Abstract
Synaptic connections in local cortical circuit are highly heterogeneous and nonrandom. A few strong synaptic connections often form “cluster” that is a tightly connected group of several neurons. Global structure of the clusters, however, has not been clarified yet. It is unclear whether clusters distribute independently and isolated in cortical network, or these clusters are a part of large-scale of global network structure. Here, we develop a network model based on recent experimental data of V1. In addition to reproducing previous result of highly skewed EPSPs, the model also allows us to study mutual relationship and global feature of clusters. We find that the network consists with two largely different sub-networks; a small-world network consists only of a few strong EPSPs and a random network consists of dense weak EPSPs. In other words, local cortical circuit shows a duality, and previously reported clusters are results of local observation of the global small-world network.
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Acknowledgement
This work was partially supported by the Ministry of Internal Affairs and Communications with a contract entitled “R&D for fundamental technology for energy-saving network control compatible to changing communication status” in FY2015 and Kakenhi 25430028 and JP16H01719.
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Watanabe, K., Teramae, Jn., Wakamiya, N. (2016). Inferred Duality of Synaptic Connectivity in Local Cortical Circuit with Receptive Field Correlation. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9947. Springer, Cham. https://doi.org/10.1007/978-3-319-46687-3_12
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DOI: https://doi.org/10.1007/978-3-319-46687-3_12
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