- Thursday, June 24th 2021 at 16:00 - 17:00 UK (Other timezones)
- General participation info | Participate online | + Phone in Meeting ID: 972 4297 4350 Passcode: 205293 Find your local number: https://ucl.zoom.us/u/aedyEiW1A6
Electro- and Magneto-encephalography (E/MEG) are the leading methods to non-invasively record human neural dynamics with millisecond temporal resolution. However, it can be extremely difficult to infer the underlying cellular and circuit level origins of these macro-scale signals without simultaneous invasive recordings. This limits the translation of E/MEG into novel principles of information processing, or into new treatment modalities for neural pathologies and psychiatric disorders. To address this need, we developed the Human Neocortical Neurosolver (HNN): a new user-friendly neural modeling tool designed to help researchers and clinicians interpret human imaging data (https://hnn.brown.edu, Neymotin et al., eLife 2020). A unique feature of HNN’s model is that it contains enough detail to account for the biophysical origin of E/MEG signals enabling direct comparison between model output and source localized data with equal units (Am). Further, cell and circuit level simulations provide a direct connection to microcircuit level dynamics that can be studied in animals. HNN’s interactive graphical user interface and workflows allow users to develop and test predictions on the origin of the most commonly measured signals, including event related potentials (ERPs) and low frequency oscillations. In this talk, I will give an overview of the theory behind the development of this tool and demonstrate its use in studying prominent 15-19Hz beta frequency oscillations implicated to be disrupt in several psychiatric conditions. Overall, HNN provides a novel inferential tool for translational neuroscience discovery.