[Comp-neuro] Review announcement

Nathan Urban nurban at cmu.edu
Tue Jul 22 14:55:39 CEST 2008


All,

I am glad for all the interesting comments.  A few points in response.

1) While I am skeptical of the claim that only 1% of networks don't 
oscillate, even if we take it as true, one of the key situations that we 
are discussing in this review is the case of unconnected networks that 
receive common aperiodic input.  My own intuitions were strongly against 
the idea that synchronous oscillations should arise in these scenarios.  
However, we showed experimentally (Galan et al 2006) that this occurs in 
neurons under certain conditions and then have explored this in 
simulations and in theory.  Perhaps not surprisingly similar phenomena 
were already known in theoretical physics from the work of Pikovsky and 
Rosenblum and others in the 1980s on the synchronization of chaotic 
systems by common inputs.  Such noise-induced synchrony is facilitated 
when neurons are good oscillators (like Hodgkin and Huxley's squid 
axons) but still works when neurons are not very robust oscillators - 
like leakyintegrate and fire neurons.  This general phenomenon of 
correlated noise-induced oscillatory synchrony is quite robust and has 
been observed  or proposed in some other biological systems.

2) Is the brain "noisy" and is this surprising?  Of course this depends 
on what you define as "noise".  For the review we defined "noise" as 
behaving as if drawn randomly from a distribution.  Thus, the fact that 
membrane current measured in vivo is gaussian distributed and the fact 
that spike trains are often well approximated by a poisson process is 
what we mean by "noisy" and if the distribution from which the signal is 
drawn has a large variance, then this is more noisy.   This does not 
mean that such signals are unreliable.   In fact, experiments like those 
of Bryant and Segundo and Mainen and Sejnowski (and our own Galan et al 
2008) point out that more noise induces more reliability, either across 
trials or across cells in the same trial. 

3) I think that an interesting question that arises from this discussion 
is how to code efficiently with strongly oscillating neurons.   Very 
efficient coding will indeed, as Jim suggests, often look like noise.  
However, various networks in the brain oscillate, and these oscillations 
often occur when we think that part of the brain is active and 
functioning (hippocampal theta oscillations, olfactory bulb gamma 
oscillations).  Given that  the regularity of oscillators reduces the 
capacity to represent information, what is the best that we can do in 
representing a lot of information when our favorite brain area is 
functioning in a way that is arguably sub-optimal (by oscillating).

4) People certainly have highlighted the idea that noise can be good for 
at least 30 years, and in fact probably a lot longer than this.  The 
original work on stochastic resonance was in teh late 1970's, I 
believe.  However, I think that biologists and even physiologists 
sometimes fail to appreciate the constructive effects of noise.  (E.g. 
see Dan Wolpert's recent review on Noise ion teh Nervous System in 
Nature Reviews Neuroscience.)  Also, there are new examples that are 
being added to the repertoire of such constructive effects noise,a dn 
tehse phenomena are being more clearly understood.  In the review we 
focus on this particular example of noise as facilitating 
synchronization of oscillations, drawing form our own experimental work 
and that of others, and also on making the parallel between synchrony 
and reliability.

Well, enough for now.  I hope that everyone reads and enjoys the review

Nathan    





jim bower wrote:
> One other general point about oscillations. Years ago a "neural network" engineer from MIT gave a talk at the Snowbird meeting, I think the first - in his talk he that, connected at random only 1 percent of networks didn't oscillate intrinsically, and he proposed to find those networks as they were clearly the only ones that were useful. 
>
> Interesting idea but dead wrong. Everything in biology oscillates, in fact everything in the natural world does. Engineers fear oscillations because they don't know how to control them. The nervous system uses them to its own purposes. In fact, my guess is that this is one of the sources of its efficiency. 
>
> Last point with respect to your car, the quality of the engineer must be based on the performance of what it has built. So last last question, does anyone know something whose perfomance is more extraordianary then the brain of a fly?  Or a slug?  
>
> I don't think so
>
> Jim
>
>
> Sent via BlackBerry by AT&T
>
> -----Original Message-----
> From: "Hans A. Braun" <braun at staff.uni-marburg.de>
>
> Date: Tue, 22 Jul 2008 11:32:54 
> To: <bower at uthscsa.edu>; Nathan Urban<nurban at cmu.edu>; <comp-neuro-bounces at neuroinf.org>; <comp-neuro at neuroinf.org>
> Subject: Re: [Comp-neuro] Review announcement
>
>
> Hi Jim,
>
>
>
> nice to hear from you with an interesting question. Here is a question back:
>
> Who says that the biological coding scheme is optimised in a way as
> engineers would do?
>
>
>
> I have been educated as an engineer. Thereby, I specifically have learnt how
> handle, if it cannot be avoided, such detrimental system properties like
> noise, nonlinearities and time delays because these can lead to
> unpredictable system behavior, including undesired oscillation and chaos –
> what regularly can be seen in all kind of biological systems. If something
> similar would happen in a car or an airplane, the responsible engineer,
> deservedly, would immediately be fired.
>
>
>
> Could it be that the engineer in evolution has used a principally different
> strategy?
>
> What was/is his/her goal?
>
> Who knows or who is interested to find the answer?
>
> - or a more appropriate question ;-) ?
>
>
>
> Coming back to the original "noise" question: During all the years as
> experimental physiologist I have got hundreds of hours recordings of impulse
> sequences from different neurons – and all look more or less noisy -
> whatever it means.
>
>
>
> Best wishes
>
> Hans Braun
>
>
>
> PS: if you are interested, here are two references to our work (an actual
> and an earlier paper):
>
>
>
> Finke C, Vollmer J, Postnova S, Braun HA (2008) Propagation effects of
> current and conductance noise in a model neuron with subthreshold
> oscillations. Mathematical Biosciences doi:10.1016/j.mbs.2008.03.007
>
> Braun HA, Wissing H, Schäfer K, Hirsch MC (1994). Oscillation and noise
> determine signal transduction in shark multimodal sensory cells. Nature 367:
> 270-273.
>
>
>
> The first one is a mathematical/computational approach which has very
> recently been published, so far only as online version.
>
> The second reference is to a much earlier experimental paper which
> demonstrates how the evolutionary engineer might have used oscillations and
> noise to achieve a particular sensitivity. This strategy, for whatever
> reasons, was only realized for sensory encoding in some evolutionary very
> old animals like sharks.
>
> Dr. Hans A. Braun, Institute of Physiology, Deutschhausstr. 2, D-35037
> Marburg, Germany.
> Tel: +49 (0)6421-286 23 05, FAX: +49 (0)6421-286 6967, E-mail:
> braun at staff.uni-marburg.de
> URL: http://www.uni-marburg.de/physiology/braun and  http://www.clabs.de
> see also: http://www.BioSim-Network.net
>
> ----- Original Message -----
> From: "jim bower" <bower at uthscsa.edu>
> To: "Nathan Urban" <nurban at cmu.edu>; <comp-neuro-bounces at neuroinf.org>;
> <comp-neuro at neuroinf.org>
> Sent: Friday, July 18, 2008 3:56 PM
> Subject: Re: [Comp-neuro] Review announcement
>
>
>   
>> Haven't done this in a long time. But who says neurons are noisy?
>>
>> From the point of view of information theory, why isn't the apperance of
>>     
> noise expected in a highly optimized coding scheme?  And why isn't synchrony
> to be avoided as redundency. Engineers avoid it, why shouldn't evolution.
>   
>> Just curious.
>>
>> Jim bower
>> Sent via BlackBerry by AT&T
>>
>> -----Original Message-----
>> From: Nathan Urban <nurban at cmu.edu>
>>
>> Date: Fri, 18 Jul 2008 08:41:22
>> To: <comp-neuro at neuroinf.org>
>> Subject: [Comp-neuro] Review announcement
>>
>>
>> Review announcement
>>
>> This review describes a constructive role for noise in synchronizing
>> populations of neurons and should be of interest to computaional
>> neurosciuentists.
>>
>>
>> Trends Neurosci. 2008 Jul 4. [Epub ahead of print]
>>     Reliability, synchrony and noise.
>>     Ermentrout GB, Galán RF, Urban NN.
>>
>> The brain is noisy. Neurons receive tens of thousands of highly
>> fluctuating inputs and generate spike trains that appear highly
>> irregular. Much of this activity is spontaneous - uncoupled to overt
>> stimuli or motor outputs - leading to questions about the functional
>> impact of this noise. Although noise is most often thought of as
>> disrupting patterned activity and interfering with the encoding of
>> stimuli, recent theoretical and experimental work has shown that noise
>> can play a constructive role - leading to increased reliability or
>> regularity of neuronal firing in single neurons and across populations.
>> These results raise fundamental questions about how noise can influence
>> neural function and computation.
>>
>>     PMID: 18603311 [PubMed - as supplied by publisher]
>>
>>
>>     
> http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T0V-4SXC918-1&_us
> er=525223&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000026389&_versio
> n=1&_urlVersion=0&_userid=525223&md5=22a86291fe13cd59541d841f692f24a2
>   
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>>     
>
>
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>   
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>
>   

-- 
____________________________________________
Nathan Urban, Ph.D. 
Associate Professor
Department of Biological Sciences
and Center for the Neural Basis of Cognition
Carnegie Mellon University
4400 Fifth Ave
Pittsburgh PA 15213
ph. 412-268-5122
fax 412-268-8423
http://www.andrew.cmu.edu/user/nurban/Lab_pages/




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