Abstract
Connectionist modeling and neuroscience have little common ground or mutual influence. Despite impressive algorithms and analysis within connectionism and neural networks, there has been little influence on neuroscience, which remains primarily an empirical science. This chapter advocates two strategies to increase the interaction between neuroscience and neural networks: (1) focus on emergent properties in neutral networks that are apparently “cognitive”, (2) take neuroimaging data seriously and develop neural models of dynamics in the both spatial and temporal dimensions.
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Hanson, S.J., Negishi, M., Hanson, C. (2001). Connectionist Neuroimaging. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_40
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DOI: https://doi.org/10.1007/3-540-44597-8_40
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