Scholarpedia Article on Complexity
Matlab Complexity Toolbox
This toolbox contains a set of functions
used to calculate complexity from the covariance (correlation) matrix of a
system. Please read the comments carefully - the functions will only give valid
results if certain statistical assumptions are fulfilled.
Included is also a function for deriving covariance matrices from anatomical connection matrices, given linear dynamics and uncorrelated noise. You can find the toolbox at this link: http://www.indiana.edu/~cortex/complexity_toolbox.html
Measuring Information Integration
This page contains a pdf version of the recent paper "Measuring Information Integration", by Giulio Tononi and Olaf Sporns, BMC Neuroscience vol, pg, 2003. In addition, the page contains a Matlab toolbox with all the scripts and functions necessary to calculate the measures of information integration proposed in the paper. Also included are the datasets (connection matrices) used to generate most of the figures in the paper. The information integration page is at: http://www.indiana.edu/~cortex/intinf_toolbox.html
Movies of neural dynamics (1.4 Mb each):
These short movies show simulations described in detail in this article, to be published in "Coordination Dynamics", a book edited by Scott Kelso and Viktor Jirsa.
Here is an example of neural dynamics with high overall integration, but low complexity - it was generated using uniformly distributed connections across the map - download
In this example, connections across the map were sparse, resulting in low integration and low complexity - download
Similarly, we find high complexity for a mixture of clustered and long-range connections - download
For relevant publications (including downloadable pdf-files) check here.