The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors

The combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) at ultra-high field (7 Tesla) offers unprecedented possibilities to probe human brain function non-invasively with high coverage, millisecond temporal precision and sub-millimeter spatial precision, unraveling cortical layers and small subcortical structures. Unfortunately, this technique has remained largely inaccessible at 7T, due to prohibitive cross-modal interference effects and physical constraints. Here, we developed a first-of-its-kind EEG-fMRI acquisition framework on a clinical 7T system combining key improvements from previous works: compact EEG transmission chain to reduce artifact incidence, reference sensors for artifact correction, and adapted leads for compatibility with a dense radiofrequency receive-array allowing state-of-the-art fMRI sensitivity and acceleration. Two implementations were tested: one using an EEG cap adapted in-house, and another using a recently-designed prototype from an industrial manufacturer, intended to be further developed into a commercial product accessible to the broader community. A comprehensive evaluation in humans showed that simultaneous acquisitions, including with sub-millimeter fMRI resolution, could be conducted without detectable safety issues or major practical constraints. The EEG exerted relatively mild perturbations on fMRI quality (6–11% loss in temporal SNR), without measurably affecting the detection of resting-state networks and visual responses. The artifacts induced on EEG could be corrected to a degree where the spatial, spectral and temporal characteristics were comparable to outside recordings, and hallmark features such as resting-state alpha and eyes-closing alpha modulation could be clearly detected. Altogether, these findings indicate excellent prospects for neuroimaging applications, that can leverage the unique possibilities achievable at 7T.

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A Novel Approach to Monitor Head Movement Inside an MR Scanner Using Voltages Induced in Coils by Time-Varying Gradients

Bhuiyan,

Chowdhury,

Glover

2023

IEEE Access

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To determine head pose within an MR scanner using measurements of gradientinduced voltage from a multiple coil. A practical implementation of this approach would involve measuring the position-sensitive voltages induced by the imaging gradients rather than additional gradient pulses. This would speed up the model formation phase and increase the temporal resolution of position monitoring. We propose a novel method to measure the gradient-induced voltages in a set of five coils to estimate the position and orientations (POS) into MR scanner. A training set of measurements was first made and then Principal Component Analysis (PCA) was applied to the POS data estimated by using Statistical Parametric Mapping (SPM8), and the principal components were collected into a design matrix. Experimental data were collected and then the coefficients derived from the training set were used to estimate the POS changes and the results compared to movement parameters found using image co-registration. The changes in POS estimated from SPM8 co-registration and from the measured voltages for the phantom and the subject. The differences in the positions were estimated by using SPM8 and the model relating the change in induced voltages to position. The range and root-mean-square (RMS) amplitude of these differences for the phantom/subject data. The results suggest that it is possible to estimate the position and orientation with 0.22mm and 0.24 root-mean-square error using this set-up. The new approach could be used for prospective or retrospective motion correction.

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The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors

Cited by 4 publications

References 44 publications

Tracking head movement inside an MR scanner using electromagnetic coils

Tracking head movement inside an MR scanner using electromagnetic coils

Unlocking new avenues for non-invasive brain monitoring with combined electroencephalography and functional magnetic resonance imaging at ultra-high field

A Novel Approach to Monitor Head Movement Inside an MR Scanner Using Voltages Induced in Coils by Time-Varying Gradients

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