Neural correlates of reaching decisions in dorsal premotor cortex: specification of multiple direction choices and final selection of action

Different baseline functional patterns of the frontal cortex in amyotrophic lateral sclerosis patients with Corticospinal tract hyperintensity

Nearly half of the amyotrophic lateral sclerosis (ALS) patients showed hyperintensity of the corticospinal tract (CST+), yet whether brain functional pattern differs between CST+and CST- patients remains obscure. In the current study, 19 ALS CST+, 41 ALS CST- patients and 37 healthy controls (HC) underwent resting state fMRI scans. We estimated local activity and connectivity patterns via the Amplitude of Low Frequency Fluctuations (ALFF) and the Network-Based Statistic (NBS) approaches respectively. The ALS CST+patients did not differ from the CST- patients in amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) score and disease duration. ALFF of the superior frontal gyrus (SFG) and the inferior frontal gyrus pars opercularis (OIFG) were highest in the HC and lowest in the ALS CST- patients, resulting in significant group differences (PFWE<0.05). NBS analysis revealed a frontal network consisting of connections between SFG, OIFG, orbital frontal gyrus, middle cingulate cortex and the basal ganglia, which exhibited HC>ALS CST+ > ALS CST- group differences (PFWE=0.037) as well. The ALFF of the OIFG was significantly correlated with ALSFRS-R (R=0.34, P=0.028) and mean connectivity of the frontal network was trend-wise significantly correlated with disease duration (R=-0.31, P=0.052) in the ALS CST- patients. However, these correlations were insignificant in ALS CST+patients (P values > 0.8). In conclusion, The ALS CST+patients exhibited different patterns of baseline functional activity and connectivity in the frontal cortex which may indicate a functional compensatory effect.

Embodied sequential sampling models and dynamic neural fields for decision-making: Why hesitate between two when a continuum is the answer

As two alternative options in a forced choice task are separated by design, two classes of computational models of decision-making have thrived independently in the literature for nearly five decades. While sequential sampling models (SSM) focus on response times and keypresses in binary decisions in experimental paradigms, dynamic neural fields (DNF) focus on continuous sensorimotor dimensions and tasks found in perception and robotics. Recent attempts have been made to address limitations in their application to other domains, but strong similarities and compatibility between prominent models from both classes were hardly considered. This article is an attempt at bridging the gap between these classes of models, and simultaneously between disciplines and paradigms relying on binary or continuous responses. A unifying formulation of representative SSM and DNF equations is proposed, varying the number of units which interact and compete to reach a decision. The embodiment of decisions is also considered by coupling cognitive and sensorimotor processes, enabling the model to generate decision trajectories at trial level. The resulting mechanistic model is therefore able to target different paradigms (forced choices or continuous response scales) and measures (final responses or dynamics). The validity of the model is assessed statistically by fitting empirical distributions obtained from human participants in moral decision-making mouse-tracking tasks, for which both dichotomous and nuanced responses are meaningful. Comparing equations at the theoretical level, and model parametrizations at the empirical level, the implications for psychological decision-making processes, as well as the fundamental assumptions and limitations of models and paradigms are discussed.

Somatosensory stimulation on the wrist enhances the subsequent hand-choice by biasing toward the stimulated hand

Hand choice is an unconscious decision frequently made in daily life. The electroencephalogram before target presentation correlates with hand choice for the target where hand choice probability reaches equilibrium. However, whether neurophysiological interventions before target presentation influence hand choice remains unknown. Therefore, this study determined whether instantaneous somatosensory electrical stimulation administered to the unilateral wrist at 0, 300, or 600 ms before the target presentation facilitates or inhibits stimulated hand choice for targets around the hand selection equilibrium point. A single electrical stimulation comprised five trains of 1 ms electrical pulses, with a 20 ms inter-pulse interval. The stimulus intensity was set at 80% of the motor threshold. This study included 14 right-handed healthy adults (five females and nine males; mean age, 25.1 ± 4.64 years). Unilateral wrist stimulation significantly increased the probability of choosing the stimulated hand and led to a faster reaction time than bilateral wrist stimulation and no-stimulation conditions. The results suggest that prior somatosensory stimulation significantly affects the hand-choice process, effectively promoting the selection of the stimulated hand. These findings highlight the potential application of this stimulation method in stroke rehabilitation to facilitate the use of the paretic hand.

Visuomotor prediction during action planning in the human frontoparietal cortex and cerebellum

The concept of forward models in the brain, classically applied to describing on-line motor control, can in principle be extended to action planning, i.e. assuming forward sensory predictions are issued during the mere preparation of movements. To test this idea, we combined a delayed movement task with a virtual reality based manipulation of visuomotor congruence during functional magnetic resonance imaging. Participants executed simple hand movements after a delay. During the delay, two aspects of the upcoming movement could be cued: the movement type and the visuomotor mapping (i.e. congruence of executed hand movements and visual movement feedback by a glove-controlled virtual hand). Frontoparietal areas showed increased delay period activity when preparing pre-specified movements (cued > uncued). The cerebellum showed increased activity during the preparation for incongruent > congruent visuomotor mappings. The left anterior intraparietal sulcus showed an interaction effect, responding most strongly when a pre-specified (cued) movement was prepared under expected visuomotor incongruence. These results suggest that motor planning entails a forward prediction of visual body movement feedback, which can be adjusted in anticipation of nonstandard visuomotor mappings, and which is likely computed by the cerebellum and integrated with state estimates for (planned) control in the anterior intraparietal sulcus.

The functional role of conscious sensation of movement

This paper proposes a new framework for investigating neural signals sufficient for a conscious sensation of movement and their role in motor control. We focus on signals sufficient for proprioceptive awareness, particularly from muscle spindle activation and from primary motor cortex (M1). Our review of muscle vibration studies reveals that afferent signals alone can induce conscious sensations of movement. Similarly, studies employing peripheral nerve blocks suggest that efferent signals from M1 are sufficient for sensations of movement. On this basis, we show that competing theories of motor control assign different roles to sensation of movement. According to motor command theories, sensation of movement corresponds to an estimation of the current state based on afferent signals, efferent signals, and predictions. In contrast, within active inference architectures, sensations correspond to proprioceptive predictions driven by efferent signals from M1. The focus on sensation of movement provides a way to critically compare and evaluate the two theories. Our analysis offers new insights into the functional roles of movement sensations in motor control and consciousness.

Dynamics of directional motor tuning in the primate premotor and primary motor cortices during sensorimotor learning

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). To reveal PM- and M1-specific reorganization in a primate, we conducted calcium imaging in common marmosets while they learned a two-target reaching (pull/push) task after mastering a one-target reaching (pull) task. Throughout learning of the two-target reaching task, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. During learning, the reaction time in pull trials increased and correlated strongly with the peak timing of PMdr activity. PMdr showed decreasing representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation of pull and push movements. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction depending on their performance in push trials in the early learning stage, whereas M1 neurons stably retained their preferred direction and high similarity of preferred direction between neighbors. These results suggest that in primate sensorimotor learning, dynamic directional motor tuning in PMdc converts the sensorimotor association formed in PMdr to the stable and specific motor representation of M1.

