Abstract
Recent findings suggest that the preparation and execution of voluntary self-paced movements are accompanied by the coordination of the oscillatory activities of distributed brain regions. Here, we use electroencephalographic source imaging methods to estimate the cortical movement-related oscillatory activity during finger extension movements. Then, we apply network theory to investigate changes (expressed as differences from the baseline) in the connectivity structure of cortical networks related to the preparation and execution of the movement. We compute the topological accessibility of different cortical areas, measuring how well an area can be reached by the rest of the network. Analysis of cortical networks reveals specific agglomerates of cortical sources that become less accessible during the preparation and the execution of the finger movements. The observed changes neither could be explained by other measures based on geodesics or on multiple paths, nor by power changes in the cortical oscillations.




Similar content being viewed by others
References
Achard, S., & Bullmore, E. (2007). Efficiency and cost of economical brain functional networks. PLoS Computational Biology, 3, e17.
Ansmann, G., & Lehnertz, K. (2011). Constrained randomization of weighted networks. Physical Review E, 84, 026103.
Astolfi, L., Cincotti, F., Mattia, D., de Vico Fallani, F., Lai, M., Baccala, L., Salinari, S., Ursino, M., Zavaglia, M., Babiloni, F. (2005). Comparison of different multivariate methods for the estimation of cortical connectivity: Simulations and applications to EEG data. In Conference proceedings of the IEEE engineering in medicine and biology society (pp. 4484–4487).
Bai, O., Mari, Z., Vorbach, S., Hallet, M. (2005). Asymmetric spatio-temporal patterns of event-related desynchronization preceding voluntary sequential finger movements: a high-resolution EEG study. Clinical Neurophysiology, 116, 1213–1221.
Baillet, S., Mosher, J., Leahy, R. (2001). Electromagnetic brain mapping. IEEE Signal Processing Magazine, 18, 14–30.
Baker, K.S., Mattingley, J.B., Chambers, C.D., Cunnington, R. (2011). Attention and the readiness for action. Neuropsychologia, 49(12), 3303–3313.
Bassett, D.S., Meyer-Lindenberg, A., Achard, S., Duke, T., Bullmore, E. (2006). Adaptive reconfiguration of fractal small-world human brain functional networks. Proceedings of the National Academy of Sciences of the United States of America, 103, 19518–19523.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57, 289–300.
Benjamini, Y., & Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics, 29, 1165–1188.
Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.-U. (2006). Complex networks: structure and dynamics. Physics Reports, 424, 175–308.
Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2, 113–120.
Borgatti, S.P. (2005). Centrality and network flow. Social Networks, 27, 55–71.
Brillinger, D.R. (2001). Time series: Data analysis and theory. Philadelphia: SIAM.
Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10, 1–13.
Bullmore, E.T., Suckling, J., Overmeyer, S., Rabe-Hesketh, S., Taylor, E., Bramme, M.J. (1999). Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain. IEEE Transactions on Medical Imaging, 18, 32–42.
Cassidy, M., Mazzone, P., Oliviero, A., Insola, A., Tonali, P., Di Lazzaro, V., Brown, P. (2002). Movement-related changes in synchronization in the human basal ganglia. Brain, 125, 1235–1246.
Cheyne, D., Bells, S., Ferrari, P., Gaetz, W., Bostan, A.C. (2008). Self-paced movements induce high-frequency gamma oscillations in primary motor cortex. Neuroimage, 42(1), 332–342.
Chung, F.R.K. (1997). Spectral graph theory. Providence: American Mathematical Society.
Cincotti, F., Mattia, D., Aloise, F., Bufalari, S., Astolfi, L., De Vico Fallani, F., Tocci, A., Bianchi, L., Marciani, M.G., Gao, S., Millan, J., Babiloni, F. (2008). High-resolution EEG techniques for brain-computer interface applications. Journal of Neuroscience Methods, 167, 31–42.
Crofts, J.J., & Higham, D.J. (2009). A weighted communicability measure applied to complex networks. Journal of the Royal Society Interface, 6, 411–414.
da Fontoura Costa, L., Rodrigues, F.A., Travieso, G., Boas, P.R.V. (2002). Characterization of complex networks: a survey of measurements. Advances in Physics, 56, 167–242.
da Fontoura Costa, L., Batista, J.L.B., Ascoli, G.A. (2011). Communication structure of cortical networks. Frontiers in Computational Neuroscience, 5, 6.
Dale, A.M., & Sereno, M.I. (1993). Improved localisation of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. Journal of Cognitive Neuroscience, 5, 162–176.
De Vico Fallani, F., Astolfi, L., Cincotti, F., Mattia, D., Marciani, M.G., Tocci, A., Salinari, S., Witte, H., Hesse, W., Gao, S., Colosimo, A., Babiloni, F. (2008). Cortical network dynamics during foot movements. Neuroinformatics, 6(1), 23–34.
De Vico Fallani, F., Rodrigues, F.A., da Fontoura Costa, L., Astolfi, L., Cincotti, F., Mattia, D., Salinari, S., Babiloni, F. (2011). Multiple pathways analysis of brain functional networks from EEG signals: an application to real data. Brain Topography, 23, 344–354.
