Integration of fMRI and simultaneous EEG: towards a comprehensive understanding of localization and time-course of brain activity in target detection

Mulert, Christoph; Jäger, L.; Schmitt, Robert; Bussfeld, P.; Pogarell, Oliver; Möller, Hans‐Jürgen; Juckel, Georg; Hegerl, Ulrich

doi:10.1016/j.neuroimage.2003.10.051

Cited by 558 publications

(349 citation statements)

References 52 publications

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“…Such an implication of the insula has also been found for illusory hand ownership by experimentally manipulating visuo-tactile information in healthy subjects (Tsakiris et al, 2007), although the insular activity in this study correlated only with implicit measures of the RHI (proprioceptive drift) and not with subjective changes in illusory hand ownership as tested in the present study. Although we cannot exclude that insular cortex was also activated in the present study and may have influenced the observed fronto-parietal EEG patterns, this is rather unlikely given our inverse solution results and that activity in the insula can be detected with EEG methods (Mulert et al, 2003).…”

Section: Fronto-parietal Regions Reflect Ownershipmentioning

confidence: 71%

Shared electrophysiology mechanisms of body ownership and motor imagery

Evans

Blanke

2013

NeuroImage

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Although we feel, see, and experience our hands as our own (body or hand ownership), recent research has shown that illusory hand ownership can be induced for fake or virtual hands and may be useful for neuroprosthetics and brain-computer interfaces. Despite the vast amount of behavioral data on illusory hand ownership, neuroimaging studies are rare, in particular electrophysiological studies. Thus, while the neural systems underlying hand ownership are relatively well described, the spectral signatures of body ownership as measured by electroencephalography (EEG) remain elusive. Here we induced illusory hand ownership in an automated, computer-controlled manner using virtual reality while recording 64-channel EEG and found that illusory hand ownership is reflected by a body-specific modulation in the mu-band over fronto-parietal cortex. In a second experiment in the same subjects, we then show that mu as well as beta-band activity in highly similar fronto-parietal regions was also modulated during a motor imagery task often used in paradigms employing non-invasive brain-computer interface technology. These data provide insights into the electrophysiological brain mechanisms of illusory hand ownership and their strongly overlapping mechanisms with motor imagery in fronto-parietal cortex. They also highlight the potential of combining high-resolution EEG with virtual reality setups and automatized stimulation protocols for systematic, reproducible stimulus presentation in cognitive neuroscience, and may inform the design of non-invasive brain-computer interfaces.

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Section: Fronto-parietal Regions Reflect Ownershipmentioning

confidence: 71%

Shared electrophysiology mechanisms of body ownership and motor imagery

Evans

Blanke

2013

NeuroImage

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“…A commonly employed strategy for eliminating the effects of gradient switching artifact in combined ERP-fMRI studies is to use of sparse fMRI and present the stimuli in intervals during which no fMRI acquisition takes place (Debener et al, 2005;Eichele et al, 2005;Liebenthal et al, 2003;Mulert et al, 2004;Strobel et al, 2008). However, the sparse positioning of ERP stimuli (and fMRI scans) restricts the number of stimuli (and the amount of data), constrains their timing and leaves some portions of the BOLD fMRI signal time-course systematically under-sampled.…”

Section: Discussionmentioning

confidence: 99%

“…To attempt to 'get the best of both worlds', researchers have combined measurements of EEG and fMRI in cognitive paradigms (Bénar et al, 2007;Debener et al, 2005;Eichele et al, 2005;Liebenthal et al, 2003;Mantini et al, 2009;Mulert et al, 2004;Strobel et al, 2008;Warbrick et al, 2009). Although such concurrent acquisition of non-invasive brain activity measurements of high temporal resolution (ERPs) and high spatial resolution (fMRI) is promising, it is also challenging, because of the effect of integration on data quality.…”

Section: Introductionmentioning

confidence: 99%

“…This 'fast' interleaved procedure suits well the ERP technique, which is typically based on EEG segments of 1 s or less, and ensures that the statistical analyses in both modalities reflect the physiological responses to the same stimuli. Indeed, many combined EEG-fMRI studies have used it (Debener et al, 2005;Eichele et al, 2005;Mulert et al, 2004;Strobel et al, 2008). However, the 'fast' interleaved procedure also has its limitations.…”

