LEADER 04317nam 2200469z- 450 001 9910161647003321 005 20231214133445.0 035 $a(CKB)3710000001041994 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/53806 035 $a(EXLCZ)993710000001041994 100 $a20202102d2016 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModularity in motor control: from muscle synergies to cognitive action representation 210 $cFrontiers Media SA$d2016 215 $a1 electronic resource (792 p.) 225 1 $aFrontiers Research Topics 311 $a2-88919-805-7 330 $aMastering a rich repertoire of motor behaviors, as humans and other animals do, is a surprising and still poorly understood outcome of evolution, development, and learning. Many degrees-of-freedom, non-linear dynamics, and sensory delays provide formidable challenges for controlling even simple actions. Modularity as a functional element, both structural and computational, of a control architecture might be the key organizational principle that the central nervous system employs for achieving versatility and adaptability in motor control. Recent investigations of muscle synergies, motor primitives, compositionality, basic action concepts, and related work in machine learning have contributed to advance, at different levels, our understanding of the modular architecture underlying rich motor behaviors. However, the existence and nature of the modules in the control architecture is far from settled. For instance, regularity and low-dimensionality in the motor output are often taken as an indication of modularity but could they simply be a byproduct of optimization and task constraints? Moreover, what are the relationships between modules at different levels, such as muscle synergies, kinematic invariants, and basic action concepts? One important reason for the new interest in understanding modularity in motor control from different viewpoints is the impressive development in cognitive robotics. In comparison to animals and humans, the motor skills of today?s best robots are limited and inflexible. However, robot technology is maturing to the point at which it can start approximating a reasonable spectrum of isolated perceptual, cognitive, and motor capabilities. These advances allow researchers to explore how these motor, sensory and cognitive functions might be integrated into meaningful architectures and to test their functional limits. Such systems provide a new test bed to explore different concepts of modularity and to address the interaction between motor and cognitive processes experimentally. Thus, the goal of this Research Topic is to review, compare, and debate theoretical and experimental investigations of the modular organization of the motor control system at different levels. By bringing together researchers seeking to understand the building blocks for coordinating many muscles, for planning endpoint and joint trajectories, and for representing motor and behavioral actions in memory we aim at promoting new interactions between often disconnected research areas and approaches and at providing a broad perspective on the idea of modularity in motor control. We welcome original research, methodological, theoretical, review, and perspective contributions from behavioral, system, and computational motor neuroscience research, cognitive psychology, and cognitive robotics. 517 $aModularity in motor control 610 $aaction representation 610 $amuscle synergies 610 $aMotor Primitives 610 $amotor learning 610 $acompositionality 610 $aneural control of movement 610 $aIntermittent control 610 $aKinematic invariants 610 $aControl architectures 610 $aRobotics 700 $aTamar Flash$4auth$01284052 702 $aAndrea d'Avella$4auth 702 $aThomas Schack$4auth 702 $aYuri P. Ivanenko$4auth 702 $aMartin Giese$4auth 906 $aBOOK 912 $a9910161647003321 996 $aModularity in motor control: from muscle synergies to cognitive action representation$93019238 997 $aUNINA