Leaky-Integrate-and-Fire Neuron as Pacemaker for Interval Timing

Komala Anamalamudi, Raju Surampudi Bapi, G. Chakraborty, Nirupa Vakkala
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Abstract

Perception of interval timing influences the behaviour of the organisms. Computational models of interval timing are categorized into Pacemaker Accumulator models, Memory-based models, Oscillator models and Random Process models, Ramping Activity models and Population Clock models. Random process models or drift diffusion models are biologically plausible models and are based on the activity of spiking neurons. In this paper, we proposed a computational model of interval timing based on spiking neurons. The results are validated against the Scalar property of interval timing.
泄漏-整合-放电神经元作为间隔计时的起搏器
对间隔时间的感知影响生物体的行为。间隔计时的计算模型分为Pacemaker Accumulator模型、Memory-based模型、Oscillator模型和Random Process模型、Ramping Activity模型和Population Clock模型。随机过程模型或漂移扩散模型是生物学上可信的模型,它们基于尖峰神经元的活动。本文提出了一种基于尖峰神经元的间隔计时计算模型。根据区间计时的标量特性对结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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