Doyle, P.G., & Snell, L. (1984). Random walks and electric networks,. Washington: The Mathematical Association of America.
Eguíluz, V.M., Chialvo, D.R., Cecchi, G.A., Baliki, M., Apkarian, A.V. (2005). Scale-free brain functional networks. Physical Review Letters, 94, 018102.
Estrada, E., & Hatano, N. (2008). Communicability in complex networks. Physical Review E, 77, 036111.
Estrada, E., Higham, D.J., Hatano, N. (2009). Communicability betweenness in complex networks. Physica A, 388, 764–774.
Fogassi, L., & Luppino, G. (2005). Motor functions of the parietal lobe. Current Opinion in Neurobiology, 15, 626–631.
Freeman, L.C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40, 35–41.
Gross, J., Timmermann, L., Kujala, J., Dirks, M., Schmitz, F., Salmelin, R., Schnitzler, A. (2002). The neural basis of intermittent motor control in humans. Proceedings of the National Academy of Sciences of the United States of America, 99, 2299–2302.
Gross, J., Schmitz, F., Schnitzler, I., Kessler, K., Shapiro, K., Hommel, B., Schnitzler, A. (2004). Modulation of long-range neural synchrony reflects temporal limitations of visual attention in humans. Proceedings of the National Academy of Sciences of the United States of America, 101, 13050–13055.
Hayasaka, S., & Nichols, T.E. (2003). Validating cluster size inference: random field and permutation methods. Neuroimage, 20, 2343–2356.
He, B. (1998). High-resolution source imaging of brain electrical activity. IEEE Engineering in Medicine and Biology Magazine, 17, 123–129.
He, B., Wang, Y., Wu, D. (1999). Estimating cortical potentials from scalp EEG’s in a realistically shaped inhomogeneous head model by means of the boundary element method. IEEE Transactions on Biomedical Engineering, 46, 1264–1268.
Horwitz, B. (1994). The elusive concept of brain connectivity. Neuroimage, 19, 466–470.
Ikeda, A., Lüders, H.O., Burgess, R.C., Shibasaki, H. (1992). Movement-related potentials recorded from supplementary motor area and primary motor area. Role of supplementary motor area in voluntary movements. Brain, 115, 1017–1043.
Imamoglu, F., Kahnt, T., Koch, C., Haynes, J.-D. (2012). Changes in functional connectivity support conscious object recognition. Neuroimage, 63, 1909–1917.
Jin, S.H., Lin, P., Hallett, M. (2012). Reorganization of brain functional small-world networks during finger movements. Human Brain Mapping, 115, 861–872.
Langer, N., Peroni, A., Jäncke, L. (2013). The problem of thresholding in small-world network analysis. PLoS ONE, 8, e53199.
Leocani, L., Toro, C., Manganotti, P., Zhuang, P., Hallett, M. (1997). Event-related coherence and event-related desynchronization/synchronization in the 10 hz and 20 Hz EEG during self-paced movements. Clinical Neurophysiology, 104, 199–206.
Lovász, L. (1993). Random walks on graphs: A survey. In D. Miklos, V.T. Sos, T. Szonyi (Eds.), Combinatorics, Paul Erdõs is eighty (Vol. 2, pp. 353–398). Budapest: János Bolyai Mathematical Society.
Mattia, D., Cincotti, F., Astolfi, L., De Vico Fallani, F., Scivoletto, G., Marciani, M.G., Babiloni, F. (2009). Motor cortical responsiveness to attempted movements in tetraplegia: evidence from neuroelectrical imaging. Clinical Neurophysiology, 119, 2231–2237.
Middleton, F.A., & Strick, P.L. (2000). Basal ganglia and cerebellar loops: motor and cognitive circuits. Brain Research. Brain Research Reviews, 31, 236–250.
Moretti, D.V., Babiloni, F., Carducci, F., Cincotti, F., Remondini, E., Rossigni, P.M., Salinari, S., Babiloni, C. (2003). Computerized processing of EEG-EOG-EMG artifacts for multi-centric studies in EEG oscillations and event-related potentials. International Journal of Psychophysiology, 47, 199–216.
Muthukumaraswamy, S.D. (2010). Functional properties of human primary motor cortex gamma oscillations. Journal of Neurophysiology, 104(5), 2873–2885.
Newman, M.E.J. (2003). The structure and function of complex networks. SIAM Review, 45, 167–256.
Newman, M.E.J. (2005). A measure of betweenness centrality based on random walks. Social Networks, 27, 39–54.
Noh, J.D., & Rieger, H. (2004). Random walks in complex networks. Physical Review Letters, 92, 118701.
Nolte, G., Bai, U., Weathon, L., Mari, Z., Vorbach, S., Hallet, M. (2004). Identifying true brain interaction from EEG data using the imaginary part of coherency. Clinical Neurophysiology, 115, 2294–2307.
