A silicon early visual system as a model animal

Vision Research

Volumn 44, Issue 17, 2004, Pages 2083-2089

  Delbrück, Tobi ^a   Liu, Shih Chii ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

Neuroprosthesis; Receptive field; Retina cells; Visual physiology tool; Visual system

Indexed keywords

COMPUTER MODEL; DISPLAY SYSTEM; ELECTRIC MODEL; NERVE CELL; PRIORITY JOURNAL; RETINA CELL; RETINA RECEPTIVE FIELD; REVIEW; VISION; VISUAL ADAPTATION; VISUAL SYSTEM;

EID: 2442501398     PISSN: 00426989     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.visres.2004.03.021     Document Type: Article

References (20)

1. Anderson J.S., Carandini M., Ferster D. Orientation tuning of input conductance, excitation, and inhibition in cat primary visual cortex. Journal of Neurophysiology. 84:2000;909-926
2. Boahen K.A. The retinomorphic approach: pixel-parallel adaptive amplification, filtering, and quantization. Journal of Analog Integrated Circuits and Signal Processing. 13:1997;53-68
3. Borg-Graham L.J., Monier C., Fregnac Y. Visual input evokes transient and strong shunting inhibition in visual cortical neurons. Nature. 393:1998;369-373
4. Bult G., Geelen G. An inherently linear and compact MOST-only current division technique. IEEE Journal of Solid-State Circuits. 27:1992;1730-1735
5. Delbrück, T. (1991). "Bump" circuits for computing similarity and dissimilarity of analog voltages. In Proceedings of the International Joint Conference on Neural Networks (pp. I-475-I-479)
6. Delbrück, T., & Mead, C. A. (1994). Analog VLSI adaptive logarithmic wide-dynamic-range photoreceptor. In Proceedings of the IEEE International Symposium on Circuits and Systems, 4 (pp. 339-342)
7. Delbrück, T., & van Schaik, A. (2004). A. Bias generators with wide dynamic range. To be presented at the IEEE International Symposium on Circuits and Systems (ISCAS 2004)
8. Dowling J.E. The Retina: An Approachable Part of the Brain. 1987;The Belknap Press of Harvard University Press, Cambridge, MA
9. Harmon L.D. Studies with artificial neurons, I: properties and functions of an artificial neuron. Kybernetik. 3:1961;89-101
10. Hirsch J.A., Alonso J.M., Reid R.C., Martinez L.M. Synaptic integration in striate cortical simple cells. Journal of Neuroscience. 18:1998;9517-9528
11. Hubel D.H., Wiesel T.N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. Journal of Physiology. 160:1962;106-154
12. Liu S.C., Kramer J., Indiveri G., Delbrück T., Burg T., Douglas R. Orientation-selective aVLSI spiking neurons. Neural Networks. 14:2001;629-643
13. Mahowald M., Douglas R. A silicon neuron. Nature. 354:1991;515-518
14. Mead C.A. Analog VLSI and neural systems. 1989;Addison-Wesley Publishing, Reading, MA
15. Mead C.A. Neuromorphic electronic systems. Proceedings of the IEEE. 78:1990;1629-1636
16. Mead C.A., Mahowald M.A. A silicon model of early visual processing. Neural Networks. 1:1988;91-97
17. Ringach D.L., Sapiro G., Shapley R. A subspace reverse-correlation technique for the study of visual neurons. Vision Research. 37:1997;2455-2464
18. Sarpeshkar R. Analog versus digital: extrapolating from electronics to neurobiology. Neural Computation. 10:1998;1601-1638
19. Schweitzer-Tong D.E. The photoneuromime: an artificial visual neuron for dynamic testing of computer-controlled experiments. Behavior Research Methods and Instrumentation. 15:1983;9-12
20. Vittoz E., Fellrath J. CMOS analog integrated circuits based on weak inversion operation. IEEE Journal of Solid-State Circuits. SC-12:1977;224-231