[Fwd: Re: [Comp-neuro] Noise, redundancy and biophysics]

jim bower reinoud at castafiore.cde.ua.ac.be
Thu Jul 24 11:22:50 CEST 2008


---------------------------- Original Message ----------------------------
Subject: Re: [Comp-neuro] Noise, redundancy and biophysics
From:    "jim bower" <bower at uthscsa.edu>
Date:    Thu, July 24, 2008 1:00 am
To:      vibert at u707.jussieu.fr
Cc:      "Sacha Nelson" <nelson at brandeis.edu>
         comp-neuro at neuroinf.org
--------------------------------------------------------------------------

Hi there.

Yes I did get your comment previously thank you.

As my postings make clear. I am very susipious of the idea of noise in the
nervous system. Are your results dependent on "noise" or on some forn of
continuous input. And how do you define noise?

Jim
Sent via BlackBerry by AT&T

-----Original Message-----
From: Jean-François Vibert <vibert at u707.jussieu.fr>

Date: Wed, 23 Jul 2008 22:24:19
To: <bower at uthscsa.edu>
Cc: Sacha Nelson<nelson at brandeis.edu>; <comp-neuro at neuroinf.org>
Subject: Re: [Comp-neuro] Noise, redundancy and biophysics


Jim,

I don't know why, but U receive the mails from the comp_neuro list, but I
cannot answer. I wrote an answer 2 days ago, but it was refused by the
list (not allowed to write on the list). May be you received it.

her is acopy.

Other two cents, since we have worked a long time ago, on effect of noise
on transfer function of neurons (Segundo, J., Stiber, M., Vibert, J.-F., &
Hanneton, S. (1995). Periodically modulated inhibition and its
post-synaptic consequences. II. Influence of pre-synaptic slope, depth,
range, noise and of post-synaptic natural discharges. Neurosci., 68(3),
693- 719.),  and large networks (J. Pham, K. Pakdaman, and J.-F. Vibert,
Noise-induced coherent oscillations in randomly connected neural networks.
Phys. Rev. E 58, 3610 - 3622 (1998) and written a review on this subject :
Segundo, J., Vibert, J.-F., Pakdaman, K., Stiber, M., & Diez Martìnez, O.
(1994). Noise and the neurosciences: A long history, a recent revival and
some theory. In K. Pribram (Ed.), Origins: Brain and self organization.
Mahwah, NJ: Erlbaum.

More recently, we have shown that the respiratory rhythm generation is
safe thanks to reticular formation induced noise on ecistatory networks
that can be secured by pacemaker neuron if noise is too low (Kosmidis EK,
Pierrefiche O, Vibert JF. Respiratory-like rhythmic activity can be
produced by an excitatory network of non-pacemaker neuron models.
J Neurophysiol. 2004 Aug;92(2):686-99.

Regards
JF Vibert


Le Mer 23 juillet 2008 16:27, jim bower a écrit :
> Sacha,
>
> I agree thus it would be nice to agree on a common definition - which has
> been very hard to do.
>
> A couple of questions:
>
> How can we possibly know what is "relevant" to a particular neuron?  We
> can decide based on our experimental protocohls, but isn't that us
> imposing on "them".
>
> "the reliability and temporal precision
> with which a single presynaptic action potential results in a
> postsynaptic action potential can be low". In the cerebellum, the 150,000
> excitatory inputs to each Purkinje cell don't appear to have any direct
> influence on the output of the cell - I suspect most excitatory synaptic
> inputs in the brain are actually doing exactly what they appear to be
> doing, nfluencing the local membrane. I believe that we neurobiologists
> may be far too "soma-centric" in thinking about how neuons and brains
> compute.
>
> Last isn't it intersting that the closer one gets to the periphery either
> on the sensory or the motor side the more "precise" the nervous system
> looks, yet somehow in the middle it looks like it needs to solve some
> signal to noise problem. But why isn't it simply loikely that we can
> better understand what is going on on either end, but in the middle we
> have no idea.
>
> Although I know bard and others who talk about noise are talking about it
> in a precise way -- however, I tend to lump the word "noise" like a number
> of other similar words in literature as a bin in which we put things we
> don't understand.
>
> I am reminded of Penzias (sorry about the spelling and wilson crawling
> around in their satalite dish with tin foil trying to remove what turned
> out to be (predicted) background cosmic radiation.
>
> (Please don't point out the role of theoretical modeling in realizing the
> truth. -- this modeling was done in the context of a science of simple
> things (physics) with among other things a common set of definitions).
>
> Jim
> Sent via BlackBerry by AT&T
>
> -----Original Message-----
> From: Sacha Nelson <nelson at brandeis.edu>
>
> Date: Wed, 23 Jul 2008 09:40:56
> To: <bower at uthscsa.edu>
> Cc: <comp-neuro at neuroinf.org>
> Subject: Re: [Comp-neuro] Noise, redundancy and biophysics
>
>
> It is worth pointing out that "Signal," "noise," and "redundancy" are
> highly relative terms. From the perspective of recognizing the word,
> adding the missing "a" would be redundnt, while from the perspective
> of telling whether or not I can spell it is not. The decoding problem
> faced by neurons is really one of separating signals relevant to a
> particular computation from signals about other events not relevant to
> that computation, but these other signals are not necessarily noise in
> the classical (e.g. thermal) sense.
>
> In nearly every case in which it has been carefully looked at, neurons
> turn out to be exquisitely sensitive (e.g relative to behavior).
> Central synaptic connections, at least in the adult, turn out to be
> far more reliable than once thought. Much of the confusion about noise
> and redundancy can be traced to arguments based on systems (e.g. the
> neocortex of mammals) where the reliability and temporal precision
> with which a single presynaptic action potential results in a
> postsynaptic action potential can be low. But this is not a hardware
> limitation imposing intrinsic noise, it is a feature of the coding
> scheme, common to many central circuits, in which each neuron receives
> a very large number (e.g. ~10K) of individual inputs. The ability to
> precisely follow a single input is sacrificed in order to be able to
> detect correlation (and possibly higher moments) across multiple
> inputs. Precisely the opposite end of the spectrum is exemplified in
> many circuits closer to the sensory periphery (retinothalamic,
> auditory brainstem etc.) or motor output (neuromuscular junction).
> Here, hundreds of synaptic boutons comprise an individual connection
> and the temporal precision with which in input spike can give rise to
> an output spike can be measured in microseconds. Yet, the basic
> biophysical properties of the individual synapses and action potential
> encoding are essentially the same, or occupy the same range of
> properties, in both kinds of circuits.
>
> For the most part, in large brains at least, the circuit level seems
> fairly well insulated from "noise" at the molecular level (i.e. the
> stochasticity of channel openings). Of course there are some important
> exceptions, and this is less likely to hold in much smaller neurons in
> smaller circuits--e.g. worms which only have 300+ neurons and that
> lack action potentials entirely.
>
> -Sacha
> _______________________________________________
> Comp-neuro mailing list
> Comp-neuro at neuroinf.org
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>


-- 
Dr Jean-François Vibert; B3E ESIM INSERM UMR-S 707
Faculté de Médecine Piere et Marie Curie
sit Saint-Antoine,
27 rue Chaligny. 75571 PARIS Cedex 12
Tel: (+33) 01-44-73-84-31; Fax: (+33) 01-44-73-84-54
e-mail Internet: vibert at u707.jussieu.fr        http://www.u707.upmc.fr







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