Leaders of neuronal cultures in a quorum percolation model

We present a theoretical framework using quorum-percolation for describing the initiation of activity in a neural culture. The cultures are modeled as random graphs, whose nodes are neurons with $kin$ inputs and $kout$ outputs, and whose input degrees $kin=k$ obey given distribution functions $p...

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Main Authors: Jean-Pierre Eckmann, Elisha Moses, Olav Stetter, Tsvi Tlusty, Cyrille Zbinden
Format: Article
Language:English
Published: Frontiers Media S.A. 2010-09-01
Series:Frontiers in Computational Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00132/full
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spelling doaj-15062c99f23243a5b5778dc9a19367e82020-11-24T21:43:42ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882010-09-01410.3389/fncom.2010.001321873Leaders of neuronal cultures in a quorum percolation modelJean-Pierre Eckmann0Elisha Moses1Olav Stetter2Tsvi Tlusty3Cyrille Zbinden4University of GenevaThe Weizmann Institute of ScienceMax Planck Institute for Dynamics and Self-OrganizationThe Weizmann Institute of ScienceUniversity of GenevaWe present a theoretical framework using quorum-percolation for describing the initiation of activity in a neural culture. The cultures are modeled as random graphs, whose nodes are neurons with $kin$ inputs and $kout$ outputs, and whose input degrees $kin=k$ obey given distribution functions $p_k$. We examine the firing activity of the population of neurons according to their input degree ($k$) classes and calculate for each class its firing probability $Phi_k(t)$ as a function of $t$. The probability of a node to fire is found to be determined by its in-degree $k$, and the first-to-fire neurons are those that have a high $k$. A small minority of high-$k$ classes may be called ``Leaders,'' as they form an inter-connected subnetwork that consistently fires much before the rest of the culture. Once initiated, the activity spreads from the Leaders to the less connected majority of the culture. We then use the distribution of in-degree of the Leaders to study the growth rate of the number of neurons active in a burst, which was experimentally measured to be initially exponential. We find that this kind of growth rate is best described by a population that has an in-degree distribution that is a Gaussian centered around $k=75$ with width $sigma=31$ for the majority of the neurons, but also has a power law tail with exponent $-2$ for ten percent of the population. Neurons in the tail may have as many as $k=4,700$ inputs. We explore and discuss the correspondence between the degree distribution and a dynamic neuronal threshold, showing that from the functional point of view, structure and elementary dynamics are interchangeable. We discuss possible geometric origins of this distribution, and comment on the importance of size, or of having a large number of neurons, in the culture.http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00132/fullPercolationgraph theoryactivation dynamicsleaders of activityNeuronal culturesQuorum
collection DOAJ
language English
format Article
sources DOAJ
author Jean-Pierre Eckmann
Elisha Moses
Olav Stetter
Tsvi Tlusty
Cyrille Zbinden
spellingShingle Jean-Pierre Eckmann
Elisha Moses
Olav Stetter
Tsvi Tlusty
Cyrille Zbinden
Leaders of neuronal cultures in a quorum percolation model
Frontiers in Computational Neuroscience
Percolation
graph theory
activation dynamics
leaders of activity
Neuronal cultures
Quorum
author_facet Jean-Pierre Eckmann
Elisha Moses
Olav Stetter
Tsvi Tlusty
Cyrille Zbinden
author_sort Jean-Pierre Eckmann
title Leaders of neuronal cultures in a quorum percolation model
title_short Leaders of neuronal cultures in a quorum percolation model
title_full Leaders of neuronal cultures in a quorum percolation model
title_fullStr Leaders of neuronal cultures in a quorum percolation model
title_full_unstemmed Leaders of neuronal cultures in a quorum percolation model
title_sort leaders of neuronal cultures in a quorum percolation model
publisher Frontiers Media S.A.
series Frontiers in Computational Neuroscience
issn 1662-5188
publishDate 2010-09-01
description We present a theoretical framework using quorum-percolation for describing the initiation of activity in a neural culture. The cultures are modeled as random graphs, whose nodes are neurons with $kin$ inputs and $kout$ outputs, and whose input degrees $kin=k$ obey given distribution functions $p_k$. We examine the firing activity of the population of neurons according to their input degree ($k$) classes and calculate for each class its firing probability $Phi_k(t)$ as a function of $t$. The probability of a node to fire is found to be determined by its in-degree $k$, and the first-to-fire neurons are those that have a high $k$. A small minority of high-$k$ classes may be called ``Leaders,'' as they form an inter-connected subnetwork that consistently fires much before the rest of the culture. Once initiated, the activity spreads from the Leaders to the less connected majority of the culture. We then use the distribution of in-degree of the Leaders to study the growth rate of the number of neurons active in a burst, which was experimentally measured to be initially exponential. We find that this kind of growth rate is best described by a population that has an in-degree distribution that is a Gaussian centered around $k=75$ with width $sigma=31$ for the majority of the neurons, but also has a power law tail with exponent $-2$ for ten percent of the population. Neurons in the tail may have as many as $k=4,700$ inputs. We explore and discuss the correspondence between the degree distribution and a dynamic neuronal threshold, showing that from the functional point of view, structure and elementary dynamics are interchangeable. We discuss possible geometric origins of this distribution, and comment on the importance of size, or of having a large number of neurons, in the culture.
topic Percolation
graph theory
activation dynamics
leaders of activity
Neuronal cultures
Quorum
url http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00132/full
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