Mapping eye, arm, and reward information in frontal motor cortices using electrocorticography in non-human primates

Goal-directed reaches give rise to dynamic neural activity across the brain as we move our eyes and arms, and process outcomes. High spatiotemporal resolution mapping of multiple cortical areas will improve our understanding of how these neural computations are spatially and temporally distributed across the brain. In this study, we used micro-electrocorticography (μECoG) recordings in two male monkeys performing visually guided reaches to map information related to eye movements, arm movements, and receiving rewards over a 1.37 cm2 area of frontal motor cortices (primary motor cortex, premotor cortex, frontal eye field, and dorsolateral pre-frontal cortex). Time-frequency and decoding analyses revealed that eye and arm movement information shifts across brain regions during a reach, likely reflecting shifts from planning to execution. We then used phase-based analyses to reveal potential overlaps of eye and arm information. We found that arm movement decoding performance was impacted by task-irrelevant eye movements, consistent with the presence of intermixed eye and arm information across much of motor cortices. Phase-based analyses also identified reward-related activity primarily around the principal sulcus in the pre-frontal cortex as well as near the arcuate sulcus in the premotor cortex. Our results demonstrate μECoG's strengths for functional mapping and provide further detail on the spatial distribution of eye, arm, and reward information processing distributed across frontal cortices during reaching. These insights advance our understanding of the overlapping neural computations underlying coordinated movements and reveal opportunities to leverage these signals to enhance future brain-computer interfaces.

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.

CBGTPy: An extensible cortico-basal ganglia-thalamic framework for modeling biological decision making

Here we introduce CBGTPy, a virtual environment for designing and testing goal-directed agents with internal dynamics that are modeled on the cortico-basal-ganglia-thalamic (CBGT) pathways in the mammalian brain. CBGTPy enables researchers to investigate the internal dynamics of the CBGT system during a variety of tasks, allowing for the formation of testable predictions about animal behavior and neural activity. The framework has been designed around the principle of flexibility, such that many experimental parameters in a decision making paradigm can be easily defined and modified. Here we demonstrate the capabilities of CBGTPy across a range of single and multi-choice tasks, highlighting the ease of set up and the biologically realistic behavior that it produces. We show that CBGTPy is extensible enough to apply to a range of experimental protocols and to allow for the implementation of model extensions with minimal developmental effort.

Biomechanical costs influence decisions made during ongoing actions

Accurate interaction with the environment relies on the integration of external information about the spatial layout of potential actions and knowledge of their costs and benefits. Previous studies have shown that when given a choice between voluntary reaching movements, humans tend to prefer actions with lower biomechanical costs. However, these studies primarily focused on decisions made before the onset of movement ("decide-then-act" scenarios), and it is not known to what extent their conclusions generalize to many real-life situations, in which decisions occur during ongoing actions ("decide-while-acting"). For example, one recent study found that biomechanical costs did not influence decisions to switch from a continuous manual tracking movement to a point-to-point movement, suggesting that biomechanical costs may be disregarded in decide-while-acting scenarios. To better understand this surprising result, we designed an experiment in which participants were faced with the decision between continuing to track a target moving along a straight path or changing paths to track a new target that gradually moved along a direction that deviated from the initial one. We manipulated tracking direction, angular deviation rate, and side of deviation, allowing us to compare scenarios where biomechanical costs favored either continuing or changing the path. Crucially, here the choice was always between two continuous tracking actions. Our results show that in this situation decisions clearly took biomechanical costs into account. Thus we conclude that biomechanics are not disregarded during decide-while-acting scenarios but rather that cost comparisons can only be made between similar types of actions.NEW & NOTEWORTHY In this study, we aim to shed light on how biomechanical factors influence decisions made during ongoing actions. Previous work suggested that decisions made during actions disregard biomechanical costs, in contrast to decisions made before movement. Our results challenge that proposal and suggest instead that the effect of biomechanical factors is dependent on the types of actions being compared (e.g., continuous tracking vs. point-to-point reaching). These findings contribute to our understanding of the dynamic interplay between biomechanical considerations and action choices during ongoing interactions with the environment.

Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information

When preparing a movement, we often rely on partial or incomplete information, which can decrement task performance. In behaving monkeys we show that the degree of cued target information is reflected in both, neural variability in motor cortex and behavioral reaction times. We study the underlying mechanisms in a spiking motor-cortical attractor model. By introducing a biologically realistic network topology where excitatory neuron clusters are locally balanced with inhibitory neuron clusters we robustly achieve metastable network activity across a wide range of network parameters. In application to the monkey task, the model performs target-specific action selection and accurately reproduces the task-epoch dependent reduction of trial-to-trial variability in vivo where the degree of reduction directly reflects the amount of processed target information, while spiking irregularity remained constant throughout the task. In the context of incomplete cue information, the increased target selection time of the model can explain increased behavioral reaction times. We conclude that context-dependent neural and behavioral variability is a signum of attractor computation in the motor cortex.

Exploring the Consistent Roles of Motor Areas Across Voluntary Movement and Locomotion

Multiple cortical motor areas are critically involved in the voluntary control of discrete movement (e.g., reaching) and gait. Here, we outline experimental findings in nonhuman primates with clinical reports and research in humans that explain characteristic movement control mechanisms in the primary, supplementary, and presupplementary motor areas, as well as in the dorsal premotor area. We then focus on single-neuron activity recorded while monkeys performed motor sequences consisting of multiple discrete movements, and we consider how area-specific control mechanisms may contribute to the performance of complex movements. Following this, we explore the motor areas in cats that we have considered as analogs of those in primates based on similarities in their cortical surface topology, anatomic connections, microstimulation effects, and activity patterns. Emphasizing that discrete movement and gait modification entail similar control mechanisms, we argue that single-neuron activity in each area of the cat during gait modification is compatible with the function ascribed to the activity in the corresponding area in primates, recorded during the performance of discrete movements. The findings that demonstrate the premotor areas' contribution to locomotion, currently unique to the cat model, should offer highly valuable insights into the control mechanisms of locomotion in primates, including humans.

EEG tensor decomposition delineates neurophysiological principles underlying conflict-modulated action restraint and action cancellation

Executive functions are essential for adaptive behavior. One executive function is the so-called 'interference control' or conflict monitoring another one is inhibitory control (i.e., action restraint and action cancelation). Recent evidence suggests an interplay of these processes, which is conceptually relevant given that newer conceptual frameworks imply that nominally different action/response control processes are explainable by a small set of cognitive and neurophysiological processes. The existence of such overarching neural principles has as yet not directly been examined. In the current study, we therefore use EEG tensor decomposition methods, to look into possible common neurophysiological signatures underlying conflict-modulated action restraint and action cancelation as mechanism underlying response inhibition. We show how conflicts differentially modulate action restraint and action cancelation processes and delineate common and distinct neural processes underlying this interplay. Concerning the spatial information modulations are similar in terms of an importance of processes reflected by parieto-occipital electrodes, suggesting that attentional selection processes play a role. Especially theta and alpha activity seem to play important roles. The data also show that tensor decomposition is sensitive to the manner of task implementation, thereby suggesting that switch probability/transitional probabilities should be taken into consideration when choosing tensor decomposition as analysis method. The study provides a blueprint of how to use tensor decomposition methods to delineate common and distinct neural mechanisms underlying action control functions using EEG data.

