Instrumentation for Measuring MEG Signals

Abstract

To measure weak magnetoencephalography (MEG) signals, two basic technical requirements are sensitive magnetic sensors and reduction of environmental noises. Until now, magnetic field sensors based on superconducting quantum interference devices (SQUIDs) made from low-temperature superconductors are the main sensors used for measuring MEG signals. For effective reduction of strong environmental magnetic noise, combination of magnetic shielding and gradiometers (hardware and/or software) are typically used. Since SQUIDs are very sensitive devices, care should be taken in handling them and in using them for multichannel MEG sensor arrays. Electrostatic shocks or strong magnetic fields can damage the normal operation of SQUIDs. Cooling of the SQUIDs needs a helmet-shape dewar which should provide reliable operation for longer than 1 year in vacuum tightness, and boil-off of the liquid He should be optimized to have refill interval longer than 1 week. For economic MEG systems, the SQUID array should be simple in the manufacturing process, and the structure of the sensor array should be compact. For the MEG system to be operated easily, the process for signal acquisition and signal processing devices needs to be simple, using a single personal computer. A magnetically shielded room (MSR) is mandatory for urban hospitals or downtown laboratory environments. Considering the high cost of magnetic alloy used in the construction of a MSR, optimization and cost-effective construction is needed. Even if the MEG measurements are done in a quiet or well-shielded environment, the signal-to-noise ratio of MEG signals are not sufficiently high, and signal processing is needed to remove some artifacts generated from the human body. This chapter presents basic technical issues for MEG instrumentation, especially in fabricating and operating economic MEG systems. In the later part of this chapter, atomic magnetometers for future non-cryogenic MEG systems, and brain magnetic resonance based on low-field nuclear magnetic resonance for visualizing brain functional activity are described.