On-scalp MEG using high-Tc SQUIDs: Measuring brain activity with superconducting magnetometers
This thesis describes work done towards realizing on-scalp magnetoencephalography (MEG) based on high critical temperature (high-Tc) superconducting quantum interference device (SQUID) sensors. MEG is a non-invasive neuroimaging modality that records the magnetic fields produced by neural currents with good spatial and high temporal resolution. However, state-of-the-art MEG is limited by the use of liquid helium-cooled sensors (T ~ 4 K). The amount of thermal insulation between the sensors and the subject's head that is required to achieve the extreme temperature difference (~300 K), typically realized in the form of superinsulation foil and ~2 centimeters of vacuum, limits measurable signals. Replacing the sensors with high-Tc SQUIDs can mitigate this problem. High-Tc SQUIDs operate at much higher temperatures (90 K) allowing significant reduction of the stand-off distance (to ~1 mm). They can furthermore be cooled with liquid nitrogen (77 K), a cheaper, more sustainable alternative to the liquid helium used for cooling in conventional MEG systems.
The work described in this thesis can be divided into three main areas: (I) simulation work for practical implementations of on-scalp systems, (II) development of a 7-channel high-Tc SQUID-based on-scalp MEG system, and (III) on-scalp MEG recordings.
In the first part, spatial information density (SID), a metric to evaluate the performance of simulated MEG sensor arrays, is introduced and - along with total information capacity - used to compare the performance of various simulated full-head on-scalp MEG sensor arrays. Simulations demonstrate the potential of on-scalp MEG, with all on-scalp systems exhibiting higher information capacity than the state-of-the-art. SID further reveals more homogeneous sampling of the brain with flexible systems. A method for localizing magnetometers in on-scalp MEG systems is introduced and tested in simulations. The method uses small, magnetic dipole-like coils to determine the location and orientation of individual sensors, enabling straightforward co-registration in flexible on-scalp MEG systems. The effects of different uncertainties and errors on the accuracy of the method were quantified.
In the second part, design, construction, and performance of a 7-channel on-scalp MEG system is described. The system houses seven densely-packed (2 mm edge-to-edge), head-aligned high-Tc SQUID magnetometers (9.2 mm x 8.6 mm) inside a single, liquid nitrogen-cooled cryostat. With a single filling, the system can be utilized for MEG recordings for >16 h with low noise levels (~0-130 fT). Using synchronized clocks and a direct injection feedback scheme, the system achieves low sensor crosstalk (<0.6%).
In the third part, on-scalp MEG recordings with the 7-channel system as well as its predecessor, a single-channel system, are presented. The recordings are divided into proof-of-principle and benchmarking experiments. The former consist of well-studied, simple paradigms such as auditory evoked activity and visual alpha. Expected signal components were clearly seen in the on-scalp recordings. The benchmarking studies were done to compare and contrast on-scalp with state-of-the-art MEG. To this end, a number of experimental stimulus paradigms were recorded on human subjects with the high-Tc SQUID-based on-scalp systems as well as a state-of-the-art, commercial full-head MEG system. Results include the expected signal gains that are associated with recording on-scalp as well as new details of the neurophysiological signals. Using the previously described on-scalp MEG co-registration method enabled source localization with high agreement to the full-head recording (the distance between dipoles localized with the two systems was 4.2 mm).
Kollektron (A423), MC2, Kemivägen 9, Göteborg
Opponent: Associate Professor Stefania Della Penna, Institute of Advanced Biomedical Technologies and Department of Neuroscience, Imaging and Clinical Sciences, G. D’Annunzio University, Chieti, Italy