Artículo

Lascano, N.; Gallardo-Diez, G.; Deriche, R.; Mazauric, D.; Wassermann, D.; Zhu H.; Niethammer M.; Styner M.; Zhu H.; Shen D.; Yap P.-T.; Aylward S.; Oguz I. "Extracting the groupwise core structural connectivity network: Bridging statistical and graph-theoretical approaches" (2017) 25th International Conference on Information Processing in Medical Imaging, IPMI 2017. 10265 LNCS:373-384
El editor solo permite decargar el artículo en su versión post-print desde el repositorio. Por favor, si usted posee dicha versión, enviela a
Consulte el artículo en la página del editor
Consulte la política de Acceso Abierto del editor

Abstract:

Finding the common structural brain connectivity network for a given population is an open problem, crucial for current neuroscience. Recent evidence suggests there’s a tightly connected network shared between humans. Obtaining this network will, among many advantages, allow us to focus cognitive and clinical analyses on common connections, thus increasing their statistical power. In turn, knowledge about the common network will facilitate novel analyses to understand the structure-function relationship in the brain. In this work, we present a new algorithm for computing the core structural connectivity network of a subject sample combining graph theory and statistics. Our algorithm works in accordance with novel evidence on brain topology. We analyze the problem theoretically and prove its complexity. Using 309 subjects, we show its advantages when used as a feature selection for connectivity analysis on populations, outperforming the current approaches. © Springer International Publishing AG 2017.

Registro:

Documento: Artículo
Título:Extracting the groupwise core structural connectivity network: Bridging statistical and graph-theoretical approaches
Autor:Lascano, N.; Gallardo-Diez, G.; Deriche, R.; Mazauric, D.; Wassermann, D.; Zhu H.; Niethammer M.; Styner M.; Zhu H.; Shen D.; Yap P.-T.; Aylward S.; Oguz I.
Filiación:Athena EPI, Université Côte d’Azur, Nice, Paris, France
Computer Science Department, FCEyN, Universidad de Buenos Aires, Buenos Aires, Argentina
ABS EPI, Université Côte d’Azur, Nice, Paris, France
Palabras clave:Brain connectivity; Core graph problem; Diffusion MRI; Group-wise connectome; Image processing; Magnetic resonance imaging; Medical imaging; Brain connectivity; Connectivity analysis; Core graph; Diffusion mris; Graph theoretical approach; Group-wise connectome; Structural connectivity; Structure-function relationship; Graph theory
Año:2017
Volumen:10265 LNCS
Página de inicio:373
Página de fin:384
DOI: http://dx.doi.org/10.1007/978-3-319-59050-9_30
Título revista:25th International Conference on Information Processing in Medical Imaging, IPMI 2017
Título revista abreviado:Lect. Notes Comput. Sci.
ISSN:03029743
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v10265LNCS_n_p373_Lascano

Referencias:

  • Bullmore, E.T., Sporns, O., Solla, S.A., Complex brain networks: Graph theoretical analysis of structural and functional systems (2009) Nat Rev. Neurosci., 10 (3), pp. 186-198
  • Gong, G., He, Y., Concha, L., Lebel, C., Gross, D.W., Evans, A.C., Beaulieu, C., Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography (2009) Cereb. Cortex, 19 (3), pp. 524-536
  • Wassermann, D., Mazauric, D., Gallardo-Diez, G., Deriche, R., Extracting the core structural connectivity network: Guaranteeing network connectedness through a graph-theoretical approach (2016) MICCAI 2016. LNCS, 9900, pp. 89-96. , Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.), Springer, Cham
  • Bassett, D.S., Porter, M.A., Wymbs, N.F., Grafton, S.T., Carlson, J.M., Mucha, P.J., Robust detection of dynamic community structure in networks (2013) Chaos, 23, p. 013142
  • Kriegeskorte, N., Simmons, W.K., Bellgowan, P.S.F., Baker, C.I., Circular analysis in systems neuroscience: The dangers of double dipping (2009) Nat. Neurosci., 12, pp. 535-540
  • Desikan, R.S., Ségonne, F., Fischl, B., Quinn, B.T., Dickerson, B.C., Blacker, D., Buckner, R.L., Killiany, R.J., An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest (2006) NeuroImage, 31 (3), pp. 968-980
  • Jbabdi, S., Sotiropoulos, S.N., Haber, S.N., Van Essen, D.C., Behrens, T.E.J., Measuring macroscopic brain connections in vivo (2015) Nat. Publ. Group, 18 (11), pp. 1546-1555
  • Brown, C.J., Miller, S.P., Booth, B.G., Zwicker, J.G., Grunau, R.E., Synnes, A.R., Chau, V., Hamarneh, G., Predictive subnetwork extraction with structural priors for infant connectomes (2016) MICCAI 2016. LNCS, 9900, pp. 175-183. , Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.), Springer, Cham
  • Garey, M.R., Johnson, D.S., (1979) Computers and Intractability: A Guide to the Theory of NP-Completeness, , W. H. Freeman & Co., New York
  • Sotiropoulos, S.N., Jbabdi, S., Xu, J., Andersson, J.L., Moeller, S., Auerbach, E.J., Glasser, M.F., Behrens, T.E., Advances in diffusion MRI acquisition and processing in the Human Connectome Project (2013) NeuroImage, 80 (3), pp. 125-143
  • Abraham, A., Pedregosa, F., Eickenberg, M., Gervais, P., Mueller, A., Kossaifi, J., Gramfort, A., Varoquaux, G., Machine learning for neuroimaging with scikit-learn (2014) Front. Neuroinform., 8, p. 14. , FebruaryA4 -

Citas:

---------- APA ----------
Lascano, N., Gallardo-Diez, G., Deriche, R., Mazauric, D., Wassermann, D., Zhu H., Niethammer M.,..., Oguz I. (2017) . Extracting the groupwise core structural connectivity network: Bridging statistical and graph-theoretical approaches. 25th International Conference on Information Processing in Medical Imaging, IPMI 2017, 10265 LNCS, 373-384.
http://dx.doi.org/10.1007/978-3-319-59050-9_30
---------- CHICAGO ----------
Lascano, N., Gallardo-Diez, G., Deriche, R., Mazauric, D., Wassermann, D., Zhu H., et al. "Extracting the groupwise core structural connectivity network: Bridging statistical and graph-theoretical approaches" . 25th International Conference on Information Processing in Medical Imaging, IPMI 2017 10265 LNCS (2017) : 373-384.
http://dx.doi.org/10.1007/978-3-319-59050-9_30
---------- MLA ----------
Lascano, N., Gallardo-Diez, G., Deriche, R., Mazauric, D., Wassermann, D., Zhu H., et al. "Extracting the groupwise core structural connectivity network: Bridging statistical and graph-theoretical approaches" . 25th International Conference on Information Processing in Medical Imaging, IPMI 2017, vol. 10265 LNCS, 2017, pp. 373-384.
http://dx.doi.org/10.1007/978-3-319-59050-9_30
---------- VANCOUVER ----------
Lascano, N., Gallardo-Diez, G., Deriche, R., Mazauric, D., Wassermann, D., Zhu H., et al. Extracting the groupwise core structural connectivity network: Bridging statistical and graph-theoretical approaches. Lect. Notes Comput. Sci. 2017;10265 LNCS:373-384.
http://dx.doi.org/10.1007/978-3-319-59050-9_30