[Armstrong, B.C., Ruiz-Blondet, M.V., Khalifian, N., Kurtz, K.J., Jin, Z. and Laszlo, S. (2015). Brainprint: Assessing the uniqueness, collectability, and permanence of a novel method for ERP biometrics, Neurocomputing 166(2015): 59-67.10.1016/j.neucom.2015.04.025]Search in Google Scholar
[Boccaletti, S., Latora, V., Moreno, Y., Chavez, M. and Hwang, D.U. (2006). Complex networks: Structure and dynamics, Physics Reports 424(4C5): 175-308.10.1016/j.physrep.2005.10.009]Search in Google Scholar
[Brunner, C., Leeb, R., Müller-Putz, G., Schlögl, A. and Pfurtscheller, G. (2008). BCI Competition 2008-Graz data set A, Graz University of Technology, Graz, http://www.bbci.de/competition/iv/desc_2a.pdf.]Search in Google Scholar
[Bullmore, E. and Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems, Nature Reviews Neuroscience 10(3): 186-198.10.1038/nrn257519190637]Search in Google Scholar
[Chavez, M., Valencia, M., Latora, V. and Martinerie, J. (2010). Complex networks: New trends for the analysis of brain connectivity, International Journal of Bifurcation & Chaos 20(6): 1677-1686.10.1142/S0218127410026757]Search in Google Scholar
[Das, K., Zhang, S., Giesbrecht, B. and Eckstein, M.P. (2009). Using rapid visually evoked EEG activity for person identification, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, MN, USA, pp. 2490-2493.10.1109/IEMBS.2009.5334858]Search in Google Scholar
[Fries, P. (2005). A mechanism for cognitive dynamics: Neuronal communication through neuronal coherence, Trends in Cognitive Sciences 9(10): 474.10.1016/j.tics.2005.08.01116150631]Search in Google Scholar
[Hebb, D.O. (2013). The Organization of Behavior: A Neuropsychological Theory, John Wiley/Chapman & Hall, Hoboken, NJ.]Search in Google Scholar
[Hema, C.R., Paulraj, M.P. and Kaur, H. (2009). Brain signatures: A modality for biometric authentication, International Conference on Electronic Design, Penang, Malaysia, pp. 1-4.10.1109/ICED.2008.4786753]Search in Google Scholar
[Huang, X., Altahat, S., Tran, D. and Sharma, D. (2012). Human identification with electroencephalogram (EEG) signal processing, International Symposium on Communications and Information Technologies, Gold Coast, Australia, pp. 1021-1026.]Search in Google Scholar
[Jain, A.K., Bolle, R. and Pankanti, S. (2005). Biometrics: Personal Identification in Networked Society, Springer-Verlag New York, New York, NY.]Search in Google Scholar
[Jamal, W., Das, S., Maharatna, K., Pan, I. and Kuyucu, D. (2015). Brain connectivity analysis from EEG signals using stable phase-synchronized states during face perception tasks, Physica A: Statistical Mechanics and Its Applications 434(2015): 273-295.10.1016/j.physa.2015.03.087]Search in Google Scholar
[Kim, T.K., Kim, H., Hwang, W. and Kee, S.C. (2003). Face description based on decomposition and combining of a facial space with LDA, International Conference on Image Processing, ICIP 2003, Barcelona, Spain, pp. 877-880.]Search in Google Scholar
[Kong, W., Lin, W., Babiloni, F., Hu, S. and Borghini, G. (2015). Investigating driver fatigue versus alertness using the Granger causality network, Sensors 15(8): 19181-19198.10.3390/s150819181457036526251909]Search in Google Scholar
[Kong, W., Zhao, X., Hu, S., Vecchiato, G. and Babiloni, F. (2013). Electronic evaluation for video commercials by impression index, Cognitive Neurodynamics 7(6): 531-535.10.1007/s11571-013-9255-z382514924427225]Search in Google Scholar
[Kong, W., Zhou, Z., Jiang, B., Babiloni, F. and Borghini, G. (2017). Assessment of driving fatigue based on intra/inter-region phase synchronization, Neurocomputing 219(2017): 474-482.10.1016/j.neucom.2016.09.057]Search in Google Scholar
[Latora, V. and Marchiori, M. (2001). Efficient behavior of small-world networks, Physical Review Letters 87(19): 198701.10.1103/PhysRevLett.87.19870111690461]Search in Google Scholar
[Le, V.Q.M., Foucher, J., Lachaux, J., Rodriguez, E., Lutz, A., Martinerie, J. and Varela, F.J. (2001). Comparison of Hilbert transform and wavelet methods for the analysis of neuronal synchrony, Journal of Neuroscience Methods 111(2): 83-98.10.1016/S0165-0270(01)00372-7]Search in Google Scholar
[Lei, G., Yao, W., Hongli, Y., Ning, Y. and Ying, L. (2014). Study of brain functional network based on sample entropy of EEG under magnetic stimulation at PC6 acupoint, Biomedical Materials and Engineering 24(1): 1063-9.10.3233/BME-130904]Search in Google Scholar
[Ling, W., Li, Y., Yang, X., Xue, Q. and Wang, Y. (2015). Altered characteristic of brain networks in mild cognitive impairment during a selective attention task: An EEG study, International Journal of Psychophysiology 98(1): 8-16.10.1016/j.ijpsycho.2015.05.015]Search in Google Scholar
[Maiorana, E., Rocca, D.L. and Campisi, P. (2015). Eigenbrains and eigentensorbrains: Parsimonious bases for EEG biometrics, Neurocomputing 171(2016): 638-648.10.1016/j.neucom.2015.07.005]Search in Google Scholar