Distinct dopaminergic spike-timing-dependent plasticity rules are suited to different functional roles

Various mathematical models have been formulated to describe the changes in synaptic strengths resulting from spike-timing-dependent plasticity (STDP). A subset of these models include a third factor, dopamine, which interacts with the timing of pre- and postsynaptic spiking to contribute to plasticity at specific synapses, notably those from cortex to striatum at the input layer of the basal ganglia. Theoretical work to analyze these plasticity models has largely focused on abstract issues, such as the conditions under which they may promote synchronization and the weight distributions induced by inputs with simple correlation structures, rather than on scenarios associated with specific tasks, and has generally not considered dopamine-dependent forms of STDP. In this paper, we analyze, mathematically and with simulations, three forms of dopamine-modulated STDP in three scenarios that are relevant to corticostriatal synapses. Two of the models considered comprise previously proposed STDP rules with modifications to incorporate dopamine, while the third is a corticostriatal dopamine-dependent STDP rule adapted from a similar one already in the literature. We test the ability of each of the three models to maintain its weights in the face of noise and to complete simple reward prediction and action selection tasks, studying the learned weight distributions and corresponding task performance in each setting. Interestingly, we find that each of the three plasticity rules is well suited to a subset of the scenarios studied but falls short in others. These results show that different tasks may require different forms of synaptic plasticity, yielding the prediction that the precise form of the STDP mechanism may vary across regions of the striatum, and other brain areas impacted by dopamine, that are involved in distinct computational functions.

Mu-ERD reflects action understanding, but the effect is small

Since the mid-2000's, many researchers have provided evidence that mu-ERD measured at the motor cortex may reflect the collective activation of upstream brain regions associated with the human mirror system during action observation paradigms; however, several recent papers have called these findings into question. Our study represents an effort to address these criticisms. In our study, participants watched videos in which the type of grip an actor used to grasp a coffee mug either conveyed the goal with 100 % certainty (unambiguous-goal trials), or offered no predictive information (ambiguous-goal trials). If mu-ERD indexes action understanding, then we predicted that mu-ERD should increase while participants watched the actor grasp the mug for unambiguous-goal trials, but not for ambiguous-goal trials. During the intervals where participants watched the actor execute the goal, mu-ERD for unambiguous-goal trials should remain steady, whereas mu-ERD for ambiguous-goal trials should now increase. Conversely, if mu-ERD does not index action understanding, and instead reflects general motor processes associated with action (such as the activation of population vectors in M1 or planning processes), then mu-ERD should show no difference across conditions. Across most comparisons, we found that mu-ERD mostly reflected general motor processes; however, there was a small effect when participants overserved unambiguous-goal trials while watching the actor execute the goal suggesting that mu-ERD does reflect mirroring, but the effect is small.

Neural Correlates of Online Action Preparation

When performing movements in rapid succession, the brain needs to coordinate ongoing execution with the preparation of an upcoming action. Here we identify the processes and brain areas involved in this ability of online preparation. Human participants (both male and female) performed pairs of single-finger presses or three-finger chords in rapid succession, while 7T fMRI was recorded. In the overlap condition, they could prepare the second movement during the first response and in the nonoverlap condition only after the first response was completed. Despite matched perceptual and movement requirements, fMRI revealed increased brain activity in the overlap condition in regions along the intraparietal sulcus and ventral visual stream. Multivariate analyses suggested that these areas are involved in stimulus identification and action selection. In contrast, the dorsal premotor cortex, known to be involved in planning upcoming movements, showed no discernible signs of heightened activity. This observation suggests that the bottleneck during simultaneous action execution and preparation arises at the level of stimulus identification and action selection, whereas movement planning in the premotor cortex can unfold concurrently with the execution of a current action without requiring additional neural activity.

Differential Modulation of Local Field Potentials in the Primary and Premotor Cortices during Ipsilateral and Contralateral Reach to Grasp in Macaque Monkeys

Hand movements are associated with modulations of neuronal activity across several interconnected cortical areas, including the primary motor cortex (M1) and the dorsal and ventral premotor cortices (PMd and PMv). Local field potentials (LFPs) provide a link between neuronal discharges and synaptic inputs. Our current understanding of how LFPs vary in M1, PMd, and PMv during contralateral and ipsilateral movements is incomplete. To help reveal unique features in the pattern of modulations, we simultaneously recorded LFPs in these areas in two macaque monkeys performing reach and grasp movements with either the right or left hand. The greatest effector-dependent differences were seen in M1, at low (≤13 Hz) and γ frequencies. In premotor areas, differences related to hand use were only present in low frequencies. PMv exhibited the greatest increase in low frequencies during instruction cues and the smallest effector-dependent modulation during movement execution. In PMd, δ oscillations were greater during contralateral reach and grasp, and β activity increased during contralateral grasp. In contrast, β oscillations decreased in M1 and PMv. These results suggest that while M1 primarily exhibits effector-specific LFP activity, premotor areas compute more effector-independent aspects of the task requirements, particularly during movement preparation for PMv and production for PMd. The generation of precise hand movements likely relies on the combination of complementary information contained in the unique pattern of neural modulations contained in each cortical area. Accordingly, integrating LFPs from premotor areas and M1 could enhance the performance and robustness of brain-machine interfaces.

Movement trajectories as a window into the dynamics of emerging neural representations

The rapid transformation of sensory inputs into meaningful neural representations is critical to adaptive human behaviour. While non-invasive neuroimaging methods are the de-facto method for investigating neural representations, they remain expensive, not widely available, time-consuming, and restrictive. Here we show that movement trajectories can be used to measure emerging neural representations with fine temporal resolution. By combining online computer mouse-tracking and publicly available neuroimaging data via representational similarity analysis (RSA), we show that movement trajectories track the unfolding of stimulus- and category-wise neural representations along key dimensions of the human visual system. We demonstrate that time-resolved representational structures derived from movement trajectories overlap with those derived from M/EEG (albeit delayed) and those derived from fMRI in functionally-relevant brain areas. Our findings highlight the richness of movement trajectories and the power of the RSA framework to reveal and compare their information content, opening new avenues to better understand human perception.

Inferring control objectives in a virtual balancing task in humans and monkeys

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal's control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject's control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.

