[1]
Sanei S, Chambers JA. EEG signal processing. John Wiley & Sons
2013.
[2]
Sommer FT, Wichert A. Exploratory analysis and data modeling in
functional neuroimaging. MIT Press 2003.
[3]
Jatoi MA, Kamel N, Malik AS, Faye I, Begum T. A survey of methods used for source localization using EEG signals. Biomed Signal Process Control 2014; 11: 42-52.
[4]
Rajapakse JC, Cichocki A. Independent component analysis and
beyond in brain imaging: EEG, MEG, fMRI, and PET. In: Neural
information processing, 2002. In: ICONIP'02 Proceedings of the 9th
International Conference on 2002: IEEE, Singapore; pp. 404-12.
[5]
Dale AM, Liu AK, Fischl BR, et al. Dynamic statistical parametric mapping: combining fMRI and MEG for high-resolution imaging of cortical activity. Neuron 2000; 26(1): 55-67.
[6]
Da Silva FL, Van Rotterdam A, Barts P, Van Heusden E, Burr W. Models of neuronal populations: The basic mechanisms of rhythmicity. Prog Brain Res 1976; 45: 281-308.
[7]
Freeman WJ. Simulation of chaotic EEG patterns with a dynamic model of the olfactory system. Biol Cybern 1987; 56(2-3): 139-50.
[8]
Jansen BH, Rit VG. Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biol Cybern 1995; 73(4): 357-66.
[9]
Wendling F, Bellanger J-J, Bartolomei F, Chauvel P. Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals. Biol Cybern 2000; 83(4): 367-78.
[10]
Zetterberg L, Kristiansson L, Mossberg K. Performance of a model for a local neuron population. Biol Cybern 1978; 31(1): 15-26.
[11]
Jatoi MA, Kamel N, Malik AS, Faye I. EEG based brain source localization comparison of sLORETA and eLORETA. Australas Phys Eng Sci Med 2014; 37(4): 713-21.
[12]
Tarantola A. Inverse problem theory and methods for model parameter estimation. SIAM 2005.
[13]
Lawson CL, Hanson RJ. Solving least squares problems. SIAM 1995.
[14]
Pascual-Marqui RD, Lehmann D, Koenig T, et al. Low Resolution Brain Electromagnetic Tomography (LORETA) functional imaging in acute, neuroleptic-naive, first-episode, productive schizophrenia. Psych Res Neuroimag 1999; 90(3): 169-79.
[15]
Pascual-Marqui RD. Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details. Methods Find Exp Clin Pharmacol 2002; 24(Suppl. D): 5-12.
[16]
Pascual-Marqui RD. Discrete, 3D distributed, linear imaging methods
of electric neuronal activity. Part 1: Exact, zero error localization.
arXiv preprint arXiv 2007.
[17]
Jatoi MA, Kamel N, Malik AS, Faye I, Bornot JM, Begum T. EEG‐based brain source localization using visual stimuli. Int J Imaging Syst Technol 2016; 26(1): 55-64.
[18]
Mosher JC, Leahy RM. Source localization using Recursively Applied and Projected (RAP) MUSIC. IEEE Trans Signal Process 1999; 47(2): 332-40.
[19]
Jatoi MA, Kamel N, Musavi SHA. Framework for estimating active brain sources using MUSIC and Root MUSIC. 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT) 2017: IEEE, Karachi, Pakistan; pp. 1-6.
[20]
López J, Litvak V, Espinosa J, Friston K, Barnes GR. Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM. Neuroimage 2014; 84: 476-87.
[21]
López JD, Espinosa JJ, Barnes GR. Random location of multiple
sparse priors for solving the MEG/EEG inverse problem. In: 2012
annual international conference of the IEEE engineering in medicine
and biology society. IEEE: San Diego, CA, USA; pp. 1534-7.
[22]
Phillips C, Mattout J, Rugg MD, Maquet P, Friston KJ. An empirical Bayesian solution to the source reconstruction problem in EEG. Neuroimage 2005; 24(4): 997-1011.
[23]
Friston K, Harrison L, Daunizeau J, et al. Multiple sparse priors for the M/EEG inverse problem. Neuroimage 2008; 39(3): 1104-20.
[25]
Wendel K, Väisänen O, Malmivuo J, et al. EEG/MEG source imaging: Methods, challenges, and open issues. Comput Intell Neurosci 2009; 2009: 1-12.
[26]
Meijs JW, Peters MJ. The EEG and MEG, using a model of eccentric spheres to describe the head. IEEE Trans Biomed Eng 1987; 12: 913-20.
[27]
Mohr M, Vanrumste B. Comparing iterative solvers for linear systems associated with the finite difference discretisation of the forward problem in electro-encephalographic source analysis. Med Biol Eng Comput 2003; 41(1): 75-84.
[28]
Hämäläinen MS, Ilmoniemi RJ. Interpreting magnetic fields of the brain: minimum norm estimates. Med Biol Eng Comput 1994; 32(1): 35-42.
[29]
Dale AM, Sereno MI. Improved localizadon of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. J Cogn Neurosci 1993; 5(2): 162-76.
[30]
Friston K, Mattout J, Trujillo-Barreto N, Ashburner J, Penny W. Variational free energy and the Laplace approximation. Neuroimage 2007; 34(1): 220-34.
27
4