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Methods to identify brain networks underlying cognition from human neuroscience data

January 11 @ 3:00 pm - 4:00 pm

How does the brain enable a cognitive task, for e.g. memory recall? Specific ‘brain networks’ or selective coalitions of brain regions, support specific cognitive tasks. EEG and MEG (Electro- and Magneto- encephalography) are valuable technologies to reveal these brain networks. However, they pose a number a technical challenges in accurately identifying these networks. In this talk, I will present two methods we have developed to: 1) identify brain networks in EEG/MEG data while a person is at rest and 2) identify time-varying ‘brain networks’ in EEG/MEG data as a person performs a task. The first method uses a Multivariate Autoregressive (MVAR) framework to identify ‘brain networks’ while the second method combines the MVAR framework with a Markov model to characterise ‘brain networks’ as they change with time. I will present simulation results which validate these methods, as well as crucial and novel insights gained from applying these methods to experimental EEG/MEG data. Finally, I will describe how I will combine these methods in future research, with biologically informed models, to gain fundamental understanding on mechanisms underpinning brain function. These methods and models would provide powerful means for scientists and clinicians to harness the potential of EEG/MEG to illuminate brain function in health and disease. Discipline/Coordinating Entity: Center for Cognitive Sciences


January 11
3:00 pm - 4:00 pm
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