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Brian DePasquale . Postdoctoral Research Associate Princeton Neuroscience Institute Princeton University depasquale {at} princeton {dot} edu . I conduct research in theoretical neuroscience and machine learning. My research uses mathematical models to characterize and explain how populations of neurons perform computations to produce behavior.
Brian DePasquale, Mark M. Churchland, LF Abbott (2016). Using firing-rate dynamics to train recurrent spiking neural networks. Recurrent Spiking Neural Networks—Dynamics, Learning, Computation, COSYNE Workshop, Salt Lake City, UT. Brian DePasquale, Christopher J. Cueva, Raoul-Martin Memmesheimer, LF Ab-bott, G. Sean Escola (2016).
Brian Depasquale. Principal Investigator Assistant Professor of Biomedical Engineering. ORCID bddepasq@bu.edu @briandepasquale Web Google Scholar @briandepasquale. Assistant Professor, Biomedical Engineering. Boston University. (617) 353-2816. Room 413, 44 Cummington Mall, Boston, MA, 02215.
2015. Building functional networks of spiking model neurons. LF Abbott, B DePasquale, RM Memmesheimer. Nature neuroscience 19 (3), 350-355. , 2016. 220. 2016. Task-dependent changes in the large-scale dynamics and necessity of cortical regions.
Brian DePasquale, Ph.D. Assistant Professor (BME) Office ERB 413. Email bddepasq@bu.edu. Phone (617) 353-2816. Website Artificial and Biological Intelligence Lab. Education Postdoctoral training, Princeton Neuroscience Institute. PhD, Columbia University. Primary Appointment Assistant Professor, Department of Biomedical Engineering.
Brian DePasquale, Mark M. Churchland, LF Abbott (2015). Using firing-rate dy-namics to train recurrent spiking neural networks. Annual Tri-Center Gatsby Meeting, Columbia University, NY, NY. Brian DePasquale, Mark M. Churchland, LF Abbott (2014). Using firing rate dy-namics to train spiking neural networks that perform tasks. Techniques and Ap-
Brian DePasquale. Postdoctoral Research Associate Princeton Neuroscience Institute Princeton University depasquale {at} princeton {dot} edu . I conduct research in theoretical neuroscience and machine learning. Presently, I work with Carlos Brody and Jonathan Pillow on latent variable models of evidence accumulation. During my Ph.D.
