Prior information preshapes the population representation of movement direction in motor cortex

Preparatory activity and the expansive null-space

The study of the cortical control of movement experienced a conceptual shift over recent decades, as the basic currency of understanding shifted from single-neuron tuning towards population-level factors and their dynamics. This transition was informed by a maturing understanding of recurrent networks, where mechanism is often characterized in terms of population-level factors. By estimating factors from data, experimenters could test network-inspired hypotheses. Central to such hypotheses are 'output-null' factors that do not directly drive motor outputs yet are essential to the overall computation. In this Review, we highlight how the hypothesis of output-null factors was motivated by the venerable observation that motor-cortex neurons are active during movement preparation, well before movement begins. We discuss how output-null factors then became similarly central to understanding neural activity during movement. We discuss how this conceptual framework provided key analysis tools, making it possible for experimenters to address long-standing questions regarding motor control. We highlight an intriguing trend: as experimental and theoretical discoveries accumulate, the range of computational roles hypothesized to be subserved by output-null factors continues to expand.

PMd and action preparation: bridging insights between TMS and single neuron research

Transcranial magnetic stimulation (TMS) research has furthered understanding of human dorsal premotor cortex (PMd) function due to its unrivalled ability to measure the inhibitory and facilitatory influences of PMd over the primary motor cortex (M1) in a temporally precise manner. TMS research indicates that PMd transiently modulates inhibitory output to effector representations within M1 during motor preparation, with the direction of modulation depending on which effectors are selected for response, and the timing of modulations co-varying with task selection demands. In this review, we critically assess this literature in the context of a dynamical systems approach used to model nonhuman primate (NHP) PMd/M1 single-neuron recordings during action preparation. Through this process, we identify gaps in the literature and propose future experiments.

Distinct dynamics of neuronal activity during concurrent motor planning and execution

The smooth conduct of movements requires simultaneous motor planning and execution according to internal goals. So far it remains unknown how such movement plans are modified without interfering with ongoing movements. Previous studies have isolated planning and execution-related neuronal activity by separating behavioral planning and movement periods in time by sensory cues. Here, we separate continuous self-paced motor planning from motor execution statistically, by experimentally minimizing the repetitiveness of the movements. This approach shows that, in the rat sensorimotor cortex, neuronal motor planning processes evolve with slower dynamics than movement-related responses. Fast-evolving neuronal activity precees skilled forelimb movements and is nested within slower dynamics. We capture this effect via high-pass filtering and confirm the results with optogenetic stimulations. The various dynamics combined with adaptation-based high-pass filtering provide a simple principle for separating concurrent motor planning and execution.

Computation Through Neural Population Dynamics

Significant experimental, computational, and theoretical work has identified rich structure within the coordinated activity of interconnected neural populations. An emerging challenge now is to uncover the nature of the associated computations, how they are implemented, and what role they play in driving behavior. We term this computation through neural population dynamics. If successful, this framework will reveal general motifs of neural population activity and quantitatively describe how neural population dynamics implement computations necessary for driving goal-directed behavior. Here, we start with a mathematical primer on dynamical systems theory and analytical tools necessary to apply this perspective to experimental data. Next, we highlight some recent discoveries resulting from successful application of dynamical systems. We focus on studies spanning motor control, timing, decision-making, and working memory. Finally, we briefly discuss promising recent lines of investigation and future directions for the computation through neural population dynamics framework.

Learning words in space and time: Contrasting models of the suspicious coincidence effect

In their 2007b Psychological Review paper, Xu and Tenenbaum found that early word learning follows the classic logic of the "suspicious coincidence effect:" when presented with a novel name ('fep') and three identical exemplars (three Labradors), word learners generalized novel names more narrowly than when presented with a single exemplar (one Labrador). Xu and Tenenbaum predicted the suspicious coincidence effect based on a Bayesian model of word learning and demonstrated that no other theory captured this effect. Recent empirical studies have revealed, however, that the effect is influenced by factors seemingly outside the purview of the Bayesian account. A process-based perspective correctly predicted that when exemplars are shown sequentially, the effect is eliminated or reversed (Spencer, Perone, Smith, & Samuelson, 2011). Here, we present a new, formal account of the suspicious coincidence effect using a generalization of a Dynamic Neural Field (DNF) model of word learning. The DNF model captures both the original finding and its reversal with sequential presentation. We compare the DNF model's performance with that of a more flexible version of the Bayesian model that allows both strong and weak sampling assumptions. Model comparison results show that the dynamic field account provides a better fit to the empirical data. We discuss the implications of the DNF model with respect to broader contrasts between Bayesian and process-level models.

The Psychology of Reaching: Action Selection, Movement Implementation, and Sensorimotor Learning

The study of motor planning and learning in humans has undergone a dramatic transformation in the 20 years since this journal's last review of this topic. The behavioral analysis of movement, the foundational approach for psychology, has been complemented by ideas from control theory, computer science, statistics, and, most notably, neuroscience. The result of this interdisciplinary approach has been a focus on the computational level of analysis, leading to the development of mechanistic models at the psychological level to explain how humans plan, execute, and consolidate skilled reaching movements. This review emphasizes new perspectives on action selection and motor planning, research that stands in contrast to the previously dominant representation-based perspective of motor programming, as well as an emerging literature highlighting the convergent operation of multiple processes in sensorimotor learning.

