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## Independent component analysis of electroencephalographic data (1996)

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### Other Repositories/Bibliography

Venue: | Adv. Neural Inform. Process. Syst |

Citations: | 306 - 61 self |

### Citations

1851 |
Independent component analysis, a new concept?”
- Comon
- 1994
(Show Context)
Citation Context ...ly independent but spatially fixed potential-generating systems which may either be spatially restricted or widely distributed. 1.2 Independent Component Analysis Independent Component Analysis (ICA) =-=[1, 3]-=- is the name given to techniques for finding a matrix, W and a vector, w, so that the elements, u = [u 1 : : : uN ] T , of the linear transform u = Wx + w of the random vector, x = [x 1 : : : xN ] T ,... |

1494 | An information-maximization approach to blind separation and blind deconvolution
- Bell, Sejnowski
- 1995
(Show Context)
Citation Context ...rea. This spatial smearing of EEG data by volume conduction does not involve significant time delays, however, suggesting that the Independent Component Analysis (ICA) algorithm of Bell and Sejnowski =-=[1]-=- is suitable for performing blind source separation on EEG data. The ICA algorithm separates the problem of source identification from that of source localization. First results of applying the ICA al... |

622 | A new learning algorithm for blind signal separation
- Amari, Cichocki, et al.
- 1996
(Show Context)
Citation Context ...early mixed by an unknown matrix A, and recorded at N sensors, x,(t),. .., x.Jt). The blind source separation problem has been studied by researchers in the neural network (Bell and Sejnowski, 1995a; =-=Amari et al., 1996-=-, Cichocki et al., 1994; Girolarni and Fyfe, 1996; Karhunen et al; 1996; Pearlmutter and Parra, 1997; Roth and Baram, 1996) and statistical signal processing communities (Cardoso and Laheld, 1996; Com... |

449 | Equivariant Adaptive Source Separation,” - Cardoso, Laheld - 1996 |

239 | Elements of information theory - TM, JA - 1991 |

170 |
Independent component analysis—a new concept
- Comon
- 1994
(Show Context)
Citation Context ...996, Cichocki et al., 1994; Girolarni and Fyfe, 1996; Karhunen et al; 1996; Pearlmutter and Parra, 1997; Roth and Baram, 1996) and statistical signal processing communities (Cardoso and Laheld, 1996; =-=Comon, 1994-=-; Larnbert, 1996; Pham, 1996; Yellin and Weinstein, 1996). Comon (1994) defined the concept of independent component analysis (ICA) as maximizing the degree of statistical independence among outputs u... |

162 | Nonlinear neurons in the lownoise limit: a factorial code maximizes information transfer. - Nadal, Parga - 1994 |

138 | A class of neural networks for independent component analysis[J]. - Karhunen, Oja, et al. - 1997 |

105 | Improved localization of cortical activity by combining EEG and MEG with MRI cortical surface reconstruction: a linear approach. - AM, MI - 1993 |

90 | Multichannel blind deconvolution: FIR matrix algebra and separation of multipath mixtures, - Lambert - 1996 |

90 | Maximum likelihood blind source separation: A contextsensitive generalization of ICA, - Pearlmutter, Parra - 1997 |

79 | Estimating alertness from the EEG power spectrum. - Jung, Makeig, et al. - 1997 |

68 |
Lapses in alertness: coherence of fluctuations in performance and the eeg spectrum. Electroencephal Clin Neurophysiol
- Makeig, Inlow
- 1993
(Show Context)
Citation Context ...ful for identifying psychophysiological state transitions. 2 Methods EEG and behavioral data were collected to develop a method of objectively monitoring the alertness of operators of complex systems =-=[8]-=-. Ten adult volunteers participated in three or more half-hour sessions, during which they pushed one button whenever they detected an above-threshold auditory target stimulus (a brief increase in the... |

29 | Electric Fields of the Brain - PL - 1981 |

26 | Negentropy and kurtosis as projection pursuit indices provide generalised ICA algorithms. - Girolami, Fyfe - 1996 |

24 | Fast blind separation based on information theory.
- Bell, Sejnowski
- 1995
(Show Context)
Citation Context ...at the p.d.f. of the speech signals was not exactly matched by the gradient of the logistic function. In the experiments in this paper, we also used the speedup technique of prewhitening described in =-=[2]-=-. 1.3 Applying ICA to EEG Data The ICA technique appears ideally suited for performing source separation in domains where, (1) the sources are independent, (2) the propagation delays of the `mixing me... |

15 | von Cramon D - Scherg - 1985 |

6 |
The CERP: event-related perturbations in steadystate responses. Brain Dynam
- Makeig, Galambos
- 1989
(Show Context)
Citation Context ...ating out the 39-Hz steady-state response (SSR) produced by the continuous 39-Hz click stimulation during the session. Note the stimulus-induced perturbation in SSR amplitude previously identified in =-=[6]-=-. Three channels (H[1-3]) pass time-limited components of the detected target response, while four others (L[1-4]) components of the (larger) undetected target response. We suggest these represent the... |

3 |
EEG and MEG source localization: a linear approach
- Dale, Sereno
- 1993
(Show Context)
Citation Context ...terns recorded on the scalp surface is mathematically underdetermined. Recent efforts to identify EEG sources have focused mostly on performing spatial segregation and localization of source activity =-=[4]-=-. By applying the ICA algorithm of Bell and Sejnowski [1], we attempt to completely separate the twin problems of source identification (What) and source localization (Where). The ICA algorithm derive... |

3 |
Dynamic changes in steady-state potentials
- Galambos, Makeig
- 1989
(Show Context)
Citation Context ...ficance of the derived ICA source channels. Although the ICA model of the EEG ignores the known variable synchronization of separate EEG generators by common subcortical or corticocortical influences =-=[5]-=-, it appears promising for identifying concurrent signal sources that are either situated too close together, or are too widely distributed to be separated by current localization techniques. Here, we... |

3 | AJ, Jung T-P, Sejnowski TJ (1996a) Independent component analysis of electroencephalographic data - Makeig, Bell |

3 | T-P, Ghahremani D, Sejnowski TJ (1996b) Independent component analysis of simulated ERP data - Makeig, Jung |

2 |
Lapses in alertness: Coherence of in performance and eeg spectrum
- Makeig, Inlow
- 1993
(Show Context)
Citation Context ...ful for identifying psychophysiological state transitions. 2 Methods EEG and behavioral data were collected to develop a method of objectively monitoring the alertness of operators of complex systems =-=[8]-=-. Ten adult volunteers participated in three or more half-hour sessions, during which they pushed one button whenever they detected an above-threshold auditory target stimulus (a brief increase in the... |

1 | Sejnowski TJ (1995a) An information-maximization approach to blind separation and blind deconvolution - AJ |

1 | Sejnowski TJ (1995b) Fast blind separation based on information theory - AJ - 1996 |

1 | Unbehauen R, Rumrnert E - Cichocki - 1994 |

1 |
C.B.C.L. Paper 138
- Olshausen
- 1996
(Show Context)
Citation Context ...nlinearity, g(u,) = (I +exp(-u))-', which gives a simple update rule, yi'=112yj and biases the algorithm toward finding sparsely-activated or super-Gaussian independent components with high kurtosis (=-=Olshausen, 1996-=-). The ICA algorithm is easily implemented and computationally efficient. Because the algorithm uses parametric probability density estimation, the number of data points needed for the method to conve... |

1 | Blind separation of instantaneous mixture of sources via an independent component analysis - DT - 1996 |

1 | Baram Y - Roth - 1996 |

1 | Dijk JG, Caekebeke JF - Sweden, Van - 1994 |