%0 Journal Article
%T Quorum Percolation in Living Neural Networks
%A Or Cohen
%A Anna Keselman
%A Elisha Moses
%A Mar¨ªa Rodr¨ªguez Mart¨ªnez
%A Jordi Soriano
%A Tsvi Tlusty
%J Quantitative Biology
%D 2010
%I arXiv
%R 10.1209/0295-5075/89/18008
%X Cooperative effects in neural networks appear because a neuron fires only if a minimal number $m$ of its inputs are excited. The multiple inputs requirement leads to a percolation model termed {\it quorum percolation}. The connectivity undergoes a phase transition as $m$ grows, from a network--spanning cluster at low $m$ to a set of disconnected clusters above a critical $m$. Both numerical simulations and the model reproduce the experimental results well. This allows a robust quantification of biologically relevant quantities such as the average connectivity $\kbar$ and the distribution of connections $p_k$
%U http://arxiv.org/abs/1007.5143v1