Computer mouse tracking reveals motor signatures in a cognitive task of spatial language grounding

In a novel computer mouse tracking paradigm, participants read a spatial phrase such as "The blue item to the left of the red one" and then see a scene composed of 12 visual items. The task is to move the mouse cursor to the target item (here, blue), which requires perceptually grounding the spatial phrase. This entails visually identifying the reference item (here, red) and other relevant items through attentional selection. Response trajectories are attracted toward distractors that share the target color but match the spatial relation less well. Trajectories are also attracted toward items that share the reference color. A competing pair of items that match the specified colors but are in the inverse spatial relation increases attraction over-additively compared to individual items. Trajectories are also influenced by the spatial term itself. While the distractor effect resembles deviation toward potential targets in previous studies, the reference effect suggests that the relevance of the reference item for the relational task, not its role as a potential target, was critical. This account is supported by the strengthened effect of a competing pair. We conclude, therefore, that the attraction effects in the mouse trajectories reflect the neural processes that operate on sensorimotor representations to solve the relational task. The paradigm thus provides an experimental window through motor behavior into higher cognitive function and the evolution of activation in modal substrates, a longstanding topic in the area of embodied cognition.

Conservation of preparatory neural events in monkey motor cortex regardless of how movement is initiated

A time-consuming preparatory stage is hypothesized to precede voluntary movement. A putative neural substrate of motor preparation occurs when a delay separates instruction and execution cues. When readiness is sustained during the delay, sustained neural activity is observed in motor and premotor areas. Yet whether delay-period activity reflects an essential preparatory stage is controversial. In particular, it has remained ambiguous whether delay-period-like activity appears before non-delayed movements. To overcome that ambiguity, we leveraged a recently developed analysis method that parses population responses into putatively preparatory and movement-related components. We examined cortical responses when reaches were initiated after an imposed delay, at a self-chosen time, or reactively with low latency and no delay. Putatively preparatory events were conserved across all contexts. Our findings support the hypothesis that an appropriate preparatory state is consistently achieved before movement onset. However, our results reveal that this process can consume surprisingly little time.

Population coding of conditional probability distributions in dorsal premotor cortex

Our bodies and the environment constrain our movements. For example, when our arm is fully outstretched, we cannot extend it further. More generally, the distribution of possible movements is conditioned on the state of our bodies in the environment, which is constantly changing. However, little is known about how the brain represents such distributions, and uses them in movement planning. Here, we record from dorsal premotor cortex (PMd) and primary motor cortex (M1) while monkeys reach to randomly placed targets. The hand’s position within the workspace creates probability distributions of possible upcoming targets, which affect movement trajectories and latencies. PMd, but not M1, neurons have increased activity when the monkey’s hand position makes it likely the upcoming movement will be in the neurons’ preferred directions. Across the population, PMd activity represents probability distributions of individual upcoming reaches, which depend on rapidly changing information about the body’s state in the environment.

Movements are continually constrained by the current body position and its relation to the surroundings. Here the authors report that the population activity of monkey dorsal premotor cortex neurons dynamically represents the probability distribution of possible reach directions.

Bump competition and lattice solutions in two-dimensional neural fields

Some forms of competition among activity bumps in a two-dimensional neural field are studied. First, threshold dynamics is included and rivalry evolutions are considered. The relations between parameters and dominance durations can match experimental observations about ageing. Next, the threshold dynamics is omitted from the model and we focus on the properties of the steady-state. From noisy inputs, hexagonal grids are formed by a symmetry-breaking process. Particular issues about solution existence and stability conditions are considered. We speculate that they affect the possibility of producing basis grids which may be combined to form feature maps.

Reorganization between preparatory and movement population responses in motor cortex

Neural populations can change the computation they perform on very short timescales. Although such flexibility is common, the underlying computational strategies at the population level remain unknown. To address this gap, we examined population responses in motor cortex during reach preparation and movement. We found that there exist exclusive and orthogonal population-level subspaces dedicated to preparatory and movement computations. This orthogonality yielded a reorganization in response correlations: the set of neurons with shared response properties changed completely between preparation and movement. Thus, the same neural population acts, at different times, as two separate circuits with very different properties. This finding is not predicted by existing motor cortical models, which predict overlapping preparation-related and movement-related subspaces. Despite orthogonality, responses in the preparatory subspace were lawfully related to subsequent responses in the movement subspace. These results reveal a population-level strategy for performing separate but linked computations.

Single neuron responses are highly complex and dynamic yet they are able to flexibly represent behaviour through their collective activity. Here the authors demonstrate that population activity patterns of motor cortex neurons are orthogonal during successive task epochs that are linked through a simple linear function.

