When reflecting on the nature of skilled action, it is easy to fall into familiar dichotomies such that one construes the flexibility and intelligence of skill at the level of intentional states while characterizing the automatic motor processes that constitute motor skill execution as learned but fixed, invariant, bottom-up, brute-causal responses. In this essay, I will argue that this picture of skilled, automatic, motor processes is overly simplistic. Specifically, I will argue that an adequate account of the (...) learned motor routines that constitute embodied skills cannot be given in a purely bottom-up, brute-causal fashion. Rather, motor control is intelligent all the way down. To establish this, I will first review two recent accounts of skill, Stanley and Krakauer and Papineau, which characterize the automatic motor control responsible for the fine-grained movements constitutive of motor skill as brute, low-level phenomena. I will then isolate five key features that should apply to skilled motor control, if these accounts are correct. Together, the accounts posit that motor control is: ballistic, invariant, independent of general action trajectories, Insensitive to semantic content, and independent of personal-level intentions. In the final section of this paper, I will appeal to optimal control theory for empirical evidence to challenge the commitment to skilled action as qualified by the above features. (shrink)

The human masticatory system is a complex functional unit characterized by a multitude of skeletal components, muscles, soft tissues, and teeth. Muscle activation dynamics cannot be directly measured on live human subjects due to ethical, safety, and accessibility limitations. Therefore, estimation of muscle activations and their resultant forces is a longstanding and active area of research. Reinforcement learning (RL) is an adaptive learning strategy which is inspired by the behavioral psychology and enables an agent to learn the dynamics of an (...) unknown system via policy-driven explorations. The RL framework is a well-formulated closed-loop system where high capacity neural networks are trained with the feedback mechanism of rewards to learn relatively complex actuation patterns. In this work, we are building on a deep RL algorithm, known as the Soft Actor-Critic, to learn the inverse dynamics of a simulated masticatory system, i.e., learn the activation patterns that drive the jaw to its desired location. The outcome of the proposed training procedure is a parametric neural model which acts as the brain of the biomechanical system. We demonstrate the model’s ability to navigate the feasible three-dimensional (3D) envelope of motion with sub-millimeter accuracies. We also introduce a performance analysis platform consisting of a set of quantitative metrics to assess the functionalities of a given simulated masticatory system. This platform assesses the range of motion, metabolic efficiency, the agility of motion, the symmetry of activations, and the accuracy of reaching the desired target positions. We demonstrate how the model learns more metabolically efficient policies by integrating a force regularization term in the RL reward. We also demonstrate the inverse correlation between the metabolic efficiency of the models and their agility and range of motion. The presented masticatory model and the proposed RL training mechanism are valuable tools for the analysis of mastication and other biomechanical systems. We see this framework’s potential in facilitating the functional analyses aspects of surgical treatment planning and predicting the rehabilitation performance in post-operative subjects. (shrink)

This article examines three aspects of the problem of understanding Benjamin Libet’s idea of conscious will causally interacting with certain neural activities involved in generating overt bodily movements. The first is to grasp the notion of cause involved, and we suggest a definition. The second is to form an idea of by what neural structure(s) and mechanism(s) a conscious will may control the motor activation. We discuss the possibility that the acts of control have to do with (...) levels of supplementary motor area activity and with the activation of populations of excitatory and inhibitory interneurons. The third aspect is to conceive of the main features of Libet’s proposed conscious mental field (CMF). We consider both an ontological and an epistemological interpretation of the CMF being nonphysical. In an attempt to refute the idea that Libet’s dualist mind–brain interactionism would violate the law of conservation of energy, we suggest that a CMF may alter the probability of the ion-channel gating by influencing structures of a size to which quantum mechanics needs to be applied. We argue that given the suggested definition of cause, and given the epistemological interpretation of the CMF being nonphysical, nothing would necessarily rule out that an element of a CMF, conscious will, may causally interact with neural activities in the brain. This defense of the idea of conscious will being causally efficacious has a bearing not only on the understanding of the mind–brain relation but also on the free will debate. (shrink)

When reflecting on the nature of skilled action, it is easy to fall into familiar dichotomies such that one construes the flexibility and intelligence of skill at the level of intentional states while characterizing the automatic motor processes that constitute motor skill execution as learned but fixed, invariant, bottom-up, brute-causal responses. In this essay, I will argue that this picture of skilled, automatic, motor processes is overly simplistic. Specifically, I will argue that an adequate account of the (...) learned motor routines that constitute embodied skills cannot be given in a purely bottom-up, brute-causal fashion. Rather, motor control is intelligent all the way down. To establish this, I will first review two recent accounts of skill, Stanley and Krakauer (Front Hum Neurosci, 2013. doi:10.3389/fnhum.2013.0050) and Papineau (R Inst Philos Suppl 73:175–196, 2013), which characterize the automatic motor control responsible for the fine-grained movements constitutive of motor skill as brute, low-level phenomena. I will then isolate five key features that should apply to skilled motor control, if these accounts are correct. Together, the accounts posit that motor control is: (1) ballistic, (2) invariant, (3) independent of general action trajectories, (4) Insensitive to semantic content, and (5) independent of personal-level intentions. In the final section of this paper, I will appeal to optimal control theory for empirical evidence to challenge the commitment to skilled action as qualified by the above features. (shrink)

