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Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus

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  • Dariusz Świetlik

Abstract

The aim of this paper is to present a computational model of the CA1 region of the hippocampus, whose properties include (a) attenuation of receptors for external stimuli, (b) delay and decay of postsynaptic potentials, (c) modification of internal weights due to propagation of postsynaptic potentials through the dendrite, and (d) modification of weights for the analog memory of each input due to a pattern of long-term synaptic potentiation (LTP) with regard to its decay. The computer simulations showed that CA1 model performs efficient LTP induction and high rate of sub-millisecond coincidence detection. We also discuss a possibility of hardware implementation of pyramidal cells of CA1 region of the hippocampus.

Suggested Citation

  • Dariusz Świetlik, 2018. "Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus," Complexity, Hindawi, vol. 2018, pages 1-13, December.
    • Handle: RePEc:hin:complx:1297150
    DOI: 10.1155/2018/1297150
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    References listed on IDEAS

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    1. Makoto Nishiyama & Kyonsoo Hong & Katsuhiko Mikoshiba & Mu-ming Poo & Kunio Kato, 2000. "Calcium stores regulate the polarity and input specificity of synaptic modification," Nature, Nature, vol. 408(6812), pages 584-588, November.
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    Cited by:

    1. Dariusz Świetlik & Jacek Białowąs, 2019. "Application of Artificial Neural Networks to Identify Alzheimer’s Disease Using Cerebral Perfusion SPECT Data," IJERPH, MDPI, vol. 16(7), pages 1-9, April.

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