Extraction of the mismatch negativity elicited by sound duration decrements: A comparison of three procedures

This study focuses on comparison of procedures for extracting the brain event-related potentials (ERPs) - brain responses to stimuli recorded using electroencephalography (EEG). These responses are used to study how the synchronization of brain electrical responses is associated with cognition such as how the brain detects changes in the auditory world. One such event-related response to auditory change is called mismatch negativity (MMN). It is typically observed by computing a difference wave between ERPs elicited by a frequently repeated sound and ERPs elicited by an infrequently occurring sound which differs from the repeated sounds. Fast and reliable extraction of the ERPs, such as the…

Extract Mismatch Negativity and P3a through Two-Dimensional Nonnegative Decomposition on Time-Frequency Represented Event-Related Potentials

This study compares the row-wise unfolding nonnegative tensor factorization (NTF) and the standard nonnegative matrix factorization (NMF) in extracting time-frequency represented event-related potentials—mismatch negativity (MMN) and P3a from EEG under the two-dimensional decomposition The criterion to judge performance of NMF and NTF is based on psychology knowledge of MMN and P3a MMN is elicited by an oddball paradigm and may be proportionally modulated by the attention So, participants are usually instructed to ignore the stimuli However the deviant stimulus inevitably attracts some attention of the participant towards the stimuli Thus, P3a often follows MMN As a result, if P3a was large…

Can back-projection fully resolve polarity indeterminacy of independent component analysis in study of event-related potential?

a b s t r a c t In the study of event-related potentials (ERPs) using independent component analysis (ICA), it is a traditional way to project the extracted ERP component back to electrodes for correcting its scaling (magnitude and polarity) indeterminacy. However, ICA tends to be locally optimized in practice, and then, the back-projection of a component estimated by the ICA can possibly not fully correct its polarity at every electrode. We demonstrate this phenomenon from the view of the theoretical analysis and numerical simulations and suggest checking and modifying the abnormal polarity of the projected component in the electrode field before further analysis. Moreover, when several co…

SINGLE-TRIAL BASED INDEPENDENT COMPONENT ANALYSIS ON MISMATCH NEGATIVITY IN CHILDREN

Independent component analysis (ICA) does not follow the superposition rule. This motivates us to study a negative event-related potential — mismatch negativity (MMN) estimated by the single-trial based ICA (sICA) and averaged trace based ICA (aICA), respectively. To sICA, an optimal digital filter (ODF) was used to remove low-frequency noise. As a result, this study demonstrates that the performance of the sICA+ODF and aICA could be different. Moreover, MMN under sICA+ODF fits better with the theoretical expectation, i.e., larger deviant elicits larger MMN peak amplitude.

Non-negative matrix factorization Vs. FastICA on mismatch negativity of children

In this presentation two event-related potentials, mismatch negativity (MMN) and P3a, are extracted from EEG by non-negative matrix factorization (NMF) simultaneously. Typically MMN recordings show a mixture of MMN, P3a, and responses to repeated standard stimuli. NMF may release the source independence assumption and data length limitations required by Fast independent component analysis (FastICA). Thus, in theory NMF could reach better separation of the responses. In the current experiment MMN was elicited by auditory duration deviations in 102 children. NMF was performed on the time-frequency representation of the raw data to estimate sources. Support to Absence Ratio (SAR) of the MMN co…

Optimal Digital Filtering versus Difference Waves on the Mismatch Negativity in an Uninterrupted Sound Paradigm

Conventionally, mismatch negativity (MMN) is analyzed through the calculation of the difference waves. This helps to eliminate some exogenous event-related potential (ERP) components. However, this reduces the signal-to-noise ratio (SNR). This study aims to test whether or not the optimal digital filtering performs better than the difference waves procedure in quantitative ERP analyses in an uninterrupted sound paradigm. The participants were 102 children aged 8-16 years. The MMN was elicited in a passive oddball paradigm presenting an uninterrupted sound consisting of two alternating tones (600 and 800 Hz) of the same duration (100 msec) with infrequent shortenings of one of the 600 Hz ton…

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Drawback of ICA Procedure on EEG: Polarity Indeterminacy at Local Optimization

Independent component analysis (ICA) has been extensively applied to reject artifacts in electroencephalography (EEG) signal processing. The first step is to extract the independent component activations from the electrode records, and then project the desired components back to the electrodes. After the composition of the projected component is analyzed in details under ICA procedure, this study shows that since ICA may extract some source components at the local optimization in high-dimensional EEG signal space, the artificial polarity indeterminacy may happen on the projected component at some electrodes. By numerical simulations, this issue also exhibits that this polarity ambiguity occ…

Independent component analysis on the mismatch negativity in an uninterrupted sound paradigm.

We compared the efficiency of the independent component analysis (ICA) decomposition procedure against the difference wave (DW) and optimal digital filtering (ODF) procedures in the analysis of the mismatch negativity (MMN). The comparison was made in a group of 54 children aged 8-16 years. The MMN was elicited in a passive oddball protocol presenting uninterrupted auditory stimulation consisting of two frequent alternating tones (600 and 800 Hz) of 100 ms duration each. Infrequently, one of the 600 Hz tones was shortened to 50 or 30 ms. The event related potentials (ERPs) were decomposed into the MMN-like and non-MMN-like independent components (ICs) through the FastICA algorithm. The ICA …

ERP denoising in multichannel EEG data using contrasts between signal and noise subspaces

Abstract In this paper, a new method intended for ERP denoising in multichannel EEG data is discussed. The denoising is done by separating ERP/noise subspaces in multidimensional EEG data by a linear transformation and the following dimension reduction by ignoring noise components during inverse transformation. The separation matrix is found based on the assumption that ERP sources are deterministic for all repetitions of the same type of stimulus within the experiment, while the other noise sources do not obey the determinancy property. A detailed derivation of the technique is given together with the analysis of the results of its application to a real high-density EEG data set. The inter…