Through our resting-state EEG studies using electrical source imaging, we have discovered that EEG connectivity abnormalities serve as a distinguishing factor between individuals with ALS and healthy controls. Furthermore, we have identified disruptions within specific oscillation frequencies, which provide insights into the underlying network dysfunctions associated with the disease. These EEG findings have also demonstrated correlations with structural changes observed in MRI scans as well as clinical motor scores, reinforcing their clinical relevance (Dukic et al., 2019). Notably, our research has unveiled the existence of stable clusters, representing novel phenotypes of ALS (Dukic et al., 2022). Collectively, our work highlights the potential of resting-state EEG as a valuable tool for characterizing and understanding the complexities of ALS.