So most neuroscientists are wrong about the brain?
From Nautilus:
Here’s Why Most Neuroscientists Are Wrong About the Brain
From a computational point of view, directions and distances are just numbers. And numbers, rendered in binary form, are just bit strings. It’s a profound truth of computer science that there is no such thing as information that is not in a deep sense numerical. Claude Shannon’s famous 1948 paper, which founded the field of information theory, used a symphony concert as an example of an information-transmission problem that could be treated numerically. A consequence is that it does not make sense to say that something stores information but cannot store numbers.
Neuroscientists have not come to terms with this truth. I have repeatedly asked roomfuls of my colleagues, first, whether they believe that the brain stores information by changing synaptic connections—they all say, yes—and then how the brain might store a number in an altered pattern of synaptic connections. They are stumped, or refuse to answer. More.
Guy needs to get out more if he thinks that all information can be treated numerically. But then, he ©. R. Gallistel) may be attempting to revive the thesis of a 2009 book that doesn’t seem to have gone anywhere.
Here is a fair-minded review:
Some of the thoughts the book provokes are healthy and invigorating. It challenges theorists of cognition to think hard about (i) which computing mechanisms are required for certain cognitive functions and (ii) how they can be realized in the nervous system. The book points out that there is a lot that we don’t understand about how the brain fulfills various cognitive functions, and this is true. The book points out that some connectionists and neuroscientists are somewhat narrow minded about the kinds of processes and mechanisms they accept as possible explanations of cognitive functions and might benefit by thinking outside the box. The book also includes a fairly clear introduction to foundational topics such as Shannon’s information theory, computation, and representation. This is all good.
But there are also plenty of problems. For one thing, the main argument of the book is unsound. More.
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