Section: Introductionmentioning

confidence: 99%

“…While the feasibility studies focused on early visual ERP components, most ERP-fMRI studies to date examined longer-latency components (e. g. N2, P2 and P3, Error-Related Negativity, Bénar et al, 2007;Debener et al, 2005;Eichele et al, 2005;Mantini et al, 2009;Mulert et al, 2004;Strobel et al, 2008;Warbrick et al, 2009). More importantly, the feasibility work above has been concerned with the detection of ERP components (peaks), whereas cognitive neuroscientists tend to investigate modulations of the amplitude, latency and scalp distribution of these components by specific experimental manipulations.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Detection of experimental ERP effects in combined EEG–fMRI: Evaluating the benefits of interleaved acquisition and Independent Component Analysis

Lavric

Bregadze

Benattayallah

2011

Clinical Neurophysiology

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Objective: The present study examined the benefit of rapid alternation of EEG and fMRI (a common strategy for avoiding artifact caused by rapid switching of MRI gradients) for detecting experimental modulations of ERPs in combined EEG-fMRI. The study also assessed the advantages of aiding the extraction of specific ERP components by means of signal decomposition using Independent Component Analysis (ICA).Methods: 'Go-nogo' task stimuli were presented either during fMRI scanning or in the gaps between fMRI scans, resulting in 'gradient' and 'no gradient' ERPs. 'Go-nogo' differences in the N2 and P3 components were subjected to conventional ERP analysis, as well as single-trial and reliability analyses.Results: Comparable N2 and P3 enhancement on 'nogo' trials was found in the 'gradient' and 'no-gradient' ERPs. ICA-based signal decomposition resulted in better validity (as indicated by topography), greater stability and lower measurement error of the predicted ERP effects. Conclusions:While there was little or no benefit of acquiring ERPs in the gaps between fMRI scans, ICA decomposition did improve the detection of experimental ERP modulations.Significance: Simultaneous and continuous EEG-fMRI acquisition is preferable to interleaved protocols. ICA-based decomposition is useful not only for artifact cancellation, but also for the extraction of specific ERP components. ABSTRACTObjective: The present study examined the benefit of rapid alternation of EEG and fMRI (a common strategy for avoiding artifact caused by rapid switching of MRI gradients) for detecting experimental modulations of ERPs in combined EEG-fMRI. The study also assessed the advantages of aiding the extraction of specific ERP components by means of signal decomposition using Independent Component Analysis (ICA).Methods: 'Go-nogo' task stimuli were presented either during fMRI scanning or in the gaps between fMRI scans, resulting in 'gradient' and 'no gradient' ERPs. 'Go-nogo' differences in the N2 and P3 components were subjected to conventional ERP analysis, as well as single-trial and reliability analyses.Results: Comparable N2 and P3 enhancement on 'nogo' trials was found in the 'gradient' and 'no-gradient' ERPs. ICA-based signal decomposition resulted in better validity (as indicated by topography), greater stability and lower measurement error of the predicted ERP effects. Conclusions:While there was little or no benefit of acquiring ERPs in the gaps between fMRI scans, ICA decomposition did improve the detection of experimental ERP modulations.Significance: Simultaneous and continuous EEG-fMRI acquisition is preferable to interleaved protocols. ICA-based decomposition is useful not only for artifact cancellation, but also for the extraction of specific ERP components.

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Spatiotemporal Dynamics of Error Processing Dysfunctions in Major Depressive Disorder

Holmes

Pizzagalli

2008

Arch Gen Psychiatry

251

231

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Unmedicated patients with MDD showed reduced accuracy and potentiated error-related negativity immediately after committing errors, highlighting dysfunctions in the automatic detection of unfavorable performance outcomes. New analytic procedures allowed us to show that abnormal reaction to committing errors was accompanied by hyperactivation in rostral ACC and medial PFC regions 80 milliseconds after committing errors and a failure to recruit dorsolateral PFC-based cognitive control. Future studies are warranted to investigate whether these dysfunctions might foster the emergence and maintenance of negative processing biases and thus increase vulnerability to depression.

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Integration of fMRI and simultaneous EEG: towards a comprehensive understanding of localization and time-course of brain activity in target detection

Cited by 558 publications

References 52 publications

Shared electrophysiology mechanisms of body ownership and motor imagery

Shared electrophysiology mechanisms of body ownership and motor imagery

Detection of experimental ERP effects in combined EEG–fMRI: Evaluating the benefits of interleaved acquisition and Independent Component Analysis

Spatiotemporal Dynamics of Error Processing Dysfunctions in Major Depressive Disorder

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