The human brain is an extremely complex biological system performing sensory, motor, linguistic and cognitive functions with very rapid neural processes. For centuries, scientists, medical doctors, and philosophers have shown great interest in studying the relationship between the neurophysiological events in the brain and mental events that constitute our cognitive abilities and subjective experiences, producing many exciting discoveries as well as theories and speculations (Gazzaniga, 2004). However, understanding the spatiotemporal dynamics of brain activities remains one of the most intriguing challenges in modern science – how the brain accomplishes its tasks, how its abilities develop and decline, what underlies the various sensory, motor, cognitive and communicative impairments and deficits, and what methods can be selectively applied for the prevention and treatment of the disorders.
Anatomically, the complexity of brain activities involves a network of billions of highly specialized neurons that communicate with each other via trillions of synaptic connections. The inner workings of the neural network largely depend on chemically mediated electric processes, which can be measured online using invasive or noninvasive techniques at various levels. Magnetoencephalography (MEG) is a completely noninvasive imaging technique that measures the exquisitely small magnetic fields outside the brain produced by neuronal currents in many brain regions (Hämäläinen, Hari, Ilmoniemi, Knuutila, & Lounasmaa, 1993; Williamson, Hoke, Stroink, & Kotani, 1989). A closely related and complementary method, electroencephalography (EEG), measures the electric fields of the regional neural activities by using electrodes directly pasted on the scalp to assess brain function at a system level.
Both EEG and MEG are great research tools for cognitive brain studies where temporal information of the evoked brain activities is considered critical. This is due to the fact that both techniques can reveal the time course of neural activation with sub-millisecond accuracy. The recordings can be performed in the absence of any behavioral responses, which makes EEG and MEG suitable for studying populations across the life span in both research and clinical settings. Relatively speaking, the MEG signals are less affected by the individual anatomical differences such as tissue conductivity. When combined with magnetic resonance imaging (MRI) and functional MRI, MEG also has the advantage of providing highly reliable localization of neuronal activity within a few millimeters on an individual basis (Barkley, 2004; Baumgartner, 2004). However, the high cost and technicality associated with MEG equipment using conventional superconducting sensors has been a major limitation on its wide acceptance in practice.