Suppr超能文献

模拟 VLSI 生物物理神经元和突触,具有可编程的膜通道动力学。

Analog VLSI Biophysical Neurons and Synapses With Programmable Membrane Channel Kinetics.

出版信息

IEEE Trans Biomed Circuits Syst. 2010 Jun;4(3):139-48. doi: 10.1109/TBCAS.2010.2048566.

Abstract

We present and characterize an analog VLSI network of 4 spiking neurons and 12 conductance-based synapses, implementing a silicon model of biophysical membrane dynamics and detailed channel kinetics in 384 digitally programmable parameters. Each neuron in the analog VLSI chip (NeuroDyn) implements generalized Hodgkin-Huxley neural dynamics in 3 channel variables, each with 16 parameters defining channel conductance, reversal potential, and voltage-dependence profile of the channel kinetics. Likewise, 12 synaptic channel variables implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The biophysical origin of all 384 parameters in 24 channel variables supports direct interpretation of the results of adapting/tuning the parameters in terms of neurobiology. We present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. Uniform temporal scaling of the dynamics of membrane and gating variables is demonstrated by tuning a single current parameter, yielding variable speed output exceeding real time. The 0.5 CMOS chip measures 3 mm 3 mm, and consumes 1.29 mW.

摘要

我们提出并描述了一个由 4 个尖峰神经元和 12 个基于电导的突触组成的模拟 VLSI 网络,该网络实现了生物物理膜动力学的硅模型和 384 个数字可编程参数中的详细通道动力学。模拟 VLSI 芯片(NeuroDyn)中的每个神经元在 3 个通道变量中实现了广义 Hodgkin-Huxley 神经动力学,每个通道变量具有 16 个参数,用于定义通道电导、反转电位和通道动力学的电压依赖性曲线。同样,12 个突触通道变量实现了神经递质和受体动力学的基于速率的一阶动力学模型,该模型考虑了 NMDA 和非 NMDA 型化学突触。所有 384 个参数中的 24 个通道变量的生物物理起源支持根据神经生物学直接解释适应/调整参数的结果。我们展示了该芯片的实验结果,其特征在于单个神经元动力学、单个突触动力学和多神经元网络动力学,展示了作为突触耦合强度函数的锁相行为。通过调整单个电流参数,可以实现膜和门控变量的均匀时间标度,从而产生超过实时的可变速度输出。该 0.5 CMOS 芯片尺寸为 3mm×3mm,功耗为 1.29mW。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验