Understanding the intricate complexity and dynamics of the human brain is fundamental to elucidating the mechanisms underlying both normal cognitive function and the complex pathophysiology of neurological and psychiatric disorders. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) stand as the primary non-invasive neuroimaging modalities, offering complementary perspectives on brain activity. EEG provides a direct measure of neural electrical activity with high temporal resolution, capturing rapid changes in brain states, while fMRI indirectly assesses neural activity through hemodynamic responses, yielding high spatial resolution and the ability to visualize deep brain structures. This report synthesizes recent breakthroughs in both EEG and fMRI techniques, alongside the biomarkers identified using these methods, for studying brain complexity and dynamics in healthy individuals and those with various neurological and psychiatric conditions. The advancements in high-density EEG systems and sophisticated signal processing, the emergence of mobile EEG for naturalistic data acquisition, and the progress in EEG-based Brain-Computer Interfaces are discussed. Furthermore, the report highlights the impact of advanced analytical methods such as dynamic functional connectivity and the transformative role of Machine Learning (ML) with paradigms from my work on cognitve disorders and human – autonomous car interactions. By examining the established and emerging EEG and fMRI biomarkers across a spectrum of brain states and disorders, this report underscores the crucial role of these neuroimaging techniques in advancing our understanding of brain complexity and dynamics and their potential for clinical translation in diagnosis and treatment monitoring.