A neural population model-based characterization and modulation of neural oscillations underlying cognitive control in healthy and depressed/anxious human subjects

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Project Summary Cognitive control, the ability to withhold a default, prepotent response in favor of a more adaptive choice is often compromised across mental disorders such as depression and anxiety. Thus, a method for improving cognitive control could be broadly useful in disorders with few effective treatments. Successfully resolving conflicts is a form of cognitive control where one must suppress a natural response to follow a less intuitive rule. Conflict processing evokes theta (4-8 Hz) oscillations in the cingulate and medial prefrontal cortex (PFC) which can be measured through invasive intracranial EEG (iEEG) as well as frontal midline scalp EEG. Chronic as well as intermittent short trains of high frequency capsular/striatal stimulation have been shown to enhance theta oscillations while improving performance on a conflict task. Furthermore, deep brain stimulation (DBS) of the internal capsule or subthalamic nucleus and transcranial current stimulation of the lateral PFC all improve performance on cognitive control tasks. These findings strongly suggest that we can modulate both cognitive control and its neural signatures by targeting the relevant brain circuits with external electrical stimulation. The goal of this research proposal is to characterize and model cortical oscillations underlying the conflict resolution aspect of cognitive control in the healthy and anxious/depressed mental states to inform design of neuromodulation interventions for restoration towards healthy mental states. We will take three complimentary approaches to achieve this goal. 1) Using iEEG recorded in epilepsy patients undergoing invasive monitoring for surgical evaluation, we will determine cortical neural oscillations underlying cognitive control in the framework of a conflict task. We will also use this to differentiate between normal and depressed or anxious subjects. 2) We will use a neural population cortical model to simulate and characterize feasible neural mechanisms underlying PFC and temporal cortical oscillations observed during conflict processing. We will use a data driven approach for estimating relevant model parameters. 3) We will use the model calibrated to individual subjects to design a cortical electrical stimulation paradigm to modulate the simulated oscillations towards a desired healthy state. We will then validate our model by testing model predictions in our human subjects and determine if we can successfully change both neural signals as well as associated behavior. Together, this will lead to a biophysically motivated model to simulate neural oscillations underlying conflict processing in healthy and pathological states and allow us to design stimulation paradigms to modulate them. This will also provide new insight into targeted neuromodulation, such as cortical stimulation for therapeutic purposes and the knowledge gained will potentially inform other functional domains compromised in mood/anxiety disorders.