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Unbiased high resolution method of EEG analysis in time-frequency space?

100%
Blinowska K. J., Duraka P. J.
Acta Neurobiologiae Experimentalis
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2001
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vol. 61
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issue 3
157-174
EN
Matching Pursuit (MP) a method of high-resolution signal analysis is described in the context of other methods operating in time-frequency space. The method relies on an adaptive approximation of a signal by means of waveforms chosen from a very large and redundant dictionary of functions. The MP performance is illustrated by simulations and examples of sleep spindles and slow wave activity analysis. An improvement of the original procedure, relying on the introduction of stochastic dictionaries, is proposed. A comparison of the performance of dyadic and stochastic dictionaries is presented. MP with stochastic dictionaries is characterized by an unmatched resolution in time-frequency space; moreover it allows for parametric description of all (periodic and transient) signal features in the framework of the same formalism. Matching pursuit is especially suitable for analysis of non-stationary signals and is a unique tool for the investigation of dynamic changes of brain activity.
2
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Propagation of EEG activity during finger movement and its imagination

81%
Kus R., Ginter J. S., Blinowska K. J.
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EN
We investigated the pattern of EEG activity propagation in the beta and gamma band during a finger movement experiment and imagination of that task. The data were analyzed by means of a short-time directed transfer function (SDTF) based on a multivariate autoregressive model. The signals from the right (or left) hemisphere were processed simultaneously (not pairwise), which is crucial for obtaining a correct picture of EEG activity transmissions. The pattern of propagation in the beta band involved for both tasks a decrease of the propagation from the motor areas during the execution of the movement ? less pronounced in the case of imagination. The performance of the motion was mainly connected with a short outburst of gamma activity from the hand sensorimotor areas. In case of imagination the gamma outflow lasted longer and concerned larger brain areas.
3
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Transmission of information during Continuous Attention Test

81%
Kus R., Blinowska K. J., Kaminski M., Basinska-Starzycka A.
Acta Neurobiologiae Experimentalis
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2008
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vol. 68
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issue 1
103-112
EN
The Short-Time Directed Transfer Function (SDTF) is an estimator based on a multivariate autoregressive model which has proved to be successful in ERP experiments, e.g. those connected with motor action and its imagination. The aim of this study is the evaluation of the performance of SDTF in the cognitive experiment. We have applied SDTF for the estimation of the pattern of EEG signal transmissions during a Continuous Attention Test (CAT). Time-frequency patterns of propagation were estimated for two experimental conditions. Statistical procedures based on thin-plate spline model were used for estimation of significant changes in respect to the reference epoch. The repeatability of the results for a subject and across the subjects were investigated. The effect of prolonged transmission in the gamma band from the prefrontal electrodes found in all subjects was explained by the active inhibition in the case when a subject had to sustain from performing the action.
4
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Propagation of EEG activity during continuous attention test

81%
Kuś R., Blinowska K. J., Kamiński M., Basińska-Starzycka A.
Bulletin of the Polish Academy of Sciences: Technical Sciences
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2005
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vol. 53
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issue 3
5
Content available remote

Time-frequency-space localization of epileptic EEG oscillations

61%
Matysiak A., Durka P. J., Montes E. M., Barwinski M., Zwolinski P., Roszkowski M., Blinowska K. J.
Acta Neurobiologiae Experimentalis
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2005
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vol. 65
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issue 3
435-442
EN
This paper presents a hybrid method for localization of oscillatory EEG activity. It consists of two steps: multichannel matching pursuit with complex Gabor dictionary, and LORETA inverse solution. Proposed algorithm was successfully applied to the localization of epileptogenic EEG in a single patient.
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