Non-target stimuli in the visual field influence movement preparation in upper-limb reaching

The present work provides an empirical test of the Dynamic Field Theory of visuospatial cognition. The Dynamic Field Theory is a bi-stable neural network model applied to explain how visual information is integrated during the preparation of reaching responses (Erlhagen and Schöner). The dynamic field theory posits that motor cortices develop peaks of activation for each possible target in the visual field. Targets that are close in space produce neural peaks with overlapping distributions, whereas targets that are far apart produce distinct peaks with non-overlapping distributions. As such, the Dynamic Field Theory predicts reaction times to potential targets that are close in space will be faster than those to targets that are far apart. The present work examined how proximal and distal distractors impact reaction time in an upper-limb reaching task. The results demonstrated that distal distractors result in prolonged reaction times compared to proximal distractors. We suggest that reaction time represents the time required to inhibit neural activity representing the location of the distractor. Thus, prolonged reaction times observed for distal distractors reflect the temporal demands associated with the competition of two non-overlapping distributions of activity in the brain. These findings support the tenets of the Dynamic Field Theory and demonstrate that non-target stimuli in the visual field can influence movement preparation.

Social cognition in simple action coordination: A case for direct perception

In this paper we sketch the outlines of an account of the kind of social cognition involved in simple action coordination that is based on direct social perception (DSP) rather than recursive mindreading. While we recognize the viability of a mindreading-based account such as e.g. Michael Tomasello's, we present an alternative DSP account that (i) explains simple action coordination in a less cognitively demanding manner, (ii) is better able to explain flexibility and strategy-switching in coordination and crucially (iii) allows for formal modeling. This account of action coordination is based on the notion of an agent's field of affordances. Coordination ensues, we argue, when, given a shared intention, the actions of and/or affordances for one agent shape the field of affordances for another agent. This a form of social perception since in particular perceiving affordances for another person involves seeing that person as an agent. It is a form of social perception since it involves perceiving affordances for another person and registering how another person's actions influence one's own perceived field of affordances.

Human posterior parietal cortex encodes the movement goal in a pro-/anti-reach task

Previous research on reach planning in humans has implicated a frontoparietal network, including the precuneus (PCu), a putative human homolog of the monkey parietal reach region (PRR), and the dorsal premotor cortex (PMd). Using a pro-/anti-reach task, electrophysiological studies in monkeys have demonstrated that the movement goal rather than the location of the visual cue is encoded in PRR and PMd. However, if only the effector but not the movement goal is specified (underspecified condition), the PRR and PMd have been shown to represent all potential movement goals. In this functional magnetic resonance imaging study, we investigated whether the human PCu and PMd likewise encode the movement goal, and whether these reach-related areas also engage in situations with underspecified compared with specified movement goals. By using a pro-/anti-reach task, we spatially dissociated the location of the visual cue from the location of the movement goal. In the specified conditions, pro- and anti-reaches activated similar parietal and premotor areas. In the PCu contralateral to the moving arm, we found directionally selective activation fixed to the movement goal. In the underspecified conditions, we observed activation in reach-related areas of the posterior parietal cortex, including PCu. However, the activation was substantially weaker in parietal areas and lacking in PMd. Our results suggest that human PCu encodes the movement goal rather than the location of the visual cue if the movement goal is specified and even engages in situations when only the visual cue but not the movement goal is defined.

Beyond slots and resources: grounding cognitive concepts in neural dynamics

Research over the past decade has suggested that the ability to hold information in visual working memory (VWM) may be limited to as few as three to four items. However, the precise nature and source of these capacity limits remains hotly debated. Most commonly, capacity limits have been inferred from studies of visual change detection, in which performance declines systematically as a function of the number of items that participants must remember. According to one view, such declines indicate that a limited number of fixed-resolution representations are held in independent memory "slots." Another view suggests that such capacity limits are more apparent than real, but emerge as limited memory resources are distributed across more to-be-remembered items. Here we argue that, although both perspectives have merit and have generated and explained impressive amounts of empirical data, their central focus on the representations--rather than processes--underlying VWM may ultimately limit continuing progress in this area. As an alternative, we describe a neurally grounded, process-based approach to VWM: the dynamic field theory. Simulations demonstrate that this model can account for key aspects of behavioral performance in change detection, in addition to generating novel behavioral predictions that have been confirmed experimentally. Furthermore, we describe extensions of the model to recall tasks, the integration of visual features, cognitive development, individual differences, and functional imaging studies of VWM. We conclude by discussing the importance of grounding psychological concepts in neural dynamics, as a first step toward understanding the link between brain and behavior.

The emergent executive: a dynamic field theory of the development of executive function

Executive function (EF) is a central aspect of cognition that undergoes significant changes in early childhood. Changes in EF in early childhood are robustly predictive of academic achievement and general quality of life measures later in adulthood. We present a dynamic neural field (DNF) model that provides a process-based account of behavior and developmental change in a key task used to probe the early development of executive function—the Dimensional Change Card Sort (DCCS) task. In the DCCS, children must flexibly switch from sorting cards either by shape or color to sorting by the other dimension. Typically, 3-year-olds, but not 5-year-olds, lack the flexibility to do so and perseverate on the first set of rules when instructed to switch. Using the DNF model, we demonstrate how rule-use and behavioral flexibility come about through a form of dimensional attention. Further, developmental change is captured by increasing the robustness and precision of dimensional attention. Note that although this enables the model to effectively switch tasks, the dimensional attention system does not “know” the details of task-specific performance. Rather, correct performance emerges as a property of system–wide interactions. We show how this captures children’s behavior in quantitative detail across 14 versions of the DCCS task. Moreover, we successfully test a set of novel predictions with 3-year-old children from a version of the task not explained by other theories.

