Journal of Statistical Planning and Inference 33 (1992) 27-65 North-Holland 21 How neural are neural networks? A comparison of information processing and storage in artificial and real neural systems Gregory A. Clark Department of Psychology, Green Hall, Princeton University, Princeton, NJ 08544, USA Robert D. Hawkins zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFEDCB Center for Neurobiology and Behavior, College of Physicians and Surgeons of Columbia University, and New York State Psychiatric Institute, 722 W. 168th St., New York, NY 10032, USA William N. Frost Department of Neurobiology and Anatomy, University of Texas Medical School, P.O. Box 20708, Houston, TX 77225, USA Received 1 August 1988; accepted 4 June 1990 Abstract: In this paper we compare the operations of biological and artificial neural networks and highlight some of the key strategies that real brains use to acquire, process, and store information. Artificial neural networks do indeed employ some of the same fundamental processes used in biological networks, such as changes in connection strengths, thus supporting the proposed similarity between the two systems, However, biological networks also exhibit several additional forms of plasticity which have received less attention in network models, including changes in neuronal excitability; changes in the fidelity (as well as strength) of synaptic transmission; changes in signal-to-noise ratios; changes in type of neurotransmitter synthesized and released; and changes in neuron number. The richness of plastic mechanisms found in biological neurons suggests there may be a number of effective computational tricks used by real nervous systems that could be advantageously incorporated into artificial neural networks. AMS Subject Classification: Primary 92B20; secondary 92C20; 68T05 Key words andphrases: Neural networks; neuronal plasticity; learning; memory; Ap/_wia; long-term potentia- tion. Correspondence to: Prof. Gregory A. Clark, Dept. of Psychology, Green Hall, Princeton University, Prince- ton, NJ 08544, USA. 0378-3758/92/$05.00 @ 1992-Elsevier Science Publishers B.V. All rights reserved