Connectionists: how the brain works?

[james bower]

May not apply to the brain for a large set of reasons.


On Mar 19, 2014, at 8:29 PM, Brian J Mingus <brian.mingus at Colorado.EDU> wrote:

> The second episode of the new Cosmos provides an excellent example of how evolution gets stuck in local minima that it can't climb out of.
> 
> - Brian
> 
> On Mar 19, 2014 6:00 PM, "james bower" <bower at uthscsa.edu> wrote:
> ah, someone once said (perhaps it was me) that arrogance and ignorance are a particularly dangerous combination in a scientist - not that there are not am absence of examples.
> 
> In fact, Michael and I have both been accused of the former, I happen to know, but not generally of the later.
> 
> :-)
> 
> However, there is also something to be said for honesty and I am afraid to say that the opinion you express is more commonly held than I would like to think, certainly, it doesn’t sit too far below the surface of many of the so called neuro-morphic models you see floating around, and I can tell you because I was there, that it was pretty apparent in the early days of the Neural Networks business as well.   Perhaps worth noting at the same time that some ‘notables’ in that effort, John Hopfield for example, didn’t share that point of view, neither as far as I can tell did Carver Mead or Richard Feynman for that matter.  Collectively the course they taught at Caltech  in the early 80s on how the heck to figure out the brain was responsible for Caltech deciding to start the first computational biology graduate program (the CNS program).  Those guys were smart enough or knew enough, or both, not to dismiss structures evolved over millions of years, under harsh and unforgiving circumstances that did remarkable things.
> 
> My advice is that nobody else should either.
> 
> Jim Bower
>  
> 
> 
> On Mar 19, 2014, at 6:13 PM, Brian J Mingus <brian.mingus at Colorado.EDU> wrote:
> 
>> The hippocampus and cerebellum might be necessary variance. Data from strokes and lesion studies suggest that they are not fully necessary, however. Also, they might be local minima in the design space, and we might be able to replace them with something simpler before we figure out exactly how they work, by first identifying what it is that they do and then inventing something better.
>> 
>> Brian
>> 
>> 
>> On Wed, Mar 19, 2014 at 2:27 PM, Michael Arbib <arbib at usc.edu> wrote:
>> Ignoring the gross differences in circuitry between hippocampus and cerebellum, etc., is not erring on the side of simplicity, it is erring, period. Have you actually looked at a Cajal/Sxentagothai-style drawing of their circuitry?
>> 
>> 
>> At 01:07 PM 3/19/2014, Brian J Mingus wrote:
>>> Hi Jim,
>>> 
>>> Focusing too much on the details is risky in and of itself. Optimal compression requires a balance, and we can't compute what that balance is (all models are wrong). One thing we can say for sure is that we should err on the side of simplicity, and adding detail to theories before simpler explanations have failed is not Ockham's heuristic. That said it's still in the space of a Big Data fuzzy science approach, where we throw as much data from as many levels of analysis as we can come up with into a big pot and then construct a theory. The thing to keep in mind is that when we start pruning this model most of the details are going to disappear, because almost all of them are irrelevant. Indeed, the size of the description that includes all the details is almost infinite, whereas the length of the description that explains almost all the variance is extremely short, especially in comparison. This is why Ockham's razor is a good heuristic. It helps prevent us from wasting time on unnecessary details by suggesting that we only inquire as to the details once our existing simpler theory has failed to work.
>>> 
>>> > On 3/14/14 3:40 PM, Michael Arbib wrote:
>>> >> At 11:17 AM 3/14/2014, Juyang Weng wrote:
>>> >>> The brain uses a single architecture to do all brain functions we are aware of!  It uses the same architecture to do vision, audition, motor, reasoning, decision making, motivation (including pain avoidance and pleasure seeking, novelty seeking, higher emotion, etc.).
>>> >>
>>> >> Gosh -- and I thought cerebral cortex, hippocampus and cerebellum were very different from each other.
>> 
> 

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