Ian Daly Reinhold Scherer
[1] M. Rubinov and O. Sporns, “Complex network mea-sures of brain connectivity: Uses and interpreta-tions.,” NeuroImage, vol. 52, pp. 1059–1069, Sept.2009. [2] K. H. Kim, J. W. Choi, and J. Yoon, “Difference ingamma-band phase synchronization during semanticprocessing of visually presented words from primaryand secondary languages.,” Brain research, vol. 1291,pp. 82–91, Sept. 2009. [3] S. Sasai, F. Homae, H. Watanabe, and G. Taga,“Frequency-specific functional connectivity in thebrain during resting state revealed by NIRS.,” Neu-roImage, vol. 56, pp. 252–7, May 2011. [4] M. Knyazeva, “EEG coherence changes during fin-ger tapping in acallosal and normal children: astudy of inter- and intrahemispheric connectivity,”Behavioural Brain Research, vol. 89, pp. 243–258,Dec. 1997. [5] I. Daly, S. J. Nasuto, and K. Warwick, “Brain Com-puter Interface control via functional connectivity dy-namics,” Pattern recognition, vol. 45, no. 6, pp. 2123–2136, 2011. [6] F. Darvas, R. Scherer, J. G. Ojemann, R. P. Rao, K. J.Miller, and L. B. Sorensen, “High gamma mappingusing EEG.,” NeuroImage, vol. 49, pp. 930–8, Jan.2010. [7] S.-P. Kim, J.-H. Kang, S.-H. Choe, J. W. Jeong,H. T. Kim, K. Yun, J. Jeong, and S.-H. Lee, “Mod-ulation of theta phase synchronization in the humanelectroencephalogram during a recognition memorytask,” Cognitive neuroscience and neuropsychology,vol. (online fi, 2012. [8] G. Viswanathan, E. Raposo, and M. da Luz, “L´evyflights and superdiffusion in the context of biologicalencounters and random searches,” Physics of Life Re-views, vol. 5, pp. 133–150, Sept. 2008. [9] A. K. Singh and S. Phillips, “Hierarchical controlof false discovery rate for phase locking measuresof EEG synchrony.,” NeuroImage, vol. 50, pp. 40–7,Mar. 2010. [10] K. Friston and O. David, “A neural mass model forMEG/EEG: coupling and neuronal dynamics,” Neu-roImage, vol. 20, pp. 1743–1755, 2003. [11] C. M. Sweeney-Reed and S. J. Nasuto, “A novel ap-proach to the detection of synchronisation in EEGbased on empirical mode decomposition,” Journal ofcomputational neuroscience, vol. 23, no. 1, pp. 79–111, 2007.181 [12] G. R. M¨uller-Putz, R. Scherer, G. Pfurtscheller, andC. Neuper, “Temporal coding of brain patterns fordirect limb control in humans,” Frontiers in Neuro-science, vol. 4, pp. 1–11, Jan. 2010. [13] Y. Wang, R. Wang, X. Gao, B. Hong, and S. Gao,“A practical VEP-based brain-computer interface.,”IEEE transactions on neural systems and rehabili-tation engineering : a publication of the IEEE En-gineering in Medicine and Biology Society, vol. 14,no. 2, pp. 234–239, 2006. [14] J. Theiler, S. Eubank, A. Longtin, B. Galdrikian, andJ. Doynefarmer, “Testing for nonlinearity in time se-ries: the method of surrogate data,” Physica D: Non-linear Phenomena, vol. 58, pp. 77–94, Sept. 1992. [15] M. Billinger, I. Daly, V. Kaiser, J. Jin, B. Allison,G. M¨uller-Putz, and C. Brunner, “Is it significant?Guidelines for reporting BCI performance,” in To-ward Practical BCIs: Bridging the Gap from Re-search to Real-World Applications, 2012. [16] J. Hu, Z. Mu, and J. Wang, Phase Locking Analysis ofMotor Imagery in Brain-Computer Interface. IEEE,May 2008. [17] P. Riccardo, J. Kennedy, and T. Blackwell, “Parti-cle swarm optimization,” Swarm Intelligence, vol. 1,no. 1, pp. 33–57, 1995. [18] P. Pudil, J. Novoviˇcov´a, and J. Kittler, “Floatingsearch methods in feature selection,” Pattern Recog-nition Letters, vol. 15, pp. 1119–1125, Nov. 1994. [19] D. E. Goldberg and J. H. Holland, “Genetic Algo-rithms and Machine Learning,” Machine Learning,vol. 3, no. 2, pp. 95 – 99, 1988.
Important Links:
Go Back