scholarly journals Understanding and Synergy: A Single Concept at Different Levels of Analysis?

2021 ◽  
Vol 15 ◽  
Author(s):  
Mark L. Latash
Keyword(s):  
Neural Control ◽  
Laws Of Nature ◽  
Hierarchical Control ◽  
Motor Units ◽  
Optimality Criteria ◽  
Uncontrolled Manifold ◽  
Biological Phenomena ◽  
Atypical Development ◽  
High Level ◽  
Large Groups

Biological systems differ from the inanimate world in their behaviors ranging from simple movements to coordinated purposeful actions by large groups of muscles, to perception of the world based on signals of different modalities, to cognitive acts, and to the role of self-imposed constraints such as laws of ethics. Respectively, depending on the behavior of interest, studies of biological objects based on laws of nature (physics) have to deal with different salient sets of variables and parameters. Understanding is a high-level concept, and its analysis has been linked to other high-level concepts such as “mental model” and “meaning”. Attempts to analyze understanding based on laws of nature are an example of the top-down approach. Studies of the neural control of movements represent an opposite, bottom-up approach, which starts at the interface with classical physics of the inanimate world and operates with traditional concepts such as forces, coordinates, etc. There are common features shared by the two approaches. In particular, both assume organizations of large groups of elements into task-specific groups, which can be described with only a handful of salient variables. Both assume optimality criteria that allow the emergence of families of solutions to typical tasks. Both assume predictive processes reflected in anticipatory adjustments to actions (motor and non-motor). Both recognize the importance of generating dynamically stable solutions. The recent progress in studies of the neural control of movements has led to a theory of hierarchical control with spatial referent coordinates for the effectors. This theory, in combination with the uncontrolled manifold hypothesis, allows quantifying the stability of actions with respect to salient variables. This approach has been used in the analysis of motor learning, changes in movements with typical and atypical development and with aging, and impaired actions by patients with various neurological disorders. It has been developed to address issues of kinesthetic perception. There seems to be hope that the two counter-directional approaches will meet and result in a single theoretical scheme encompassing biological phenomena from figuring out the best next move in a chess position to activating motor units appropriate for implementing that move on the chessboard.

scholarly journals The Hand: Shall We Ever Understand How It Works?

Motor Control ◽  
2015 ◽  
Vol 19 (2) ◽  
pp. 108-126 ◽  
Author(s):  
Mark L. Latash
Keyword(s):  
Motor Control ◽  
Equilibrium Point ◽  
Neurological Disorder ◽  
Neural Control ◽  
Hierarchical Control ◽  
Uncontrolled Manifold ◽  
Human Hand ◽  
Uncontrolled Manifold Hypothesis ◽  
Target Article ◽  
Point Control

The target article presents a review of the neural control of the human hand. The review emphasizes the physical approach to motor control. It focuses on such concepts as equilibrium-point control, control with referent body configurations, uncontrolled manifold hypothesis, principle of abundance, hierarchical control, multidigit synergies, and anticipatory synergy adjustments. Changes in aspects of the hand neural control with age and neurological disorder are discussed. The target article is followed by six commentaries written by Alexander Aruin, Kelly Cole, Monica Perez, Robert Sainburg, Marco Sanello, and Wei Zhang.

scholarly journals Production and Perception of Intentional and Unintentional Actions

2021 ◽  
Vol 76 (1) ◽  
pp. 51-66
Author(s):  
Mark L. Latash
Keyword(s):  
Neural Control ◽  
Dimensional Space ◽  
Laws Of Nature ◽  
Control Level ◽  
Force Production ◽  
Uncontrolled Manifold ◽  
Whole Body ◽  
External Force Field ◽  
Co Activation ◽  
Spatial Coordinates

Abstract Physical approach to biological movement is based on the idea of control with referent spatial coordinates for effectors, from the whole body to single muscles. Within this framework, neural control signals induce changes in parameters of corresponding biology-specific laws of nature, and motor performance emerges as a result of interaction with the external force field. This approach is naturally compatible with the principle of abundance and the uncontrolled manifold hypothesis, which offer the framework for analysis of movement stability. The presence of two basic commands, reciprocal and co-activation, makes even single-effector tasks abundant and allows stabilizing their performance at the control level. Kinesthetic perception can be viewed as the process of estimating afferent signals within a reference system provided by the efferent process. Percepts are reflections of stable iso-perceptual manifolds in the combined afferent-efferent multi-dimensional space. This approach offers new, logical and based on laws of nature, interpretations for such phenomena as muscle co-activation, unintentional drifts in performance, and vibration-induced kinesthetic illusions. It also allows predicting new phenomena such as counter-intuitive effects of muscle co-activation of force production and perception, vibration-induced force illusions, performance drifts at two different speeds, and high variability in matching the contribution of individual elements in multi-element tasks. This approach can be developed for various subfields of movement studies including studies of athletics, movement disorders, and movement rehabilitation.

