title: Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals.
abstract: Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2-3 days and used 1-2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory.
authors.affiliation: Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Xiang
authors.affiliation: Department of Neurosurgery, Saint Louis University St. Louis, MO, USA.
authors.forename: Qian
authors.initials: Q
authors.lastname: Luo
authors.affiliation: Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA ; Cleveland Clinic Foundation, Department of Radiation Oncology Cleveland, OH, USA.
authors.forename: Rupesh
authors.initials: R
authors.lastname: Kotecha
authors.affiliation: Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA.
authors.forename: Abraham
authors.initials: A
authors.lastname: Korman
authors.affiliation: Department of Communication Sciences and Disorders, University of Cincinnati Cincinnati, OH, USA.
authors.forename: Fawen
authors.initials: F
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences Beijing, China.
authors.forename: Huan
authors.initials: H
authors.lastname: Luo
authors.affiliation: Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA.
authors.forename: Hisako
authors.initials: H
authors.lastname: Fujiwara
authors.affiliation: Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA.
authors.forename: Nat
authors.initials: N
authors.lastname: Hemasilpin
authors.affiliation: Division of Neurology, MEG Center, Cincinnati Children's Hospital Medical Center Cincinnati, OH, USA.
authors.forename: Douglas F
authors.initials: DF
authors.lastname: Rose
keywords: brain; high-frequency oscillations; magnetic source imaging; magnetoencephalography; multi-frequency