Stop affordance task: a measure of the motor interference effect

The term affordance refers to the property or quality of an object that indicates the ways in which it could potentially be used. Affordances elicit automatic motor representations that sometimes differ from the current action representation, resulting in behavioural interference effects. This affordance-induces interference could result in automatic and involuntary behavioural inhibition, probably according to the same mechanism that controls the voluntary motor inhibition. Nevertheless, few studies have considered how voluntary response inhibition is modulated by affordance. In this study, we assess the effect of affordance on voluntary action inhibition using a stop-signal task with an affordance object as a Stop Signal. An image of a mug, with the handle orientated in the same or in the opposite direction of the hand recruited to respond at the target, was used as Stop Signal. Our results showed a reduction of the time necessary to withhold the response when the handle of the mug was pointed toward the hand pre-activated to respond. This effect indicates an increased inhibition due to the mismatch between the motor representation elicited by the affordance and the motor representation pre-activated by the target. This suggests a specific interference effect, reflected in an enhanced ability to inhibit an ongoing action.

Conflicts between short- and long-term experiences affect visual perception through modulating sensory or motor response systems: Evidence from Bayesian inference models

The independent effects of short- and long-term experiences on visual perception have been discussed for decades. However, no study has investigated whether and how these experiences simultaneously affect our visual perception. To address this question, we asked participants to estimate their self-motion directions (i.e., headings) simulated from optic flow, in which a long-term experience learned in everyday life (i.e., straight-forward motion being more common than lateral motion) plays an important role. The headings were selected from three distributions that resembled a peak, a hill, and a flat line, creating different short-term experiences. Importantly, the proportions of headings deviating from the straight-forward motion gradually increased in the peak, hill, and flat distributions, leading to a greater conflict between long- and short-term experiences. The results showed that participants biased their heading estimates towards the straight-ahead direction and previously seen headings, which increased with the growing experience conflict. This suggests that both long- and short-term experiences simultaneously affect visual perception. Finally, we developed two Bayesian models (Model 1 vs. Model 2) based on two assumptions that the experience conflict altered the likelihood distribution of sensory representation or the motor response system. The results showed that both models accurately predicted participants' estimation biases. However, Model 1 predicted a higher variance of serial dependence compared to Model 2, while Model 2 predicted a higher variance of the bias towards the straight-ahead direction compared to Model 1. This suggests that the experience conflict can influence visual perception by affecting both sensory and motor response systems. Taken together, the current study systematically revealed the effects of long- and short-term experiences on visual perception and the underlying Bayesian processing mechanisms.

Position- and scale-invariant object-centered spatial localization in monkey frontoparietal cortex dynamically adapts to cognitive demand

Egocentric encoding is a well-known property of brain areas along the dorsal pathway. Different to previous experiments, which typically only demanded egocentric spatial processing during movement preparation, we designed a task where two male rhesus monkeys memorized an on-the-object target position and then planned a reach to this position after the object re-occurred at variable location with potentially different size. We found allocentric (in addition to egocentric) encoding in the dorsal stream reach planning areas, parietal reach region and dorsal premotor cortex, which is invariant with respect to the position, and, remarkably, also the size of the object. The dynamic adjustment from predominantly allocentric encoding during visual memory to predominantly egocentric during reach planning in the same brain areas and often the same neurons, suggests that the prevailing frame of reference is less a question of brain area or processing stream, but more of the cognitive demands.

Optimal reaching subject to computational and physical constraints reveals structure of the sensorimotor control system

Optimal feedback control provides an abstract framework describing the architecture of the sensorimotor system without prescribing implementation details such as what coordinate system to use, how feedback is incorporated, or how to accommodate changing task complexity. We investigate how such details are determined by computational and physical constraints by creating a model of the upper limb sensorimotor system in which all connection weights between neurons, feedback, and muscles are unknown. By optimizing these parameters with respect to an objective function, we find that the model exhibits a preference for an intrinsic (joint angle) coordinate representation of inputs and feedback and learns to calculate a weighted feedforward and feedback error. We further show that complex reaches around obstacles can be achieved by augmenting our model with a path-planner based on via points. The path-planner revealed "avoidance" neurons that encode directions to reach around obstacles and "placement" neurons that make fine-tuned adjustments to via point placement. Our results demonstrate the surprising capability of computationally constrained systems and highlight interesting characteristics of the sensorimotor system.

Distinct neural mechanisms for action access and execution in the human brain: insights from an fMRI study

Goal-directed actions are fundamental to human behavior, whereby inner goals are achieved through mapping action representations to motor outputs. The left premotor cortex (BA6) and the posterior portion of Broca's area (BA44) are two modulatory poles of the action system. However, how these regions support the representation-output mapping within the system is not yet understood. To address this, we conducted a finger-tapping functional magnetic resonance imaging experiment using action categories ranging from specific to general. Our study found distinct neural behaviors in BA44 and BA6 during action category processing and motor execution. During access of action categories, activity in a posterior portion of BA44 (pBA44) decreased linearly as action categories became less specific. Conversely, during motor execution, activity in BA6 increased linearly with less specific categories. These findings highlight the differential roles of pBA44 and BA6 in action processing. We suggest that pBA44 facilitates access to action categories by utilizing motor information from the behavioral context while the premotor cortex integrates motor information to execute the selected action. This finding enhances our understanding of the interplay between prefrontal cortical regions and premotor cortex in mapping action representation to motor execution and, more in general, of the cortical mechanisms underlying human behavior.

We know what attention is!

Attention is one of the most thoroughly investigated psychological phenomena, yet skepticism about attention is widespread: we do not know what it is, it is too many things, there is no such thing. The deficiencies highlighted are not about experimental work but the adequacy of the scientific theory of attention. Combining common scientific claims about attention into a single theory leads to internal inconsistency. This paper demonstrates that a specific functional conception of attention is incorporated into the tasks used in standard experimental paradigms. In accepting these paradigms as valid probes of attention, we commit to this common conception. The conception unifies work at multiple levels of analysis into a coherent scientific explanation of attention. Thus, we all know what attention is.

TAT-HUM: Trajectory analysis toolkit for human movements in Python

Human movement trajectories can reveal useful insights regarding the underlying mechanisms of human behaviors. Extracting information from movement trajectories, however, can be challenging because of their complex and dynamic nature. The current paper presents a Python toolkit developed to help users analyze and extract meaningful information from the trajectories of discrete rapid aiming movements executed by humans. This toolkit uses various open-source Python libraries, such as NumPy and SciPy, and offers a collection of common functionalities to analyze movement trajectory data. To ensure flexibility and ease of use, the toolkit offers two approaches: an automated approach that processes raw data and generates relevant measures automatically, and a manual approach that allows users to selectively use different functions based on their specific needs. A behavioral experiment based on the spatial cueing paradigm was conducted to illustrate how one can use this toolkit in practice. Readers are encouraged to access the publicly available data and relevant analysis scripts as an opportunity to learn about kinematic analysis for human movements.

Motor cortex retains and reorients neural dynamics during motor imagery

The most prominent characteristic of motor cortex is its activation during movement execution, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioural and imaging studies, it is unknown how the specific activity patterns and temporal dynamics in motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people who retain some residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population activity into three orthogonal subspaces, where one was similarly active during both action and imagery, and the others were active only during a single task type-action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamic features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by reorienting the components related to motor output and/or feedback into a unique, output-null imagery subspace.

