Name
Abstract | ||
|---|---|---|
The understanding of brain networks becomes increasingly the focus of current research. In the context of functional magnetic resonance imagery (fMRI) data of the human brain, networks have been mostly detected using standard clustering approaches. In this work, we present a new method of detecting functional networks using fMRI data. The novelty of this method is that these networks have the property that every network member is closely connected with every other member. This definition might to be better suited to model important aspects of brain activity than standard cluster definitions. The algorithm that we present here is based on a concept from theoretical biology called "replicator dynamics.". |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/TMI.2002.1009384 | Medical Imaging, IEEE Transactions |
Keywords | Field | DocType |
biomedical mri,brain models,medical image processing,closely connected network members,fmri data analysis,functional magnetic resonance imaging,functional networks detection,human brain,important brain activity aspects modeling,medical diagnostic imaging,replicator dynamics,standard cluster definitions,neuroscience,principal component analysis,clustering algorithms,brain mapping,data analysis,cluster analysis,network topology,algorithms,magnetic resonance imaging,magnetic resonance | Brain mapping,Mathematical and theoretical biology,Replicator equation,Brain activity and meditation,Brain morphometry,Human brain,Artificial intelligence,Novelty,Cluster analysis,Mathematics | Journal |
Volume | Issue | ISSN |
21 | 5 | 0278-0062 |
Citations | PageRank | References |
21 | 1.28 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gabriele Lohmann | 1 | 356 | 40.09 |
| Stefan Bohn | 2 | 21 | 1.28 |