[Comp-neuro] Review announcement

jim bower bower at uthscsa.edu
Tue Jul 29 21:04:48 CEST 2008

). Hi Jim (from a limo in oakland...!):

Would you mind pointing me to data suggesting that cortical columns  
don't exist? That (among many others you've made, of course!) is an  
interesting point!

Garrison Cottrell

Well, this started as questioning over generalized assumptions and a concern with definitions -- so why not? 

How about this. Can anyone propose a consistent definition of a cortical column?

You might want to start by reading Vernon Mouncastle's original paper (1958 I think), in which there was a very clear definition.  (Several years ago he also published a review defending, in effect the original definition). 

If you read closely, there is actually very little evidence for his original definition. However his assertion that columns represent the " fundamental computational unit "of the cerebral cortex of course does persist as the idea is very attractive as a way to simplify and reduce complexty (and thus see previous). 

Here are some more specific questions: 

Do columns have boundaries as Mountcastle clealry believed and believes? If not they are strange columns, if they don't then doesn't that imply that the mapping function is continuous and not discrete?  What does that imply about a functional unit? 

Mountcastles original observation was that neurons sampled by a single electrode inserted perpendicular to the surface of the cortex have the same receptive fields and represented the same subclass of tactle receptors  in all layers of somatosensory cortex . This of course is not true. 

Visual cortex however saved the day. 

While you can patch together a quasi-columnar pattern in V1, if you try hard enough, it becomes harder and harder the further "in" you go. 

Personally, I believe that the belief in cortical columns is a consequence of the dominance of computational and experimental  studies of the visual system in mammals. (The turtle 'visual' cortex isn't organized this way) as well as our innate desire to find some regularly repeatable and defiable simplification. 

The assertion that V1-like cortical columns are the funamental computational unit of cerebral cortex has real difficulties if you look at the olfactory system. As I suggested earlier, in my view the likely "inventor" of the cerebral cortical style of computation. Forcing columns into olfactory cortex is extremely difficult. For sure there is a radial organization of cerebral cortex, that is clear from looking at the dendrites of pyramidal cells. -  but cortical columns with discrete boundaries, and containing neurons with similar receptive fields (and in .ointcastles original conception representing the same types or peripheral receptors or in other words coding the same information about the stimulous, is an excellent example of what I referred to last week as the tyranny of ideas in neuroscience and computational neuroscience. Which will continue in  the absence of a formal system of description and definitions based on the structure of the brain itself. 

Jim Bower 

Sent via BlackBerry by AT&T

-----Original Message-----
From: Garrison Cottrell <gary at cs.ucsd.edu>

Date: Tue, 29 Jul 2008 10:21:21 
To: <bower at uthscsa.edu>
Subject: Re: [Comp-neuro] Review announcement

Hi Jim (from a limo in oakland...!):

Would you mind pointing me to data suggesting that cortical columns  
don't exist? That (among many others you've made, of course!) is an  
interesting point!


On Jul 28, 2008, at 4:32 PM, jim bower wrote:

> Ross
> Great -  thanks for support from an unexpected source. ;-).
> While it is completely contrary to the intuition of most  
> experimentalists who are fond of their single neuron data, it is  
> quite likely that individual neurons in at least the mammalian brain  
> don't matter. Although, as I have mentioned before, one must be  
> aware that neurobiologists pick stimuli to maximize the presumption  
> that they do.
> On the other hand, in the extreme one could find oneself arguing a  
> la Lashley that there is no structure in cortex and everything is  
> completely distributed. This is also clearly not true. I have  
> suspected for some time that the need for communication (as  
> reflected very loosly in cortical oscillations) is what detemines  
> the size of the population of neurons across which different types  
> of computations are implemented but within which, individuals  
> actually don't matter much. These populations are probably analogous  
> to cortical areas.
> One other point however, is that abstract modelers tend to think of  
> cortex as one thing and so do many neurobiologists who like to think  
> in terms of things like the cortical microcircuit (or as in the case  
> recently of the blue brain project of a cortical column, which  
> actually doesn't exist - but anyway) in fact it is likely that  
> cerebral cortex is a sequence of things. Getting at what cortex does  
> will require that we understand where this sequence starts and ends.  
> And, no time here and on my poor blackberry to discuss this, but if  
> you are trying to sort these things out in the context of the visual  
> system, as most are, you may be starting at the wrong end. It seems  
> to me likely that it is the olfactory system that invented basic  
> cortical circuitry. And there is a rather interesting story emerging  
> there about just how random cortical activity and connectivity is.
> Jim bower
> Jim
> Sent via BlackBerry by AT&T
> -----Original Message-----
> From: "Ross Gayler" <r.gayler at gmail.com>
> Date: Tue, 29 Jul 2008 08:07:20
> To: <bower at uthscsa.edu>
> Cc: <comp-neuro at neuroinf.org>
> Subject: Re: [Comp-neuro] Review announcement
> I had avoided weighing into this discussion on the grounds that my  
> interest
> lies in abstract connectionist models that are quite remote from the
> physiological detail that has been the focus here.  However, I would  
> like to
> reinforce a comment that Jim Bower made.
>> the more sophisticated a coding system, the harder it is likely to  
>> be to
> distinguish signal from "noise".
> Vector Symbolic Architectures are a family of abstract connectionist  
> models
> that use very high-dimensional vectors to represent complex data  
> structures
> that might be required for cognition. (Here's a quick challenge  
> question for
> you. How might the brain represent "The astronomer believes that the  
> little
> star orbits the big star"?)  In VSA these data structures are  
> represented by
> the pattern of activity over, say, 10,000 neurons (abstracted as a  
> 10,000
> dimensional vector).  This is a thoroughly distributed  
> representation in
> which there is no necessary significance to the activity of any  
> individual
> neuron - it is only the overall pattern of activity that represents.
> Furthermore, and this is the point I wanted to make, individual  
> patterns of
> activity are generally indistinguishable from random vectors.  It is  
> only
> the relationship between representing vectors that carries useful
> information.  An external observer cannot decode the representing  
> vectors
> without knowing what other vectors are stored in the clean-up memory  
> of the
> system.  I take these representations to be a very clear  
> demonstration of
> Jim's point that in a sophisticated coding system it is harder to
> distinguish signal from noise.
> This paper (http://cogprints.org/3983/) provides some pointers into  
> the VSA
> literature.  The most extensive treatment of a specific  
> instantiation of VSA
> is Tony Plate's book
> (http://csli-publications.stanford.edu/site/1575864304.html)
> Ross Gayler
> -----Original Message-----
> From: comp-neuro-bounces at neuroinf.org
> [mailto:comp-neuro-bounces at neuroinf.org] On Behalf Of jim bower
> Sent: Saturday, 26 July 2008 7:31 AM
> To: rod rinkus; comp-neuro-bounces at neuroinf.org; minai_ali at yahoo.com
> Cc: comp-neuro at neuroinf.org
> Subject: [Possible Spam] Re: [Comp-neuro] Review announcement
> One last plea for caution. No matter how convenient "noise" may be for
> abstract models, one can argue I think pretty convincingly that life  
> itself
> differentiates itself from a-biological chemical evolution through  
> its use
> of extreme degrees of structure and context specific organization to  
> "beat"
> thermodynamics.
> As such anything that smells gaussian, disordered, something you can  
> average
> over, or something that is completely generic rather than highly  
> specific to
> the circumstances at hand (behavioral or computational) should raise
> concern.
> The long history of biology is that the closer you look, the more  
> structure,
> not less structure you see.  And everytime I have heard it suggested
> otherwise, closer inspection has suggested that we simply weren't  
> giving
> biology enough credit.
> One quick example, a number of years ago, in fact during the first  
> summer of
> the first computational neuroscience course in woods hole, a well know
> investigator of aplesia neurons gave a general MBL talk in which he  
> sought
> to identify every conductance in the neuron of interest. In addition  
> to the
> big "important" ones he found several small ones, whose presence he  
> chalked
> up to sloppyness in protein transcription.
> Given my predispositions, I suggested that he change the temperature  
> of the
> bath as aplesia live in tide pools. The next summer he gave a talk  
> on the
> remarkable resiliance of neuronal function under different ambient
> temperatures confered by the complex conductances present in the cell
> membrane.
> While convenient, many of these "noise" mechanisms strike me as  
> being simply
> not sophisticated enough. And I will point out now for the last  
> time, that
> the more sophisticated a coding system, the harder it is likely to  
> be to
> distinguish signal from "noise".
> Jim Bower
> Sent via BlackBerry by AT&T
> -----Original Message-----
> From: "rod rinkus" <rinkus at comcast.net>
> Date: Thu, 24 Jul 2008 00:33:59
> To: <minai_ali at yahoo.com>
> Cc: <comp-neuro at neuroinf.org>
> Subject: RE: [Comp-neuro] Review announcement
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Gary Cottrell 858-534-6640 FAX: 858-534-7029
Computer Science and Engineering 0404
CSE Building, Room 4130
University of California San  
Diego                                      -
9500 Gilman Drive # 0404
La Jolla, Ca. 92093-0404

"Only connect!" -E.M. Forster

"I am awaiting the day when people remember the fact that discovery  
does not work by deciding what you want and then discovering it."
-David Mermin

Email: gary at ucsd.edu
Home page: http://www-cse.ucsd.edu/~gary/

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