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Predictive Coding in Cortical Microcircuits

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 5164)

Abstract

We investigate the influence of spike timing dependent plasticity (STDP) on the prediction properties of recurrent microcircuits. We use sparsely connected networks in which the synaptic modifications introduced by STDP are complemented by two homeostatic plasticity mechanisms: synaptic normalization and intrinsic plasticity. In the presence of structured external input, STDP changes the connectivity matrix of the network such that the recurrent connections capture the particularities of the input stimuli, allowing the network to anticipate future inputs. Network activation patterns reflect different input expectations and can be separated by an unsupervised clustering technique.

Keywords

  • STDP
  • intrinsic plasticity
  • prediction
  • recurrent networks

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  • DOI: 10.1007/978-3-540-87559-8_40
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© 2008 Springer-Verlag Berlin Heidelberg

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Lazar, A., Pipa, G., Triesch, J. (2008). Predictive Coding in Cortical Microcircuits. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_40

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  • DOI: https://doi.org/10.1007/978-3-540-87559-8_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87558-1

  • Online ISBN: 978-3-540-87559-8

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