scholarly journals Movements that are both variable and optimal

2012 ◽  
Vol 34 (1) ◽  
pp. 5-13 ◽  
Author(s):  
Mark L. Latash
Keyword(s):  
Cost Function ◽  
Neural Control ◽  
Healthy Aging ◽  
Motor Coordination ◽  
Uncontrolled Manifold ◽  
Cost Functions ◽  
Secondary Tasks ◽  
Performance Variables ◽  
Neurophysiological Mechanisms ◽  
Atypical Development

AbstractThis brief review addresses two major aspects of the neural control of multi-element systems. First, theprinciple of abundance suggests that the central nervous system unites elements into synergies (co-variation ofelemental variables across trials quantified within the framework of the uncontrolled manifold hypothesis) that stabilizeimportant performance variables. Second, a novel method, analytical inverse optimization, has been introduced tocompute cost functions that define averaged across trials involvement of individual elements over a range of values oftask-specific performance variables. The two aspects reflect two features of motor coordination: (1) using variablesolutions that allow performing secondary tasks and stabilizing performance variables; and (2) selecting combinationsof elemental variables that follow an optimization principle. We suggest that the conflict between the two approaches (asingle solution vs. families of solutions) is apparent, not real. Natural motor variability may be due to using the samecost function across slightly different initial states; on the other hand, there may be variability in the cost function itselfleading to variable solutions that are all optimal with respect to slightly different cost functions. The analysis of motorsynergies has revealed specific changes associated with atypical development, healthy aging, neurological disorders, andpractice. These have allowed formulating hypotheses on the neurophysiological mechanisms involved in the synergiccontrol of actions.

scholarly journals Biomechanics as a window into the neural control of movement

2016 ◽  
Vol 52 (1) ◽  
pp. 7-20 ◽  
Author(s):  
Mark L. Latash
Keyword(s):  
Motor Control ◽  
Neural Control ◽  
Laws Of Nature ◽  
Motor Program ◽  
Uncontrolled Manifold ◽  
Living Systems ◽  
Motor Synergies ◽  
The Central Nervous System ◽  
Definition Of ◽  
Neural Control Of Movement

Abstract Biomechanics and motor control are discussed as parts of a more general science, physics of living systems. Major problems of biomechanics deal with exact definition of variables and their experimental measurement. In motor control, major problems are associated with formulating currently unknown laws of nature specific for movements by biological objects. Mechanics-based hypotheses in motor control, such as those originating from notions of a generalized motor program and internal models, are non-physical. The famous problem of motor redundancy is wrongly formulated; it has to be replaced by the principle of abundance, which does not pose computational problems for the central nervous system. Biomechanical methods play a central role in motor control studies. This is illustrated with studies with the reconstruction of hypothetical control variables and those exploring motor synergies within the framework of the uncontrolled manifold hypothesis. Biomechanics and motor control have to merge into physics of living systems, and the earlier this process starts the better.

Real-Time Planning and Nonlinear Control for Quadrupedal Locomotion With Articulated Tails

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Randall T. Fawcett ◽  
Abhishek Pandala ◽  
Jeeseop Kim ◽  
Kaveh Akbari Hamed
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Center Of Mass ◽  
Hierarchical Control ◽  
Nonlinear Feedback ◽  
Nonlinear Controller ◽  
External Disturbances ◽  
Quadrupedal Locomotion ◽  
Control Scheme ◽  
High Level

Abstract The primary goal of this paper is to develop a formal foundation to design nonlinear feedback control algorithms that intrinsically couple legged robots with bio-inspired tails for robust locomotion in the presence of external disturbances. We present a hierarchical control scheme in which a high-level and real-time path planner, based on an event-based model predictive control (MPC), computes the optimal motion of the center of mass (COM) and tail trajectories. The MPC framework is developed for an innovative reduced-order linear inverted pendulum (LIP) model that is augmented with the tail dynamics. At the lower level of the control scheme, a nonlinear controller is implemented through the use of quadratic programming (QP) and virtual constraints to force the full-order dynamical model to track the prescribed optimal trajectories of the COM and tail while maintaining feasible ground reaction forces at the leg ends. The potential of the analytical results is numerically verified on a full-order simulation model of a quadrupedal robot augmented with a tail with a total of 20 degrees-of-freedom. The numerical studies demonstrate that the proposed control scheme coupled with the tail dynamics can significantly reduce the effect of external disturbances during quadrupedal locomotion.