Cortical control of arm movements: a dynamical systems perspective

Our ability to move is central to everyday life. Investigating the neural control of movement in general, and the cortical control of volitional arm movements in particular, has been a major research focus in recent decades. Studies have involved primarily either attempts to account for single-neuron responses in terms of tuning for movement parameters or attempts to decode movement parameters from populations of tuned neurons. Even though this focus on encoding and decoding has led to many seminal advances, it has not produced an agreed-upon conceptual framework. Interest in understanding the underlying neural dynamics has recently increased, leading to questions such as how does the current population response determine the future population response, and to what purpose? We review how a dynamical systems perspective may help us understand why neural activity evolves the way it does, how neural activity relates to movement parameters, and how a unified conceptual framework may result.

Bayesian models: the structure of the world, uncertainty, behavior, and the brain

Experiments on humans and other animals have shown that uncertainty due to unreliable or incomplete information affects behavior. Recent studies have formalized uncertainty and asked which behaviors would minimize its effect. This formalization results in a wide range of Bayesian models that derive from assumptions about the world, and it often seems unclear how these models relate to one another. In this review, we use the concept of graphical models to analyze differences and commonalities across Bayesian approaches to the modeling of behavioral and neural data. We review behavioral and neural data associated with each type of Bayesian model and explain how these models can be related. We finish with an overview of different theories that propose possible ways in which the brain can represent uncertainty.

Cortical preparatory activity: representation of movement or first cog in a dynamical machine?

The motor cortices are active during both movement and movement preparation. A common assumption is that preparatory activity constitutes a subthreshold form of movement activity: a neuron active during rightward movements becomes modestly active during preparation of a rightward movement. We asked whether this pattern of activity is, in fact, observed. We found that it was not: at the level of a single neuron, preparatory tuning was weakly correlated with movement-period tuning. Yet, somewhat paradoxically, preparatory tuning could be captured by a preferred direction in an abstract "space" that described the population-level pattern of movement activity. In fact, this relationship accounted for preparatory responses better than did traditional tuning models. These results are expected if preparatory activity provides the initial state of a dynamical system whose evolution produces movement activity. Our results thus suggest that preparatory activity may not represent specific factors, and may instead play a more mechanistic role.

Neural mechanisms for interacting with a world full of action choices

The neural bases of behavior are often discussed in terms of perceptual, cognitive, and motor stages, defined within an information processing framework that was originally inspired by models of human abstract problem solving. Here, we review a growing body of neurophysiological data that is difficult to reconcile with this influential theoretical perspective. As an alternative foundation for interpreting neural data, we consider frameworks borrowed from ethology, which emphasize the kinds of real-time interactive behaviors that animals have engaged in for millions of years. In particular, we discuss an ethologically-inspired view of interactive behavior as simultaneous processes that specify potential motor actions and select between them. We review how recent neurophysiological data from diverse cortical and subcortical regions appear more compatible with this parallel view than with the classical view of serial information processing stages.

Tests of the dynamic field theory and the spatial precision hypothesis: capturing a qualitative developmental transition in spatial working memory

This study tested a dynamic field theory (DFT) of spatial working memory and an associated spatial precision hypothesis (SPH). Between 3 and 6 years of age, there is a qualitative shift in how children use reference axes to remember locations: 3-year-olds' spatial recall responses are biased toward reference axes after short memory delays, whereas 6-year-olds' responses are biased away from reference axes. According to the DFT and the SPH, quantitative improvements over development in the precision of excitatory and inhibitory working memory processes lead to this qualitative shift. Simulations of the DFT in Experiment 1 predict that improvements in precision should cause the spatial range of targets attracted toward a reference axis to narrow gradually over development, with repulsion emerging and gradually increasing until responses to most targets show biases away from the axis. Results from Experiment 2 with 3- to 5-year-olds support these predictions. Simulations of the DFT in Experiment 3 quantitatively fit the empirical results and offer insights into the neural processes underlying this developmental change.