Separating cognitive and motor processes in the behaving mouse

The cognitive processes supporting complex animal behavior are closely associated with ubiquitous movements responsible for our posture, facial expressions, ability to actively sample our sensory environments, and other critical processes. These movements are strongly related to neural activity across much of the brain and are often highly correlated with ongoing cognitive processes, making it challenging to dissociate the neural dynamics that support cognitive processes from those supporting related movements. In such cases, a critical issue is whether cognitive processes are separable from related movements, or if they are driven by common neural mechanisms. Here, we demonstrate how the separability of cognitive and motor processes can be assessed, and, when separable, how the neural dynamics associated with each component can be isolated. We establish a novel two-context behavioral task in mice that involves multiple cognitive processes and show that commonly observed dynamics taken to support cognitive processes are strongly contaminated by movements. When cognitive and motor components are isolated using a novel approach for subspace decomposition, we find that they exhibit distinct dynamical trajectories. Further, properly accounting for movement revealed that largely separate populations of cells encode cognitive and motor variables, in contrast to the 'mixed selectivity' often reported. Accurately isolating the dynamics associated with particular cognitive and motor processes will be essential for developing conceptual and computational models of neural circuit function and evaluating the function of the cell types of which neural circuits are composed.

Cortical β Power Reflects a Neural Implementation of Decision Boundary Collapse in Speeded Decisions

A prominent account of decision-making assumes that information is accumulated until a fixed response threshold is crossed. However, many decisions require weighting of information appropriately against time. Collapsing response thresholds are a mathematically optimal solution to this decision problem. However, our understanding of the neurocomputational mechanisms underlying dynamic response thresholds remains significantly incomplete. To investigate this issue, we used a multistage drift-diffusion model (DDM) and also analyzed EEG β power lateralization (BPL). The latter served as a neural proxy for decision signals. We analyzed a large dataset (n = 863; 434 females and 429 males) from a speeded flanker task and data from an independent confirmation sample (n = 119; 70 females and 49 males). We showed that a DDM with collapsing decision thresholds, a process wherein the decision boundary reduces over time, captured participants' time-dependent decision policy more accurately than a model with fixed thresholds. Previous research suggests that BPL over motor cortices reflects features of a decision signal and that its peak, coinciding with the motor response, may serve as a neural proxy for the decision threshold. We show that BPL around the response decreased with increasing RTs. Together, our findings offer compelling evidence for the existence of collapsing decision thresholds in decision-making processes.

The role of dorsal premotor cortex in joint action inhibition

Behavioral interpersonal coordination requires smooth negotiation of actions in time and space (joint action-JA). Inhibitory control may play a role in fine-tuning appropriate coordinative responses. To date, little research has been conducted on motor inhibition during JA and on the modulatory influence that premotor areas might exert on inhibitory control. Here, we used an interactive task in which subjects were required to reach and open a bottle using one hand. The bottle was held and stabilized by a co-actor (JA) or by a mechanical holder (vice clamp, no-JA). We recorded two TMS-based indices of inhibition (short-interval intracortical inhibition-sICI; cortical silent period-cSP) during the reaching phase of the task. These reflect fast intracortical (GABAa-mediated) and slow corticospinal (GABAb-mediated) inhibition. Offline continuous theta burst stimulation (cTBS) was used to interfere with dorsal premotor cortex (PMd), ventral premotor cortex (PMv), and control site (vertex) before the execution of the task. Our results confirm a dissociation between fast and slow inhibition during JA coordination and provide evidence that premotor areas drive only slow inhibitory mechanisms, which in turn may reflect behavioral co-adaptation between trials. Exploratory analyses further suggest that PMd, more than PMv, is the key source of modulatory drive sculpting movements, according to the socio-interactive context.

A theory of the skill-performance relationship

The skill-performance relationship is a cornerstone of a meritocratic society. People are selected for schools, colleges and jobs based on the premise that more skillful individuals perform better. Scientific understanding of the skill-performance relationship demands that the effect of skill on performance is objectively assessed without subjective, social, and political considerations. One of the best areas for this analysis is sports. In many sports settings, the skill-performance relationship can objectively be examined at the technical, behavioral, psychological, and neurological levels. This examination reveals that skill and performance are inextricably intertwined. While skill affects performance, performance in turn defines and affects skill. To disentangle the previously confusing and interchangeable use of these key constructs, the paper presents a theoretical model specifying that ability and effort have their own direct effects on performance, as well as indirect effects on performance through skill possession and skill execution in cognitive and physical domains of human performance. Thus, ability and skill are not the same. Although skill is a key determinant of performance, recent theory and research suggests that successful performers are successful not just because of their skills per se, but because they take advantage of their skills by creating more occurrences of momentum, making them last longer, and using them to bounce back faster from streaks of unsuccessful performance. Thus, momentum is an important mediator of the effects of skill on performance.

The DDHD2-STXBP1 interaction mediates long-term memory via generation of saturated free fatty acids

The phospholipid and free fatty acid (FFA) composition of neuronal membranes plays a crucial role in learning and memory, but the mechanisms through which neuronal activity affects the brain's lipid landscape remain largely unexplored. The levels of saturated FFAs, particularly of myristic acid (C14:0), strongly increase during neuronal stimulation and memory acquisition, suggesting the involvement of phospholipase A1 (PLA1) activity in synaptic plasticity. Here, we show that genetic ablation of the PLA1 isoform DDHD2 in mice dramatically reduces saturated FFA responses to memory acquisition across the brain. Furthermore, DDHD2 loss also decreases memory performance in reward-based learning and spatial memory models prior to the development of neuromuscular deficits that mirror human spastic paraplegia. Via pulldown-mass spectrometry analyses, we find that DDHD2 binds to the key synaptic protein STXBP1. Using STXBP1/2 knockout neurosecretory cells and a haploinsufficient STXBP1+/- mouse model of human early infantile encephalopathy associated with intellectual disability and motor dysfunction, we show that STXBP1 controls targeting of DDHD2 to the plasma membrane and generation of saturated FFAs in the brain. These findings suggest key roles for DDHD2 and STXBP1 in lipid metabolism and in the processes of synaptic plasticity, learning, and memory.

Interhemispheric inhibition between dorsal premotor and primary motor cortices is released during preparation of unimanual but not bimanual movements

Previous research applying transcranial magnetic stimulation during unimanual reaction time tasks indicates a transient change in the inhibitory influence of the dorsal premotor cortex over the contralateral primary motor cortex shortly after the presentation of an imperative stimulus. The degree of interhemispheric inhibition from the dorsal premotor cortex to the contralateral primary motor cortex shifts depending on whether the targeted effector representation in the primary motor cortex is selected for movement. Further, the timing of changes in inhibition covaries with the selection demands of the reaction time task. Less is known about modulation of dorsal premotor to primary motor cortex interhemispheric inhibition during the preparation of bimanual movements. In this study, we used a dual coil transcranial magnetic stimulation to measure dorsal premotor to primary motor cortex interhemispheric inhibition between both hemispheres during unimanual and bimanual simple reaction time trials. Interhemispheric inhibition was measured early and late in the 'pre-movement period' (defined as the period immediately after the onset of the imperative stimulus and before the beginning of voluntary muscle activity). We discovered that interhemispheric inhibition was more facilitatory early in the pre-movement period compared with late in the pre-movement period during unimanual reaction time trials. In contrast, interhemispheric inhibition was unchanged throughout the pre-movement period during symmetrical bimanual reaction time trials. These results suggest that there is greater interaction between the dorsal premotor cortex and contralateral primary motor cortex during the preparation of unimanual actions compared to bimanual actions.

