| Autor: |
Artemy eKolchinsky, Martijn P. eVan Den Heuvel, Alessandra eGriffa, Patric eHagmann, Luis M. eRocha, Olaf eSporns, Joaquin eGoñi |
| Jazyk: |
angličtina |
| Rok vydání: |
2014 |
| Předmět: |
|
| Zdroj: |
Frontiers in Neuroinformatics, Vol 8 (2014) |
| Druh dokumentu: |
article |
| ISSN: |
1662-5196 |
| DOI: |
10.3389/fninf.2014.00066 |
| Popis: |
The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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