Using human brain connectivity to identify the causal neuroanatomical substrate of depression symptoms

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PROJECT SUMMARY Depression is the leading cause of disability worldwide and new treatments are needed. Identifying the brain regions causing depression symptoms can lead to treatment targets and better therapies. However, identifying these regions has been difficult. Neuroimaging of patients identifies brain areas where activity correlates with depression symptoms, but can't determine whether these regions actual cause symptoms. Animal models allow for causal manipulations, but only approximate human symptoms. The goal of this grant is to link depression symptoms to human neuroanatomy in a causal way. Here I focus on two sources of information that can provide theses causal neuroanatomical links. The first is patients with focal brain lesions causing depression symptoms. The second is patients with depression who have received focal brain stimulation for symptomatic relief. In both cases, there is a causal link between symptoms and the site of the lesion or stimulation. However, this causal link can be indirect. Lesion-induced symptoms can come from brain regions connected to the lesion location rather than the lesion location itself. Similarly, benefits of brain stimulation can come from modulation of distant regions connected to the site of stimulation. As such, utilizing these causal sources of information requires a map of human brain connectivity. Due to NIH initiatives like the human connectome project and high powered MRI scanners, such maps are now available. I've recently developed a technique that uses these brain connectivity maps to better localize lesion induced symptoms and identify regions mediating response to focal brain stimulation. Here, I leverage this technique to identify brain regions causing depression symptoms (Aim 1) and brain regions mediating antidepressant response to focal brain stimulation (Aim 2). Successful completion of these aims will lend insight into the causal neuroanatomical substrate of depression symptoms. Such knowledge will facilitate identification of biomarkers for evaluating future therapies, optimal therapeutic targets for invasive and noninvasive brain stimulation, and individualized targets based on patient-specific symptom profiles. These treatment targets can then be empirically tested in future therapeutic trials.