Year-end Sale % OFF 
Abstract
In the last decade, an increasing interest has arisen in investigating the relationship between the electrophysiological and hemodynamic measurements of brain activity, such as EEG and (BOLD) fMRI. In particular, changes in BOLD have been shown to be associated with changes in the spectral profile of neural activity, rather than with absolute power. Concurrently, recent findings showed that different EEG rhythms are independently related to changes in the BOLD signal: therefore, it would be also important to distinguish between the contributions of the different EEG rhythms to BOLD fluctuations when modeling the relationship between the two signals. Here we propose a method to perform EEG-informed fMRI analysis where the changes in the spectral profile are modeled, and, at the same time, the distinction between rhythms is preserved. We compared our model with two other frequency-dependent regressors modeling using simultaneous EEG-fMRI data from healthy subjects performing a motor task. Our results showed that the proposed method better captures the correlations between BOLD signal and EEG rhythms modulations, identifying task-related, well localized activated volumes. Furthermore, we showed that including among the regressors also EEG rhythms not primarily involved in the task enhances the performance of the analysis, even when only correlations with BOLD signal and specific EEG rhythms are explored.
Highlights
The complementary features of electroencephalography (EEG) and blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) constituted the basis for recent developments in the integration of these neuroimaging modalities (Liu et al, 1998, 2006; Dale et al, 2000; Babiloni et al, 2005; He and Liu, 2008)
STIMULUS ONSET-BASED fMRI ANALYSIS The results of the SO fMRI analysis showed activations related to the performed motor task
In this paper, we investigated the relationship between neural activity and BOLD signal in simultaneously acquired EEG and www.frontiersin.org fMRI data during a motor task in healthy human subjects
Summary
The complementary features of electroencephalography (EEG) and blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) constituted the basis for recent developments in the integration of these neuroimaging modalities (Liu et al, 1998, 2006; Dale et al, 2000; Babiloni et al, 2005; He and Liu, 2008). Some attempts have been made in order to achieve a better understanding of the frequency-dependent neurovascular coupling In this framework, Goense and Logothetis (2008) used simultaneous intra-cortical LFP-BOLD recordings and a multiple regression model, in which activity in many different frequency bands, covering the entire LFP range of frequencies, was employed to predict BOLD activity in alert behaving monkeys. The authors linked these two observations through a dimensional analysis, proposing a “Heuristic” model, hereinafter named HEU. Such model states that BOLD activations are accompanied by an increase of the “average” frequency of the EEG neural activity, and it defines the average in the root mean square (RMS) sense. The HEU model was tested by Rosa et al (2010) on EEG-fMRI data recorded during a visual stimulation, and showed the ability to provide a better fit than the model proposed by Goense and Logothetis (2008), where no shift
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
