Peter Hankins has written an excellent commentary criticizing the “positive comparisons” I make after contrasting brains with computers.
“… the concept of processing speed has no useful application in the brain rather than that it isn’t fixed.”
While this statement may intuitively appeal to some philosophers, temporal limitations in neural processing are both critical for neuronal function and well accepted in both neuroscience and psychometrics. At the biological level, the membrane capacitance of neurons is important for regulating the firing rate of neurons, which itself has an upper limit. Myelination is another feature of neurons which is clearly critical for the speed that information can be processed. At the level of individual differences, “processing speed” is a well-established psychometric construct which can be reliably measured, can reliably predict higher cognitive function, may be related to myelination, and is thought by some to be a parameter that is critical for capturing age-related change in cognition.
Peter Hankins says:
“Are brains analogue? Granted they’re not digital…I take digital and analogue to be two different ways of representing real-world quantities; I don’t think we really know exactly how the brain represents things at the moment.”
It’s increasingly accepted that the brain uses a sparse, distributed code for representing information. Computational models based on these principles are able to account for an increasingly wide variety of interactions between cognition, pharmacology, and deep brain stimulation. Work on the sparse distributed nature of these representations, and the learning processes which generate them, has driven the development and partial success of pattern classifiers for deciphering fMRI data – providing converging evidence that we do have an increasingly good idea of how brains represent information. Peter is probably uncomfortable with equating “sparse distributed representation” with “analog,” as I may have in my original post.
Of course, there are arguments that portions of the brain do represent information in a digital fashion, though in my opinion these similarities are somewhat superficial.
“… are brains ‘massively parallel’? … Chris is really warning against an excessively modular view.”
It’s true I abhor modular views of cognition, but it’s hard for me to imagine how the brain is not a massively parallel device – in the intuitive use of that phrase. Most attempts to identify the flow of information processing through cortical networks end up positing bidirectional connectivity between most cortical regions. I think Peter’s derision of the “massively parallel” phrase actually confounds the issue of “massively parallel” with “massively parallel computing”. And what we mean by “computing” is, of course, the crux of the issue.