[Comp-neuro] Hilbert's questions

james bower bower at uthscsa.edu
Tue Aug 12 19:44:57 CEST 2008


Wonderful what can be done with selective attention to detail,  
overarching principles, and preconceived notions.

"the hippocampus is essentially a solved problem" speaks for itself.

so where the 'laws' of planetary motion, for about 1700 years.

There is no doubt, that course (what it does) to fine (how it does it)  
science is very efficient -- problem is, the course tends to impose on  
the fine.

Aspects of cognitive neuroscience may be the best examples, perhaps in  
the history of science, of the danger of overarching ideas, in the  
presence of non-structural models.


Jim Bower



On Aug 12, 2008, at 12:19 PM, Randall O'Reilly wrote:

> There has been a remarkable absence of consideration for the  
> functional level of the brain: i.e., the huge field of cognitive  
> neuroscience, in this discussion and in the field of computational  
> neuroscience in general.  There is no way you are going to figure  
> out something as complex as the brain using a purely bottom-up  
> strategy.  If you look at the work in computational *cognitive*  
> neuroscience, where the behavioral level of analysis is taken  
> seriously, the picture is much less bleak than the assessments  
> provided here.  There are many models that relate the biological  
> properties of neurons and brain areas to cognitive functions  
> associated with those brain areas, and do a very good job of  
> capturing a large proportion of the variance of both levels.
>
> For example, the hippocampus is essentially a "solved problem" in  
> terms of the general framework for how its biological properties  
> enable its well established role in memory.  Recent work by  
> Tonagawa's group and several others have verified the predictions  
> from a number of generally convergent computational models,  
> regarding the specific roles of areas CA3, DG, CA1, etc.  By  
> capturing the most global, high-level properties of the system  
> first, across both behavior and biology, these models provide a  
> framework within which more detailed questions and models can be  
> developed.
>
> In almost every domain, a hierarchical coarse-to-fine strategy is  
> the most efficient way to understand something.  First you figure  
> out the most basic properties of the system, and then you fill in  
> the details.  Some would argue that this is not possible in the  
> brain, but I think the existing work already refutes that argument.   
> People who remain fixated on individual neurons and synapses may not  
> appreciate this, and regard the system as a huge unsolved puzzle,  
> but this is just because they are so zoomed in on the details that  
> they are missing the big picture.  The big picture is filling in  
> quite rapidly.  There are similarly successful models for prefrontal  
> cortex, basal ganglia, and sensory neocortex, etc.
>
> Taken together these models strongly suggest that, to understand how  
> the system actually functions, you don't need to simulate every last  
> detail of a neuron, nor its connectivity.  Certain details are  
> rather important (e.g., inhibition in the hippocampus is critical  
> for establishing a sparse distributed representation, which  
> minimizes interference and enables episodic memory, place cells,  
> etc), but in general a fairly simple "integrate and fire" model of  
> the neuron is sufficient to capture a large portion of the  
> functional variance of what the brain actually does.
>
> Of course, I can't "prove" any of these assertions to the  
> satisfaction of all skeptics, and I'm rather an optimist overall,  
> but I think this field is definitely missing out on the big  
> picture.  Certainly there is a huge amount still unknown, but if you  
> squint your eyes just right, I think the picture is filling in quite  
> nicely..
>
> - Randy
>
> On Aug 12, 2008, at 9:47 AM, james bower wrote:
>
>> I would say for sure that individual neurons are communicating --  
>> just that communication is not dependent on any individual neuron  
>> (in mammals), nor can one understand what they are communicating  
>> independent of the population - a nice enigma.
>>
>> With respect to wiring - 'we' believe that nervous systems  
>> represent what they know in their wiring -- 'we' also believe that  
>> the modification of wiring takes place at the level of individual  
>> neurons (and even synapses).  So for didactic purposes:
>>
>>
>> 1) does the function of an individual brain depend on the detailed  
>> wiring of that brain (likely)
