Computaional Physics
Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
Networks analysis, complexity, and brain function
Complexity - Special issue: Selection, tinkering, and emergence in complex networks
Digital Signal Processing (4th Edition)
Digital Signal Processing (4th Edition)
Computing communities in large networks using random walks
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
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The relationship between the structure and function of cortical networks is analyzed in terms of signal transmission between different cortical regions in the brains of cat and macaque, as modeled by the fundamental dynamics of diffusion. We investigated the relationship between modular network organization and diffused signal reception and verified that cortical areas in the same topological communities tend to receive signals with similar alterations. In addition, we modeled the diffusion dynamics on the network by a FIR filter whose coefficients correspond to the number of walks of different lengths between the source and destination nodes. Such an approach underlies the possibility to recover, at the destination node, the original signal provided the distribution of paths is known. We verified that the system functions obtained for regions belonging to different cortical communities present distinct roots, reinforcing the strict relationship between the structure and function in cortical networks.