[Feindel Brain Imaging Lecture] Network Modeling with Biologically-Based Cellular Models - Dr. Frances K Skinner
TheÌýFeindelÌýBrain Imaging Lecture Series
"Network Modeling with Biologically-Based Cellular Models"
Monday, November 23, 2015 at 1:00 pm
de Grandpré Communications Centre, Montreal Neurological Institute
(Toronto Western Research Institute, University Health Network, University of Toronto)
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Abstract:
Due to its complex dynamics and multi-scale structure, it is an extreme challenge to figure out how our brains work. ÌýExperiments alone cannot provide an understanding – modeling and computation are essential. ÌýGiven the high degree of technical expertise required in experimentation, modeling, computation and analyses, it is clear that to move forth in our understanding, open and interactive collaborations between several individuals and disciplines are needed.
Oscillatory activities are produced by several brain structures, including the hippocampus, and have been shown to be important for brain functioning. ÌýThe hippocampus is a heavily studied brain structure due to its importance in learning and memory, as well as being associated with disease states such as epilepsy and Alzheimer’s disease. ÌýIn this talk, I will present some of the modeling work being done in my group to understand the essential features and mechanisms for the generation of rhythmic output in microcircuits of the hippocampus. ÌýThrough collaborative efforts, we have developed and are developing cellular and network models with tight experimental linkages, and in which theoretical insights and constraints can be brought to bear. ÌýWe are using them to help identify critical cellular and synaptic ‘balances’ that underlie population output. ÌýIn this way, we aim to use our models to not only understand normal brain functioning but also diseased states when these balances go awry.
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Brief Bio:
Frances Skinner studied Applied Mathematics and Computer Science at the University of Waterloo (B.Math) and then did graduate studies at the University of Toronto in Biomedical Engineering (M.A.Sc., Ph.D.). ÌýShe got involved in the world of Neuroscience during postdoctoral studies in Boston and California, and has been part of the burgeoning field of Computational Neuroscience ever since. ÌýShe is interested in determining neuronal and network mechanisms that contribute to brain functioning during normal and diseased states. ÌýTo this end, the research in her lab focuses on mathematical model development and usage at the interface of theory, computation, and experiment.
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