Abstract
The mismatch response (MMR) is thought to be a neurophysiological measure of novel auditory detection that could serve as a translational biomarker of various neurological diseases. When recorded with electroencephalography (EEG) or magnetoencephalography (MEG), the MMR is traditionally extracted by subtracting the event-related potential/field (ERP/ERF) elicited in response to “deviant” sounds that occur randomly within a train of repetitive “standard” sounds. However, there are several problems with such a subtraction, which include increased noise and the neural adaptation problem. On the basis of the original theory underlying MMR (i.e., the memory-comparison process), the MMR should be present only in deviant epochs. Therefore, we proposed a novel method called weighted-BSST/k, which uses only the deviant response to derive the MMR. Deviant concatenation and weight assignment are the primary procedures of weighted-BSST/k, which maximize the benefits of time-delayed correlation. We hypothesized that this novel weighted-BSST/k method highlights responses related to the detection of the deviant stimulus and is more sensitive than independent component analysis (ICA). To test this hypothesis and the validity and efficacy of the weighted-BSST/k in comparison with ICA (infomax), we evaluated the methods in 12 healthy adults. Auditory stimuli were presented at a constant rate of 2 Hz. Frequency MMRs at a sensor level were obtained from the bilateral temporal lobes with the subtraction approach at 96–276 ms (the MMR time range), defined based on spatio-temporal cluster permutation analysis. In the application of the weighted-BSST/k, the deviant responses were given a constant weight using a rectangular window on the MMR time range. The ERF elicited by the weighted deviant responses demonstrated one or a few dominant components representing the MMR that fitted well with that of the sensor space analysis using the conventional subtraction approach. In contrast, infomax or weighted-infomax revealed many minor or pseudo components as constituents of the MMR. Our single-trial, contrast-free approach may assist in using the MMR in basic and clinical research, and it opens a new and potentially useful way to analyze event-related MEG/EEG data.
Highlights
The mismatch negativity component in electroencephalography (EEG), and its magnetoencephalographic (MEG) counterpart the mismatch field, are eventrelated responses (EPRs/event-related field (ERF)) widely used to measure auditory processing in cognitive neuroscience [1–6]
In an attempt to develop solutions to address the limitations of Independent component analysis (ICA) and second-order blind identification (SOBI), we proposed a novel method of blind source separation (BSS) called the T/k type of decorrelation method (DC) (BSST/k) [35–38]
The analysis comprised four parts (Figure 2, double squares): (i) defining the reference standard based on the spatiotemporal cluster permutation from the sensor-space analysis; (ii) qualitative evaluation of each component based on its similarity to the reference standard; (iii) statistical assessment of component distribution patterns with the z-scored scatter plot; and (iv) the relative contribution of each component
Summary
The mismatch negativity component in electroencephalography (EEG), and its magnetoencephalographic (MEG) counterpart the mismatch field (or mismatch response, MMR), are eventrelated responses (EPRs/ERFs) widely used to measure auditory processing in cognitive neuroscience [1–6]. The MMR is recorded using an oddball paradigm, where the repeated presentation of a stimulus (standard) is occasionally replaced by a different stimulus (deviant). The MMR is computed as the difference between the deviant and standard responses. The prevailing view is that the MMR reflects the detection of change in the auditory system that can be measured without attention, alternative interpretations exist [11–14]. The MMR has been widely used to assess auditory processing in children and clinical groups [10, 15, 16]
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