>> 2) can we therefore understand how brains function in general, by  
>> working on multiple individuals let alone multiple species
>> 3) in other words, what level of wiring specification do we need?
>>
>> and do we have the patience?
>>
>> Speaking of grubby, now probably mostly lost in history, the first  
>> ''realistic network" modeling effort I ever saw presented was of  
>> the sea slug tritonia, by an engineer (MIT) turned serious  
>> experimentalist, Peter Getting - Neuroscience 1981, I think.
>>
>> Peter Getting had originally taken a faculty position at Stanford,  
>> and, on the assumption that wiring was everything, set about trying  
>> to understand the connections between the few (I think 6) types of  
>> motoneurons that control the swimming (if you want to call it that)  
>> of Tritonia.  Problem was that after his 6 year junior faculty  
>> appointment, he had only completed characterizing 3 of the 6 (as I  
>> remember) sets of connections.  This was not deemed reasonable  
>> progress, he was denied tenure and ended up taking a position in  
>> Iowa, where he steadfastly continued to complete the circuitry.  He  
>> did, and presented the results at the neuroscience meeting -- and I  
>> remember being astounded.  Peter would have actually been a major  
>> part of the first course in woods hole, had he not had a massive  
>> stroke while running (which he did many miles per day), ending up  
>> incapacitated.
>>
>> However, for sure, we now know from invertebrate systems that the  
>> individual connections of individual neurons within an individual  
>> matter --
>>
>> So -- if one believes in the importance of wiring -- shouldn't we  
>> all be working in invertebrate preparations?
>>
>> Not an entirely rhetorical question -- it is clear from the history  
>> of science in general and physics in particular that picking the  
>> right problem is a key to progress.  Thus, Newton 'discovered' the  
>> inverse square law by examining the (nearly) circular orbit of the  
>> moon around the earth, for which he also had much better distance  
>> data, rather than looking at the sexier elliptical movements of the  
>> planets around the sun.
>>
>> Maybe we should give up on cerebral cortex for several hundred  
>> years and all study tritonia instead.
>>
>>
>> Jim
>>
>>
>>
>> On Aug 12, 2008, at 10:08 AM, Bill Lytton wrote:
>>
>>>
>>>> grandest level it seems to me there is only one question: "What  
>>>> is each neuron communicating,
>>>> and how is the message encoded."
>>>
>>> I thought it was noted in recent discourse that the answer is  
>>> nothing and not? -- ie
>>> populations are needed.
>>>
>>>> That said, it could be an interesting exercise to come up with a  
>>>> list of the current Top Ten
>>>> Topics attracting the attention of
>>>
>>> Personally I would echo Martin and Douglas in their many papers  
>>> (from which I recommend Neuron
>>> 2007 56:226-238 for its broad scope) that we need to know how it  
>>> is wired where 'it' may be
>>> neocortex, thalamus, olfactory cortex or even bug whateveritis-ex.
>>>
>>> Framed computationally this could involve wiring exploration  
>>> (which we are doing lately) or
>>> development algorithms or new Hebb variants.  Of course, without  
>>> the accompanying
>>> physiological/anatomical exploration this will be meaningless.
>>>
>>> Admittedly this is a rather low-level question without the grand  
>>> sweep of a Hilbert q. but
>>> then biology is often grubby (even literally) rather than ethereal.
>>>
>>> Bill
>>>
>>> -- 
>>> William W. Lytton, MD
>>> Professor of Physiology, Pharmacology, Biomedical Engineering,  
>>> Neurology
>>> State University of NY, Downstate Medical Center, Brooklyn, NY
>>> billl at neurosim.downstate.edu http://it.neurosim.downstate.edu/~billl
>>> ________________________________________________________________
>>
>>
>>
>>
>> ==================================
>>
>> Dr. James M. Bower Ph.D.
>>
>> Professor of Computational Neuroscience
>>
>> Research Imaging Center
>> University of Texas Health Science Center -
>> -  San Antonio
>> 8403 Floyd Curl Drive
>> San Antonio Texas  78284-6240
>>
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==================================

Dr. James M. Bower Ph.D.

Professor of Computational Neuroscience

Research Imaging Center
University of Texas Health Science Center -
-  San Antonio
8403 Floyd Curl Drive
San Antonio Texas  78284-6240

Main Number:  210- 567-8100
Fax: 210 567-8152
Mobile:  210-382-0553

CONFIDENTIAL NOTICE:
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