Cortical learning through the spike-timing-dependent plasticity modulated by intrinsic membrane potential fluctuation

IF 0.4 Q4 ENGINEERING, MULTIDISCIPLINARY Journal of Advanced Simulation in Science and Engineering Pub Date : 2019-01-01 DOI:10.15748/JASSE.6.32
Taishi Matsumura, T. Yuasa, Siu Kang
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Abstract

Cortical neurons exhibit membrane fluctuations and spontaneous transitions between distinct different two states characterized by subthreshold level of membrane potential. It has been known by modeling study that the mechanism of the spontaneous fluctuation originates from not only reverberation in a cortical circuit but intrinsic factor at a single neuron level. The two-state transitions are widely found in many brain regions and these transitions typically occurred spontaneously and synchronously. However, its computational advantage is still unclear. In this study, we investigated synaptic learning for external inputs in a model neuron whose dynamics of membrane potential fluctuation was modulated through the modification of ionic channel dynamics. It was observed that the membrane fluctuation could modulate the learning property to sequential inputs through the spike-timing-dependent plasticity.
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通过固有膜电位波动调节的spike- time依赖性可塑性的皮质学习
皮层神经元在膜电位阈下水平上表现出不同状态之间的膜波动和自发转换。模型研究表明,自发波动的机制不仅源于皮层回路的混响,而且源于单个神经元水平的内在因素。双态转换在许多大脑区域广泛发现,这些转换通常是自发和同步发生的。然而,其计算优势尚不清楚。在这项研究中,我们研究了一个模型神经元的突触学习,该模型神经元的膜电位波动动力学是通过离子通道动力学的修饰来调节的。研究发现,膜波动可以通过脉冲时间依赖的可塑性调节神经网络对序列输入的学习特性。
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