As Director of the Laboratory for Computational Neurodiagnostics (LCNeuro), Dr. Mujica-Parodi leads a multidisciplinary team working at the intersection of human neuroimaging and computational neuroscience. Her primary area of research is regulatory dynamics of neural control circuits, with applications to psychiatric (anxiety, depression, schizophrenia, bipolar disorder) and neurological (age-based cognitive impairment, epilepsy, ALS) disorders.  Integrating data acquired from animal neuronal recordings (patch clamp, field recordings, calcium imaging, local field potentials) and human neuroimaging (7T fMRI-MRS, M/EEG), LCNeuro leverages multi-scale biophysical modeling to investigate how minute changes in cellular-scale mechanisms (e.g., metabolism) give rise to emergent circuit behavior measured at the clinical scale.  Analytic approaches include those informed by control systems engineering, dynamical systems, and statistical physics (Maximum Caliber, Ising models).  In parallel, these multi-scale, multi-modal circuits are incorporated within Neuroblox (www.neuroblox.ai/docs): a software platform created with Earl Miller (MIT), Alan Edelman (MIT), Richard Granger (Dartmouth), and Helmut Strey (Stony Brook). Neuroblox is designed to permit basic and clinical neuroscientists to run simulations of either hypothesis or data-driven neural circuit architectures, to estimate their behavior under different conditions and their trajectories over time. As researchers identify circuits, those circuits can be independently tested by other users experiments, allowing for community-wide curation of libraries of integrated models, experimentally validated across different species, populations, and applications.