Connectionists: How the brain works

[Juyang Weng]

Tsvi, I understand your point, but there are too many model designers
who are like blind men who touch the elephant at a reachable skin patch 
only.
They do not have the culture to motivate them to move to elephant's 
other body parts.

-John

On 5/23/14 10:37 AM, Tsvi Achler wrote:
> I think it is also interesting to ask the opposite question: what type
> of models would be especially difficult to introduce to the community?
> Here is my short list:
> 1. Models that go against years of dogma (eg arguing against the idea
> that neural networks learn through a gradient descent mechanism)
> 2. Models reinterpreting existing data in a different way but overall
> getting similar results.
> -Tsvi
>
>
> On Thu, May 22, 2014 at 6:01 PM, Brad Wyble <bwyble at gmail.com> wrote:
>> I concur with Dan. I'd caution anyone against the idea that a good theory of
>> brain function should also ascribe to standards of mathematical aesthetics
>> (i.e. that it can be reduced to a single function). Nature is functionally
>> elegant, but that does not also mean that it can be reduced to an elegant
>> mathematical formalism.
>>
>> That said, I really like the question posed by Janet, which is to wonder at
>> when the research community at large should start to take a new model
>> seriously. I don't think that there is a clear answer to this question  but
>> there do seem to be two major factors:  one is the degree to which the model
>> compresses data into a simpler form (i.e. how good is the theory), and the
>> other is the degree to which the model fills a perceived explanatory void in
>> the field.  Models that are rapidly adopted hit both of these marks.
>>
>> -Brad
>>
>>
>>
>> On Thu, May 22, 2014 at 7:45 PM, Levine, Daniel S <levine at uta.edu> wrote:
>>> I would disagree about the single equation.  The brain needs to do a lot
>>> of different things to deal with the cognitive requirements of a changing
>>> and complex world, so that different functions (sensory pattern processing,
>>> motor control, etc.) may call for different structures and therefore
>>> different equations.  Models of the brain become most useful when they can
>>> explain cognitive and behavioral functions that we take for granted in
>>> day-to-day life.
>>>
>>> -----Original Message-----
>>> From: Connectionists
>>> [mailto:connectionists-bounces at mailman.srv.cs.cmu.edu] On Behalf Of Janet
>>> Wiles
>>> Sent: Thursday, May 22, 2014 6:01 PM
>>> To: Yu Shan
>>> Cc: connectionists at mailman.srv.cs.cmu.edu
>>> Subject: Re: Connectionists: How the brain works
>>>
>>> When does a model escape from a research lab? Or in other words, when do
>>> researchers beyond the in-group investigate, test, or extend a model?
>>>
>>> I have asked many colleagues this question over the years. Well-written
>>> papers help, open source code helps, tutorials help. But the most critical
>>> feature seems to be that it can be communicated in a single equation. Think
>>> about backprop, reinforcement learning, Bayes theorem.
>>>
>>> Janet Wiles
>>> Professor of  Complex and Intelligent Systems, School of Information
>>> Technology and Electrical Engineering The University of Queensland
>>>
>>>
>>> -----Original Message-----
>>> From: Connectionists
>>> [mailto:connectionists-bounces at mailman.srv.cs.cmu.edu] On Behalf Of Yu Shan
>>> Sent: Friday, 23 May 2014 7:37 AM
>>> To: Juyang Weng
>>> Cc: connectionists at mailman.srv.cs.cmu.edu
>>> Subject: Re: Connectionists: How the brain works
>>>
>>>> Suppose that one gave all in this connectionists list a largely
>>>> correct model about how the brain works, few on this list would be
>>>> able to understand it let alone agree with it!
>>>>
>>> Let's look at a recent example. Nikolic proposed his theory
>>> (http://www.danko-nikolic.com/practopoiesis/) about how the brain works a
>>> few weeks ago to the Connectionists. Upon finishing reading this paper, I
>>> was quite exited. The theory is elegantly simple and yet has great
>>> explanatory power. It is also consistent with what we know about evolution
>>> as well as the brain's organization and development.
>>> Of course, we don't know yet if it is a "largely correct model about how
>>> the brain works". But, to my opinion, it has a great potential.
>>> Actually I am thinking how to implement those ideas in my own future
>>> research.
>>>
>>> However, the author's efforts of introducing this work to the
>>> Connectionists received little attention. Connectionists reach 5000+ people,
>>> who are probably the most interested and capable audience for such a topic.
>>> This makes the silence particularly intriguing. Of course, one possible
>>> reason is that lots of people here already studied this theory and deemed it
>>> irrelevant.
>>>
>>> But a more likely reason, I think, is most people did not give it much
>>> thought. If that is the case, it raises an interesting question: what is the
>>> barrier that a theory of how the brain works need to overcome in order to be
>>> treated seriously? In other words, what do we really want to know?
>>>
>>> Shan Yu, Ph.D
>>> Brainnetome Center and National Laboratory of Pattern Recognition
>>> Institute of Automation Chinese Academy of Sciences Beijing 100190, P. R.
>>> China http://www.brainnetome.org/en/shanyu
>>>
>>>
>>
>>
>> --
>> Brad Wyble
>> Assistant Professor
>> Psychology Department
>> Penn State University
>>
>> http://wyblelab.com

-- 
--
Juyang (John) Weng, Professor
Department of Computer Science and Engineering
MSU Cognitive Science Program and MSU Neuroscience Program
428 S Shaw Ln Rm 3115
Michigan State University
East Lansing, MI 48824 USA
Tel: 517-353-4388
Fax: 517-432-1061
Email: weng at cse.msu.edu
URL: http://www.cse.msu.edu/~weng/
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