Salvador Dura-BernalView profile
Assistant Professor
Salvador Dura-Bernal, PhD, is an Assistant Professor in the Department of Physiology and Pharmacology at SUNY Downstate Medical Center. He leads a computational neuroscience lab focused on multiscale brain modeling, machine learning applications in neuroscience, and biomimetic neuroprosthetics. His research bridges molecular, cellular, and systems-level neuroscience through biophysically detailed simulations. Developed NetPyNE, an open-source Python package for multiscale neuronal network modeling Collaborates with Nathan Kline Institute and global computational neuroscience organizations Co-Director of SUNY Downstate's Global Center for AI in Mental Health Research interests include: multiscale cortical circuit modeling, neural coding mechanisms, neuroprosthetic systems using spiking networks, and brain-machine interfaces. His work combines supercomputing simulations with experimental data validation, focusing on thalamocortical interactions and neuromodulatory effects. Recent publications demonstrate his team's success in creating biologically accurate models for motor and auditory cortices, with applications in understanding brain disorders and developing treatment strategies. The lab employs machine learning for model optimization and analysis, including evolutionary algorithms and Bayesian networks. 2024: Theoretical thalamus model for deviance detection 2023: Primary motor cortex model validated with in vivo data 2022: Somatosensory thalamocortical NetPyNE implementation Scientific contributions include: SUNY Downstate Annual Research Day best work (2022) Key developer of NetPyNE software Editorial board member for NeuroML NIH reviewer for BRAIN Initiative The lab trains graduate students and postdoctoral fellows, currently mentoring Joao Moreira (M.Sc.) and three postdocs. Research funding includes NIH grants for integrating NetPyNE with The Virtual Brain tool and developing neuroprosthetic systems that could replace damaged brain regions with in silico models.










