[Comp-neuro] Review announcement

[Etienne B. Roesch]

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
>
> Sent via BlackBerry by AT&T

-----
Etienne Roesch
Department of Computing
Imperial College
London SW7 2AZ
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