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Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI)(More)
A brain–computer interface (BCI) based on motor imagery (MI) translates the subject’s motor intention into a control signal through classifying electroencephalogram (EEG) patterns of different imagination tasks, for example, hand movements. Auto-regression (AR) model is one of the popular methods to describe motor imagery patterns, which is widely used by(More)
In [1] we proposed two methods to identify the reference electrode signal under the key assumption that the reference signal is independent from EEG sources. This assumption is shown to be possibly true for intracranial EEG with a scalp reference. In this paper, we theoretically prove that the obtained reference signal by using the second method in [1] or(More)
How to determine the scale parameter and the cluster number are two important open issues of spectral clustering remained to be studied. In this paper, it is aimed to overcome these two problems. Firstly, we analyze the principle of spectral clustering from normalized cut. Secondly, on one hand, a weighted local scale was proposed to improve both the(More)
Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG(More)
In this paper we first point out a fatal drawback that the widely used Granger causality (GC) needs to estimate the autoregressive model, which is equivalent to taking a series of backward recursive operations which are infeasible in many irreversible chemical reaction models. Thus, new causality (NC) proposed by Hu et al. (2011) is theoretically shown to(More)
—Interaction between different brain regions has received wide attention recently. Granger causality (GC) is one of the most popular methods to explore causality relationship between different brain regions. In 2011, Hu et. al [1] pointed out shortcomings and/or limitations of GC by using a large of number of illustrative examples and showed that GC is only(More)
How to evaluate the effect of commercials is significantly important in neuromarketing. In this paper, we proposed an electronic way to evaluate the influence of video commercials on consumers by impression index. The impression index combines both the memorization and attention index during consumers observing video commercials by tracking the EEG(More)
Granger causality (GC) has been widely applied in economics and neuroscience to reveal causality influence of time series. In our previous paper (Hu et al., in IEEE Trans on Neural Netw, 22(6), pp. 829–844, 2011), we proposed new causalities in time and frequency domains and particularly focused on new causality in frequency domain by pointing out the(More)