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HRMEG: High-resolution magnetoencephalography: Towards non-invasive corticography

Periodic Reporting for period 3 - HRMEG (HRMEG: High-resolution magnetoencephalography: Towards non-invasive corticography)

Reporting period: 2019-09-01 to 2021-02-28

Human brain function can be studied non-invasively with several methods. For example, using a variant of magnetic resonance imaging, one can monitor changes in the flow of oxygenated blood to get indirect information about brain activations. This method – called functional magnetic resonance imaging or fMRI for short – is spatially rather accurate but unfortunately too slow to track neural events at the speed they occur. Measuring the electric activity of neurons directly gives high temporal resolution and enables monitoring neural processing at its native speed. Such measurements can be carried out by recording the neurally-generated electric potential differences on the scalp (electroencephalography or EEG) or the magnetic fields just outside of the head (magnetoencephalography or MEG). Due to the varying conductivities of the intervening tissues, the spatial resolution of EEG is inferior to that of MEG. Therefore, out of the non-invasive neuroimaging methods that can track neural events at the speed they occur, MEG is considered to have the best spatial resolution.

However, current MEG system are still limited in spatial resolution since the employed superconducting sensors must be kept several centimeters away from the scalp of the study subject, which reduces signal strength and decreases spatial resolution compared to having the sensors right on the scalp. Interestingly, recent advances in quantum optics have provided a novel magnetic sensing technology – optically-pumped magnetometer – that enables constructing non-superconducting yet sufficiently sensitive sensors for MEG. This high-resolution magnetoencephalography (HRMEG) project leverages these developments and aims at constructing a novel MEG whose spatial resolution outperforms that of current MEG systems. The higher spatial resolution enables non-invasive recordings of certain brain signals, particularly the so-called gamma-band signals, in unprecedented fidelity. Importantly, this higher resolution can be achieved in study subjects of all ages, unlike in conventional MEG where the sensor array cannot be adapted e.g. to the smaller heads of children.

The HRMEG approach and system opens a new way to study the working human brain. It will likely be applied first in basic neuroscientific research of sensory and cognitive functions but will hopefully be translated also to clinical use, where it could significantly improve diagnostics of certain neurological diseases and ameliorate pre-surgical evaluation of epilepsy patients.

The HRMEG project encompasses the design and construction of a high-resolution MEG system employing optically-pumped magnetometers. Such a system comprises not only the sensors but subsystems to control the sensors, acquire the signals, suppress external magnetic interference and perform co-registration with MR-images. The project also entails development and adaptation of data analysis techniques for such a system as well as applications of the system for brain–computer interfaces and characterization of brain responses to continuous naturalistic sensory stimuli such as movies.
The first half of the project has focused on the development of the measurement system. To this end, we have constructed a helmet that holds a set of optically-pumped magnetometers at freely-selectable locations around the head of the subject. In this helmet, the depth of the individual sensors can be adjusted such that they just touch the scalp of the subject, optimally accommodating all subjects irrespective of their head size and shape. To ensure proper operation of the sensors and to reduce external magnetic interference, we have also designed and constructed a compensation coil system that is placed around the sensor array; the currents in the compensation coils are dynamically controlled by signals from the magnetometers such that the magnetic field is kept below 1 nT (nanotesla) in all three directions of the field (Iivanainen et al., 2019a). We have also developed a system that optically measures the positions and orientations of the sensors with respect to the head surface of the subject. By combining this information with the structural magnetic resonance images of the subject, we can accurately estimate the locations and strengths of the neural sources underlying the measured magnetic signals (Zetter et al. 2018; 2019).

Although we will continue improving the system hardware, we have already performed the first human measurements; we presented the subjects with dynamic visual stimuli while recording HRMEG with the sensors placed on the occipital part of the head, i.e. above the visual cortices. The HRMEG system detected clear visually-induced responses, including suppression of the alpha activity at around 10 Hz and elevation of both narrow-band (30-40 Hz) and broad-band gamma (above 50 Hz) activity. We compared the HRMEG results with those obtained with conventional MEG in the same subjects and found that HRMEG yielded better signal-to-noise ratio and was able to better separate activatios in the two gamma bands (Iivanainen et al., 2019b).

In anticipation of applying the HRMEG system to brain–computer interfacing, we have developed a convolutional neural network classifier that allows training across multiple subjects' MEG data and rapid adaptation to the invidual's MEG responses (Zubarev et al., 2019).

The main result of the first half of the project is a working HRMEG system, with which we have successfully performed initial human brain measurements.
Within its limited scope, the constructed system performs better than current state-of-the-art MEG systems based on conventional technology: the HRMEG system yields better signal-to-noise ratio and spatial resolvability of neocortical brain sources and enables the sensor array to be adapted to the head size and shape of the subject, which is particularly important when studying children. Our current HRMEG system only covers roughly one lobe of the brain but that has already turned out to be sufficient to demonstrate these advantages with respect to conventional technology.

Further improvements in the instrumentations will take place towards the end of the project and, importantly, the system will be applied to address neuroscientific questions beyond the possibilities of current non-invasive brain imaging methods.
HRMEG setup for measuring brain responses to visual stimuli (FIg. 1) and results (Fig. 2)