Gulf Coast Consortium for Theoretical and Computational Neuroscience
Leveraging computational power to better understand the mind through researchers empowered to share ideas, information and technology.
The Theoretical and Computational Neuroscience (TCN) provides a mechanism and environment for interactions that potentially could generate novel projects of a significant scale outside of the reach of any one institution. From a research perspective, the TCN serves as a catalyst that attracts and unites those interested in theoretical or computational neuroscience, pools resources and expertise, and results in inter-institutional collaborations that compete for grants.
Please join us for: GCC for Theoretical and Computational Neuroscience 15th Annual Conference, January 26, 2018
Confirmed speakers include Stuart Geman, James Manning Professor of Applied Mathematics, Brown University; Cristina Savin, Assistant Professor of Neural Science and Data Science, New York University Center for Data Science; and Shaul Druckman, Visiting Scientist and Group Leader, Janelia Research Campus. Registration and Agenda
The conference and poster session will be at the BioScience Research Collaborative, 6500 Main St. Organizers are Fabrizio Gabbiani, BCM; Krešimir Josić, UH; Xaq Pitkow, Rice and BCM; Harel Shouval, UTHealth.
First Center for Neuroscience and Machine Learning NeuroNex Workshop, January 25
Registration and Agenda
Experimental Neuroscience has successfully identified the molecules and many of the neural pathways of the mind. In a number of important cases, e.g., spatial memory in rats, it has directly linked these players and pathways to behavior. In many cases it remains, however, unclear to what extent these finding actually "explain" behavior. For although our neurons share a common chemical composition, there are over 100 billion neurons per brain--each talking with approximately 10000 of its neighbors across synapses that are rapidly strengthened or weakened as a function of activity.
In order to bridge mind and molecule we must tame this neural net. The complexity of the net, together with its ability to change under our eyes, argues against relying solely on intuition and for the construction of a theoretical framework that yields computationally tractable predictions and helps guide further experiment.
Traditional Neuroscience uses reductionism to formulate hypotheses and tests them experimentally, while Theoretical and Computational Neuroscience builds on Information Theory, Dynamical Systems Theory, and Computer Science to create theoretical models to be tested numerically. Collaborations of neuroscientists, individually trained in experimental and computational approaches, are not unusual on the basis of experimental data. In extension of this, we advocate a synergistic use of both approaches to control the experiment itself. Commensurate with our escalating knowledge of neural function, the complexity of experiments to analyze both healthy and diseased brain function is ever-increasing. In this situation, it is necessary to utilize the analytic and predictive nature of Theoretical and Computational Neuroscience not only between but rather during experiments.
Krešimir Josić, PhD, University of Houston
Harel Shouval, PhD, The University of Texas Health Science Center at Houston
Fabrizio Gabbiani, PhD, Baylor College of Medicine
Prahlad Ram, PhD, MD Anderson Cancer Center
Kelly Dineley, PhD, The University of Texas Medical Branch at Galveston
Xaq Pitkow, PhD, Baylor College of Medicine/Rice University
All faculty participating in the Theoretical and Computational Neuroscience Consortium are affiliated with one of the Gulf Coast Consortia member institutions:
Baylor College of Medicine
University of Houston
University of Texas Health Science Center - Houston
University of Texas M.D. Anderson Cancer Center
University of Texas Medical Branch - Galveston
Institute of Biosciences and Technology at Texas A&M Health Science Center
neurotheory.net is currently under construction.