Dataset Information

"Eyes Open - Eyes Closed" EEG/fMRI data set including dedicated "Carbon Wire Loop" motion detection channels.

ABSTRACT: This data set contains electroencephalography (EEG) data as well as simultaneous EEG with functional magnetic resonance imaging (EEG/fMRI) data. During EEG/fMRI, the EEG cap was outfitted with a hardware-based add-on consisting of carbon-wire loops (CWL). These yielded six extra?CWL? signals related to Faraday induction of these loops in the main magnetic field "Measurement and reduction of motion and ballistocardiogram artefacts from simultaneous EEG and fMRI recordings" (Masterton et al., 2007) [1]. In this data set, the CWL data make it possible to do a direct regression approach to deal with the BCG and specifically He artifact. The CWL-EEG/fMRI data in this paper has been recorded on two MRI scanners with different Helium pump systems (4 subjects on a 3 T TIM Trio and 4 subjects on a 3T VERIO). Separate EEG/fMRI data sets have been recorded for the helium pump ON as well as the helium pump OFF conditions. The EEG-only data (same subjects) has been recorded for a motion artifact-free reference EEG signal outside of the scanner. This paper also links to an EEGlab "EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis" (Delorme and Makeig, 2004) [2] plugin to perform a CWL regression approach to deal with the He pump artifact, as published in the main paper "Carbon-wire loop based artifact correction outperforms post-processing EEG/fMRI corrections-A validation of a real-time simultaneous EEG/fMRI correction method" (van der Meer et al., 2016) [3].

SUBMITTER: van der Meer J

PROVIDER: S-EPMC5063756 | biostudies-other | 2016 Jun

REPOSITORIES: biostudies-other

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"Eyes Open - Eyes Closed" EEG/fMRI data set including dedicated "Carbon Wire Loop" motion detection channels.

van der Meer Johan J Pampel André A van Someren Eus E Ramautar Jennifer J van der Werf Ysbrand Y Gomez-Herrero German G Lepsien Jöran J Hellrung Lydia L Hinrichs Hermann H Möller Harald H Walter Martin M

Data in brief 20160309

This data set contains electroencephalography (EEG) data as well as simultaneous EEG with functional magnetic resonance imaging (EEG/fMRI) data. During EEG/fMRI, the EEG cap was outfitted with a hardware-based add-on consisting of carbon-wire loops (CWL). These yielded six extra׳CWL׳ signals related to Faraday induction of these loops in the main magnetic field "<i>Measurement and reduction of motion and ballistocardiogram artefacts from simultaneous EEG and fMRI recordings"</i> (Masterton et al ...[more]

PMID: 27761491

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Project description:Recent BOLD-fMRI studies have revealed spatial distinction between variability- and mean-based between-condition differences, suggesting that BOLD variability could offer complementary and even orthogonal views of brain function with traditional activation. However, these findings were mainly observed in block-designed fMRI studies. As block design may not be appreciate for characterizing the low-frequency dynamics of BOLD signal, the evidences suggesting the distinction between BOLD variability and mean are less convincing. Based on the high reproducibility of signal variability modulation between continuous eyes-open (EO) and eyes-closed (EC) states, here we employed EO/EC paradigm and BOLD-fMRI to compare variability- and mean-based EO/EC differences while the subjects were in light. The comparisons were made both on block-designed and continuous EO/EC data. Our results demonstrated that the spatial patterns of variability- and mean-based EO/EC differences were largely distinct with each other, both for block-designed and continuous data. For continuous data, increases of BOLD variability were found in secondary visual cortex and decreases were mainly in primary auditory cortex, primary sensorimotor cortex and medial nuclei of thalamus, whereas no significant mean-based differences were observed. For the block-designed data, the pattern of increased variability resembled that of continuous data and the negative regions were restricted to medial thalamus and a few clusters in auditory and sensorimotor networks, whereas activation regions were mainly located in primary visual cortex and lateral nuclei of thalamus. Furthermore, with the expanding window analyses we found variability results of continuous data exhibited a rather slower dynamical process than typically considered for task activation, suggesting block design is less optimal than continuous design in characterizing BOLD variability. In sum, we provided more solid evidences that variability-based modulation could represent orthogonal views of brain function with traditional mean-based activation.

Project description:Motion artefacts (MAs) are induced within EEG data collected simultaneously with fMRI when the subject's head rotates relative to the magnetic field. The effects of these artefacts have generally been ameliorated by removing periods of data during which large artefact voltages appear in the EEG traces. However, even when combined with other standard post-processing methods, this strategy does not remove smaller MAs which can dominate the neuronal signals of interest. A number of methods are therefore being developed to characterise the MA by measuring reference signals and then using these in artefact correction. These methods generally assume that the head and EEG cap, plus any attached sensors, form a rigid body which can be characterised by a standard set of six motion parameters. Here we investigate the motion of the head/EEG cap system to provide a better understanding of MAs. We focus on the reference layer artefact subtraction (RLAS) approach, as this allows measurement of a separate reference signal for each electrode that is being used to measure brain activity. Through a series of experiments on phantoms and subjects, we find that movement of the EEG cap relative to the phantom and skin on the forehead is relatively small and that this non-rigid body movement does not appear to cause considerable discrepancy in artefacts between the scalp and reference signals. However, differences in the amplitude of these signals is observed which may be due to differences in geometry of the system from which the reference signals are measured compared with the brain signals. In addition, we find that there is non-rigid body movement of the skull and skin which produces an additional MA component for a head shake, which is not present for a head nod. This results in a large discrepancy in the amplitude and temporal profile of the MA measured on the scalp and reference layer, reducing the efficacy of MA correction based on the reference signals. Together our data suggest that the efficacy of the correction of MA using any reference-based system is likely to differ for different types of head movement with head shake being the hardest to correct. This provides new information to inform the development of hardware and post-processing methods for removing MAs from EEG data acquired simultaneously with fMRI data.

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Dataset Information

"Eyes Open - Eyes Closed" EEG/fMRI data set including dedicated "Carbon Wire Loop" motion detection channels.

Publications

"Eyes Open - Eyes Closed" EEG/fMRI data set including dedicated "Carbon Wire Loop" motion detection channels.

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