Modulation of network dynamics across mood states using closed-loop deep brain stimulation for depression

Major Depressive Disorder (MDD) is a prevalent and debilitating disorder, where one-third of this population is treatment-resistant. Depression is characterized by cognitive dysfunction, including deficits in cognitive control, defined as flexible adaptation of cognitive and behavior commensurate with one’s current goals. Application of deep brain stimulation (DBS), a common therapy used for treatment-resistant depression (TRD), has previously shown enhancement in cognitive control during experimental tasks, but therapeutically shown mixed results, and our understanding of the effect of DBS on neural dynamics in brain networks associated with impaired cognitive dysfunction and control in neuropsychiatric disorders is not well-known. In addition, our understanding of how the frequency of neurostimulation plays a role in modulating neural activity and communication in cognitive control networks in depression is limited. To tackle these unknowns, in the F99 phase, Anusha will collect intracranial local field potential recordings (LFP) through depth electrodes implanted across the prefrontal cortex, orbitofrontal cortex, amygdala and anterior cingulate cortex in patients with TRD, recruited through a parent UH3 study (UH3-NS103549). Participants perform a cognitive control behavioral task before, and during high-frequency electrical stimulation delivered through DBS electrodes implanted in the ventral capsule/ventral striatum and subcallosal cingulate. Additionally, Anusha will collect LFP recordings during stimulation experiments where a range of electrical stimulation frequencies (6,50,130 Hz) are applied systematically during resting state through DBS electrodes. Using the collected data, Anusha will characterize behaviorally defined cognitive control subnetworks in participants with TRD, and explore the effect of low-frequency oscillations that are known to be associated with conflict processing and cognitive control in healthy subjects. She will expand this work to perform functional connectivity analysis during the behavioral task. Anusha will also apply these techniques for analysis of data collected in stimulation experiments during resting state. Understanding cognitive control is imperative to not only improving our understanding of cognitive dysfunction in depression, but is a step towards individualizing and optimizing therapy around electrophysiological markers associated with behavioral impairment in neuropsychiatric disorders, in lieu of or in addition to clinical evaluation of symptoms. In the K00 phase, Anusha will extend her research to more granular circuit dissection using rodent models of psychiatric disease, and leverage her doctoral training in statistical and computational neuroscience to analyze data from such studies, while continuing to perform research in human subjects to study cognitive control. The proposed training during the F99 and K00 phases will ensure multidisciplinary training to reach her career goal as an independent research investigator focused on using a multidisciplinary approach to help achieve a comprehensive understanding of cognitive dysfunction in neuropsychiatric disorders.