Abstract
The execution of habitual actions is thought to rely on the exploitation of procedural motor memories. These memories encode motor commands as organized in functional sequences with well defined boundaries in the Striatum. Here, we present a biophysical model of the striatal network composed by inhibitory medium spiny neurons (MSNs) governed by anti-hebbian STDP. We show that these two features allow for learning an arbitrary sequence through multiple exposures to cortical inputs and reproducing it under a single, non-specific excitatory drive. Our results shed light on the computational properties of biologically plausible inhibitory networks and suggest a simple, yet effective mechanism of behavioral control through striatal circuits.
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Maffei, G., Puigbò, JY., Verschure, P.F.M.J. (2017). Learning Modular Sequences in the Striatum. In: Mangan, M., Cutkosky, M., Mura, A., Verschure, P., Prescott, T., Lepora, N. (eds) Biomimetic and Biohybrid Systems. Living Machines 2017. Lecture Notes in Computer Science(), vol 10384. Springer, Cham. https://doi.org/10.1007/978-3-319-63537-8_52
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DOI: https://doi.org/10.1007/978-3-319-63537-8_52
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