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      Multifunctional Pattern-Generating Circuits

      Author(s): 1 , 2
      Publication date Created:
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      Journal: Annual Review of Neuroscience
      Publisher: Annual Reviews

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          Abstract

          The ability of distinct anatomical circuits to generate multiple behavioral patterns is widespread among vertebrate and invertebrate species. These multifunctional neuronal circuits are the result of multistable neural dynamics and modular organization. The evidence suggests multifunctional circuits can be classified by distinct architectures, yet the activity patterns of individual neurons involved in more than one behavior can vary dramatically. Several mechanisms, including sensory input, the parallel activity of projection neurons, neuromodulation, and biomechanics, are responsible for the switching between patterns. Recent advances in both analytical and experimental tools have aided the study of these complex circuits.

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          Combinations of muscle synergies in the construction of a natural motor behavior.

          Andrea d'Avella, Philippe Saltiel, Emilio Bizzi (2003)
          A central issue in motor control is how the central nervous system generates the muscle activity patterns necessary to achieve a variety of behavioral goals. The many degrees of freedom of the musculoskeletal apparatus provide great flexibility but make the control problem extremely complex. Muscle synergies--coherent activations, in space or time, of a group of muscles--have been proposed as building blocks that could simplify the construction of motor behaviors. To evaluate this hypothesis, we developed a new method to extract invariant spatiotemporal components from the simultaneous recordings of the activity of many muscles. We used this technique to analyze the muscle patterns of intact and unrestrained frogs during kicking, a natural defensive behavior. Here we show that combinations of three time-varying muscle synergies underlie the variety of muscle patterns required to kick in different directions, that the recruitment of these synergies is related to movement kinematics, and that there are similarities among the synergies extracted from different behaviors.
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            From swimming to walking with a salamander robot driven by a spinal cord model.

            Auke Jan Ijspeert, Gabriela Crespi, Auke Jan Ijspeert … (2007)
            The transition from aquatic to terrestrial locomotion was a key development in vertebrate evolution. We present a spinal cord model and its implementation in an amphibious salamander robot that demonstrates how a primitive neural circuit for swimming can be extended by phylogenetically more recent limb oscillatory centers to explain the ability of salamanders to switch between swimming and walking. The model suggests neural mechanisms for modulation of velocity, direction, and type of gait that are relevant for all tetrapods. It predicts that limb oscillatory centers have lower intrinsic frequencies than body oscillatory centers, and we present biological data supporting this.
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              Biological pattern generation: the cellular and computational logic of networks in motion.

              Sten Grillner (2006)
              In 1900, Ramón y Cajal advanced the neuron doctrine, defining the neuron as the fundamental signaling unit of the nervous system. Over a century later, neurobiologists address the circuit doctrine: the logic of the core units of neuronal circuitry that control animal behavior. These are circuits that can be called into action for perceptual, conceptual, and motor tasks, and we now need to understand whether there are coherent and overriding principles that govern the design and function of these modules. The discovery of central motor programs has provided crucial insight into the logic of one prototypic set of neural circuits: those that generate motor patterns. In this review, I discuss the mode of operation of these pattern generator networks and consider the neural mechanisms through which they are selected and activated. In addition, I will outline the utility of computational models in analysis of the dynamic actions of these motor networks.
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                Author and article information

                Journal
                Title: Annual Review of Neuroscience
                Abbreviated Title: Annu. Rev. Neurosci.
                Publisher: Annual Reviews
                ISSN (Print): 0147-006X
                ISSN (Electronic): 1545-4126
                Publication date Created: July 2008
                Publication date (Print): July 2008
                Volume: 31
                Issue: 1
                Pages: 271-294
                Affiliations
                [1 ]Department of Biomedical Optics, Max Planck Institute for Medical Research, Heidelberg, 69120 Germany; email:
                [2 ]Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, California 92093-0357; email:
                Article
                DOI: 10.1146/annurev.neuro.31.060407.125552
                PubMed ID: 18558856
                SO-VID: 7d589d9e-d9b9-4aed-a54c-1110884f2344
                Copyright © © 2008
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