[Comp-neuro] Noise, redundancy and biophysics

jim bower bower at uthscsa.edu
Wed Jul 23 16:27:51 CEST 2008


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). 

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-----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.


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