Suppr超能文献

新兴离子-神经元动力学的晶体管类似物。

Transistor analogs of emergent iono-neuronal dynamics.

作者信息

Rachmuth Guy, Poon Chi-Sang

出版信息

HFSP J. 2008 Jun;2(3):156-66. doi: 10.2976/1.2905393. Epub 2008 Apr 18.

Abstract

Neuromorphic analog metal-oxide-silicon (MOS) transistor circuits promise compact, low-power, and high-speed emulations of iono-neuronal dynamics orders-of-magnitude faster than digital simulation. However, their inherently limited input voltage dynamic range vs power consumption and silicon die area tradeoffs makes them highly sensitive to transistor mismatch due to fabrication inaccuracy, device noise, and other nonidealities. This limitation precludes robust analog very-large-scale-integration (aVLSI) circuits implementation of emergent iono-neuronal dynamics computations beyond simple spiking with limited ion channel dynamics. Here we present versatile neuromorphic analog building-block circuits that afford near-maximum voltage dynamic range operating within the low-power MOS transistor weak-inversion regime which is ideal for aVLSI implementation or implantable biomimetic device applications. The fabricated microchip allowed robust realization of dynamic iono-neuronal computations such as coincidence detection of presynaptic spikes or pre- and postsynaptic activities. As a critical performance benchmark, the high-speed and highly interactive iono-neuronal simulation capability on-chip enabled our prompt discovery of a minimal model of chaotic pacemaker bursting, an emergent iono-neuronal behavior of fundamental biological significance which has hitherto defied experimental testing or computational exploration via conventional digital or analog simulations. These compact and power-efficient transistor analogs of emergent iono-neuronal dynamics open new avenues for next-generation neuromorphic, neuroprosthetic, and brain-machine interface applications.

摘要

神经形态模拟金属氧化物硅(MOS)晶体管电路有望实现紧凑、低功耗且高速的离子-神经元动力学仿真,其速度比数字仿真快几个数量级。然而,它们固有的输入电压动态范围与功耗以及硅芯片面积之间的权衡,使得它们对由于制造误差、器件噪声和其他非理想因素导致的晶体管失配高度敏感。这种限制使得除了具有有限离子通道动力学的简单尖峰之外,无法实现强大的模拟超大规模集成(aVLSI)电路来执行新兴的离子-神经元动力学计算。在此,我们展示了通用的神经形态模拟构建模块电路,其在低功耗MOS晶体管弱反转区域内运行,可提供接近最大的电压动态范围,这对于aVLSI实现或可植入仿生设备应用来说是理想的。所制造的微芯片能够可靠地实现动态离子-神经元计算,例如突触前尖峰或突触前和突触后活动的巧合检测。作为一项关键的性能基准,芯片上的高速且高度交互式的离子-神经元模拟能力使我们能够迅速发现混沌起搏器爆发的最小模型,这是一种具有根本生物学意义的新兴离子-神经元行为,迄今为止通过传统数字或模拟仿真一直无法进行实验测试或计算探索。这些紧凑且节能的新兴离子-神经元动力学晶体管模拟为下一代神经形态、神经假体和脑机接口应用开辟了新途径。

相似文献

引用本文的文献

6
Neuromorphic silicon neuron circuits.神经形态硅神经元电路。
Front Neurosci. 2011 May 31;5:73. doi: 10.3389/fnins.2011.00073. eCollection 2011.
8
Chaotic dynamics of cardioventilatory coupling in humans: effects of ventilatory modes.人体心肺耦合的混沌动力学:通气模式的影响。
Am J Physiol Regul Integr Comp Physiol. 2009 Apr;296(4):R1088-97. doi: 10.1152/ajpregu.90862.2008. Epub 2009 Feb 4.
10
Effects of inspiratory loading on the chaotic dynamics of ventilatory flow in humans.吸气负荷对人体通气气流混沌动力学的影响。
Respir Physiol Neurobiol. 2009 Jan 1;165(1):82-9. doi: 10.1016/j.resp.2008.10.015. Epub 2008 Nov 1.

本文引用的文献

2
Synaptic dynamics in analog VLSI.模拟超大规模集成电路中的突触动力学。
Neural Comput. 2007 Oct;19(10):2581-603. doi: 10.1162/neco.2007.19.10.2581.
6
Neuromorphic walking gait control.神经形态行走步态控制
IEEE Trans Neural Netw. 2006 Mar;17(2):496-508. doi: 10.1109/TNN.2005.863454.
9
The blue brain project.蓝脑计划。
Nat Rev Neurosci. 2006 Feb;7(2):153-60. doi: 10.1038/nrn1848.
10
Silicon microsystems for neuroscience and neural prostheses.用于神经科学和神经假体的硅微系统。
IEEE Eng Med Biol Mag. 2005 Sep-Oct;24(5):22-9. doi: 10.1109/memb.2005.1511497.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验