I am a psychiatrist, neurophysiologist, and biomedical engineer who is striving to combine the approaches of all three disciplines to create a new conceptual and practical approach to the treatment of neuropsychiatric disorders. My research program is based on the theory that psychiatric disorders have distinct signatures in terms of abnormal spatiotemporal dynamic patterns of electrical activity in large brain networks. My present research goal is to use mouse models of psychiatric disorders to determine the nature of abnormalities in brain electrical activity, causally restore normal patterns of electrical activity to normalize behavioral symptoms, and understand biomarkers for vulnerability to mood and thought disorders. For example, we have subjected mice to chronic social defeat stress paradigm that creates behavioral abnormalities to model depression. We have shown that symptoms of depression are associated with specific spatiotemporal dynamic abnormalities in the electrical activity among the prefrontal cortex, the amygdala and the ventral tegmental area. We have demonstrated that we can normalize both the electrical activity patterns and the mouse’s behavior with causal stimulation that overrides the abnormal patterns associated with depression. Our long-term goal is to elaborate the findings with an extensive program that involves many models of depression, bipolar disorder, post-traumatic stress disorder, and autism. We use machine-learning approaches to extract the critical spatiotemporal dynamic activity patterns from our electrical neural recordings, and a closed-loop optogenetic stimulation system to create either normal or abnormal activity patterns. In the long-term, we believe that our research program will yield new diagnostic markers for psychiatric disorders based in brain emergent electrical properties and new “brain pacemakers” that directly target aberrant neural networks to cure psychiatric disease.