Rapid Online Corrections for Proprioceptive and Visual Perturbations Recruit Similar Circuits in Primary Motor Cortex

An important aspect of motor function is our ability to rapidly generate goal-directed corrections for disturbances to the limb or behavioral goal. The primary motor cortex (M1) is a key region involved in processing feedback for rapid motor corrections, yet we know little about how M1 circuits are recruited by different sources of sensory feedback to make rapid corrections. We trained two male monkeys (Macaca mulatta) to make goal-directed reaches and on random trials introduced different sensory errors by either jumping the visual location of the goal (goal jump), jumping the visual location of the hand (cursor jump), or applying a mechanical load to displace the hand (proprioceptive feedback). Sensory perturbations evoked a broad response in M1 with ∼73% of neurons (n = 257) responding to at least one of the sensory perturbations. Feedback responses were also similar as response ranges between the goal and cursor jumps were highly correlated (range of r = [0.91, 0.97]) as were the response ranges between the mechanical loads and the visual perturbations (range of r = [0.68, 0.86]). Lastly, we identified the neural subspace each perturbation response resided in and found a strong overlap between the two visual perturbations (range of overlap index, 0.73-0.89) and between the mechanical loads and visual perturbations (range of overlap index, 0.36-0.47) indicating each perturbation evoked similar structure of activity at the population level. Collectively, our results indicate rapid responses to errors from different sensory sources target similar overlapping circuits in M1.

Turning the Light Switch on Binding: Prefrontal Activity for Binding and Retrieval in Action Control

According to action control theories, responding to a stimulus leads to the binding of response and stimulus features into a common representation, that is, an event file. Repeating any component of an event file retrieves all previously bound information, leading to performance costs for partial repetitions measured in so-called binding effects. Although otherwise robust and stable, binding effects are typically completely absent in "localization tasks," in which participants localize targets with spatially compatible responses. Yet, it is possible to observe binding effects in such when location features have to be translated into response features. We hypothesized that this modulation of binding effects is reflected in task involvement of the dorsolateral pFC (DLPFC). Participants localized targets with either direct (i.e., spatially compatible key) or translated (i.e., diagonally opposite to the spatially compatible key) responses. We measured DLPFC activity with functional near-infrared spectroscopy. On the behavioral level, we observed binding effects in the translated response condition, but not in the direct response condition. Importantly, prefrontal activity was also higher in the translated mapping condition. In addition, we found some evidence for the strength of the difference in binding effects in behavioral data being correlated with the corresponding effects in prefrontal activity. This suggests that activity in the DLPFC reflects the amount of executive control needed for translating location features into responses. More generally, binding effects seem to emerge only when the task at hand involves DLPFC recruitment.

Prospection of Potential Actions during Visual Working Memory Starts Early, Is Flexible, and Predicts Behavior

For visual working memory to serve upcoming behavior, it is crucial that we prepare for the potential use of working-memory contents ahead of time. Recent studies have demonstrated how the prospection and planning for an upcoming manual action starts early after visual encoding, and occurs alongside visual retention. Here, we address whether such "output planning" in visual working memory flexibly adapts to different visual-motor mappings, and occurs even when an upcoming action will only potentially become relevant for behavior. Human participants (female and male) performed a visual-motor working memory task in which they remembered one or two colored oriented bars for later (potential) use. We linked, and counterbalanced, the tilt of the visual items to specific manual responses. This allowed us to track planning of upcoming behavior through contralateral attenuation of β band activity, a canonical motor-cortical EEG signature of manual-action planning. The results revealed how action encoding and subsequent planning alongside visual working memory (1) reflect anticipated task demands rather than specific visual-motor mappings, (2) occur even for actions that will only potentially become relevant for behavior, and (3) are associated with faster performance for the encoded item, at the expense of performance to other working-memory content. This reveals how the potential prospective use of visual working memory content is flexibly planned early on, with consequences for the speed of memory-guided behavior.SIGNIFICANCE STATEMENT It is increasingly studied how visual working memory helps us to prepare for the future, in addition to how it helps us to hold onto the past. Recent studies have demonstrated that the planning of prospective actions occurs alongside encoding and retention in working memory. We show that such early "output planning" flexibly adapts to varying visual-motor mappings, occurs both for certain and potential actions, and predicts ensuing working-memory guided behavior. These results highlight the flexible and future-oriented nature of visual working memory, and provide insight into the neural basis of the anticipatory dynamics that translate visual representations into adaptive upcoming behavior.

Cortico-spinal modularity in the parieto-frontal system: A new perspective on action control

Classical neurophysiology suggests that the motor cortex (MI) has a unique role in action control. In contrast, this review presents evidence for multiple parieto-frontal spinal command modules that can bypass MI. Five observations support this modular perspective: (i) the statistics of cortical connectivity demonstrate functionally-related clusters of cortical areas, defining functional modules in the premotor, cingulate, and parietal cortices; (ii) different corticospinal pathways originate from the above areas, each with a distinct range of conduction velocities; (iii) the activation time of each module varies depending on task, and different modules can be activated simultaneously; (iv) a modular architecture with direct motor output is faster and less metabolically expensive than an architecture that relies on MI, given the slow connections between MI and other cortical areas; (v) lesions of the areas composing parieto-frontal modules have different effects from lesions of MI. Here we provide examples of six cortico-spinal modules and functions they subserve: module 1) arm reaching, tool use and object construction; module 2) spatial navigation and locomotion; module 3) grasping and observation of hand and mouth actions; module 4) action initiation, motor sequences, time encoding; module 5) conditional motor association and learning, action plan switching and action inhibition; module 6) planning defensive actions. These modules can serve as a library of tools to be recombined when faced with novel tasks, and MI might serve as a recombinatory hub. In conclusion, the availability of locally-stored information and multiple outflow paths supports the physiological plausibility of the proposed modular perspective.

