EEG Microstates Change in Response to Increase in Dopaminergic Stimulation in Typical Parkinson’s Disease Patients

Resting-state functional connectivity studies with fMRI showed that the brain is intrinsically organized into large-scale functional networks for which the hemodynamic signature is stable for about 10s. Spatial analyses of the topography of the spontaneous EEG also show discrete epochs of stable global brain states (so-called microstates), but they remain quasi-stationary for only about 100 ms. In order to test the relationship between the rapidly fluctuating EEG-defined microstates and the slowly oscillating fMRI-defined resting states, we recorded 64-channel EEG in the scanner while subjects were at rest with their eyes closed. Conventional EEG-microstate analysis determined the typical four EEG topographies that dominated across all subjects. The convolution of the time course of these maps with the hemodynamic response function allowed to fit a linear model to the fMRI BOLD responses and revealed four distinct distributed networks. These networks were spatially correlated with four of the resting-state networks (RSNs) that were found by the conventional fMRI group-level independent component analysis (ICA). These RSNs have previously been attributed to phonological processing, visual imagery, attention reorientation, and subjective interoceptive-autonomic processing. We found no EEG-correlate of the default mode network. Thus, the four typical microstates of the spontaneous EEG seem to represent the neurophysiological correlate of four of the RSNs and show that they are fluctuating much more rapidly than fMRI alone suggests. Copyright 2010 Elsevier Inc. All rights reserved.

In young, first-episode, productive, medication-naive patients with schizophrenia, EEG microstates (building blocks of mentation) tend to be shortened. Koenig et al. [Koenig, T., Lehmann, D., Merlo, M., Kochi, K., Hell, D., Koukkou, M., 1999. A deviant EEG brain microstate in acute, neuroleptic-naive schizophrenics at rest. European Archives of Psychiatry and Clinical Neuroscience 249, 205-211] suggested that shortening concerned specific microstate classes. Sequence rules (microstate concatenations, syntax) conceivably might also be affected. In 27 patients of the above type and 27 controls, from three centers, multichannel resting EEG was analyzed into microstates using k-means clustering of momentary potential topographies into four microstate classes (A-D). In patients, microstates were shortened in classes B and D (from 80 to 70 ms and from 94 to 82 ms, respectively), occurred more frequently in classes A and C, and covered more time in A and less in B. Topography differed only in class B where LORETA tomography predominantly showed stronger left and anterior activity in patients. Microstate concatenation (syntax) generally were disturbed in patients; specifically, the class sequence A-->C-->D-->A predominated in controls, but was reversed in patients (A-->D-->C-->A). In schizophrenia, information processing in certain classes of mental operations might deviate because of precocious termination. The intermittent occurrence might account for Bleuler's "double bookkeeping." The disturbed microstate syntax opens a novel physiological comparison of mental operations between patients and controls.

The brain is active even in the absence of explicit input or output as demonstrated from electrophysiological as well as imaging studies. Using a combined approach we measured spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal along with electroencephalography (EEG) in eleven healthy subjects during relaxed wakefulness (eyes closed). In contrast to other studies which used the EEG frequency information to guide the functional MRI (fMRI) analysis, we opted for transient EEG events, which identify and quantify brain electric microstates as time epochs with quasi-stable field topography. We then used this microstate information as regressors for the BOLD fluctuations. Single trial EEGs were segmented with a specific module of the LORETA (low resolution electromagnetic tomography) software package in which microstates are represented as normalized vectors constituted by scalp electric potentials, i.e., the related 3-dimensional distribution of cortical current density in the brain. Using the occurrence and the duration of each microstate, we modeled the hemodynamic response function (HRF) which revealed BOLD activation in all subjects. The BOLD activation patterns resembled well known resting-state networks (RSNs) such as the default mode network. Furthermore we "cross validated" the data performing a BOLD independent component analysis (ICA) and computing the correlation between each ICs and the EEG microstates across all subjects. This study shows for the first time that the information contained within EEG microstates on a millisecond timescale is able to elicit BOLD activation patterns consistent with well known RSNs, opening new avenues for multimodal imaging data processing. Copyright 2010. Published by Elsevier Inc.