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

ObjectiveCombining magnetic resonance imaging (MRI) and electroencephalography (EEG) provides a powerful tool for investigating brain function at varying spatial and temporal scales. Simultaneous acquisition of both modalities can provide unique information that a single modality alone cannot reveal. However, current simultaneous EEG-fMRI studies are limited to a small set of MRI sequences due to the image quality and safety limitations of commercially available MR-conditional EEG nets. We tested whether the Inknet2, a high-resistance polymer thick film (PTF) based EEG net that uses conductive ink, could enable the acquisition of a variety of MR image modalities with minimal artifacts by reducing the RF-shielding caused by traditional MR-conditional nets.ApproachWe first performed simulations to model the effect of the EEG nets on the magnetic field and image quality. We then performed phantom scans to test image quality with a conventional copper EEG net, with the new Inknet2, and without any EEG net. Finally, we scanned five human subjects at 3 Tesla (3T) and three human subjects at 7 Tesla (7T) with and without the Inknet2 to assess structural and functional MRI image quality.Main resultsAcross these simulations, phantom scans, and human studies, the Inknet2 induced fewer artifacts than the conventional net and produced image quality similar to scans with no net present.SignificanceOur results demonstrate that high-quality structural and functional multimodal imaging across a variety of MRI pulse sequences at both 3T and 7T is achievable with an EEG net made with conductive ink and polymer thick film technology.

show abstract

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

Sainz Martinez,

Wirsich,

Jäger

et al. 2024

Preprint

View full text Add to dashboard Cite

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.

show abstract

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

Cited by 6 publications

References 44 publications

Tracking head movement inside an MR scanner using electromagnetic coils

Tracking head movement inside an MR scanner using electromagnetic coils

High-quality multimodal MRI with simultaneous EEG using conductive ink and polymer-thick film nets

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

Contact Info

Product

Resources

About