Do all neural models really look alike?

Author(s): Grossberg, S. |

Year: 1978

Citation: Psychological Review, 85, 592-596.

Abstract: Several of the formal approaches that are used to explain psychophysiologicalphenomena lead to different properties and principles of organization. Theseapproaches include computer, linear, and nonlinear models. The present noteillustrates this by citing differences between the linear theory of Anderson et al.and the nonlinear theory of Grossberg. For example, when linear signals arejoined to neural mechanisms, the resultant model is unstable and is unable toadapt or retune its sensitivity in response to changing input patterns. Nonlinearsignals overcome these difficulties and also compute reflectances, a Weber-Fechner law, and complex decision schemes that transform input patterns be-fore they are stored in short-term memory. The nonlinear theory also expressesorganizational principles that have been used to analyze a class of problems inperception, reinforcement, sensory-motor development, and goal-oriented cogni-tive behavior.

Topics: Mathematical Foundations of Neural Networks,

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