Abstract
In the cortex, spontaneous neuronal avalanches can be characterized by spatiotemporal activity clusters with a cluster size distribution that follows a power law with exponent –1.5. Recordings in the striatum revealed that striatal activity was also characterized by spatiotemporal clusters that followed a power law distribution albeit, with significantly steeper slope, i.e., they lacked the large spatial clusters that are commonly expected for avalanche dynamics. In this study, we used computational modeling to investigate the influence of intrastriatal inhibition and corticostriatal interplay as important factors to understand the experimental findings and overall information transmission among these circuits.
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Acknowledgements
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n°604102 (HBP), the Swedish Research Council, NIAAA (grant 2R01AA016022), Swedish e-Science Research Centre, and EuroSPIN – an Erasmus Mundus Joint Doctorate program. The authors are thankful to Andreas Klaus for helpful discussion.
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Belić, J.J., Hellgren Kotaleski, J. (2016). Striatal Processing of Cortical Neuronal Avalanches – A Computational Investigation. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9886. Springer, Cham. https://doi.org/10.1007/978-3-319-44778-0_9
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