Abstract
Computationalism about the brain is the view that the brain literally performs computations. For the view to be interesting, we need an account of computation. The most well-developed account of computation is Turing Machine computation, the account provided by theoretical computer science which provides the basis for contemporary digital computers. Some have thought that, given the seemingly-close analogy between the all-or-nothing nature of neural spikes in brains and the binary nature of digital logic, neural computation could be a species of digital computation. A few recent authors have offered arguments against this idea; here, I review recent findings in neuroscience that further cement the implausibility of this view. However, I argue that we can retain the view that the brain is a computer if we expand what we mean by “computation” to include analog computation. I articulate an account of analog computation as the manipulation of analog representations based on previous work on the difference between analog and non-analog representations, extending a view originally articulated in Shagrir (Stud Hist Philos Sci 41(3):271–279, 2010). Given that analog computation constitutes a significant chapter in the history of computation, this revision of computationalism to include analog computation is not an ad hoc addition. Brains may well be computers, but of the analog kind, rather than the digital kind.
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Notes
That is, insofar as a Turing Machine can be said to have an architecture, given that it is an abstract mathematical object.
More precisely, computationalism can be a view about the brain or about the mind. In this essay, I focus only on computationalism about the brain.
In fact, this is how older light dimmers actually work: they send a rapid series of pulses to the light bulb, with a shorter gap between pulses for brighter light, and a longer gap for dimmer light.
Of course, virtually all modern digital computers use binary digits, so the string would actually be “101011001”.
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Maley, C.J. Toward Analog Neural Computation. Minds & Machines 28, 77–91 (2018). https://doi.org/10.1007/s11023-017-9442-5
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DOI: https://doi.org/10.1007/s11023-017-9442-5