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To bridge the gap between top-down neuroimaging and bottom-up neuroscience modeling
Current technology does not provide a non-invasive, in vivo assessment of activity at the level of synapses, receptors, and ion channels, which forms the basis of neuronal communication. This limitation is relevant because abnormalities at the microscopic level are thought to underlie complex disorders such as schizophrenia, epilepsy, autism, and Alzheimer’s disease.
In our lab we develop and identify large-scale computational models of brain activity to bridge the gaps in imaging between micro- and macroscopic scales, between structure and function, and to identify key biophysical properties underlying the empirically observed dynamics.
We aim to develop new, innovative methods that enable us to link computational models to individual subject predictions, thus realizing the translational potential of advanced neuroimaging.
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