[Comp-neuro] Review announcement

Lyle Graham lyle at biomedicale.univ-paris5.fr
Wed Jul 23 12:51:04 CEST 2008


Bonjour,

un Pastis ici

Nothing particularly new, but one way to frame it is: A recorded signal 
from [insert favorite system, e.g. impoverished anesthetized cat visual 
cortex] during the presentation of some defined stimulus has three 
interacting components - that which is evoked by the stimulus, that 
which reflects the physics of the structure, and that arising from the 
code of whatever other functional processing, broadly defined, is going 
on at the moment. The stochastic part of the second component 
corresponds to noise in the engineering sense. When there are only weak 
assumptions as to the qualitative nature of the third component, it is 
often useful to quantify it with the same framework as the stochastic 
second component.

This parsing leads to questions such as, given everything else the 
animal is thinking about right now, how much can this particular signal 
describe this particular stimulus? Also, it reminds me that "noise" is a 
function of the observer - thus in a given case if there is no useful 
information in the echo from other processing, that motivates the 
question how a stochastic component can be a functionally bug and/or 
feature.

n.b. I would be willing to bet that for a large body of data, the "other 
processing going on" is as rich and significant - thus indistinguishable 
- whether the beast grew up in the savannah or the animal facility. 
Which means that there are plenty of ideas still to be gleaned from 
impoverished and even anesthetized animals.

Lyle

-- 
Lyle J. Graham
Laboratory of Neurophysics and Physiology, CNRS UMR 8119
www.neurophys.biomedicale.univ-paris5.fr/~graham
Université Paris Descartes
45 rue des Saint-Pères, 75006 Paris

Tel: 33 1 42 86 20 92 
Fax: 33 1 49 27 90 62 
Secrétariat: 33 1 42 86 21 38 



jim bower wrote:
> I see your vino and raise you two caipirinhas. ;-)
>
>
> "Ease of propegating synchronous signals". Doesn't this fundamentally depend on neurons essentially being temporal / spatial summing devices?  Which they aren't at least not the ones I deal with. 
>
> BTW when I suggest that oscillations are epiphenomina, I mean when recorded at the level of extracellular field potentials. I have no doubt myself that the brain and neurons care about periodicity. This is clear as has been pointed out here already in the periodic behavior of motor systems and therefore the neurons that coordinate movement (CPGs).   
>
> My personal suspicions revolve around the specific significance of synchrony, which it seems to me is inevitably tied to an integrate and fire assumption about neuronal processing (and core therefore to most abstract models of neurons and networks). 
>
> With respect to "noise" again, I personally thing the term should be banned or barring that, we should agree on a common definition which is surprisingly hard to do even in computational neuroscience. 
>
> Finally, the most tightly regulated (I.e. Neuronal event associated with the largest number and probably most complex ion channels) is spike initiation and in particular, the regulation of spike to spike firing patterns. Doesn't that suggest that the timing of individual spikes and spike trains is critical to signal transduction?  This is what raises concern for me when I am told that neurons are intrinsically noisy devices. They sure spend a lot of energy controlling the timing of their outputs. 
>
> Jim
> Sent via BlackBerry by AT&T
>
> -----Original Message-----
> From: "G. Bard Ermentrout" <bard at math.pitt.edu>
>
> Date: Tue, 22 Jul 2008 15:22:43 
> Cc: <comp-neuro at neuroinf.org>; <comp-neuro-bounces at neuroinf.org>
> Subject: Re: [Comp-neuro] Review announcement
>
>
> For what it is worth - I have puzzled over the ubiquity of oscillations in 
> the CNS and still wonder what they are good for. Jim and others argue 
> epiphenomena, and this could still be correct, but it is real hard for me 
> to believe that nature would ignore a free byproduct like this.  One thing 
> about oscillations is that they have associated with them a zero 
> eigenvalue at the single cell, microcircuit or other level and what this 
> does is it makes it very eay to modulate the timing of their spikes. Much 
> more so than with fixed points. Thus it very easy from the point of view 
> of efficiency to move the spikes around in sych a way as to e.g. compute 
> correlations via the stochastic synchrony mechanism and thus propagate 
> feedfoward synchronous or correlated activity to other areas or layers. 
> Synchrony or near synchrony is very efficient at propagating in 
> feedforward networks.  Oscillations make it real easy to read out 
> correlations and also make it very easy to quickly desynchronize groups 
> with simple modulation of their intrinsic dynamaics - e.g. ACh  which can 
> greatly affect how a neuron responds to the timing of an input and to 
> other neurons to which it is attached.
>
> >From Rome with one vino too many,
>
> bard Ermentrout
>
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>   
jim bower wrote:
> What is the evidence the brain uses redundency?  How do you refine redundency?  Is a 1024 x 1024 screen redundent because some pixals sometimes carry the same image (depending on the image being portrayed). And what are the consequences for all of our ideas about the brain that most of the neuronal data we have is in response to impoverished stimuli in anesthetized animals who otherwise are mostly bred in captivity and themselves live impoverished lives?
>
> We have never built anything near the complexity or capabilty of any brain I know, how can our understanding of the systems we can engineer have any hope of revealing the nature of the neural code. 
>
> By the way if cryptographers were as fast to declare the signals they look at as statistical noise, they would be out of a job. 
>
>
> Jim
> Sent via BlackBerry by AT&T

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