Bayesian Multi--Dipole Modeling in the Frequency Domain

TL;DR

This paper introduces a Bayesian multi-dipole localization method in the frequency domain for EEG/MEG data, providing richer information than existing techniques, validated through synthetic and real data tests.

Contribution

The paper presents a novel Bayesian approach for localizing multiple neural sources in the frequency domain, improving source characterization over traditional methods.

Findings

Performs well under low SNR and correlated sources

Provides richer posterior information than DICS

Confirmed feasibility with real MEG data

Abstract

Background: Magneto- and Electro-encephalography record the electromagnetic field generated by neural currents with high temporal frequency and good spatial resolution, and are therefore well suited for source localization in the time and in the frequency domain. In particular, localization of the generators of neural oscillations is very important in the study of cognitive processes in the healthy and in the pathological brain. New method: We introduce the use of a Bayesian multi-dipole localization method in the frequency domain. Given the Fourier Transform of the data at one or multiple frequencies and/or trials, the algorithm approximates numerically the posterior distribution with Monte Carlo techniques. Results: We use synthetic data to show that the proposed method behaves well under a wide range of experimental conditions, including low signal-to-noise ratios and correlated sources. We use dipole clusters to mimic the effect of extended sources. In addition, we test the algorithm on real MEG data to confirm its feasibility. Comparison with existing method(s): Throughout the whole study, DICS (Dynamic Imaging of Coherent Sources) is used systematically as a benchmark. The two methods provide similar general pictures; the posterior distributions of the Bayesian approach contain much richer information at the price of a higher computational cost. Conclusions: The Bayesian method described in this paper represents a reliable approach for localization of multiple dipoles in the frequency domain.