Lilianne R. Mujica-Parodi is Director of the Laboratory for Computational Neurodiagnostics (LCNeuro). LCNeuro’s research focuses on the application of control systems engineering and dynamical systems to imaging-derived time series, at all scales: from human fMRI, M/EEG, fNIRS to rodent LFP and calcium imaging. Our aim is to develop computational neuroscience models able to predict individual-specific clinical trajectories for neurological and psychiatric disorders. The parallel development of instrumentation complements our analytical approaches by optimizing brain time series for dynamic fidelity.
One of LCNeuro’s primary goals is to identify key points of failure in the regulation of neural control circuits which, depending upon how they break, lead to signs and symptoms that cluster as distinct psychiatric diagnoses. As a test case for this approach, we are working to understand how the prefrontal-limbic circuit “computes” potential threat in the face of incomplete sensory data, across a clinical spectrum that ranges from pathological fear (generalized anxiety disorder, phobia, post-traumatic stress disorder, paranoid schizophrenia) to recklessness.
A second direction at LCNeuro considers fMRI connectivity as the solution to an optimization problem imposed, in part, by metabolic constraints at the mitochondrial scale. Theoretically, we use biomimetic modeling to predict trajectories, based on biological “rules” of energy optimization, which are then validated against data. Experimentally, we expand and contract neurons’ access to energy while observing consequent self-organization and re-organization of networks. We hope that that this work will help us understand, as well as ultimately prevent and treat, brain aging; specifically, the epidemiologically observed impact of insulin resistance on cognitive decline.
The third arm of our research works on maximizing signal/noise for fMRI data, using a combination of acquisition parameters and artifact-removal. Both require access to a “ground truth” for time series dynamics, which led to our invention (with Helmut Strey, Ph.D.) of a patent-pending calibration device (BrainDancer Dynamic Phantom for fMRI), in commercial partnership with ALA Scientific Instruments, Inc.
Ph.D. Columbia University
Mujica-Parodi LR, Amgalan A, Sultan SF, et al. Diet modulates brain network stability, a biomarker for brain aging, in young adults. Proc Natl Acad Sci U S A. 2020;117(11):6170‐6177. doi:10.1073/pnas.1913042117
Mujica-Parodi LR, Strey HH. Making Sense of Computational Psychiatry. Int J Neuropsychopharmacol. 2020;23(5):339‐347. doi:10.1093/ijnp/pyaa013
Mujica-Parodi LR, Cha J, Gao J. From Anxious to Reckless: A Control Systems Approach Unifies Prefrontal-Limbic Regulation Across the Spectrum of Threat Detection. Front Syst Neurosci. 2017;11:18. Published 2017 Apr 7. doi:10.3389/fnsys.2017.00018
2010 National Science Foundation Career Award
2011 Presidential Early Career Award for Scientists and Engineers (White House, Washington DC)
2017 W.M. Keck Foundation Research Award