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This article is part of the supplement: Abstracts from the Twenty Second Annual Computational Neuroscience Meeting: CNS*2013

Open Access Featured talk presentation

Sensory dynamics transformation into effective motor behavior

Roberto Latorre1*, Rafael Levi12 and Pablo Varona1

Author Affiliations

1 Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049 Madrid, Spain

2 The Whitney Laboratory for Marine Bioscience, University of Florida, 9505 Ocean Shore Blvd., St. Augustine, FL 32080, USA

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BMC Neuroscience 2013, 14(Suppl 1):F2  doi:10.1186/1471-2202-14-S1-F2

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/14/S1/F2


Published:8 July 2013

© 2013 Latorre et al; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Featured talk presentation

How sensory information is transformed into effective motor action is one of the most fundamental questions in neuroscience. The intrinsic dynamics of sensory networks can play an important role in the sensory-motor transformation. However, it is difficult to experimentally assess the study of all the stages present in the processing of a sensory-motor transformation. Biophysical models of sensory, central and motor systems can largely contribute to understand the information processing mechanisms involved in this transformation. Nevertheless, because of the lack of experimental results, there are very few models including all these stages to address the transformation of sensory dynamics into a motor program.

Complex intrinsic sensory dynamics can be related to multifunctionality in the sensory-motor transformation. Multifunctionality of neural systems has only been partially addressed in neuroscience research. One remarkable example of relationship between intrinsic sensory dynamics and multifunctionality is the gravimetric organ of the mollusk Clione limacina[1,2]. In this work we used conductance based models of sensory, central and motor circuits and electrophysiological recordings to address the study of the dual role of a sensory network to organize two different context-dependent motor programs. Our experimental and modeling results indicate that the sensory signals are modified to fit the changing behavioral context, and they are readily interpreted by the rest of the nervous system to produce the correct motor output. We show that a winner-take all dynamics in the gravimetric sensory network drives the repetitive rhythm of Clione's wing CPG model during routine swimming [3]. On the other hand, a winnerless competition dynamics in the same sensory network organizes the irregular pattern observed in the wing CPG during hunting behavior [1]. These two dynamics are interpreted by the wing CPG to generate the characteristic rhythmic motion during routine swimming and the fast irregular motion that is observed during hunting behavior. Our modeling results also indicate that specific activation phase locks in the sensory network dynamics are transformed into specific motor events in the wing CPG. The activation phase locks can play an important role in motor coordination.

These results support the view that the dual dynamics of the statocyst network by itself can explain the two motor programs observed during routine swimming and during hunting behavior in Clione [4]. In other words, the motor program could be generated right at the sensory network fitting the changing behavioral context in the sensory signals. In this way, the rest of the neurons in the sensory-motor transformation can just react normally to this signaling.

Acknowledgements

This work was supported by MINECO TIN2012-30883 and IPT-2011-0727-020000.

References

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    J Neurophysiol 2004, 91:336-345. PubMed Abstract | Publisher Full Text OpenURL

  2. Levi R, Varona P, Arshavsky YI, Rabinovich MI, Selverston AI: The Role of Sensory Network Dynamics in Generating a Motor Program.

    J Neuroscience 2005, 25:9807-9815. Publisher Full Text OpenURL

  3. Panchin YV, Arshavsky YI, Deliagina TG, Popova LB, Orlovsky GN: Control of locomotion in marine mollusk Clione Limacina. IX. Neuronal mechanisms of spatial orientation.

    J Neurophysiol 1995, 73:1924-1937. PubMed Abstract | Publisher Full Text OpenURL

  4. Latorre R, Levi R, Varona P: Transformation of context-dependent sensory dynamics into motor behavior.

    PLoS Computational Biology 2013, 9(2):e1002908. PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL