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How Synchronization Protects from Noise

Overview of attention for article published in PLoS Computational Biology, January 2010
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Title
How Synchronization Protects from Noise
Published in
PLoS Computational Biology, January 2010
DOI 10.1371/journal.pcbi.1000637
Pubmed ID
Authors

Nicolas Tabareau, Jean-Jacques Slotine, Quang-Cuong Pham

Abstract

THE FUNCTIONAL ROLE OF SYNCHRONIZATION HAS ATTRACTED MUCH INTEREST AND DEBATE: in particular, synchronization may allow distant sites in the brain to communicate and cooperate with each other, and therefore may play a role in temporal binding, in attention or in sensory-motor integration mechanisms. In this article, we study another role for synchronization: the so-called "collective enhancement of precision". We argue, in a full nonlinear dynamical context, that synchronization may help protect interconnected neurons from the influence of random perturbations-intrinsic neuronal noise-which affect all neurons in the nervous system. More precisely, our main contribution is a mathematical proof that, under specific, quantified conditions, the impact of noise on individual interconnected systems and on their spatial mean can essentially be cancelled through synchronization. This property then allows reliable computations to be carried out even in the presence of significant noise (as experimentally found e.g., in retinal ganglion cells in primates). This in turn is key to obtaining meaningful downstream signals, whether in terms of precisely-timed interaction (temporal coding), population coding, or frequency coding. Similar concepts may be applicable to questions of noise and variability in systems biology.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 205 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 9 4%
United States 7 3%
United Kingdom 4 2%
Switzerland 3 1%
France 3 1%
Netherlands 2 <1%
Brazil 2 <1%
Portugal 1 <1%
Turkey 1 <1%
Other 3 1%
Unknown 170 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 65 32%
Researcher 37 18%
Student > Master 19 9%
Professor 19 9%
Professor > Associate Professor 14 7%
Other 37 18%
Unknown 14 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 59 29%
Engineering 32 16%
Computer Science 25 12%
Physics and Astronomy 19 9%
Neuroscience 17 8%
Other 33 16%
Unknown 20 10%