DICs

DICS, short for Dynamic Imaging of Coherent Sources, is a frequency-domain beamforming technique used in electroencephalography (EEG) and magnetoencephalography (MEG) to localize the sources of oscillatory brain activity and to map functional connectivity at specific frequencies. It is designed to identify where in the brain rhythmic activity at a given frequency originates, and how activity at different locations may be coherent.

Method and principle: DICS builds spatial filters for each location in a predefined source space using the lead-field matrix and the cross-spectral density (CSD) matrix derived from sensor data at the frequency of interest. The filters are constructed so that signals from the target location are passed with minimal attenuation while signals from elsewhere are suppressed. The estimated source power at a location is obtained by applying the filter to the CSD; coherence or coupling between locations can be assessed from the cross-spectral relationships.

Development and use: DICS emerged as a frequency-domain counterpart to time-domain beamformers like the LCMV approach. It has become a standard tool for localizing generators of brain rhythms in EEG/MEG studies and for investigating functional connectivity within specific frequency bands, such as alpha or beta bands.

Advantages and limitations: DICS is well suited to studying oscillatory activity and frequency-specific connectivity. Its accuracy depends on a good forward model, accurate CSD estimation, and adequate signal-to-noise ratio. It can be challenged by highly correlated source activity and model misspecification, which can reduce localization precision.

Software availability: Implementations exist in major neuroimaging toolkits, including FieldTrip (MATLAB) and MNE-Python, among others.

Etymology and note: The term DICS is usually capitalized as an acronym, though you may encounter lowercase in informal references.