Organic electronics Axon-Hillock neuromorphic circuit: towards biologically compatible, and physically flexible, integrate-and-fire spiking neural networks

被引:23
|
作者
Hosseini, Mohammad Javad Mirshojaeian [1 ]
Donati, Elisa [2 ,3 ]
Yokota, Tomoyuki [4 ]
Lee, Sunghoon [4 ]
Indiveri, Giacomo [2 ,3 ]
Someya, Takao [4 ]
Nawrocki, Robert A. [1 ]
机构
[1] Purdue Univ, Sch Engn Technol, W Lafayette, IN 47907 USA
[2] Univ Zurich, Inst Neuroinformat, Zurich, Switzerland
[3] Swiss Fed Inst Technol, Zurich, Switzerland
[4] Univ Tokyo, Dept Elect & Elect Engn, Tokyo, Japan
关键词
spiking neural network; neuromorphic circuits; organic electronics; Axon-Hillock circuit; integrate-and-fire spiking neuron; ON-CHIP; DEVICES; ARCHITECTURE; PEDOTPSS; HARDWARE; DESIGN; MODEL;
D O I
10.1088/1361-6463/abc585
中图分类号
O59 [应用物理学];
学科分类号
摘要
Spiking neural networks (SNNs) have emerged as a promising computational paradigm to emulate the features of natural neural tissue physiology. While hardware implementations of SNNs are being conceived to emulate biological systems, they typically rely on hard and rigid silicon electronics that are not bio-compatible. In the physical, or materials realm, organic electronics offer mechanical flexibility and bio-compatibility, allowing for the construction of neural processing systems that can be directly interfaced to biological networks. This study introduces an organic electronics implementation of an Integrate-and-Fire spiking neuron based on the Axon-Hillock CMOS circuit. The circuit employs organic p-type and n-type field effective transistors and reproduces the behavior of the CMOS neuromorphic counterpart. We demonstrate its operating characteristics measuring its spike rate output as a function of its input current. We show how it properly integrates input currents and demonstrate its computing abilities in a basic current summing experiment. The static and dynamic power dissipation is calculated to be less than 0.4 and 40 mu W, respectively. This is the first demonstration of the spiking Axon-Hillock neuromorphic circuit using organic materials.
引用
收藏
页数:10
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