Neural dynamics in reconfigurable silicon

IF 3.8 2区医学 Q2 ENGINEERING, BIOMEDICAL

IEEE Transactions on Biomedical Circuits and Systems Pub Date : 2010-05-01 DOI:10.1109/ISCAS.2010.5536960

Arindam Basu, Shubha Ramakrishnan, P. Hasler

引用次数: 0

Abstract

A neuromorphic analog chip is presented that is capable of implementing massively parallel neural computations while retaining the programmability of digital systems. We show measurements from neurons with Hopf bifurcations and integrate and fire neurons, excitatory and inhibitory synapses, passive dendrite cables and central pattern generators implemented on the chip. This chip provides a platform for not only simulating detailed neuron dynamics but also using the same to interface with actual cells in applications like a dynamic clamp. The programmability is achieved using floating gate transistors with on-chip programming control. The switch matrix for interconnecting the components also consists of floating-gate transistors. Massive computational area efficiency is obtained by using the reconfigurable interconnect as synaptic weights.

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可重构硅中的神经动力学

提出了一种神经形态模拟芯片，能够实现大规模并行神经计算，同时保持数字系统的可编程性。我们展示了在芯片上实现的具有Hopf分岔、整合和激发神经元、兴奋性和抑制性突触、被动树突电缆和中枢模式发生器的神经元的测量结果。该芯片提供了一个平台，不仅可以模拟详细的神经元动态，还可以在动态钳等应用中使用相同的接口与实际细胞连接。可编程性是采用带有片上编程控制的浮栅晶体管实现的。用于互连元件的开关矩阵也由浮栅晶体管组成。采用可重构互连作为突触权值，获得了大量的计算面积效率。

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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来源期刊

IEEE Transactions on Biomedical Circuits and Systems 工程技术-工程：电子与电气

CiteScore

10.00

自引率

13.70%

发文量

174

审稿时长

3 months

期刊介绍： The IEEE Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems Society to a wide variety of related areas such as: • Bioelectronics • Implantable and wearable electronics like cochlear and retinal prosthesis, motor control, etc. • Biotechnology sensor circuits, integrated systems, and networks • Micropower imaging technology • BioMEMS • Lab-on-chip Bio-nanotechnology • Organic Semiconductors • Biomedical Engineering • Genomics and Proteomics • Neuromorphic Engineering • Smart sensors • Low power micro- and nanoelectronics • Mixed-mode system-on-chip • Wireless technology • Gene circuits and molecular circuits • System biology • Brain science and engineering: such as neuro-informatics, neural prosthesis, cognitive engineering, brain computer interface • Healthcare: information technology for biomedical, epidemiology, and other related life science applications. General, theoretical, and application-oriented papers in the abovementioned technical areas with a Circuits and Systems perspective are encouraged to publish in TBioCAS. Of special interest are biomedical-oriented papers with a Circuits and Systems angle.