Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics

• Published in: Annual review of biomedical engineering Vol. 20; p. 171
• Main Authors: He, Bin, Sohrabpour, Abbas, Brown, Emery, Liu, Zhongming
• Format: Journal Article
• Language: English
• Published: United States 04.06.2018
• Subjects: Algorithms; Animals; Bayes Theorem; Brain - diagnostic imaging; Electroencephalography - methods; Electrophysiology - methods; Humans; Magnetic Resonance Imaging - methods; Magnetoencephalography - methods; Neurosciences - trends; Signal Processing, Computer-Assisted; Software; inverse problem; source localization; electrophysiological source imaging; functional connectivity; EEG; MEG
• ISSN: 1545-4274
• DOI: 10.1146/annurev-bioeng-062117-120853

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.