Nunez, P.L., Srinivasan, R., Westdorp, A.F., Wijesinghe, R.S., Tucker, D.M., Silberstein, R.B., Cadusch, P.J. (1997). EEG coherency I: statistics, reference electrode, volume conduction, laplacians, cortical imaging, and interpretation at multiple scales. Electroencephalography and Clinical Neurophysiology, 103, 499–515.
Ohara, S., Mima, T., Baba, K., Ikeda, A., Kunieda, T., Matsumoto, R., Yamamoto, J., Matsuhashi, M., Nagamine, T., Hirasawa, K., Hori, T., Mihara, T., Hashimoto, N., Salenius, S., Shibasaki, H. (2001). Increased synchronization of cortical oscillatory activities between human supplementary motor and primary sensorimotor areas during voluntary movements. Journal of Neuroscience, 21(23), 9377–9386.
Pantazis, D., Nichols, T.E., Baillet, S., Leahy, R.M. (2005). A comparison of random field theory and permutation methods for the statistical analysis of MEG data. Neuroimage, 25, 383–394.
Pfurtscheller, G., & Lopes da Silva, F.H. (1999). Event-related EEG/MEG synchronization and desynchronization: basic principles. Clinical Neurophysiology, 11, 1842–1857.
Pollok, B., Gross, J., Schnitzler, A. (2002). Human cortical EEG rhythms during the observation of simple aimless movements. A high resolution EEG study. Neuroimage, 17, 559–572.
Pollok, B., Gross, J., Schnitzler, A. (2006). How the brain controls repetitive finger movements. Journal of Physiology - Paris, 99, 8–13.
Reijneveld, J.C., Ponten, S.C., Berendse, H.W., Stam, C.J. (2007). The application of graph theoretical analysis to complex networks in the brain. Clinical Neurophysiology, 118, 2317–2331.
Rodrigues, F.A., & da Fontoura Costa, L. (2010). Generalized connectivity between any two nodes in a complex network. Physical Review E, 81, 036113.
Schlögel, A., & Supp, G. (2006). Analyzing event-related EEG data with multivariate autoregressive parameters. In C. Neuper, & W. Klimesh (Eds.), Progress in brain research (Vol. 159, pp. 135–147). The Netherlands: Elsevier.
Schoffelen, J.M., & Gross, J. (2009). Source connectivity analysis with MEG and EEG. Human Brain Mapping, 30, 1857–1865.
Sporns, O., Chialvo, D.R., Kaiser, M., Hilgetag, C.C. (2004). Organization, development and function of complex brain networks. Trends in Cognitive Sciences, 8, 418–425.
Srinivasan, R., Nunez, P.L., Silberstein, R.B. (1998). Spatial filtering and neocortical dynamics: estimates of EEG coherence. IEEE Transactions on Biomedical Engineering, 45, 814–826.
Stephenson, K., & Zelen, M. (1989). Rethinking centrality: methods and examples. Social Networks, 11, 1–37.
Toppi, J., De Vico Fallani, F., Vecchiato, G., Maglione, A.G., Cincotti, F., Mattia, D., Salinari, S., Babiloni, F., Astolfi, L. (2012). How the statistical validation of functional connectivity patterns can prevent erroneous definition of small-world properties of a brain connectivity network.Computational and Mathematical Methods in Medicine, 2012, 130985.
Valencia, M., Pastor, M.A., Fernández-Seara, M.A., Artieda, J., Martinerie, J., Chavez, M. (2009). Complex modular structure of large-scale brain networks. Chaos, 19, 02311.
van Wijk, B.C.M., Stam, C.J., Daffertshofer, A. (2010). Comparing brain networks of different size and connectivity density using graph theory. PLoS ONE, 5, e13701.
Varela, F., Lachaux, J.-P., Rodriguez, E., Martinerie, J. (2001). The brainweb: phase synchronization and large-scale integration. Nature Reviews Neuroscience, 2, 229–239.
Wolpert, D.M., Ghahramani, Z., Jordan, M.I. (1995). An internal model for sensorimotor integration. Science, 269, 1880–1882.
Zamora-López, G., Zhou, C., Kurths, J. (2009). Graph analysis of cortical networks reveals complex anatomical communication substrate. Chaos, 19, 015117.
Acknowledgments
This study was supported in part by Cochlear Inc. and by a grant of “Ministero dell’Istruzione, dell’Universita e della Ricerca”, Direzione Generale per l’ Internazionalizzazione della Ricerca, in a bilateral project between Italy and Hungary. M. V. acknowledges financial support from the Spanish Ministry of Science and Innovation; Juan de la Cierva Programme Ref. JCI-2010-07876. F. D. V. F. is founded by the French program “Investissements d’avenir” ANR-10-IAIHU-06. M.V. and M.C. acknowledge financial support from the Gobierno de Navarra, Education Department, Jerónimo de Ayanz Programme M. C. thanks to the CIMA and University of Navarra, for their kind hospitality during the different visits for the preparation of this work.
Conflict of Interest
The authors declare that they have no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Chavez, M., De Vico Fallani, F., Valencia, M. et al. Node Accessibility in Cortical Networks During Motor Tasks. Neuroinform 11, 355–366 (2013). https://doi.org/10.1007/s12021-013-9185-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12021-013-9185-2