[Comp-neuro] Review announcement

Ali Minai minai_ali at yahoo.com
Tue Jul 22 19:41:48 CEST 2008


Noise does this and much, much more. It can inject variety, break symmetry, generate novelty, provide energy, facilitate search, carry signal, and do many other things. Indeed, the only time noise is really a problem is when one is trying to do achieve a pre-determined goal (e.g., following a pre-computed trajectory). Since natural systems - notably the nervous system - rarely (if ever) try to do this, they thrive on noise. Perhaps we should give the phenomenon a less pejorative name. "Noise" signals such a linear mindset:-).

Ali


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Ali A. Minai
Associate Professor
Associate Head for Electrical Engineering
Department of Electrical & Computer Engineering
University of Cincinnati
Cincinnati, OH 45221-0030

Phone: (513) 556-4783
Fax: (513) 556-7326
Email: aminai at ececs.uc.edu
          minai_ali at yahoo.com

WWW: http://www.ececs.uc.edu/~aminai/

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--- On Tue, 7/22/08, Etienne B. Roesch <Etienne.Roesch at pse.unige.ch> wrote:
From: Etienne B. Roesch <Etienne.Roesch at pse.unige.ch>
Subject: Re: [Comp-neuro] Review announcement
To: comp-neuro at neuroinf.org
Cc: comp-neuro-bounces at neuroinf.org
Date: Tuesday, July 22, 2008, 11:28 AM


 
Yeah, I am loving the discussion! More, more!
As an early postdoc, I still have in my working memory the classes I went through in grad school, and I remember this connectionist lecturer arguing that noise was actually a good thing for classifier-like systems (and by extension neural nets, and by extension plausible neural nets -- which are not classifiers stricto senso I agree) in that it allows an easier discrimination of the input in a probabilistic context. Given that redundancy of information/signal plays a big part in how the brain does the job, wouldn't noise be a clever mechanism to discriminate close-to-threshold stimuli? What do you think?
Best regards,

Le 22 juil. 08 à 17:17, jim bower a écrit :
I am actually in a remote part of brazil at the moment, so limited to typing on my blackberry.
Impressive typing skills, I have to admit. ;-)

However, yes I was curious if a discussion could be induced. That was originally what this mailing list was set up for, I know, because I started it. ;-).  However things have become a bit complacent so I figured what the heck. 
Again limited in my ability to respond but a couple of things. I think as computational neurobiologists or scientists in general, we need to be aware of the extent which what we can measure (oscillations, synchronous spikes, etc) limits the way we think about how things work. Many many years ago now when cortical oscillations became more generally interesting to people once found in visual cortex we suggested based on our realistic cortical models that they were an epiphenomina more (loosly) reflecting and underlying mechanism for coordinating communication and processing between regions than carriers of any information themselves. I continue to believe or set my primary assumption that until proven otherwise, every spike is significant for something and worse yet so is the lack of a spike. (Certainly in digital coding 0s are as important as 1s. 
Yes "serious scientists" prefer more constrained and defined discussions than this. -  but we can easily get lost "drinking our own whisky". As a famous computational math-bio guy is fond of saying. 
;-)
Truth is all these issues really remain wide open. 
But and the big but, no evidence that nature is sloppy or unsophisticated. 
One last point, the assumption that in fact nature is very sophisticated and that the structure of the brain deeply reflects a complex, sophisticated function pushes in the direction of first building models reflecting that structure, even if you are still clueless about function. 
I am in brazil teaching at the latin american school for computational neuroscience, where realistic modeling lives on. ;-)
Best to all 
Jim
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 -----Etienne RoeschDepartment of ComputingImperial CollegeLondon SW7 2AZ_______________________________________________
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