Analog Versus Digital: Extrapolating from Electronics to Neurobiology

We review the pros and cons of analog and digital computation. We propose that computation that is most efficient in its use of resources is neither analog computation nor digital computation but, rather, a mixture of the two forms. For maximum efficiency, the information and information-processing resources of the hybrid form must be distributed over many wires, with an optimal signal-to-noise ratio per wire. Our results suggest that it is likely that the brain computes in a hybrid fashion and that an underappreciated and important reason for the efficiency of the human brain, which consumes only 12 W, is the hybrid and distributed nature of its architecture.

[1]  Rahul Sarpeshkar,et al.  Efficient precise computation with noisy components: extrapolating from an electronic cochlea to the brain , 1997 .

[2]  Peter B. Denyer,et al.  VLSI Signal Processing: A Bit-Serial Approach , 1985 .

[3]  Rob R. de Ruyter van Steveninck,et al.  Coding Efficiency and the Metabolic Cost of Sensory and Neural Information , 2000, Information Theory and the Brain.

[4]  G. Shepherd.  The Synaptic Organization of the Brain , 1979 .

[5]  J. von Neumann,et al.  Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components , 1956 .

[6]  Salman,et al.  Voltage Fluctuations and Collective Effects in Ion-Channel Protein Ensembles. , 1996, Physical review letters.

[7]  L. Aiello,et al.  The Expensive-Tissue Hypothesis: The Brain and the Digestive System in Human and Primate Evolution , 1995, Current Anthropology.

[8]  C. Stevens,et al.  An evaluation of causes for unreliability of synaptic transmission. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[9]  J J Hopfield,et al.  Rapid local synchronization of action potentials: toward computation with coupled integrate-and-fire neurons. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Douglas A. Kerns.  Experiments in very large-scale analog computation , 1993 .

[11]  C. Mead,et al.  White noise in MOS transistors and resistors , 1993, IEEE Circuits and Devices Magazine.

[12]  B.J. Hosticka,et al.  Performance comparison of analog and digital circuits , 1985, Proceedings of the IEEE.

[13]  L. Trussell,et al.  A characterization of excitatory postsynaptic potentials in the avian nucleus magnocellularis. , 1994, Journal of neurophysiology.

[14]  Eric A. Vittoz,et al.  Future of analog in the VLSI environment , 1990, IEEE International Symposium on Circuits and Systems.

[15]  Carver A. Mead,et al.  Neuromorphic electronic systems , 1990, Proc. IEEE.

[16]  Louis J. DeFelice,et al.  Introduction to membrane noise , 1981 .

[17]  Rahul Sarpeshkar,et al.  A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea , 1998 .

[18]  Vivien A. Casagrande,et al.  Biophysics of Computation: Information Processing in Single Neurons , 1999 .

[19]  Christof Koch,et al.  Biophysics of Computation: Information Processing in Single Neurons (Computational Neuroscience Series) , 1998 .

[20]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[21]  Paul J. Layzell,et al.  Explorations in design space: unconventional electronics design through artificial evolution , 1999, IEEE Trans. Evol. Comput..

[22]  Thomas A. DeMassa,et al.  Digital Integrated Circuits , 1985, 1985 IEEE GaAs IC Symposium Technical Digest.

[23]  Hermann A. Haus,et al.  Circuit Theory of Linear Noisy Networks , 1959 .

[24]  Gert Cauwenberghs.  A micropower CMOS algorithmic A/D/A converter , 1995 .

[25]  Naftali Tishby,et al.  Cortical activity flips among quasi-stationary states. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Rob R. de Ruyter van Steveninck,et al.  The metabolic cost of neural information , 1998, Nature Neuroscience.

[27]  Paul M. Furth.  Bit-Energy Comparison of Discrete and Continuous Signal Representations At the Circuit Level , 1996 .

[28]  Lynn Conway,et al.  Introduction to VLSI systems , 1978 .

[29]  Carver Mead,et al.  Analog VLSI and neural systems , 1989 .

[30]  Anantha P. Chandrakasan,et al.  Low-power CMOS digital design , 1992 .

[31]  David Andrew Martin.  ADAP: A Mixed-Signal Array Processor With Early Vision Applications , 1996 .