EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD

Sequential adaptive elastic net (SAEN) approach, complex-valued LARS solver for weighted Lasso/elastic-net problems, and sparsity (or model) order detection with an application to single-snapshot source localization.

Real-time EEG source localization based on Smarting mBrainTrain EEG headset and implemented in Matlab.

Source localization and connectivity analysis of high-density EEG data

ICA preprocessing & source localization for EEG. Please read wiki for detailed info:

Sparsity enables subcortical source estimation, Krishnaswamy et al, PNAS 2017

Coupled matrix-tensor factorization for integrating EEG and ffMRI on the brain cortical surface with source reconstruction

TRAP MUSIC algorithm for MEG/EEG multi-source localization

Code to analyze high-density EEG and concurrent EMG/EOG datastreams during balance perturbations (replicates results from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6088363/)

The Brain Entropy in space and time (BEst) plug-in in the Brainstorm software

Localization of brain sources measured by EEG using 3 approaches: Gibbs sampler (Markov chain Monte Carlo algorithm), Minimum Norm Estimates (MNE) and Source Imaging based on Structured Sparsity (SISSY)

This projects presents a couple of signal methods for detecting and localizing an acoustic signal source by using an Arduino Board and 4 microphones.

Biomedical Signal & Image Processing Lab Projects.

EEG Signal Processing project, solving the brain source localization problem using various methods and models.

Processing bioelectrical signals and medical images

EEG forward problem pipeline