no functional characterization of F5a at the single-cell level exists. We investigated the neuronal selectivity for three-dimensional (3D) shape and grasping activity in F5a. In contrast to neighboring regions F5p and 45B, the great majority of F5a neurons showed selectivity for disparity-defined curved surfaces, and most neurons preserved this selectivity across positions in depth, indicating higher-order disparity selectivity. Thus, as predicted by monkey fMRI data, F5a neurons showed robust 3D-shape selectivity in the absence of a motor response. To investigate the relationship between disparity selectivity and grasping activity, we recorded from 3D-shape-selective F5a neurons during a visually guided grasping task and during grasping in the dark. F5a neurons encoding the depth profile of curved surfaces frequently responded during grasping of real-world objects in the light, but not in the dark, whereas nearby neurons were also active in the dark. The presence of 3D-shape-selective and "visual-dominant" neurons demonstrates that the F5a sector is distinct from neighboring regions of ventral premotor cortex, in line with recent anatomical connectivity studies.

Three-dimensional shape coding in grasping circuits: a comparison between the anterior intraparietal area and ventral premotor area F5a.

Depth information is necessary for adjusting the hand to the three-dimensional (3-D) shape of an object to grasp it. The transformation of visual information into appropriate distal motor commands is critically dependent on the anterior intraparietal area (AIP) and the ventral premotor cortex (area F5), particularly the F5p sector. Recent studies have demonstrated that both AIP and the F5a sector of the ventral premotor cortex contain neurons that respond selectively to disparity-defined 3-D shape. To investigate the neural coding of 3-D shape and the behavioral role of 3-D shape-selective neurons in these two areas, we recorded single-cell activity in AIP and F5a during passive fixation of curved surfaces and during grasping of real-world objects. Similar to those in AIP, F5a neurons were either first- or second-order disparity selective, frequently showed selectivity for discrete approximations of smoothly curved surfaces that contained disparity discontinuities, and exhibited mostly monotonic tuning for the degree of disparity variation. Furthermore, in both areas, 3-D shape-selective neurons were colocalized with neurons that were active during grasping of real-world objects. Thus, area AIP and F5a contain highly similar representations of 3-D shape, which is consistent with the proposed transfer of object information from AIP to the motor system through the ventral premotor cortex.

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.

Methylphenidate is more effective to improve inhibitory control and working memory compared to tDCS in children and adolescents with attention deficit/hyperactivity disorder: a proof-of-concept study.

Introduction: Attention-deficit/hyperactivity disorder (ADHD) is characterized by an inappropriate, pervasive and persistent pattern of inattention, hyperactivity, and/or impulsivity and associated with substantial functional impairment. Despite considerable advances in the understanding and management of ADHD, some patients do not respond well to methylphenidate (MPH), the first-choice pharmacological treatment. Over the past decades, among non-invasive brain stimulation techniques, transcranial direct current stimulation (tDCS) has proven to be an effective and safe technique to improve behavior and cognition in children with neurodevelopmental disorders, including ADHD, by modifying cortical excitability. However, the effect of tDCS has never been directly compared with that of the MPH. The present randomized sham-controlled trial evaluated the effect of a single session of anodal tDCS compared with the administration of a single dose of MPH in children and adolescents with ADHD. Methods: After completing baseline assessment (T0), 26 children and adolescents with ADHD were exposed to 3 conditions with a 24-h interval-sessions: (A) a single session of anodal tDCS over the left dorsolateral prefrontal cortex (DLPFC); (B) a single session of sham tDCS over the left DLPFC; (C) a single dose of MPH. Results: Our results showed that after administering a single dose of MPH, children and adolescents with ADHD improved inhibitory control and visual-spatial WM compared with baseline, anodal, and sham tDCS. However, a single session of active tDCS over the left DLPFC was not effective compared with either baseline or sham tDCS. Discussion: In conclusion, our protocol in ADHD involving a single tDCS session did not demonstrate consistent improvements in neurocognitive features compared with baseline, sham tDCS, or single MPH administration. Different protocols need to be developed to further test the effectiveness of tDCS in improving ADHD symptoms.

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.