Biomedical Engineering and Bioengineering Commons^™

Neural Correlates Of Multisensory Integration For Feedback Stabilization Of The Wrist, Aaron J. Suminski, Raymond C. Doudlah, Robert A. Scheidt

Biomedical Engineering Faculty Research and Publications

Robust control of action relies on the ability to perceive, integrate, and act on information from multiple sensory modalities including vision and proprioception. How does the brain combine sensory information to regulate ongoing mechanical interactions between the body and its physical environment? Some behavioral studies suggest that the rules governing multisensory integration for action may differ from the maximum likelihood estimation rules that appear to govern multisensory integration for many perceptual tasks. We used functional magnetic resonance (MR) imaging techniques, a MR-compatible robot, and a multisensory feedback control task to test that hypothesis by investigating how neural mechanisms involved in …

Eeg And Fmri Coupling And Decoupling Based On Joint Independent Component Analysis (Jica), Nicholas Heugel, Scott A. Beardsley, Einat Liebenthal

Biomedical Engineering Faculty Research and Publications

Background

Meaningful integration of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) requires knowing whether these measurements reflect the activity of the same neural sources, i.e., estimating the degree of coupling and decoupling between the neuroimaging modalities.

New method

This paper proposes a method to quantify the coupling and decoupling of fMRI and EEG signals based on the mixing matrix produced by joint independent component analysis (jICA). The method is termed fMRI/EEG-jICA.

Results

fMRI and EEG acquired during a syllable detection task with variable syllable presentation rates (0.25–3 Hz) were separated with jICA into two spatiotemporally distinct components, a primary …