Dynamic encoding of movement direction in motor cortical neurons

When we perform a skilled movement such as reaching for an object, we can make use of prior information, for example about the location of the object in space. This helps us to prepare the movement, and we gain improved accuracy and speed during movement execution. Here, we investigate how prior information affects the motor cortical representation of movements during preparation and execution. We trained two monkeys in a delayed reaching task and provided a varying degree of prior information about the final target location. We decoded movement direction from multiple single-unit activity recorded from M1 (primary motor cortex) in one monkey and from PMd (dorsal premotor cortex) in a second monkey. Our results demonstrate that motor cortical cells in both areas exhibit individual encoding characteristics that change dynamically in time and dependent on prior information. On the population level, the information about movement direction is at any point in time accurately represented in a neuronal ensemble of time-varying composition. We conclude that movement representation in the motor cortex is not a static one, but one in which neurons dynamically allocate their computational resources to meet the demands defined by the movement task and the context of the movement. Consequently, we find that the decoding accuracy decreases if the precise task time, or the previous information that was available to the monkey, were disregarded in the decoding process. An optimal strategy for the readout of movement parameters from motor cortex should therefore take into account time and contextual parameters.

Swing it to the left, swing it to the right: enacting flexible spatial language using a neurodynamic framework

Research is continually expanding the empirical and theoretical picture of embodiment and dynamics in language. To date, however, a formalized neural dynamic framework for embodied linguistic processes has yet to emerge. To advance embodied theories of language, the present work develops a formalized neural dynamic framework of spatial language that explicitly integrates linguistic processes and dynamic sensory-motor systems. We then implement and test our spatial language architecture on a robotic platform continuously linked to real-time camera input. In a suite of tasks using everyday objects we demonstrate the framework's capacity for both contextually-dependent behavioral flexibility and the seamless integration of spatial, non-spatial, and symbolic representations. To our knowledge this is the first unified, neurally-grounded architecture integrating these processes and behaviors.

A layered neural architecture for the consolidation, maintenance, and updating of representations in visual working memory

Many everyday tasks rely on our ability to hold information about a perceived stimulus in mind after that stimulus is no longer visible and to compare this information with incoming perceptual information. This ability has been shown to rely on a short-term form of visual memory that has come to be known as visual working memory. Research and theory at both the behavioral and neural levels has begun to provide important insights into the basic properties of the neuro-cognitive systems underlying specific aspects of this form of memory. However, to date, no neurally-plausible theory has been proposed that addresses both the storage of information in working memory and the comparison process in a single framework. The present paper presents a layered neural field architecture that addresses these limitations. In a series of simulations, we show how the model can be used to capture each of the components underlying performance in simple visual comparison tasks--from the encoding, consolidation, and maintenance of information in working memory, to comparison and updating in response to changed inputs. Importantly, the proposed model demonstrates how these elementary perceptual and cognitive functions emerge from the coordinated activity of an integrated, dynamic neural system.

Redundancy, self-motion, and motor control

Outside the laboratory, human movement typically involves redundant effector systems. How the nervous system selects among the task-equivalent solutions may provide insights into how movement is controlled. We propose a process model of movement generation that accounts for the kinematics of goal-directed pointing movements performed with a redundant arm. The key element is a neuronal dynamics that generates a virtual joint trajectory. This dynamics receives input from a neuronal timer that paces end-effector motion along its path. Within this dynamics, virtual joint velocity vectors that move the end effector are dynamically decoupled from velocity vectors that do not. Moreover, the sensed real joint configuration is coupled back into this neuronal dynamics, updating the virtual trajectory so that it yields to task-equivalent deviations from the dynamic movement plan. Experimental data from participants who perform in the same task setting as the model are compared in detail to the model predictions. We discover that joint velocities contain a substantial amount of self-motion that does not move the end effector. This is caused by the low impedance of muscle joint systems and by coupling among muscle joint systems due to multiarticulatory muscles. Back-coupling amplifies the induced control errors. We establish a link between the amount of self-motion and how curved the end-effector path is. We show that models in which an inverse dynamics cancels interaction torques predict too little self-motion and too straight end-effector paths.

The dynamic nature of knowledge: insights from a dynamic field model of children's novel noun generalization

This paper examines the tie between knowledge and behavior in a noun generalization context. An experiment directly comparing noun generalizations of children at the same point in development in forced-choice and yes/no tasks reveals task-specific differences in the way children's knowledge of nominal categories is brought to bear in a moment. To understand the cognitive system that produced these differences, the real-time decision processes in these tasks were instantiated in a dynamic field model. The model captures both qualitative and quantitative differences in performance across tasks and reveals constraints on the nature of children's accumulated knowledge. Additional simulations of developmental change in the yes/no task between 2 and 4 years of age illustrate how changes in children's representations translate into developmental changes in behavior. Together, the empirical data and model demonstrate the dynamic nature of knowledge and are consistent with the perspective that knowledge cannot be separated from the task-specific processes that create behavior in the moment.

Interpreting neurodynamics: concepts and facts

The dynamics of neuronal systems, briefly neurodynamics, has developed into an attractive and influential research branch within neuroscience. In this paper, we discuss a number of conceptual issues in neurodynamics that are important for an appropriate interpretation and evaluation of its results. We demonstrate their relevance for selected topics of theoretical and empirical work. In particular, we refer to the notions of determinacy and stochasticity in neurodynamics across levels of microscopic, mesoscopic and macroscopic descriptions. The issue of correlations between neural, mental and behavioral states is also addressed in some detail. We propose an informed discussion of conceptual foundations with respect to neurobiological results as a viable step to a fruitful future philosophy of neuroscience.