Effects of transcranial direct current stimulation over human motor cortex on cognitive-motor and sensory-motor functions

The primary motor cortex (M1) is broadly acknowledged for its crucial role in executing voluntary movements. Yet, its contributions to cognitive and sensory functions remain largely unexplored. Transcranial direct current stimulation (tDCS) is a noninvasive neurostimulation method that can modify brain activity, thereby enabling the establishment of a causal link between M1 activity and behavior. This study aimed to investigate the online effects of tDCS over M1 on cognitive-motor and sensory-motor functions. Sixty-four healthy participants underwent either anodal or sham tDCS while concurrently performing a set of standardized robotic tasks. These tasks provided sensitive and objective assessments of brain functions, including action selection, inhibitory control, cognitive control of visuomotor skills, proprioceptive sense, and bimanual coordination. Our results revealed that anodal tDCS applied to M1 enhances decision-making capacity in selecting appropriate motor actions and avoiding distractors compared to sham stimulation, suggesting improved action selection and inhibitory control capabilities. Furthermore, anodal tDCS reduces the movement time required to accomplish bimanual movements, suggesting enhanced bimanual performance. However, we found no impact of anodal tDCS on cognitive control of visuomotor skills and proprioceptive sense. This study suggests that augmenting M1 activity via anodal tDCS influences cognitive-motor and sensory-motor functions in a task-dependent manner.

Superior colliculus bidirectionally modulates choice activity in frontal cortex

Action selection occurs through competition between potential choice options. Neural correlates of choice competition are observed across frontal cortex and downstream superior colliculus (SC) during decision-making, yet how these regions interact to mediate choice competition remains unresolved. Here we report that SC can bidirectionally modulate choice competition and drive choice activity in frontal cortex. In the mouse, topographically matched regions of frontal cortex and SC formed a descending motor pathway for directional licking and a re-entrant loop via the thalamus. During decision-making, distinct neuronal populations in both frontal cortex and SC encoded opposing lick directions and exhibited competitive interactions. SC GABAergic neurons encoded ipsilateral choice and locally inhibited glutamatergic neurons that encoded contralateral choice. Activating or suppressing these cell types could bidirectionally drive choice activity in frontal cortex. These results thus identify SC as a major locus to modulate choice competition within the broader action selection network.

Computational mechanism underlying switching of motor actions

Surviving in a constantly changing environment requires not only the ability to select actions, but also the flexibility to stop and switch actions when necessary. Extensive research has been devoted to understanding how the brain switches actions, yet the computations underlying switching and how it relates to selecting and stopping processes remain elusive. A central question is whether switching is an extension of the stopping process or involves different mechanisms. To address this question, we modeled action regulation tasks with a neurocomputational theory and evaluated its predictions on individuals performing reaches in a dynamic environment. Our findings suggest that, unlike stopping, switching does not necessitate a proactive pause mechanism to delay movement onset. However, switching engages a pause mechanism after movement onset, if the new target location is unknown prior to switch signal. These findings offer a new understanding of the action-switching computations, opening new avenues for future neurophysiological investigations.

Investigating Cerebellar Modulation of Premovement Beta-Band Activity during Motor Adaptation

Enhancing cerebellar activity influences motor cortical activity and contributes to motor adaptation, though it is unclear which neurophysiological mechanisms contributing to adaptation are influenced by the cerebellum. Pre-movement beta event-related desynchronization (β-ERD), which reflects a release of inhibitory control in the premotor cortex during movement planning, is one mechanism that may be modulated by the cerebellum through cerebellar-premotor connections. We hypothesized that enhancing cerebellar activity with intermittent theta burst stimulation (iTBS) would improve adaptation rates and increase β-ERD during motor adaptation. Thirty-four participants were randomly assigned to an active (A-iTBS) or sham cerebellar iTBS (S-iTBS) group. Participants performed a visuomotor task, using a joystick to move a cursor to targets, prior to receiving A-iTBS or S-iTBS, following which they completed training with a 45° rotation to the cursor movement. Behavioural adaptation was assessed using the angular error of the cursor path relative to the ideal trajectory. The results showed a greater adaptation rate following A-iTBS and an increase in β-ERD, specific to the high β range (20-30 Hz) during motor planning, compared to S-iTBS, indicative of cerebellar modulation of the motor cortical inhibitory control network. The enhanced release of inhibitory activity persisted throughout training, which suggests that the cerebellar influence over the premotor cortex extends beyond adaptation to other stages of motor learning. The results from this study further understanding of cerebellum-motor connections as they relate to acquiring motor skills and may inform future skill training and rehabilitation protocols.

Express Visuomotor Responses Reflect Knowledge of Both Target Locations and Contextual Rules during Reaches of Different Amplitudes

When humans reach to visual targets, extremely rapid (∼90 ms) target-directed responses can be observed in task-relevant proximal muscles. Such express visuomotor responses are inflexibly locked in time and space to the target and have been proposed to reflect rapid visuomotor transformations conveyed subcortically via the tecto-reticulo-spinal pathway. Previously, we showed that express visuomotor responses are sensitive to explicit cue-driven information about the target, suggesting that the express pathway can be modulated by cortical signals affording contextual prestimulus expectations. Here, we show that the express visuomotor system incorporates information about the physical hand-to-target distance and contextual rules during visuospatial tasks requiring different movement amplitudes. In one experiment, we recorded the activity from two shoulder muscles as 14 participants (6 females) reached toward targets that appeared at different distances from the reaching hand. Increasing the reaching distance facilitated the generation of frequent and large express visuomotor responses. This suggests that both the direction and amplitude of veridical hand-to-target reaches are encoded along the putative subcortical express pathway. In a second experiment, we modulated the movement amplitude by asking 12 participants (4 females) to deliberately undershoot, overshoot, or stop (control) at the target. The overshoot and undershoot tasks impaired the generation of large and frequent express visuomotor responses, consistent with the inability of the express pathway to generate responses directed toward nonveridical targets as in the anti-reach task. Our findings appear to reflect strategic, cortically driven modulation of the express visuomotor circuit to facilitate rapid and effective response initiation during target-directed actions.SIGNIFICANCE STATEMENT Express (∼90 ms) arm muscle responses that are consistently tuned toward the location of visual stimuli suggest a subcortical contribution to target-directed visuomotor behavior in humans, potentially via the tecto-reticulo-spinal pathway. Here, we show that express muscle responses are modulated appropriately to reach targets at different distances, but generally suppressed when the task required nonveridical responses to overshoot/undershoot the real target. This suggests that the tecto-reticulo-spinal pathway can be exploited strategically by the cerebral cortex to facilitate rapid initiation of effective responses during a visuospatial task.

Abstract perceptual choice signals during action-linked decisions in the human brain

Humans can make abstract choices independent of motor actions. However, in laboratory tasks, choices are typically reported with an associated action. Consequentially, knowledge about the neural representation of abstract choices is sparse, and choices are often thought to evolve as motor intentions. Here, we show that in the human brain, perceptual choices are represented in an abstract, motor-independent manner, even when they are directly linked to an action. We measured MEG signals while participants made choices with known or unknown motor response mapping. Using multivariate decoding, we quantified stimulus, perceptual choice, and motor response information with distinct cortical distributions. Choice representations were invariant to whether the response mapping was known during stimulus presentation, and they occupied a distinct representational space from motor signals. As expected from an internal decision variable, they were informed by the stimuli, and their strength predicted decision confidence and accuracy. Our results demonstrate abstract neural choice signals that generalize to action-linked decisions, suggesting a general role of an abstract choice stage in human decision-making.