Resituating cognitive mechanisms within heterarchical networks controlling physiology and behavior

2019 ◽  
Vol 29 (5) ◽  
pp. 620-639 ◽  
Author(s):  
William Bechtel
Keyword(s):  
Cognitive Control ◽  
Cognitive Science ◽  
Neural Control ◽  
Science Research ◽  
Control Mechanisms ◽  
Cognitive Mechanisms ◽  
Physiological Processes ◽  
High Level ◽  
And Behavior ◽  
Production Mechanisms

Cognitive science has traditionally focused on mechanisms involved in high-level reasoning and problem-solving processes. Such mechanisms are often treated as autonomous from but controlling underlying physiological processes. I offer a different perspective on cognition which starts with the basic production mechanisms through which organisms construct and repair themselves and navigate their environments and then I develop a framework for conceptualizing how cognitive control mechanisms form a heterarchical network that regulates production mechanisms. Many of these control mechanisms perform cognitive tasks such as evaluating circumstances and making decisions. Cognitive control mechanisms are present in individual cells, but in metazoans, intracellular control is supplemented by a nervous system in which a multitude of neural control mechanisms are organized heterarchically. On this perspective, high-level cognitive mechanisms are not autonomous, but are elements in larger heterarchical networks. This has implications for future directions in cognitive science research.

Further evidence of incomplete neural control of muscle properties in cat tibialis anterior motor units

1995 ◽  
Vol 268 (2) ◽  
pp. C527-C534 ◽  
Author(s):  
G. A. Unguez ◽  
R. R. Roy ◽  
D. J. Pierotti ◽  
S. Bodine-Fowler ◽  
V. R. Edgerton
Keyword(s):  
Motor Unit ◽  
Tibialis Anterior ◽  
Neural Control ◽  
Periodic Acid ◽  
Muscle Fibers ◽  
Motor Units ◽  
Fiber Types ◽  
Muscle Properties ◽  
Periodic Acid Schiff ◽  
The Mean

To examine the influence of a motoneuron in maintaining the phenotype of the muscle fibers it innervates, myosin heavy chain (MHC) expression, succinate dehydrogenase (SDH) activity, and cross-sectional area (CSA) of a sample of fibers belonging to a motor unit were studied in the cat tibialis anterior 6 mo after the nerve branches innervating the anterior compartment were cut and sutured near the point of entry into the muscle. The mean, range, and coefficient of variation for the SDH activity and the CSA for both motor unit and non-motor unit fibers for each MHC profile and from each control and each self-reinnervated muscle studied was obtained. Eight motor units were isolated from self-reinnervated muscles using standard ventral root filament testing techniques, tested physiologically, and compared with four motor units from control muscles. Motor units from self-reinnervated muscles could be classified into the same physiological types as those found in control tibialis anterior muscles. The muscle fibers belonging to a unit were depleted of glycogen via repetitive stimulation and identified in periodic acid-Schiff-stained frozen sections. Whereas muscle fibers in control units expressed similar MHCs, each motor unit from self-reinnervated muscles contained a mixture of fiber types. In each motor unit, however, there was a predominance of fibers with the same MHC profile. The relative differences in the mean SDH activities found among fibers of different MHC profiles within a unit after self-reinnervation and those found among fibers in control muscles were similar, i.e., fast-2 < fast-1 < or = slow MHC fibers.(ABSTRACT TRUNCATED AT 250 WORDS)

Robust Bipedal Locomotion Based on a Hierarchical Control Structure

Robotica ◽  
2019 ◽  
Vol 37 (10) ◽  
pp. 1750-1767 ◽  
Author(s):  
Jianwen Luo ◽  
Yao Su ◽  
Lecheng Ruan ◽  
Ye Zhao ◽  
Donghyun Kim ◽  
...  
Keyword(s):  
Center Of Pressure ◽  
Center Of Mass ◽  
Hierarchical Control ◽  
Middle Level ◽  
Smooth Transition ◽  
Whole Body ◽  
Joint Torques ◽  
Low Level ◽  
Hybrid Controller ◽  
High Level

