Computational analyses in cognitive neuroscience: In defense of biological implausibility
Journal/Book: Psychonomic Bull Rev. 1999; 6: 1710 Fortview Rd, Austin, TX 78704, USA. Psychonomic Soc Inc. 173-182.
Abstract: Because cognitive neuroscience researchers attempt to understand the human mind by bridging behavior and brain, they expect computational analyses to be biologically plausible. In this paper, biologically implausible computational analyses are shown to have critical and essential roles in the various stages and domains of cognitive neuroscience research. Specifically, biologically implausible computational analyses can contribute to (I) understanding and characterizing the problem that is being studied, (2) examining the availability of information and its representation, and (3) evaluating and understanding the neuronal solution. In the context of the distinct types of contributions made by certain computational analyses, the biological plausibility of those analyses is altogether irrelevant. These biologically implausible models are nevertheless relevant and important for biologically driven research.
Note: Article Dror IE, Univ Southampton, Dept Psychol, Southampton SO17 1BJ, Hants, ENGLAND
Keyword(s): NEURAL-NETWORK MODEL; ECHOLOCATING BAT; TARGET; SONAR; RECOGNITION; ACTIVATION; SYSTEMS; MEMORY; VISION