Principles of flexible computation
Discovering principles of flexible information processing in the cortex is critical to understanding the mechanisms of brain-state dependent sensory processing and cognition. We investigate the principles of flexible computations in multiple neural substrates: synaptic integration in single neurons, dynamics in excitatory-inhibitory networks, information routing between networks. In combination with theoretical frameworks such as dynamical systems and information theory, we use tools such as probabilistic graphical models, unsupervised learning, multicompartmental biophysical models and phenomenological models to conduct our research. Work in our group ranges from purely computational to active collaborations with experimental groups at WTI and beyond.
Monika Jadi received her Bachelor's degree in 1995 from the Visvesvaraya National Institute of Technology in Electrical Engineering and her Doctoral degree in 2010 from the University of Southern California in Biomedical Engineering (Neuroengineering). She did her post-doctoral research at the Salk Institute and started her lab at Yale in 2017. She enjoys practicing the classical dance form of Kathak and the outdoors.