Connectionists: The Atoms of Neural Computation: A reply to Gary Marcus

[Dror Cohen]

"lumpers and splitters" I like that :).

There is another aspect to this debate that I think is often overlooked.

Biological systems exhibit high degeneracy. In this context, degeneracy
refers to the ability of different mechanisms to produce the same function.
This is to be contrasted with redundancy, which occurs when similar
mechanisms produce the same function.  See below for an excellent overview.

Degeneracy and Complexity in Biological Systems
Gerald M. Edelman and Joseph A. Gally
PNAS 2001


There may be large variability in the types of neurons in the cortex, but
my bet is that their functions overlap - that is, this variability, in
part, is an example of degeneracy.

I'm interested in doing some simulations to develop this idea, if anyone is
interested please feel free to email me.

Thanks,

Dror



On Tue, Nov 4, 2014 at 9:13 AM, Terry Sejnowski <terry at salk.edu> wrote:

> The debate between lumpers and splitters on cortical areas will not be
> settled
> until we have the right tools to probe them anatomically and functionally.
>
> We don't even know how many types of neurons there are in the cortex.
> Estimates range from 100 to 1000.
>
> One of the goals of the BRAIN Initiative is to find out how many
> there are and how they vary between different parts of the cortex:
>
> http://www.braininitiative.nih.gov/2025/index.htm
>
> An important source of variability between neurons is differential patterns
> of gene methylation, which is uniquely different in neurons compared
> with other cell types in the body:
>
> Lister, R. Mukamel, et al.  Global epigenomic reconfiguration
> during mammalian brain development, Science, 341, 629, 2013
>
>
> http://directorsblog.nih.gov/2013/08/27/charting-the-chemical-choreography-of-brain-development/#more-1983
>
>
> http://papers.cnl.salk.edu/PDFs/Global%20epigenomic%20reconfiguration%20during%20mammalian%20brain%20development%202013-4331.pdf
>
> We now have optical techniques to record from 1000 cortical neurons
> simultaneously and that will increase by a factor of 100-1000x
> over the next decade.
>
> This will create a big data problem for neuroscience that readers of
> this list could help solve:
>
> Sejnowski, T. J. Churchland, P.S. Movshon, J.A.
> Putting big data to good use in neuroscience,
> Nature Neuroscience, 17, 1440-1441, 2014
>
>
> http://papers.cnl.salk.edu/PDFs/Putting%20big%20data%20to%20good%20use%20in%20neuroscience%202014-4397.pdf
>
> Terry
>
> -----
>
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