Snapping: A paradigm for modeling coordination of motor synergies

Liaw, Jim-Shih; Weerasuriya, Ananda; Arbib, Michael A.

doi:10.1016/s0893-6080(05)80163-7

Cited by 4 publications

(19 citation statements)

References 42 publications

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“…The latency of IPSPs is shorter than that of EPSPs. They concluded that there are two separate pathways from the optic tectum to the motoneurons and that the inhibitory pathway has a lower threshold, possibly to reset the different motor components (Liaw et al 1994).…”

Section: Motor Neurons and Musclesmentioning

confidence: 99%

“…The transformation of sensory signals into appropriate spatio-temporal patterns of activity in the motoneurons is postulated to be carried out in part by MPG. In this paper we extend the model described in Liaw et al (1994) by incorporating a larger number of components along with their corresponding control structure, in turn giving rise to the emergence of several MPGs.…”

Section: Introductionmentioning

confidence: 99%

“…We show how different afferent feedback signals about the status of the different components of the motor apparatus play a critical role in motor control as well as in learning. This paper, along with its companion paper, extend the model by Liaw et al (1994) by integrating a number of different motor pattern generators, different types of afferent feedback, as well as the corresponding control structure within an adaptive framework we call Schema-Based Learning. We develop a model of the different MPGs involved in prey-catching as a vehicle to investigate the following questions: What are the characteristic features of the activity of a single muscle?…”

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confidence: 99%

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Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture

et al. 2005

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A motor action often involves the coordination of several motor synergies and requires flexible adjustment of the ongoing execution based on feedback signals. To elucidate the neural mechanisms underlying the construction and selection of motor synergies, we study prey-capture in anurans. Experimental data demonstrate the intricate interaction between different motor synergies, including the interplay of their afferent feedback signals (Weerasuriya 1991; Anderson and Nishikawa 1996). Such data provide insights for the general issues concerning two-way information flow between sensory centers, motor circuits and periphery in motor coordination. We show how different afferent feedback signals about the status of the different components of the motor apparatus play a critical role in motor control as well as in learning. This paper, along with its companion paper, extend the model by Liaw et al. (1994) by integrating a number of different motor pattern generators, different types of afferent feedback, as well as the corresponding control structure within an adaptive framework we call Schema-Based Learning. We develop a model of the different MPGs involved in prey-catching as a vehicle to investigate the following questions: What are the characteristic features of the activity of a single muscle? How can these features be controlled by the premotor circuit? What are the strategies employed to generate and synchronize motor synergies? What is the role of afferent feedback in shaping the activity of a MPG? How can several MPGs share the same underlying circuitry and yet give rise to different motor patterns under different input conditions? In the companion paper we also extend the model by incorporating learning components that give rise to more flexible, adaptable and robust behaviors. To show these aspects we incorporate studies on experiments on lesions and the learning processes that allow the animal to recover its proper functioning.

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Section: Motor Neurons and Musclesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture

et al. 2005

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“…In vertebrates motor control involves the action of a much larger number of neurons and may also include more involved factors such as motivation and behavioral choice. All these aspects are orders of magnitude more complex in most vertebrates where the neural mechanisms of the control of the muscle activity are also poorly understood due to the complexity of the premotor and motor circuits involved (Liaw et al 1994). For instance, in the mammalian respiratory CPGs the underlying rhythmic pattern of neural activity consists of three phases: inspiratory, postinspiratory, and stage-2 expiratory.…”

Section: Discussionmentioning

confidence: 99%

A Central pattern generator to control a pyloric-based system

et al. 2000

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A central pattern generator (CPG) is built to control a mechanical device (plant) inspired by the pyloric chamber of the lobster. Conductance-based models are used to construct the neurons of the CPG. The plant has an associated function that measures the amount of food flowing through it per unit of time. We search for the best set of solutions that give a high positive flow of food in the maximization function. The plant is symmetric and the model neurons are identical to avoid any bias in the space of solutions. We find that the solution is not unique and that three neurons are sufficient to produce positive flow. We propose an effective principle for CPGs (effective on-off connectivity) and a few predictions to be corroborated in the pyloric system of the lobster.

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“…The behavioral selection is made before opening of the mouth and before contacting the prey and once it has been carried out, the immediate motor response occurs within a very short period of time. The transformation of visual information into appropriate spatiotemporal patterns of motor activity is carried out by the motor or central pattern generators located in the medial reticular formation of the brainstem [Weerasuriya, 1983[Weerasuriya, , 1989Schwippert et al, 1989;Liaw et al, 1994;Corbacho et al, 2005] ( fig. 1 ).…”

Section: Introductionmentioning

confidence: 99%

Brainstem Circuits Underlying the Prey-Catching Behavior of the Frog

Matesz¹,

Kecskes²,

Bácskai³

et al. 2014

Brain Behav Evol

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Prey-catching behavior (PCB) of the frog consists of a sequence of movements as a stimulus-response chain of the behavioral pattern in which each action presents a signal for the subsequent event. The transformation of visual information into appropriate spatiotemporal patterns of motor activity is carried out by the motor pattern generators located in the brainstem reticular formation. The motor pattern generators provide input to the motoneurons either directly or via the last-order premotor interneurons (LOPI). Although the feeding program is predetermined in this way, various sensory mechanisms control the motor activity. By using neuronal labeling methods, we have studied the morphological details of sensorimotor integration related to the hypoglossal motoneurons to provide further insight into the neuronal circuits underlying the PCB in ranid frogs. Our major findings are as follows. (1) Dendrodendritic and dendrosomatic contacts established by the crossing dendrites of hypoglossal (XII) motoneurons may serve as a morphological option for co-activation, synchronization and proper timing of the bilateral activity of tongue muscles. The crossing dendrites may also provide a feedforward amplification of various signals to the XII motoneurons. The overlapping dendritic territories of the motoneurons innervating protractor and retractor muscles may facilitate the coordinated activities of the agonistic and antagonistic muscles. (2) The musculotopic organization of the XII motoneurons is reflected in the distribution of LOPI for the protractor and retractor muscles of the tongue. (3) Direct sensory inputs from the trigeminal, vestibular, glossopharyngeal-vagal, hypoglossal and spinal afferent fibers to the XII motoneurons may modulate the basic motor pattern and contribute to the plasticity of neuronal circuits. (4) The electrical couplings observed in the vestibulocerebellar neuronal circuits may synchronize and amplify the afferent signals. The combination of chemical and electrical impulse transmission provides a mechanism by which motoneurons can be activated sequentially.

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Snapping: A paradigm for modeling coordination of motor synergies

Cited by 4 publications

References 42 publications

Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture

Schema-based learning of adaptable and flexible prey-catching in anurans I. The basic architecture

A Central pattern generator to control a pyloric-based system

Brainstem Circuits Underlying the Prey-Catching Behavior of the Frog

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