Influence of uncertainty and surprise on human corticospinal excitability during preparation for action

Actions are guided by prior sensory information [1–10], which is inherently uncertain. However, how the motor system is sculpted by trial-by-trial content of current sensory information remains largely unexplored. Previous work suggests that conditional probabilities, learned under a particular context, can be used preemptively to influence the output of the motor system [11–14]. To test this we used transcranial magnetic stimulation (TMS) to read out corticospinal excitability (CSE) during preparation for action in an instructed delay task [15, 16]. We systematically varied the uncertainty about an impending action by changing the validity of the instructive visual cue. We used two information-theoretic quantities to predict changes in CSE, prior to action, on a trial-by-trial basis: entropy (average uncertainty) and surprise (the stimulus-bound information conveyed by a visual cue) [17–19]. Our data show that during preparation for action, human CSE varies according to the entropy and surprise conveyed by visual events guiding action. CSE increases on trials with low entropy about the impending action and low surprise conveyed by an event. Commensurate effects were observed in reaction times. We suggest that motor output is biased according to contextual probabilities that are represented dynamically in the brain.

Moving to higher ground: The dynamic field theory and the dynamics of visual cognition

In the present report, we describe a new dynamic field theory that captures the dynamics of visuo-spatial cognition. This theory grew out of the dynamic systems approach to motor control and development, and is grounded in neural principles. The initial application of dynamic field theory to issues in visuo-spatial cognition extended concepts of the motor approach to decision making in a sensori-motor context, and, more recently, to the dynamics of spatial cognition. Here we extend these concepts still further to address topics in visual cognition, including visual working memory for non-spatial object properties, the processes that underlie change detection, and the 'binding problem' in vision. In each case, we demonstrate that the general principles of the dynamic field approach can unify findings in the literature and generate novel predictions. We contend that the application of these concepts to visual cognition avoids the pitfalls of reductionist approaches in cognitive science, and points toward a formal integration of brains, bodies, and behavior.

Generality with specificity: the dynamic field theory generalizes across tasks and time scales

A central goal in cognitive and developmental science is to develop models of behavior that can generalize across both tasks and development while maintaining a commitment to detailed behavioral prediction. This paper presents tests of one such model, the Dynamic Field Theory (DFT). The DFT was originally proposed to capture delay-dependent biases in spatial recall and developmental changes in spatial recall performance. More recently, the theory was generalized to adults' performance in a second spatial working memory task, position discrimination. Here we use the theory to predict a specific, complex developmental pattern in position discrimination. Data with 3- to 6-year-old children and adults confirm these predictions, demonstrating that the DFT achieves generality across tasks and time scales, as well as the specificity necessary to generate novel, falsifiable predictions.

Changes in corticospinal excitability and the direction of evoked movements during motor preparation: a TMS study

BACKGROUND

Preparation of the direction of a forthcoming movement has a particularly strong influence on both reaction times and neuronal activity in the primate motor cortex. Here, we aimed to find direct neurophysiologic evidence for the preparation of movement direction in humans. We used single-pulse transcranial magnetic stimulation (TMS) to evoke isolated thumb-movements, of which the direction can be modulated experimentally, for example by training or by motor tasks. Sixteen healthy subjects performed brisk concentric voluntary thumb movements during a reaction time task in which the required movement direction was precued. We assessed whether preparation for the thumb movement lead to changes in the direction of TMS-evoked movements and to changes in amplitudes of motor-evoked potentials (MEPs) from the hand muscles.

RESULTS

When the required movement direction was precued early in the preparatory interval, reaction times were 50 ms faster than when precued at the end of the preparatory interval. Over time, the direction of the TMS-evoked thumb movements became increasingly variable, but it did not turn towards the precued direction. MEPs from the thumb muscle (agonist) were differentially modulated by the direction of the precue, but only in the late phase of the preparatory interval and thereafter. MEPs from the index finger muscle did not depend on the precued direction and progressively decreased during the preparatory interval.

CONCLUSION

Our data show that the human corticospinal movement representation undergoes progressive changes during motor preparation. These changes are accompanied by inhibitory changes in corticospinal excitability, which are muscle specific and depend on the prepared movement direction. This inhibition might indicate a corticospinal braking mechanism that counteracts any preparatory motor activation.

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the dynamic field theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks-the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity-generating novel, testable predictions-and generality-spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Reference-related inhibition produces enhanced position discrimination and fast repulsion near axes of symmetry

Models proposed to account for reference frame effects in spatial cognition often account for performance in some tasks well, but fail to generalize to other tasks. Here, we demonstrate that a new process account of spatial working memory--the dynamic field theory (DFT)--can bridge the gap between perceptual and memory processes in position discrimination and spatial recall, highlighting that the processes underlying spatial recall also operate in position discrimination. In six experiments, we tested two novel predictions of the DFT: first, that discrimination is enhanced near symmetry axes, especially when the perceptual salience of the axis is increased; and second, that performance far from a reference axis depends on the direction in which the second stimulus is presented. The DFT also predicts the magnitude of this direction-dependent modulation. These effects arise from reference-related inhibition in the theory. We discuss how the processes captured by the DFT relate to existing psychophysical models and operate across a diverse array of spatial tasks.

