Brains as analog-model computers

Abstract
Computational neuroscientists not only employ computer models and simulations in studying brain functions. They also view the modeled nervous system itself as computing. What does it mean to say that the brain computes? And what is the utility of the ‘brain-as-computer’ assumption in studying brain functions? In previous work, I have argued that a structural conception of computation is not adequate to address these questions. Here I outline an alternative conception of computation, which I call the analog-model. The term ‘analog-model’ does not mean continuous, non-discrete or non-digital. It means that the functional performance of the system simulates mathematical relations in some other system, between what is being represented. The brain-as-computer view is invoked to demonstrate that the internal cellular activity is appropriate for the pertinent information-processing task.Keywords: Computation; Computational neuroscience; Analog computers; Representation; Simulation
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References found in this work BETA
Frances Egan (1995). Computation and Content. Philosophical Review 104 (2):181-203.
Frances Egan (2010). Computational Models: A Modest Role for Content. Studies in History and Philosophy of Science Part A 41 (3):253-259.
H. P. Grice (1957). Meaning. Philosophical Review 66 (3):377-388.
Rick Grush (2001). The Semantic Challenge to Computational Neuroscience. In Peter K. Machamer, Peter McLaughlin & Rick Grush (eds.), Theory and Method in the Neurosciences. University of Pittsburgh Press. 155--172.

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