Remarks on Bootstrap Percolation in Metric Networks

Physics – Condensed Matter – Statistical Mechanics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

10.1088/1751-8113/42/20/205004

We examine bootstrap percolation in d-dimensional, directed metric graphs in the context of recent measurements of firing dynamics in 2D neuronal cultures. There are two regimes, depending on the graph size N. Large metric graphs are ignited by the occurrence of critical nuclei, which initially occupy an infinitesimal fraction, f_* -> 0, of the graph and then explode throughout a finite fraction. Smaller metric graphs are effectively random in the sense that their ignition requires the initial ignition of a finite, unlocalized fraction of the graph, f_* >0. The crossover between the two regimes is at a size N_* which scales exponentially with the connectivity range \lambda like_* \sim \exp\lambda^d. The neuronal cultures are finite metric graphs of size N \simeq 10^5-10^6, which, for the parameters of the experiment, is effectively random since N<< N_*. This explains the seeming contradiction in the observed finite f_* in these cultures. Finally, we discuss the dynamics of the firing front.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Remarks on Bootstrap Percolation in Metric Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Remarks on Bootstrap Percolation in Metric Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Remarks on Bootstrap Percolation in Metric Networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-260533

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.