SummaryTo improve biped locomotion’s robustness to internal and external disturbances, this study proposes a hierarchical structure with three control levels. At the high level, a foothold sequence is generated so that the Center of Mass (CoM) trajectory tracks a planned path. The planning procedure is simplified by selecting the midpoint between two consecutive Center of Pressure (CoP) points as the feature point. At the middle level, a novel robust hybrid controller is devised to drive perturbed system states back to the nominal trajectory within finite cycles without chattering. The novelty lies in that the hybrid controller is not subject to linear CoM dynamic constraints. The hybrid controller consists of two sub-controllers: an oscillation controller and a smoothing controller. For the oscillation controller, the desired CoM height is specified as a sine-shaped function, avoiding a new attractive limit cycle. However, this controller results in the inevitable chattering because of discontinuities. A smoothing controller provides continuous properties and thus can inhibit the chattering problem, but has a smaller region of attraction compared with the oscillation controller. A hybrid controller merges the two controllers for a smooth transition. At the low level, the desired CoM motion is defined as tasks and embedded in a whole body operational space (WBOS) controller to compute the joint torques analytically. The novelty of the low-level controller lies in that within the WBOS framework, CoM motion is not subject to fixed CoM dynamics and thus can be generalized.

scholarly journals Management of Dysphagia in Acquired and Progressive Neurologic Conditions

2019 ◽  
Vol 40 (03) ◽  
pp. 203-212
Author(s):  
Michelle Ciucci ◽  
Jesse Hoffmeister ◽  
Karen Wheeler-Hegland
Keyword(s):  
Neural Control ◽  
Ethical Decision Making ◽  
Discussion Boards ◽  
Neurogenic Dysphagia ◽  
Transdisciplinary Approach ◽  
Life Issues ◽  
Solid Foundation ◽  
End Of Life Issues ◽  
High Level ◽  
Management Of Dysphagia

AbstractAs the act of deglutition involves much of the central and peripheral nervous systems, neurologic disease can affect swallowing behaviors ranging from mild to profound in severity. The key in working with neurogenic dysphagia is to have a solid foundation in normal swallowing processes, including neural control. Within this framework, then, understanding how the neurologic condition affects neural control will guide hypothesis-based assessment and evidence-based treatment. The purpose of this article is to provide an overview of evaluation and treatment of neurogenic dysphagia in adult populations as well to propose assessment of co-occurring speech, language, and airway compromise. Furthermore, it is vital to be familiar with ethical decision making and end-of-life issues. Continuing education in the form of research articles, conferences, and professional discussion boards is useful in maintaining a high level of service delivery. Whenever possible, an inter- or transdisciplinary approach is recommended.

Whole-Body Balancing Walk Controller for Position Controlled Humanoid Robots

2016 ◽  
Vol 13 (01) ◽  
pp. 1650011 ◽  
Author(s):  
Seung-Joon Yi ◽  
Byoung-Tak Zhang ◽  
Dennis Hong ◽  
Daniel D. Lee
Keyword(s):  
Hierarchical Control ◽  
Humanoid Robots ◽  
Whole Body ◽  
Appropriate Behavior ◽  
Low Level ◽  
Push Recovery ◽  
Hierarchical Control Architecture ◽  
High Level ◽  
Experimental Trials ◽  
Decision Boundaries

Bipedal humanoid robots are intrinsically unstable against unforeseen perturbations. Conventional zero moment point (ZMP)-based locomotion algorithms can reject perturbations by incorporating sensory feedback, but they are less effective than the dynamic full body behaviors humans exhibit when pushed. Recently, a number of biomechanically motivated push recovery behaviors have been proposed that can handle larger perturbations. However, these methods are based upon simplified and transparent dynamics of the robot, which makes it suboptimal to implement on common humanoid robots with local position-based controllers. To address this issue, we propose a hierarchical control architecture. Three low-level push recovery controllers are implemented for position controlled humanoid robots that replicate human recovery behaviors. These low-level controllers are integrated with a ZMP-based walk controller that is capable of generating reactive step motions. The high-level controller constructs empirical decision boundaries to choose the appropriate behavior based upon trajectory information gathered during experimental trials. Our approach is evaluated in physically realistic simulations and on a commercially available small humanoid robot.

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