Mechanisms and neuroanatomy of response selection in tool and non-tool action tasks: Evidence from left-hemisphere stroke

The ability to select between potential actions is central to the complex process of tool use. After left hemisphere stroke, individuals with limb apraxia make more hand action errors when gesturing the use of tools with conflicting hand actions for grasping-to-move and use (e.g., screwdriver) relative to tools that are grasped-to-move and used with the same hand action (e.g., hammer). Prior research indicates that this grasp-use interference effect is driven by abnormalities in the competitive action selection process. The goal of this project was to determine whether common mechanisms and neural substrates support the competitive selection of task-appropriate responses in both tool and non-tool domains. If so, the grasp-use interference effect in a tool use gesturing task should be correlated with response interference effects in the classic Eriksen flanker and Simon tasks, and at least partly overlapping neural regions should subserve the 3 tasks. Sixty-four left hemisphere stroke survivors (33 with apraxia) participated in the tool- and non-tool interference tasks and underwent T1 anatomical MRI. There were robust grasp-use interference effects (grasp-use conflict test) and response interference effects (Eriksen flanker and Simon tasks), but these effects were not correlated. Lesion-symptom mapping analyses showed that lesions to the left inferior parietal lobule, ventral premotor cortex, and insula were associated with grasp-use interference. Lesions to the left inferior parietal lobule, postcentral gyrus, insula, caudate, and putamen were associated with response interference in the Eriksen flanker task. Lesions to the left caudate and putamen were also associated with response interference in the Simon task. Our results suggest that the selection of hand posture for tool use is mediated by distinct cognitive mechanisms and partly distinct neuroanatomic substrates from those mapping a stimulus to an appropriate motor response in non-tool domains.

Cortical contribution to visuomotor coordination in locomotion and reaching

One of the hallmarks of mammals is their ability to make precise visually guided limb movements to attain objects. This is best exemplified by the reach and grasp movements of primates, although it is not unique to this mammalian order. Precise, coordinated, visually guided movements are equally as important during locomotion in many mammalian species, especially in predators. In this context, vision is used to guide paw trajectory and placement. In this review we examine the contribution of the fronto-parietal network in the control of such movements. We suggest that this network is responsible for visuomotor coordination across behaviours and species. We further argue for analogies between cytoarchitectonically similar cortical areas in primates and cats.

A motor plan is accessible for voluntary initiation and involuntary triggering at similar short latencies

Movement goals are an essential component of motor planning, altering voluntary and involuntary motor actions. While there have been many studies of motor planning, it is unclear if motor goals influence voluntary and involuntary movements at similar latencies. The objectives of this study were to determine how long it takes to prepare a motor action and to compare this time for voluntary and involuntary movements. We hypothesized a prepared motor action would influence voluntarily and involuntarily initiated movements at the same latency. We trained subjects to reach with a forced reaction time paradigm and used a startling acoustic stimulus (SAS) to trigger involuntary initiation of the same reaches. The time available to prepare was controlled by varying when one of four reach targets was presented. Reach direction was used to evaluate accuracy. We quantified the time between target presentation and the cue or trigger for movement initiation. We found that reaches were accurately initiated when the target was presented 48 ms before the SAS and 162 ms before the cue to voluntarily initiate movement. While the SAS precisely controlled the latency of movement onset, voluntary reach onset was more variable. We, therefore, quantified the time between target presentation and movement onset and found no significant difference in the time required to plan reaches initiated voluntarily or involuntarily (∆ = 8 ms, p = 0.2). These results demonstrate that the time required to plan accurate reaches is similar regardless of if they are initiated voluntarily or triggered involuntarily. This finding may inform the understanding of neural pathways governing storage and access of motor plans.

Evidence Accumulation Rate Moderates the Relationship between Enriched Environment Exposure and Age-Related Response Speed Declines

Older adults exposed to enriched environments (EEs) maintain relatively higher levels of cognitive function, even in the face of compromised markers of brain health. Response speed (RS) is often used as a simple proxy to measure the preservation of global cognitive function in older adults. However, it is unknown which specific selection, decision, and/or motor processes provide the most specific indices of neurocognitive health. Here, using a simple decision task with electroencephalography (EEG), we found that the efficiency with which an individual accumulates sensory evidence was a critical determinant of the extent to which RS was preserved in older adults (63% female, 37% male). Moreover, the mitigating influence of EE on age-related RS declines was most pronounced when evidence accumulation rates were shallowest. These results suggest that the phenomenon of cognitive reserve, whereby high EE individuals can better tolerate suboptimal brain health to facilitate the preservation of cognitive function, is not just applicable to neuroanatomical indicators of brain aging but can be observed in markers of neurophysiology. Our results suggest that EEG metrics of evidence accumulation may index neurocognitive vulnerability of the aging brain.Significance Statement Response speed in older adults is closely linked with trajectories of cognitive aging. Here, by recording brain activity while individuals perform a simple computer task, we identify a neural metric that is a critical determinant of response speed. Older adults exposed to greater cognitive and social stimulation throughout a lifetime could maintain faster responding, even when this neural metric was impaired. This work suggests EEG is a useful technique for interrogating how a lifetime of stimulation benefits brain health in aging.

Behavioral measurements of motor readiness in mice

Motor planning facilitates rapid and precise execution of volitional movements. Although motor planning has been classically studied in humans and monkeys, the mouse has become an increasingly popular model system to study neural mechanisms of motor planning. It remains yet untested whether mice and primates share common behavioral features of motor planning. We combined videography and a delayed response task paradigm in an autonomous behavioral system to measure motor planning in non-body-restrained mice. Motor planning resulted in both reaction time (RT) savings and increased movement accuracy, replicating classic effects in primates. We found that motor planning was reflected in task-relevant body features. Both the specific actions prepared and the degree of motor readiness could be read out online during motor planning. The online readout further revealed behavioral evidence of simultaneous preparation for multiple actions under uncertain conditions. These results validate the mouse as a model to study motor planning, demonstrate body feature movements as a powerful real-time readout of motor readiness, and offer behavioral evidence that motor planning can be a parallel process that permits rapid selection of multiple prepared actions.

Continuous evaluation of cost-to-go for flexible reaching control and online decisions

Humans consider the parameters linked to movement goal during reaching to adjust their control strategy online. Indeed, rapid changes in target structure or disturbances interfering with their initial plan elicit rapid changes in behavior. Here, we hypothesize that these changes could result from the continuous use of a decision variable combining motor and cognitive components. We combine an optimal feedback controller with a real-time evaluation of the expected cost-to-go, which considers target- and movement-related costs, in a common theoretical framework. This model reproduces human behaviors in presence of changes in the target structure occurring during movement and of online decisions to flexibly change target following external perturbations. It also predicts that the time taken to decide to select a novel goal after a perturbation depends on the amplitude of the disturbance and on the rewards of the different options, which is a direct result of the continuous monitoring of the cost-to-go. We show that this result was present in our previously collected dataset. Together our developments point towards a continuous evaluation of the cost-to-go during reaching to update control online and make efficient decisions about movement goal.