Replicability of MEG and EEG measures of the auditory N1/N1m-response

Abstract

We investigated the replicability of the source location, amplitude and latency measures of the auditory evoked N1 (EEG) and N1m (MEG) responses. Each of the 5 subjects was measured 6 times in two recording sessions. Responses to monaural stimuli were recorded from 122 MEG and 64 EEG channels simultaneously. The EEG data were modeled with a symmetrically-located dipole pair. For the MEG data, one dipole in each hemisphere was located independently using a subset of channels. Standard deviation (SD) was used as a measure for replicability. The average SD of the x, y and z coordinates of the contralateral N1m dipole was about 2 mm, whereas the corresponding figures for the ipsilateral N1m and the contra- and ipsilateral N1 were about twice as large. The SDs of the dipole amplitudes and latencies were almost equal with MEG and EEG. The amplitude and latency measures of the MEG field gradient waveforms were almost as replicable as those of the dipole models. The results suggest that both MEG and EEG can be used for investigating the simultaneous activity of the left and right auditory cortices independently, MEG being superior in certain experimental setups.

Introduction

Recent developments in magnetoencephalography (MEG) and electroencephalography (EEG) technologies have led to multichannel instruments collecting signals from the whole scalp area above the cortex (Wikswo et al., 1993). Equivalent current dipole (ECD) models are often used to computationally estimate the locations of the sources generating the event-related potentials (ERP) and fields (ERF). MEG is often used for investigating the simultaneous activity of the left and right auditory cortices independently. Although Scherg and von Cramon (1986)have shown that this is also possible with ERP data, multichannel EEG is not as commonly used for this purpose. In this study, the replicability of the location, amplitude and latency measures of the auditory evoked potential N1 and its magnetic counterpart N1m were investigated in order to evaluate the suitability of the multichannel MEG and EEG to group-level studies of auditory evoked responses from both hemispheres.

The auditory N1 response is a vertex-negative deflection in the EEG, peaking at around 100 ms from stimulus onset. It consists of several subcomponents, with a major contribution from a source at the primary auditory cortex, usually referred to as the supratemporal component (Näätänen and Picton, 1987). The corresponding magnetic deflection, N1m, mainly reflects the tangential part of the supratemporal component of the electric N1 (Hari et al., 1980). Even though the auditory N1 and N1m are known to have multiple spatially separate sources (Woods, 1995), they are often modeled with a single current dipole at each hemisphere, because most of the sources have been reported to reside in or near the primary auditory cortex (Näätänen, 1992).

ERPs are often quantified with the peak amplitudes and latencies of deflections measured between electrode pairs. The scalp potential distributions of the N1 response generated in left and right auditory cortices are smooth, and overlap both temporally and spatially (Scherg and von Cramon, 1986). Thus, it is not possible to investigate the simultaneous activity of the cortices independently just by observing the potential distribution, but methods like the spatiotemporal dipole source model (Scherg, 1990) can be used to reconstruct the time behavior of multiple sources from the EEG data.

ERFs are characterized by the peak amplitudes and latencies of the deflections in both the measured field gradient (expressed in fT/cm) and the calculated dipole moment waveforms (expressed in nAm). With MEG, the activity of the auditory cortices can be investigated relatively independently just by measuring the magnetic field gradients over the left and right temporal lobes (Hämäläinen et al., 1993). Dipole models are applied if the underlying source locations of the measured activity are of interest.

The inaccuracy in dipole location can be divided into systematic errors and random variation. The systematic errors originate from the inadequacy of the model and possible errors in the calibration of the instrument. The random variation originates from the varying factors affecting the localization: instrumental noise, brain activity not related to the processing of the stimulus event, variation of the response under study, head movements and random errors introduced when measuring the positions of the electrodes and the marker coils. Of these factors, for example, the variation associated with the marker coil locations is expected to be larger from one recording session to another than within one session.

In previous studies, Pantev et al. (1991)and Gallen et al. (1994)investigated the replicability of MEG source localization with repeated measurements of one subject with auditory and somatosensory stimuli. Their results suggest standard deviations of 2 mm for the x, y and z coordinates of the auditory N1m dipole. Yamamoto et al. (1988)performed repeated MEG measurements of a realistically-shaped phantom with a current dipole simulating auditory evoked responses. The localization results fit inside a sphere with a 3 mm radius. Recently, Siedenberg et al. (1996)compared the late components of electric and magnetic responses to auditory stimuli from multiple subjects. They reported an average difference of 7 mm for the auditory N1m dipole location between stimulus blocks.

In the present study, the replicability of the location, the amplitude and latency measures of the auditory N1 and its magnetic counterpart N1m, as indexed by the standard deviation (SD) of repeated measurements, were investigated with repeated measurements on multiple subjects. The activity at the left and right hemispheres was separately investigated with dipole models applied to both electric and magnetic responses. The results were also compared with those acquired from the ERF waveforms directly. The experiment was designed to reveal the contributions of the different sources of variation to the overall standard deviation.