Professor Matthew Chafee PhD

This group analyzes neural dynamics in real and artificial prefrontal networks to understand how neural signals mediate computation and how network failure may lead to human diseases such as schizophrenia. The researchers record neural activity in animal models using electrode arrays. They analyze these neural datasets to measure how behavioral and cognitive variables are encoded by neural activity. They focus on how synaptically mediated interactions between neurons sculpt attractor dynamics in networks. This requires analyzing large amounts of neurophysiological data recorded over many channels acquired at high sampling rates (leading to large data files). The analyses involve fitting statistical models to the data, which is computationally intensive. The researchers also develop artificial neural networks that reveal how synaptically mediated interactions between neurons compute information needed for successful task performance. Training and implementing these network models is computationally intensive.