ABSTRACT Depression affects around ten percent of people in the United States. Two-thirds of these patients do not respond to traditional antidepressants and are diagnosed with treatment-resistant depression (TRD). Also, conventional antidepressants take approximately three to four weeks to show effects. Ketamine, a drug that has been traditionally used as an anesthetic agent, represents a promising hope. At doses lower than those utilized for anesthesia, ketamine has been found to improve depressive symptoms in more than half of the patients diagnosed with TRD. Recently, an isomer of ketamine, esketamine, has been approved by the FDA for the treatment of TRD. Repeated dosing of ketamine and esketamine augment their antidepressant effect, prolonging the therapeutic benefit from a few days to up to a few weeks and increasing response and remission rates. Animal models of depression have shown that a single dose of ketamine works by increasing neuroplasticity, the ability of the brain to change and adapt. However, how repeated ketamine treatments augment the antidepressant effect is not known. Understanding the underlying mechanism of augmented therapeutic effect in humans would make it possible to a) prolong ketamine’s antidepressant effect beyond a few weeks, b) increase response and remission rates, and c) develop novel molecules with better response and remission rates. Therefore, we are proposing to combine two techniques to understand the brain changes associated with the augmented improvements in patients. The first technique is electroencephalography (EEG), which monitors the electrical activity of the neocortex, the part of the brain involved in memory, decision making, and mood, features that are affected in depression. Using an EEG task that measures neuroplasticity, we will probe the neocortex to identify changes in neuroplasticity associated with the sustained antidepressant effects in patients diagnosed with TRD treated with repeated ketamine dosing. They will undergo the EEG task before they begin their treatment, after their first treatment, and then again after they finish all their treatments. The second technique is computer modeling of the neocortex using a computer model that has been developed to understand the brain mechanisms generating EEG, called the Human Neocortical Neurosolver (HNN). We will use HNN to make mechanistic interpretations of the neocortical mechanisms underlying the EEG changes associated with the sustained antidepressant effect. This will identify the neocortical changes responsible for the sustained therapeutic response, which may allow for better treatment targeting.