[McFarland, D.J., McCane, L.M., David, S.V. and Wolpaw, J.R. (1997). Spatial filter selection for EEG-based communication, Electroencephalography & Clinical Neurophysiology 103(3): 386-394.10.1016/S0013-4694(97)00022-2]Search in Google Scholar
[Nguyen, P., Tran, D., Huang, X. and Sharma, D. (2012). A proposed feature extraction method for EEG-based person identification, Proceedings of the 2012 International Conference on Artificial Intelligence, Las Vegas, NV, USA, pp. 1-6.]Search in Google Scholar
[Onnela, J.P., Saramäki, J., Kertész, J. and Kaski, K. (2005). Intensity and coherence of motifs in weighted complex networks, Physical Review E 71(6 Pt 2): 065103.10.1103/PhysRevE.71.06510316089800]Search in Google Scholar
[Paranjape, R.B., Mahovsky, J., Benedicenti, L. and Koles, Z. (2001). The electroencephalogram as a biometric, Canadian Conference on Electrical and Computer Engineering, Haran Karmaker, Toronto, Vol. 2, pp. 1363-1366.]Search in Google Scholar
[Park, H.J. and Friston, K. (2013). Structural and functional brain networks: from connections to cognition, Science 342(6158): 1238411.10.1126/science.123841124179229]Search in Google Scholar
[Peng, Y. and Lu, B.-L. (2017). Discriminative extreme learning machine with supervised sparsity preserving for image classification, Neurocomputing 261(2017): 242-252.10.1016/j.neucom.2016.05.113]Search in Google Scholar
[Pfurtscheller, G. and Neuper, C. (2001). Motor imagery and direct brain-computer communication, Proceedings of the IEEE 89(7): 1123-1134.10.1109/5.939829]Search in Google Scholar
[Poulos, M., Rangoussi, M. and Alexandris, N. (1999). Neural network based person identification using EEG features, IEEE International Conference on Acoustics, Speech, and Signal Processing, Phoenix, AZ, USA, pp. 1117-1120.10.1109/ICASSP.1999.759940]Search in Google Scholar
[Pujol, F.A., Mora, H. and Girona-Selva, J.A. (2016). A connectionist computational method for face recognition, International Journal of Applied Mathematics and Computer Science 26(2): 451-465, DOI: 10.1515/amcs-2016-0032.10.1515/amcs-2016-0032]Open DOISearch in Google Scholar
[Rosenblum, M.G., Pikovsky, A.S. and Kurths, J. (1996). Phase synchronization of chaotic oscillators, Physical Review Letters 76(11): 1804.10.1103/PhysRevLett.76.180410060525]Search in Google Scholar
[Rosenblum, M.G., Pikovsky, A.S. and Kurths, J. (2012). Synchronization approach to analysis of biological systems, Fluctuation & Noise Letters 04(1): L53-L62.10.1142/S0219477504001653]Search in Google Scholar
[Rubinov, M. and Sporns, O. (2009). Complex network measures of brain connectivity: Uses and interpretations, Neuroimage 52(3): 1059-1069.10.1016/j.neuroimage.2009.10.00319819337]Search in Google Scholar
[Sakkalis, V., Oikonomou, T., Tsiaras, V. and Tollis, I. (2015). Graph-theoretic indices of evaluating brain network synchronization: Application in an alcoholism paradigm, Neuromethods 91(2015): 159-169.10.1007/7657_2013_62]Search in Google Scholar
[Saramäki, J., Kivelä, M., Onnela, J.-P., Kaski, K. and Kertész, J. (2007). Generalizations of the clustering coefficient to weighted complex networks, Physical Review E: Statistical, Nonlinear, and Soft Matter Physics 75(2 Pt 2): 027105.10.1103/PhysRevE.75.02710517358454]Search in Google Scholar
[Stam, C.J. (2009). From Synchronisation to Networks: Assessment of Functional Connectivity in the Brain, Springer New York, New York, NY.10.1007/978-0-387-93797-7_5]Search in Google Scholar
[Steyrl, D., Scherer, R., Faller, J. and Müller-Putz, G.R. (2016). Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: A practical and convenient non-linear classifier, Biomedical Engineering/ Biomedizinische Technik 61(1): 77-86.10.1515/bmt-2014-011725830903]Search in Google Scholar
[Su, F., Xia, L., Cai, A. and Ma, J. (2010). Evaluation of recording factors in EEG-based personal identification: A vital step in real implementations, IEEE International Conference on Systems, Man and Cybernetics, Istanbul, Turkey, pp. 3861-3866.10.1109/ICSMC.2010.5641768]Search in Google Scholar
[Vukašinović, V., Šilc, J. and Škrekovski, R. (2014). Modeling acquaintance networks based on balance theory, International Journal of Applied Mathematics and Computer Science 24(3): 683-696, DOI: 10.2478/amcs-2014-0050.10.2478/amcs-2014-0050]Open DOISearch in Google Scholar
[Ye, J., Janardan, R. and Li, Q. (2004). Two-dimensional linear discriminant analysis, Photogrammetric Engineering & Remote Sensing 5(6): 1431-1441.]Search in Google Scholar
[Yeom, S.K., Suk, H.I. and Lee, S.W. (2013). Person authentication from neural activity of face-specific visual self-representation, Pattern Recognition 46(4): 1159-1169.10.1016/j.patcog.2012.10.023]Search in Google Scholar