alexa Editorial. Integration of EEG and fMRI


Journal of Electrical & Electronic Systems

Author(s): Debener Stefan, Herrmann Christoph S

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The combination of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) provides us with the opportunity to study human brain function non-invasively with high temporal and spatial resolution. Over the past few years, many experts have addressed problems in the field of EEG–fMRI integration, and substantial progress has been made. However, among the persisting challenges is the question of how simultaneously to collect good quality EEG and fMRI data. Furthermore, the problem of recovering a reasonable EEG signal quality from simultaneous recordings is not yet solved. Finally, the most fundamental problem probably relates to the question of how statistically to integrate EEG and fMRI signals. The articles published in this special issue reflect the current state of research in this rapidly evolving area and provide new insights that help to address these problems. Pioneering efforts regarding the integration of separately recorded neuroimaging and event-related potential (ERP) data date back more than 20 years. Herrmann and Debener summarize the progress made from the first truly simultaneous recording of EEG–fMRI data to the current standard. Today, there exist specifically designed commercially available EEG systems that facilitate the collection of high-density EEG recordings inside the MRI scanner. Yet, MRI laboratories are certainly not EEG-friendly environments, and inside scanner EEG recordings suffer from artefacts that can easily be several orders of magnitude larger than the outside scanner EEG signal. The article of Warbrick et al. is concerned with practical aspects related to simultaneous EEG–fMRI recordings. Specifically, the authors examined how different MRI scanning strategies, in combination with different artefact removal procedures, affect the resulting quality of visual evoked potentials. The authors conclude that EEG recordings require minimal changes to the fMRI acquisition protocol. The issue of compromised data quality is also addressed by the following two papers. Importantly, Mullinger et al. examined the impact of EEG electrodes and cables on MRI image quality, an issue that has been largely neglected so far. The results indicate that the EEG setup does not result in a dramatic reduction of the MRI image quality. Debener et al. studied the properties of the ballistocardiogram, an artefact that clearly compromises the quality of EEG signals recorded inside the MRI. A model addressing the origin of the ballistocardiogram is presented, aiming to explain the spatial and temporal dynamics of this artefact. This in turn may help to further optimize ballistocardiogram removal techniques. The following articles address the question of how to combine and integrate EEG and fMRI signals. Wibral and colleagues compared the usage of independent component analysis (ICA) for evoked potential research with fMRI-informed dipole seeding, a technique that can be used for the combination of separately recorded EEG and fMRI data. Eichele et al. and Moosmann et al. specifically explored ways of directly integrating EEG–fMRI signals. Importantly, these two studies consider EEG and fMRI signals on a single-trial level, which enables the investigation of a possible coupling between EEG and the fMRI blood oxygenation level dependent (BOLD) signal. It is remarkable that all three papers that are concerned with EEG–fMRI integration consider ICA as an important signal processing tool. Indeed, ICA has been shown to be a powerful tool for the processing of EEG and fMRI signals, and seems extremely helpful for the integration of both measures. The last group of papers addresses more practical research questions. Using a silent fMRI acquisition technique, Thaerig et al. found that a well known auditory evoked potential amplitude manipulation, namely the N100 amplitude increase with loudness, can be obtained from inside scanner EEG recordings. By application of the EEG-informed fMRI analysis approach, Scheeringa et al. for the first time provide evidence for a direct link between EEG activity in the theta frequency range and regionally circumscribed fMRI BOLD activity. Interestingly, the identified network of brain areas coupled to theta activity is known as the default mode brain system. This work, and that of Eichele et al., in particular demonstrate the added value of direct EEG–fMRI integration, as they show that both measures provide information beyond that which can be achieved by either technique alone. And finally, Khader and colleagues review the available evidence for a close correspondence between slow potentials of the EEG and fMRI BOLD signals. While it is not yet known which EEG signals do, and which do not, correspond to the fMRI BOLD signal, this paper highlights the importance of exploring EEG–fMRI integration from different angles. The special issue is an expansion of the symposium “Multimodal Imaging: Integration of EEG and fMRI data”, presented at the 32nd German Congress on Psychology and the Brain, held in Dresden, Germany in 2006. Several of the papers were also presented at the 13th Annual Meeting of the Organization for Human Brain Mapping in Chicago, Illinois, 2007. We would like to thank Dr. John Andreassi, editor of the International Journal of Psychophysiology, for supporting us in compiling this special issue. The people that provided the most direct support are the reviewers. We are very grateful for their service.

This article was published in International Journal of Psychophysiology and referenced in Journal of Electrical & Electronic Systems

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