Moving Toward a Grand Theory of Development: In Memory of Esther Thelen

This paper is in memory of Esther Thelen, who passed away while President of the Society for Research in Child Development. A survey of Esther Thelen's career reveals a trajectory from early work on simple movements like stepping, to the study of goal-directed reaching, to work on the embodiment of cognition, and, ultimately, to a grand theory of development--dynamic systems theory. Four central concepts emerged during her career: (1) a new emphasis on time; (2) the proposal that behavior is softly assembled from the interaction of multiple subsystems; (3) the embodiment of perception, action, and cognition; and (4) a new respect for individuality. Esther Thelen communicated these ideas to scientists and practitioners alike, so the ultimate benefactors of her work were children.

Neural variability in premotor cortex provides a signature of motor preparation

We present experiments and analyses designed to test the idea that firing rates in premotor cortex become optimized during motor preparation, approaching their ideal values over time. We measured the across-trial variability of neural responses in dorsal premotor cortex of three monkeys performing a delayed-reach task. Such variability was initially high, but declined after target onset, and was maintained at a rough plateau during the delay. An additional decline was observed after the go cue. Between target onset and movement onset, variability declined by an average of 34%. This decline in variability was observed even when mean firing rate changed little. We hypothesize that this effect is related to the progress of motor preparation. In this interpretation, firing rates are initially variable across trials but are brought, over time, to their "appropriate" values, becoming consistent in the process. Consistent with this hypothesis, reaction times were longer if the go cue was presented shortly after target onset, when variability was still high, and were shorter if the go cue was presented well after target onset, when variability had fallen to its plateau. A similar effect was observed for the natural variability in reaction time: longer (shorter) reaction times tended to occur on trials in which firing rates were more (less) variable. These results reveal a remarkable degree of temporal structure in the variability of cortical neurons. The relationship with reaction time argues that the changes in variability approximately track the progress of motor preparation.

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

We show that while a primate chooses between two reaching actions, its motor system first represents both options and later reflects selection between them. When two potential targets appeared, many (43%) task-related, directionally tuned cells in dorsal premotor cortex (PMd) discharged if one of the targets was near their preferred direction. At the population level, this generated two simultaneous sustained directional signals corresponding to the current reach options. After a subsequent nonspatial cue identified the correct target, the corresponding directional signal increased, and the signal for the rejected target was suppressed. The PMd population reliably predicted the monkey's response choice, including errors. This supports a planning model in which multiple reach options are initially specified and then gradually eliminated in a competition for overt execution, as more information accumulates.

Interactions between cognitive and sensorimotor functions in the motor cortex: evidence from the preparatory motor sets anticipating a perturbation

The many signs of cognitive processes in the activation pattern of the primary motor cortex or in corticospinal (CS) excitability gave rise to the idea that the motor cortex is a crucial node in the processing of cognitive information related to sensorimotor functions. Moreover, it became clear that the preparatory motor sets offer a privileged window to investigate the interaction between cognitive and sensorimotor function in the motor cortex. In the present review, we examine how the study of the preparatory motor sets anticipating a mechanical movement perturbation contributes to enlightening this question. Following the initial observation made by Hammond that some components of the stretch reflex can be modulated by a prior intention either to resist or to relax in response to a subsequent perturbation, first evidence of the phenomenon was obtained in behaving monkeys. Moreover, this study related this peripheral fact to the observed anticipatory activity of motor cortex neurons after a prior instruction telling the animal how to respond to the subsequent perturbation, which triggered the instructed movement. Indeed, this anticipatory activity was found to be different according to the instruction. In the 1980s, this work inspired a lot of studies in human beings that brought support to the idea of a cognitive tuning of the long latency stretch response (LLSR). Specifically, the MI component of the response was shown to be modulated by a prior intent to resist versus to let go when faced with the perturbation. Recently, new approaches have been developed to obtain evidence of a cognitive tuning of CS excitability, thanks to transcranial magnetic stimulation (TMS). TMS has been used both as a reliable tool for quantifying the CS excitability via the motor evoked potentials (MEPs), and to centrally perturb the organization of movement. Such central perturbations offer the unique opportunity to activate the descending motor tracts while shunting, for a short time period, the ascending tracts assisting the movement. Thus, CS excitability was measured before the movement was perturbed. These studies demonstrated the readiness of the CS tract to be involved in anticipatory compensatory responses to central movement perturbations induced by TMS in relation to the subject's cognitive attitudes. The question of the cerebral regions upstream of the motor cortex that could be responsible for this modulation in CS excitability remains largely open.

