[Comp-neuro] Re: Attractors, variability and noise

Andrew Coward andrew.coward at anu.edu.au
Wed Aug 13 19:32:27 CEST 2008

What we can or cannot understand is fundamental to both science and  
understanding complex commercial systems.

For many years I was engaged in the design of very complex electronic  
systems. To give some idea of the complexity, it took the efforts of  
several  thousand engineers working for three or four years to design  
the orignial system (a telecommunications switch). Practical  
understanding of the system existed, in the sense that it was  
possible to diagnose and repair faults, add and modify features  
without undesirable side effects on other features etc. This  
understanding depended on the organization of the design into a  
hierarchy of descriptions on many different levels of description  
(functions could be described in terms of transistors, logic gates,  
standard cells within integrated circuits, integrated circuits,  
printed circuit boards, subsystems, and an analogous hierarchy for  
software).  A description of the complete system in terms of  
individual transistors would have an incomprehensible level of  
detail, but higher level descriptions are approximate to some degree.  
However, there are well understood routes to go from a more  
approximate higher level description to a more precise detailed  
description (for subsets of the phenomenon of interest so that  
comprehension is possible). Shifting between different levels of  
description makes it possible to achieve adequate levels of  

The physical sciences follow a very similar approach {Coward and Sun  
2007]. There are no attempts to understand the movement of continents  
directly in terms of quantum mechanics. Rather, there are hierarchies  
of description (continental drift, geology, crystallography, and if  
necessary atomic theory and even quantum mechanics). The higher  
levels are more approximate, but if higher precision were essential  
in some domain, a more exact, detailed description is possible.  It  
is relevant that even research at the borders of quantum mechanics  
starts with "purely classical language that ignores quantum  
probabilities, wave functions and so forth ..... subsequently  
overlaying quantum concepts upon a classical framework" [Greene,  
1999, page 380].

Understanding the brain will require an analogous hierarchy of  
descriptions. In other words, we have to find good approximations at  
several intermediate levels that can be mapped both into psychology  
and into more detailed neuron type models. One attempt at such a  
multilevel theory is [Coward 2005]. The danger of massive neuron  
modelling efforts is that we can create a system which may have  
properties similar to brains but do not help with genuine  
intellectual understanding.

Andrew Coward

Coward, L. A. and Sun, R. (2007). Hierarchical Approaches to  
Understanding Consciousness. Neural Networks 20(9), 947 - 954.

Greene, G. (1999). The Elegant Universe. Norton.

Coward, L. A. (2005). A System Architecture Approach to the Brain:  
from Neurons to Consciousness. New York: Nova Science Publishers.

On 13-Aug-08, at 8:16 AM, james bower wrote:

> Obviously, the question of what we can and can't understand as  
> individuals, or groups of individuals is somewhere near the core of  
> this discussion.  Many would claim, as Brad does here, that of  
> necessity our descriptions of things (brains) can not exceed the  
> ability of humans to communicate what they understand.
> Several years ago, I was approached by a senior VP at Dessault (the  
> French company that makes the Mirage Jet Fighter), who was  
> interested in the GENESIS project.  The reason she was interested  
> was because her company was already facing a "sum is greater than  
> the parts" problem with the software system they use to design  
> their jets.  She told me that there was no one individual who  
> understood the entire software system, and therefore, no one who  
> could assure that there wasn't some collective flaw resulting from  
> the interaction of the multiple software modules contributed by  
> different teams.  I told her that I now understand why test pilots  
> are paid so much money.
> The point is this, high tech manufacturing already operates in the  
> domain where no one individual, or even group of individuals  
> understands the totality of the software systems they have built to  
> make airplanes, chips, etc.  Yet these software systems are at the  
> very heart of ever more sophisticated machines (although certainly  
> vastly less sophisticated than the brain).  In Physics, it has been  
> said that Gottried Leibniz (1646-1716) was the last human who knew  
> everything.  So why in neuroscience is "communicability" a factor  
> used to argue for abstract models, or levels of description that  
> ignore neurons.   What happens if using GENESIS or NEURON or both  
> with middle ware like NeuroConstruct, we collectively contribute to  
> building a virtual representation of the real brain - that any one  
> of us can use to poke around in something we find interesting.   
> Perhaps (although as I have said I doubt it), some Newton of the  
> present or future might be able to come up with more general  
> principles that apply to the structure or function of brain regions  
> - or brains themselves -- but to start this process with a mandate  
> for general principles to begin with - makes no sense to me.
> One other point -- the philosopher Daniel Dennett suggested when  
> considering the view of consciousness advocated by Koch and Crick,  
> that there was, in fact, a hidden duelism in their approach.  I  
> would say that duelism in fact isn't very hidden at all in most  
> theories of cognitive neuroscience and must be suspected in any  
> approach that assumes that the physical stuff of the brain doesn't  
> matter, or can be ignored.
> Jim Bower
> On Aug 13, 2008, at 9:05 AM, Brad Wyble wrote:
>> On Tue, Aug 12, 2008 at 12:55 PM, Ali Minai <minai_ali at yahoo.com>  
>> wrote:
>> When we go looking for the "meaning" of attractors, or - even more  
>> problematically - identity of meaning across attractors, aren't we  
>> back to the homunculus or dualism? Shouldn't all "meaning"  
>> ultimately be grounded in physiological response (sensor activity,  
>> behavior, autonomic activity, biochemical activity, etc.) and all  
>> else regarded as post-hoc constructs that we use for descriptive  
>> convenience? Or do people think that "appleness" exists  
>> independently of "applehood" - if you know what I mean? :-).
>> Ali
>> Behaviorism reborn?
>> Remember that we are trying to describe these systems in terms  
>> that we as humans can understand.  So that 'descriptive  
>> convenience' is really what science is looking for.    We are not  
>> cognitively equipped to understand the brain in terms of input/ 
>> output relationships, or big tables of neurophysiological data.    
>> The Tyranny of ideas exists precisely because we think with ideas.
>> I suspect that an ultimate understanding of the brain is going to  
>> consist of a hierarchy of ideas about how individual subsystems  
>> work because that's how scientists communicate across levels of  
>> description.
>> Models are important both for shaping those ideas and anchoring  
>> them formally, but ultimately the scientific process depends on  
>> the communication of theories from one mind to another.
>>  -Brad
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> ==================================
> Dr. James M. Bower Ph.D.
> Professor of Computational Neuroscience
> Research Imaging Center
> University of Texas Health Science Center -
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