Back to Search
Start Over
Quorum Percolation in Living Neural Networks
- Source :
- O. Cohen et al 2010 EPL 89 18008
- Publication Year :
- 2010
-
Abstract
- 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 $p_k$<br />Comment: 87.19.L-: Neuroscience 87.19.ll: Models of single neurons and networks 64.60.ah: Percolation http://iopscience.iop.org/0295-5075/89/1/18008 http://www.weizmann.ac.il/complex/tlusty/papers/EuroPhysLett2010.pdf
Details
- Database :
- arXiv
- Journal :
- O. Cohen et al 2010 EPL 89 18008
- Publication Type :
- Report
- Accession number :
- edsarx.1007.5143
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1209/0295-5075/89/18008