Compositionality of arm movements can be realized by propagating synchrony

Authors:
Alexander Hanuschkin;J. Michael Herrmann;Abigail Morrison;Markus Diesmann
Affiliations:
Functional Neural Circuits Group, Faculty of Biology, Freiburg, Germany 79104 and Bernstein Center Freiburg, Freiburg, Germany;IPAB, School of Informatics, University of Edinburgh, Edinburgh, UK and BCCN Göttingen and MPI for Dynamics and Self-Organization, Göttingen, Germany;Functional Neural Circuits Group, Faculty of Biology, Freiburg, Germany 79104 and Bernstein Center Freiburg, Freiburg, Germany and Laboratory of Computational Neurophysics, RIKEN Brain Science Ins ...;Bernstein Center Freiburg, Freiburg, Germany and Laboratory of Computational Neurophysics, RIKEN Brain Science Institute, Wako City, Japan and RIKEN Computational Science Research Program, Wako Ci ...
Venue:
Journal of Computational Neuroscience
Year:
2011

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Abstract

We present a biologically plausible spiking neuronal network model of free monkey scribbling that reproduces experimental findings on cortical activity and the properties of the scribbling trajectory. The model is based on the idea that synfire chains can encode movement primitives. Here, we map the propagation of activity in a chain to a linearly evolving preferred velocity, which results in parabolic segments that fulfill the two-thirds power law. Connections between chains that match the final velocity of one encoded primitive to the initial velocity of the next allow the composition of random sequences of primitives with smooth transitions. The model provides an explanation for the segmentation of the trajectory and the experimentally observed deviations of the trajectory from the parabolic shape at primitive transition sites. Furthermore, the model predicts low frequency oscillations (