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

James Schwaber schwaber at mail.dbi.tju.edu
Fri Aug 22 22:35:30 CEST 2008


Your post brought to mind what my neuroimaging colleagues have told me. 
The active brain regions shift with practice, repeats of any kind. And 
what is active also depends on other 'demands' on the brain or brain 
injury. They describe their observations as consistent with the brain 
NOT having specific, assigned functional localization, but rather 
providing a large set of essentially specialized computational 
capabilities localized in various architectures or regions. Then when a 
functional requirement is placed against this the best available 
capabilities for the requirement are recruited on the fly - and these 
will change depending on what other requirements are in play. And the 
requirement itself is not stable but changes with practice.

Axel HUTT wrote:
> Walter,
>   
>> One thing that has always struck me about the difference between  
>> biology and physics, is that in physics department seminars, the  
>> resident Dons of the field  would stand up and walk out within several  
>> milliseconds of a speaker making a statement violating some well  
>> established physical principle (conservation law or something), while  
>> in biology, one finds oneself listening intently through most seminars  
>> to determine whether the story teller does or doesn't know what they  
>> are doing.  There are little signs (smiling gels, action potentials  
>> that don't overshoot, etc), but really one is often at sea.
>>
>> So, there is clearly something different about the freedom to tell  
>> stories in both disciplines.
>>
>> In biology, when you work on a new paper, the first thing you do is  
>> organize the figures (the story). In math you organize the equations.   
>> In biology the traces you pick for your figures are the best ones you  
>> can find (and photoshop can help) whereas physics and mathematics look  
>> for general solutions.
>>
>>     
> as a physicist, may be I am allowed to say that most people working
> seriously in classical topics of physics (standard topics taught at
> university like quantum theory, relativity theory, solid state physics,
> at the end everything not related to chemistry or biology) are
> religious fundamentalists in the religion physics as a religion (and we
> are back at the tyranny of ideas mentioned previously in the
> discussion). However physicists with interest also in other fields, 
> such like biology, chemistry, computer science or human sciences
> are more relaxed and give other people more freedom in their ideas.
> Since this is the case for most neuroscientists, I would expect (or
> hope) that there are only few physicists like the ones you described. 
>
> Similar to your example, recently I (physicist by education) had a very
> interesting discussion with a colleague (cognitive neuroscientist  by
> education) about subtle differences in our underlying research
> approaches in neuroscience. Either of us aims to model mathematically 
> neural dynamics but:
> she takes a close look of the system under study (e.g. the basal
> ganglia), aims to grasp its major properties (e.g. spiking dynamics
> under different experimental conditions, axonal connectivity
> structures, neuron types etc), takes a model, puts in all knowledge
> (e.g. parameter ranges) as far as possible and studies the model 
> under these constraints to match the model results to the knowledge 
> obtained previously. IMHO a great approach.
> In contrast, my research considers rather general models, which imply
> all possible parameters and connections. The outcome of my research are
> conditions on the parameters, connectivities, neuron types etc. under
> which one finds a specific behavior. The specific behavior is taken 
> from the literature.Hence I could argue that my approach is more general
> and might be applied to many different brain areas in different species
> in different experimental setups. However, I guess her results are 
> a bit closer to the real neural behavior.
>
> Although the approach of my colleague and mine essentially may aim to
> describe the same experimental phenomenon, we choose rather distinct 
> approaches. At the end of the discussion, we agreed that our own
> specific interests decides on the approach.
>
>
>
>
>
>   
>> This is my problem with all for one and one for all -- somewhere,  
>> somehow, someway, neuroscience has to find a mechanism to better  
>> discriminate between efforts -- let alone force the development of  
>> some set of common definitions with which and on which to tell stories  
>> (and judge stories).  Otherwise, they are just stories and subject to  
>> all the politics, trends, fads, and social pressures that apply to all  
>> story tellers.  So a core part of this debate, I think, is how we  
>> advance the 'art' of storytelling in biology.
>>     
>
> in my experience a good way to solve the problems is the choice of a 
> specific mutual question, which is studied by different groups.
> For instance, several years ago I was very interested in the origin
> and detection of cognitive components in event-related potentials (EEG
> measured during cognitive experimental paradigms). I have observed
> many different approaches in the literature for their classification:
> the neuropsychologists classify single time series them by their
> latency, height, duration and sometimes their spatial location on the
> scalp. Computer scientists have detected them by multivariate 
> data analysis tools (e.g. developed by D.Lehmann and P.D.
> Pascual-Marquis). I have taaken their results into account and argued
> that the ERP-component may be the result of highly synchronized 
> underlying neural activity and thus modeled the multivariate
> ERP-components by a set of ordinary differential equations. It turned
> out that the ERP-component P30 in middle-latent auditory evoked 
> potentials exhibits a unique dynamical behavior (equivalent topology)
> in three different subjects. Further one conclusion was that the 
> brain exhibits a kind of chaotic itinerancy suspected by many authors,
> e.g. as Tsuda or recently Gros. 
> I am sure further work on the origin of ERPs is difficult and highly
> interdisciplinary but probably fruitful to gain specific insights 
> to cognitive processes. All groups irrespective of their education 
> may contribute to the understanding as far as one focusses to the 
> same question.
>
> Have a nice weekend
>
>
> Axel
>
>
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>   
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