This ground-breaking book brings together researchers from a wide range of disciplines to discuss the control and coordination of processes involved in perceptually guided actions. The research area of motor control has become an increasingly multidisciplinary undertaking. Understanding the acquisition and performance of voluntary movements in biological and artificial systems requires the integration of knowledge from a variety of disciplines from neurophysiology to biomechanics.

to small scales. Further, it is often useful to describe motor control and sensorimotor coordination in terms of external elds such as force elds and sensory images. We survey the basic concepts of eld computation, including both feed-forward eld operations and eld dynamics resulting from recurrent connections. Adaptive and learning mechanisms are discussed brie y. The application of eld computation to motor control is illustrated by several examples: external force elds associated with spinal neurons, population coding (...) of direction in motor cortex, continuous transformation of direction elds, and linear gain elds and coordinate transformations in posterior parietal cortex. Next we survey some eld-based representations of motion, including direct, Fourier, Gabor and wavelet or multiresolution representations. Finally we consider brie y the application of these representations to constraint satisfaction, which has many applications in motor control. (shrink)

The concept of voluntary motor control(VMC) frequently appears in the neuroscientific literature, specifically in the context of cortically-mediated, intentional motor actions. For cognitive scientists, this concept of VMC raises a number of interesting questions:(i) Are there dedicated, modular-like structures within the motor system associated with VMC? Or (ii) is it the case that VMC is distributed over multiple cortical as well as subcortical structures?(iii) Is there any one place within the so-calledhierarchy of motor control (...) where voluntary movements could be said to originate? And (iv) in the current neurological literature how is the adjective voluntary in VMC being used? These questions are here considered in the context of how higher- and lower-levels of motor control, plan, initiate, coordinate, sequence, and modulate goal-directed motor outputs in response to changing internal and external inputs. Particularly relevant are the conceptual implications of current neurological modeling of VMC concerning causal agency. (shrink)

The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies (...) in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language. Key Words: efference copies; emulation theory of representation; forward models; Kalman filters; motor control; motor imagery; perception; visual imagery. (shrink)

The Theory of Event Coding (TEC) provides a preliminary account of the interaction between perception and action, which is consistent with several recent findings in the area of motor control. Significant issues require integration and elaboration, however; particularly, distractor interference, automatic motor corrections, internal models of action, and neuroanatomical bases for the link between perception and action.

In his article Grush proposes a potentially useful framework for explaining motor control, imagery, and perception. In our commentary we will address two issues that the model does not seem to deal with appropriately: one concerns motor control, and the other, the visual and motor imagery domains. We will consider these two aspects in turn.

Inferences made from endocasts of fossil skulls cannot provide information on the function of particular neocortical areas or the subcortical pathways to prefrontal cortex that form part of the neural substrate for speech, syntax, and certain aspects of cognition. The neural bases of syntax cannot be disassociated from “communication.” Manual motor control was probably a preadaptive factor in the evolution of humansyntactic ability, but neurophysiological data on living humans show that speech motor control and syntax are (...) more closely linked. The evolution of fully modern speech occurred fairly recently; thoughHomo habilismay have had some degree of speech and syntactic ability, it was not fully modern. Stone tools are uncertain indices of language or cognition. (shrink)

Understanding of the λ model has greatly increased in recent years as evidenced by most of the commentaries. Some commentators underscored the potential of the model to integrate aspects of different sensorimotor systems in the production of movement. Other commentators focused on not-yet-fully-developed parts of the model. A few persisted in misunderstanding some of its basic concepts, and on these grounds they reject it. In responding to commentaries we continue to elaborate on some fundamental points of the model, especially (...) class='Hi'>control variables, the idea of movement production by shifting the positional frame of reference and the hypothesis of biomechanical correspondence in motor control. We also continue to develop our ideas on the intrinsic generation of the frame of reference associated with external space and utilized for the control of arm movement and locomotion. The dynamic principles underlying the model are discussed in light of the dynamical systems approach. (shrink)

Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, and action control comprising (...) levels of generative models. I argue that this view is not entailed by a general Bayesian/predictive processing outlook. Bayesian approaches are compatible with distinct formats of mental representation. Focusing on Bayesian approaches to motor control, I argue that the junctures between different types of mental representation are places where the transitivity of hierarchical prediction may be broken, and I consider the upshot of this conclusion for broader discussions of cognitive architecture. (shrink)

