[Comp-neuro] Hilbert's questions
randy.oreilly at colorado.edu
Tue Aug 12 19:19:21 CEST 2008
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
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..
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
> 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.
> 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.
>> William W. Lytton, MD
>> Professor of Physiology, Pharmacology, Biomedical Engineering,
>> 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
> Main Number: 210- 567-8100
> Fax: 210 567-8152
> Mobile: 210-382-0553
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