Identification of signal propagation through the cortex using hd-EEG, validated with fMRI

The brain has always been of interest to us since we had a basic understanding
of the human body. To understand the brain we need to know how the brain
functions. Multiple devices are capable to do so. Two of the most use
non-invasive devices are functional Magnetic Resonance Imaging (fMRI) and high
density electroencephalography (hd-EEG). These devices enable us to find
functional sources in the brain.
fMRI has a great spatial resolution (~2-3 mm). Its temporal resolution is
rather low (5-6 seconds). Hd-EEG measures electric potentials generated by
cortical areas. This data can be used to reconstruct the activity of sources in
the cortex. This reconstruction is called the inverse problem. Hd-EEG has a
high sampling frequency, but its spatial resolution is low (~5-6 mm). fMRI and
hd-EEG are coupled by the metabolism of the neuron. If a neuron is more active,
it requires more oxygen. This requires vascodilation in that area.
The inverse problem has seen many solutions over the years. These can be
seperated into two categories, the dipole source algorithms and the distributed
source algorithms. The inverse problem solvers can be regulated in multiple
ways. One of these inverse problem solvers is the Variational Bayesian
Multimodal ElectroencephaloGraphy (VBMEG) algorithm.
A previous proof-of-principle study concluded that the VBMEG algorithm can
track the dynamic information flow in the brain. The algorithm uses hd-EEG data
as input. This data can be supplemented with MRI, dMRI and fMRI data to
increase the accuracy of the algorithm.
The algorithm has been tested using simulations and in studies with visual
parameters as input. What has not been validated is the comparison between
hd-EEG source reconstruction using the VBMEG algorithm and fMRI activity maps.
That is what this study is about.

The objective of this study is to validate the VBMEG algorithm by comparing
hd-EEG with fMRI activity. If validated, it will be validated that the accuracy
of the VBMEG algorithm is improved when fMRI is incorporated to the source
reconstruction, compared to the VBMEG algorithm without fMRI.

The study consists of two parts. The first part of the study is the fMRI part,
in which a participant will take place in the MR scanner. A special MR
compatible wrist manipulator robot (MRCWM) has been developed (Dyon Bode, 2017)
which is able to apply a specific motion sequence perturbing a person*s wrist.
The state of the brain is different due to the application of this motion
compared to resting state. If the participant performs different tasks, the
brain is put into different states. The activity can be compared for each state
and Regions of Interest (ROI*s) can be identified.
The second part of the experiment has the participant use the MRCWM while
recording EEG. The tasks performed are the same for fMRI as for EEG. Using the
VBMEG algorithm, DTI and MRI, the sources and dynamic information flow between
sources in the brain can be estimated. EEG source localization is compared to
the fMRI results, validating the spatial accuracy of the VBMEG method. If
validated, the fMRI is introduced to the VBMEG algorithm to validate that the
accuracy is increased compared to EEG input alone.

Participating in the experiment requires participants to visit the Amsterdam
UMC, location AMC once. The visit will last for about 6 hours for the fMRI and
EEG experiments. The risks for the participant are low to non-existent. Below,
the risks are defined which are related to the MR scanner, EEG scanner and the
MRCWM.

Hd-EEG
There are no risks related to the hd-EEG recording. Hd-EEG recordings are safe
and require no burden on the subject, except fatigue due to a long time sitting
still.

MR scan.
The MR scanner has a strong magnet, which results in multiple exclusion
criteria for participants. These participants have implanted pacemaker,
intracranial aneurysm clips, cochlear implants, certain prosthetic devices,
implanted drug infusion pumps, neurostimulators, bone-growth stimulators,
certain intrauterine contraceptive devices or any other type of iron-based
metal implants. Other contraindicators are general metal objects such as
shrapnel, bullets, as well as surgical pins, clips. There are other exclusion
criteria. These are listed in chapter 5.4.

MR Compatible Wrist Manipulator robot (MRCWM)
The MRCWM can apply physically constrained maximum torques (1.5 Nm) and maximum
angles (±67°), pre-set, such that the participant cannot be harmed. Due to the
risk the connection poses between the MR incompatible part and the MR
compatible part, the connection should remain intact as long as possible. Risks
of the MRCWM are defined in the Medical Device Regulation (MDR) and are
considered low