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001-es BibID:	BIBFORM039400
Első szerző:	Spisák Tamás (programtervező matematikus, informatikus)
Cím:	BrainCON : software tool for graph theory based multimodal brain connectivity analysis and visualization / Tamás Spisák, Gábor Opposits, Sándor Attila Kis, Béla Clemens, Miklós Emri
Dátum:	2012
ISSN:	0968-5243
Megjegyzések:	Purpose of the software: Graph theory based structural and functional brainconnectivity analysis is a novel method providing new insights into the dynam-ics and complexity of the brain by modeling it's regional interactions[1]. Dueto the heterogeneity and dynamic development of the applied mathematicalmodels and analysis techniques the software support of this field is still poorlyaccomplished[2].Our purpose was to develop a user friendly software system dedicated for theanalysis and visualization of multimodal brain connectivity data based onEEG, fMRI and DTI data.Methods/Implementation: The software system has modular architecturewhich provides the opportunity to rapidly follow the latest improvements ofconnectivity analysis and visualization methods by incremental development.Reconstruction of brain networks is modality dependent and can be performedwith various state-of-the-art software tools, eg. BrainLOC[3], Matlab and R forfMRI, FSL or Matlab softwares for DTI and NeuroGuide for EEG-LORETAdata. These software tools can be easily fitted into the processing pipeline of thesystem. The resulting connectivity matrices can be displayed and thresholdedinteractively. Various interchangeable components are present for global (eg.small-worldness), modular (eg. community detection, modularity scores)and nodal (eg. various hub-scores) analysis of binary and weighted graphs inboth individual and population level[4]. Cost-integration[5] technique wasimplemented to solve the problem of thresholding networks. Interpreting theresults is aided by real-time 2D and 3D "galss brain" visualization techniquesand various plots.The program is built upon the MultiModal Medical Imaging software librarysystem(www.minipetct.com/m3i) and runs on Windows 7 and Windows Xpoperation systems and various Linux distributions (www.minipetct.com/braincon). The hardware requirements of the application match the currentaverage PC configurations used in medical image analysis.The software system was implemented mainly in C++ and partly in R.Features illustrated at the exhibit: At the exhibit connectivity data analysisis demonstrated using variuos modalities.Different methods are evaluated on the same data, connectivity patterns andhub-scores corresponding to brain regions are visualized in 3D.References:[1] Sporns, O., The human connectome: a complex network, Annals of theNew York Academy of Sciences, 1224(1):109-125, 2011. [2] Leergaard et.al., Mapping the Connectome: Multi-Level Analysis of Brain Connectivity,Frontiers in Neuroinformatics, 6, 2012. [3] Spisák, T. et. al., Region manage-ment toolkit for atlas-space image processing, MAGMA 24 (S1):543, 2011.[4] Rubinov, et. al., Complex network measures of brain connectivity: usesand interpretations, Neuroimage, 52(3):1059-1069, 2010. [5] Ginestet et. al.,Brain network analysis: separating cost from topology using cost-integration,PloS1, 6(7):e21570, 2011.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idézhető absztrakt brain connectivity graph theory software
Megjelenés:	Magnetic Resonance Materials In Physics Biology And Medicine. - 25 : S1 (2012), p. 616. -
További szerzők:	Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Kis Sándor Attila (1973-) (fizikus) Clemens Béla (1950-) (neurológus) Emri Miklós (1962-) (fizikus)
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