A closer look at the apparent correlation of structural and functional connectivity in excitable neural networks

Sci Rep. 2015 Jan 19:5:7870. doi: 10.1038/srep07870.

Abstract

The relationship between the structural connectivity (SC) and functional connectivity (FC) of neural systems is a central focus in brain network science. It is an open question, however, how strongly the SC-FC relationship depends on specific topological features of brain networks or the models used for describing excitable dynamics. Using a basic model of discrete excitable units that follow a susceptible - excited - refractory dynamic cycle (SER model), we here analyze how functional connectivity is shaped by the topological features of a neural network, in particular its modularity. We compared the results obtained by the SER model with corresponding simulations by another well established dynamic mechanism, the Fitzhugh-Nagumo model, in order to explore general features of the SC-FC relationship. We showed that apparent discrepancies between the results produced by the two models can be resolved by adjusting the time window of integration of co-activations from which the FC is derived, providing a clearer distinction between co-activations and sequential activations. Thus, network modularity appears as an important factor shaping the FC-SC relationship across different dynamic models.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Brain / physiology*
  • Humans
  • Nerve Net / physiology*
  • Neural Networks, Computer*