David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Synthese 153 (3):393-416 (2006)
The view that the brain is a sort of computer has functioned as a theoretical guideline both in cognitive science and, more recently, in neuroscience. But since we can view every physical system as a computer, it has been less than clear what this view amounts to. By considering in some detail a seminal study in computational neuroscience, I first suggest that neuroscientists invoke the computational outlook to explain regularities that are formulated in terms of the information content of electrical signals. I then indicate why computational theories have explanatory force with respect to these regularities:in a nutshell, they underscore correspondence relations between formal/mathematical properties of the electrical signals and formal/mathematical properties of the represented objects. I finally link my proposal to the philosophical thesis that content plays an essential role in computational taxonomy
|Keywords||POSTERIOR PARIETAL NEURONS COMPUTATION INDIVIDUALISM PSYCHOLOGY CONNECTIONISM REDUCTIONISM EXTERNALISM NETWORK SCIENCE VISION|
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Citations of this work BETA
Gualtiero Piccinini & Carl Craver (2011). Integrating Psychology and Neuroscience: Functional Analyses as Mechanism Sketches. Synthese 183 (3):283-311.
Gualtiero Piccinini (2007). Computing Mechanisms. Philosophy of Science 74 (4):501-526.
David Michael Kaplan (2011). Explanation and Description in Computational Neuroscience. Synthese 183 (3):339-373.
Eric Hochstein (2016). One Mechanism, Many Models: A Distributed Theory of Mechanistic Explanation. Synthese 193 (5):1387-1407.
Nir Fresco (2010). Explaining Computation Without Semantics: Keeping It Simple. [REVIEW] Minds and Machines 20 (2):165-181.
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