[Comp-neuro] Review announcement
Etienne B. Roesch
Etienne.Roesch at pse.unige.ch
Tue Jul 22 17:28:04 CEST 2008
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
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
> 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
> Sent via BlackBerry by AT&T
Department of Computing
London SW7 2AZ
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