Testing the dynamic field theory: working memory for locations becomes more spatially precise over development

The dynamic field theory predicts that biases toward remembered locations depend on the separation between targets, and the spatial precision of interactions in working memory that become enhanced over development. This was tested by varying the separation between A and B locations in a sandbox. Children searched for an object 6 times at an A location, followed by 3 trials at a B location. Two- and 4-year-olds', but not 6-year-olds', responses were biased toward A when A and B were 9-in. and 6-in. apart. When A and B were separated by 2 in., however, 4- and 6-year-olds' responses were biased toward A. Thus, the separation at which responses were biased toward A decreased across age groups, supporting the predictions of the theory.

Direct Evidence for a Binding between Cognitive and Motor Functions in Humans: A TMS Study

During voluntary motor actions, the cortico-spinal (CS) excitability is known to be modulated, on the one hand by cognitive (intention-related) processes and, on the other hand, by motor (performance-related) processes. Here, we studied the way these processes interact in the tuning of CS excitability during voluntary wrist movement. We used transcranial magnetic stimulation (TMS) both as a reliable tool for quantifying the CS excitability, through the motor-evoked potentials (MEPs), and as a central perturbation evoking a movement (because the stimulation intensity was above threshold) with subjects instructed to prepare (without changing their muscle activation) either to “let go” or to “resist” to this evoked movement. We studied the simultaneous evolution of both the motor performance and the MEPs in the wrist flexor and extensor, separately for the successful trials (on average, 66% of the trials whatever the condition) and the unsuccessful trials; this allowed us to dissociate the intentionand performance-related processes. To their great surprise, subjects were found able to cognitively prepare themselves to resist a TMS-induced central perturbation; they all reported an important cognitive effort on the evoked movement. Moreover, because TMS only evoked short-latency MEPs (and no long-latency components), the amplitude of these short-latency MEPs was found to be related in a continuous way to the actual movement whatever the prior intention. These results demonstrate that prior intention allows an anticipatory modulation of the CS excitability, which is not only selective (as already known) but also efficient, giving the intended motor behavior a real chance to be realized. This constitutes a direct evidence of the role of the CS excitability in the binding between cognitive and motor processes in humans.

Preshaping and continuous evolution of motor cortical representations during movement preparation

While a goal-directed movement is prepared, motor cortical neurons selectively change their activity in relation to prior information about movement direction. Only little is known, however, about the neuronal representation of partial information about this parameter. We investigated this question by training monkeys in a multidirectional centre-out pointing task. A preparatory signal provided prior information about one, two or three possible adjacent targets, thus manipulating the level of certainty about movement direction. After a 1-s delay, the response signal specified one of the precued targets to indicate the actual movement to be performed. Based on the directional tuning curves of individual motor cortical neurons determined during the reaction time interval, we constructed distributions of the population activation (DPAs), which we were then able to estimate as well during the preparatory period. We found that these distributions were preshaped by prior information, with peaks of activation centred over the range of precued movement directions. These peaks sharpened as the response signal approached, and shifted to the specified movement direction subsequent to that signal. Wider ranges of precued movement directions were represented by broader DPAs. Trials in which monkeys produced short reaction times were characterized by narrower distributions than trials with long reaction times. Our study thus provides evidence for (i) a graded preshaping of the neuronal population representation of movement direction by partial information about this parameter, and (ii) the continuous evolution of the preshaped population representation during the preparatory period towards movement initiation.

Context-related representation of timing processes in monkey motor cortex

Precise timing is essential for motor performance, though the neuronal representation of time is unknown. To explore neuronal correlates of timing processes during movement preparation and execution, we compared the activities of neurons recorded in monkey motor cortex during the performance of two tasks requiring correct time estimation in different contextual situations. Despite the fact that both tasks had many common features (e.g. same movements, same time intervals to estimate), they involved different degrees of spatial and temporal uncertainty. Our findings indicate that time is indeed represented in neuronal activity of the motor cortex, albeit strongly dependent on context and not in an invariant manner as a distinct process per se.

Motor planning: effect of directional uncertainty with discrete spatial cues

We investigated the effect of spatial uncertainty on motor planning by using the cueing method in a reaching task (experiment 1). Discrete spatial cues indicated the different locations in which the target could be presented. The number of cues as well as their direction changed from trial to trial. We tested the adequacy of two models of motor planning to account for the data. The switching model assumes that only one motor response can be planned at a time, whereas the capacity-sharing model assumes that multiple motor responses can be planned in parallel. Both models predict the same relation between average reaction time (RT) and number of cues, but they differ in their prediction of the shape of the distribution of the reaction time. The results showed that RT increased with the number of cues independently from their spatial dispersion. This relation was well described by the function predicted by both models, whereas it was poorly described by the Hick-Hyman law. In addition, the distribution of RT conformed to the prediction of the capacity-sharing model and not to that of the switching model. We investigated the role that the requirement of a spatially directed motor response might have had on this pattern of results by testing subjects in a simple RT task (experiment 2) with the same cueing presentation as in experiment 1. The results contrasted with those in experiment 1 and showed that RT was dependent on the spatial dispersion of the cues and not on their number. The results of the two experiments suggest that the mode of processing of potential targets is dependent on the spatial constraints of the task. The processing resources can be either divided relative to the spatial distribution of possible targets or across multiple independent discrete representations of these targets.