Browse > Article
http://dx.doi.org/10.5369/JSST.2009.18.2.128

Hardware implementation of a pulse-type neuron chain with a synapse function for hodgkin-huxley model  

Jung, Jin-Woo (Department of Nano Engineering, Inje University)
Kwon, Bo-Min (Department of Nano Engineering, Inje University)
Park, Ju-Hong (Department of Nano Engineering, Inje University)
Kim, Jin-Su (Department of Nano Engineering, Inje University)
Lee, Je-Won (Department of Nano Engineering, Inje University)
Park, Yong-Su (Department of Electronics, Chungcheong University)
Song, Han-Jung (Department of Nano Engineering, Inje University)
Publication Information
Journal of Sensor Science and Technology / v.18, no.2, 2009 , pp. 128-134 More about this Journal
Abstract
Integrated circuit of a new neuron chain with a synapse function for Hodgkin-Huxley model which is a good electrical model about a real biological neuron is implemented in a $0.5{\mu}m$ 1 poly 2 metal CMOS technology. Pulse type neuron chain consist of series connected current controlled single neurons through synapses. For the realization of the single neuron, a pair of voltage mode oscillators using operational transconductance amplifiers and capacitors is used. The synapse block which is a connection element between neurons consist of a voltage-current conversion circuit using current mirror. SPICE simulation results of the proposed circuit show 160 mV amplitude pulse output and propagation of the signal through synapses. Measurements of the fabricated pulse type neuron chip in condition of ${\pm}2.5\;V$ power supply are shown and compared with the simulated results.
Keywords
Hodgkin-Huxley model; neuron chain; synapse; pulse type; CMOS;
Citations & Related Records
연도 인용수 순위
  • Reference
1 H. J. Song, and J. G. Harris, 'A CMOS neural oscillator using negative resistance', IEEE International symposium on Circuits and Systems, pp. 152-155, Bangkok, Thailand, 2003
2 K. Judd and K. Aihara, 'Pulse propagation networks: A neural network model thal uses temporal coding by action potentials', Neural Networks, vol. 6, no. 2, pp. 203-218, 1993   DOI   ScienceOn
3 T. Taniguchi, Y. Horio and K. Aihara, 'An IC implementation of asynchronous pulse neuron model : in Roc', International Symposium on Nonlinear Theory and its applications, pp. 921-924, Xi'an, China, 2002
4 Y. Ota and B. M. Wilamowski, 'Analog implementation of pluse-coupled neural', IEEE Transactions on Neural Networks, vol. 10, no. 3, pp. 539-544, 1999   DOI   ScienceOn
5 B. Liu and J. F. Frenzel, 'A CMOS neuron for VLSI circuit implementation of pulsed neural networks,' Proceedings of the 28th annual conference of IEEE industrial Electronics society, vol. 4, no. 5-8, pp. 3182-3185, Sevilla, Spain, 2002
6 W. J. Freeman, Y. Yao, and B. Burke, 'Central pattern generating and recognizing in olfactory bulb: A correlation learning rule', Neural Networks, vol. 1, pp. 227-288, 1988.   DOI   ScienceOn
7 G. Moon, M. Zaghloul, and R. Newcomb, 'CMOS design of pulse coded adaptive neural processing element using neural-type cells,' IEEE International Symposium on Circuits and Systems, pp. 2224 -2227, San Diego, CA, USA, 1992
8 B. Linares-Barranco, E. Sanchez-Sinencio, A. Rodriguez- Vaquez, and J. L. Huertas, 'CMOS analog neural network systems based on oscillatory neurons', IEEE International Symposium on Circuits and Systems, pp. 2236-2239, San Diego, CA, USA, 1992
9 Y. Ota and B. M. Wilamowski, 'CMOS implementation of a pulse-coded neural network with a current controlled oscillator,' IEEE International Symposium on Circuits and Systems, pp. 410-413, Atlanta, GA, USA, 1996
10 V. M. G. Tavares, J. C. Principe, and J. G. Harris, 'A silicon olfactory bulb oscillator', IEEE International Symposium on Circuits and Systems, vol. 3, pp. 410-413, Geneva, Switzerland, 2000
11 A. L. Hodgkin and A. F Huxley, 'A quantitative description of memtrane current and its application to conduction and excitation in nerve', J. Physiol., vol. 117, pp. 500-544, 1952   DOI
12 D. Terman, and D. L. Wang, 'Global competition and local cooperation in a network of neural', Physica D., vol. 81, pp. 148-176, 1995   DOI   ScienceOn
13 C. Mead, Analog VLSI and neural systems, Addison- wesley publishing company, 1989