David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Studies in History and Philosophy of Science Part A 41 (3):271-279 (2010)
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
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
J. A. Fodor (1980). Methodological Solipsism Considered as a Research Strategy in Cognitive Psychology. Behavioral and Brain Sciences 3 (1):63.
Patricia S. Churchland, Terrence J. Sejnowksi & Brian P. McLaughlin (1996). The Computational Brain. Philosophy of Science 63 (1):137.
H. P. Grice (1957). Meaning. Philosophical Review 66 (3):377-388.
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 & Sonya Bahar (2013). Neural Computation and the Computational Theory of Cognition. Cognitive Science 37 (3):453-488.
Worth Boone & Gualtiero Piccinini (forthcoming). The Cognitive Neuroscience Revolution. Synthese:1-26.
Eric Hochstein (forthcoming). One Mechanism, Many Models: A Distributed Theory of Mechanistic Explanation. Synthese:1-21.
Kenneth Aizawa (2010). Computation in Cognitive Science: It is Not All About Turing-Equivalent Computation. Studies in History and Philosophy of Science Part A 41 (3):227-236.
Similar books and articles
Bruce J. MacLennan (1993). Grounding Analog Computers. Philosophical Explorations 2:8-51.
Russell Trenholme (1994). Analog Simulation. Philosophy of Science 61 (1):115-131.
John Haugeland (1981). Analog and Analog. Philosophical Topics 12 (1):213-226.
Hans Moravec (1979). Today's Computers, Intelligent Machines and Our Future. Analog 99 (2):59-84.
Barbara Webb (2004). Small Brains and Minimalist Emulation: When is an Internal Model No Longer a Model? Behavioral and Brain Sciences 27 (3):421-422.
Marcin Miłkowski (2011). Beyond Formal Structure: A Mechanistic Perspective on Computation and Implementation. Journal of Cognitive Science 12 (4):359-379.
Philip Cam (1989). Notes Toward a Faculty Theory of Cognitive Consciousness. In Peter Slezak (ed.), Computers, Brains and Minds. Kluwer 167--191.
Yorick Wilks (1982). Reviews. [REVIEW] British Journal for the Philosophy of Science 33 (3):191-195.
Chris Mortensen (1989). Mental Images: Should Cognitive Science Learn From Neurophysiology? In Peter Slezak (ed.), Computers, Brains and Minds. Kluwer 123--136.
Rob Wilson (2001). Rodney Cotterill, Enchanted Looms: Conscious Networks in Brains and Computers. [REVIEW] Minds and Machines 11 (3):433-437.
Tim van Gelder (1998). Computers and Computation in Cognitive Science. In T.M. Michalewicz (ed.), Advances in Computational Life Sciences Vol.2: Humans to Proteins. Melbourne: CSIRO Publishing
C. F. Boyle (1994). Computation as an Intrinsic Property. Minds and Machines 4 (4):451-67.
Kazuyuki Aihara & Jun Kyung Ryeu (2001). Chaotic Neurons and Analog Computation. Behavioral and Brain Sciences 24 (5):810-811.
Added to index2010-09-14
Total downloads19 ( #147,771 of 1,726,249 )
Recent downloads (6 months)2 ( #289,836 of 1,726,249 )
How can I increase my downloads?