A hypothesis about sensorimotor integration (the λ model) is described and applied to movement control and kinesthesia. The central idea is that the nervous system organizes positional frames of reference for the sensorimotor apparatus and produces active movements by shifting the frames in terms of spatial coordinates. Kinematic and electromyographic patterns are not programmed, but emerge from the dynamic interaction among the system s components, including external forces within the designated frame of reference. Motoneuronal threshold properties and proprioceptive inputs (...) to motoneurons may be cardinal components of the physiological mechanism that produces positional frames of reference. The hypothesis that intentional movements are produced by shifting the frame of reference is extended to multi-muscle and multi-degrees-of-freedom systems with a solution of the redundancy problem that allows the control of a joint alone or in combination with other joints to produce any desired limb configuration and movement trajectory. The model also implies that for each motor behavior, the nervous system uses a strategy that minimizes the number of changeable control variables and keeps the parameters of these changes invariant. Examples are provided of simulated kinematic and electromyographic signals from single- and multi-joint arm movements produced by suggested patterns of control variables. Empirical support is provided and additional tests of the model are suggested. The model is contrasted with others based on the ideas of programming of motoneuronal activity, muscle forces, stiffness, or movement kinematics. (shrink)

Several target articles in this BBS special issue address the topic of cerebellar and olivary functions, especially as they pertain to motor earning. Another important topic is the neural interaction between the limbic system and the cerebellum during associative learning. In this commentary we present some of our data on olivo-cerebellar and limbic-cerebellar interactions during eyeblink conditioning. [HOUK et al.; SIMPSON et al.; THACH].

The model identifies a spatial coordinate frame within which the sensorimotor apparatus produces movement. Its spatial nature simplifies its coupling with spatial reference frames used concurrently by vision and proprioception. While the positional reference frame addresses the performance of spatial tasks, it seems to have little to say about movements involving energy expenditure as the principle component of the task.

Intimate relationships between emotion and action have long been acknowledged, yet contemporary theories and experimental research within affective and movement neuroscience have not been linked into a coherent framework bridging these two fields. Accumulating psychological and neuroimaging evidence has, however, brought new insights regarding how emotions affect the preparation, execution, and control of voluntary movement. Here we review main approaches and findings on such emotion–action interactions. To assimilate key emotion concepts of action tendencies and motive states with fundamental constructs (...) of the motor system, we underscore the need for integrating an information-processing approach of motor control into affective neuroscience. This should provide a rich foundation to bridge the two fields, allowing further refinement and empirical testing of emotion theories and better understanding of affective influences in movement disorders. (shrink)

Examination of infant spontaneous and goal-directed arm movements supports Feldman and Levin's hypothesis of a functional hierarchy. Early infant movements are dominated by biomechanical and dynamic factors without external frames of reference. Development involves not only learning to generate these frames of reference, but also protecting the higher-level goal of the movement from internal and external perturbations.

Current models of speech motor control rely on either trajectory-based control (DIVA, GEPPETO, ACT) or a dynamical systems approach based on feedback control (Task Dynamics, FACTS). While both approaches have provided insights into the speech motor system, it is difficult to connect these findings across models given the distinct theoretical and computational bases of the two approaches. We propose a new extension of the most widely used dynamical systems approach, Task Dynamics, that incorporates many of (...) the strengths of trajectory-based approaches, providing a way to bridge the theoretical divide between what have been two separate approaches to understanding speech motor control. The Task Dynamics (TD) model posits that speech gestures are governed by point attractor dynamics consistent with a critically damped harmonic oscillator. Kinematic trajectories associated with such gestures should therefore be consistent with a second-order dynamical system, possibly modified by blending with temporally overlapping gestures or altering oscillator parameters. This account of observed kinematics is powerful and theoretically appealing, but may be insufficient to account for deviations from predicted kinematics – i.e., changes produced in response to some external perturbations to the jaw, changes in control during acquisition and development, or effects of word/syllable frequency. Optimization, such as would be needed to minimize articulatory effort, is also incompatible with the current TD model, though the idea that the speech production systems economizes effort has a long history and, importantly, also plays a critical role in current theories of domain-general human motor control. To address these issues, we use Dynamic Movement Primitives (DMPs) to expand a dynamical systems framework for speech motor control to allow modification of kinematic trajectories by incorporating a simple, learnable forcing term into existing point attractor dynamics. We show that integration of DMPs with task- based point-attractor dynamics enhances the potential explanatory power of TD in a number of critical ways, including the ability to account for external forces in planning and optimizing both kinematic and dynamic movement costs. At the same time, this approach preserves the successes of Task Dynamics in handling multi-gesture planning and coordination. (shrink)

Control theory is a popular theoretical framework for explaining cognitive domains such as motor control and “mindreading.” Such accounts frequently characterize their “internal models” as “simulating” things outside the brain. But in what sense are these “simulations”? Do they involve the kind of “replication” simulation found in the simulation theory of mindreading? I will argue that some but not all control -theoretic appeals to “simulation” involve R-simulation. To do so, I examine in detail a recent computational (...) model of motor control and action perception based in control theory. I argue that the architecture does not use R-simulation during motor control, but does during action perception. A novel result of this analysis is that the forward model—the control - theoretic mechanism most often described as performing simulation—is not well characterized in terms of R- simulation. I conclude with some lessons for research on the mechanisms of mindreading. (shrink)