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Emergence of Highly Nonrandom Functional Synaptic Connectivity Through STDP

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Neural Information Processing. Theory and Algorithms (ICONIP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6443))

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Abstract

We investigated the network topology organized through spike-timing-dependent plasticity (STDP) using pair- and triad-connectivity patterns, considering difference of excitatory and inhibitory neurons.

As a result, we found that inhibitory synaptic strength affects statistical properties of the network topology organized through STDP more strongly than the bias of the external input rate for the excitatory neurons. In addition, we also found that STDP leads highly nonrandom structure to the neural network. Our analysis from a viewpoint of connectivity pattern transitions reveals that STDP does not uniformly strengthen and depress excitatory synapses in neural networks. Further, we also found that the significance of triad-connectivity patterns after the learning results from the fact that the probability of triad-connectivity-pattern transitions is much higher than that of combinations of pair-connectivity-pattern transitions.

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Author information

Authors and Affiliations

  1. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Ohkubo, Saitama city, Saitama, 338–8570, Japan

    Hideyuki Kato & Tohru Ikeguchi

  2. Brain Science Institute, Saitama University, 255 Shimo-Ohkubo, Saitama city, Saitama, 338–8570, Japan

    Tohru Ikeguchi

Authors
  1. Hideyuki Kato
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  2. Tohru Ikeguchi
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Editor information

Editors and Affiliations

  1. School of Information Technology, Murdoch University, 6150, Murdoch, WA, Australia

    Kok Wai Wong

  2. The Australian National University, 0200, Canberra, ACT, Australia

    B. Sumudu U. Mendis

  3. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Northfields Avenue, 2522, P.O. Box, Wollongong, NSW, Australia

    Abdesselam Bouzerdoum

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Kato, H., Ikeguchi, T. (2010). Emergence of Highly Nonrandom Functional Synaptic Connectivity Through STDP. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Theory and Algorithms. ICONIP 2010. Lecture Notes in Computer Science, vol 6443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17537-4_15

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  • DOI: https://doi.org/10.1007/978-3-642-17537-4_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17536-7

  • Online ISBN: 978-3-642-17537-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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