. The decisions we make day-to-day are motivated by our intrinsic drives to approach rewarding, and avoid punishing, outcomes. These drives conflict in decisions with both rewarding and punishing outcomes (termed ?approach-avoidance conflict?, AAC). Each individual's balance of reward- and punishment- drives bias the approach or avoidance of a given AAC decision. Affective disorders are characterized by a disruption in this balance, causing greater avoidance in AAC decisions. Therefore, it is critically important to elucidate the neural substrates underlying reward- and punishment- drives, and how their disruption constitutes clinically imbalanced behavior. However, while neuroimaging work has corroborated a correlational relationship of the amygdala and prefrontal cortex to avoidant behavior in humans, no study has mapped the amygdala's direct electrophysiological signals (i.e., non-BOLD) relevant to AAC behavior in humans, nor substantiated its causal influence on circuit dynamics and output behavior. The goal of the current work is to elucidate the amygdala's causal role in approach- and avoidance-driven behavior, and the functional relevance of the prefrontal cortex to this relationship. The primary hypothesis is that the amygdala will actively drive avoidance through its connectivity with the prefrontal cortex. The hypothesis will be tested with three primary aims: 1) To map amygdala electrophysiology relevant to behavior during AAC using invasive amygdala recordings (iEEG) 2) To examine the causal role of the amygdala in AAC by inhibiting it using direct amygdala stimulation and 3) To elucidate the prefrontal cortical activation, in operation with the amygdala, as a function of AAC behavior by recording high-density cortical electroencephalogram (hdEEG) simultaneous to iEEG. AAC behavior will be quantified using a novel, validated task assessing approach-avoidance conflict drives. All electrophysiological recordings and stimulation will be delivered during the task. Amygdala signal will be primarily quantified as the high gamma power signal recorded with iEEG. Prefrontal cortical signal will be primarily quantified as the theta-band power recorded with hdEEG. Connectivity between the amygdala and prefrontal cortex will be quantified through theta-gamma coupling metrics. This proposal is innovative as it leverages the integration of cutting-edge cognitive neuroscience methods to characterize the neural signal driving avoidance behavior in humans. Regardless of the outcomes, the study will generate new questions in the field, and provide a rigorous benchmark against which to hold further work in the field. Findings from the proposed work will provide critical information to the field regarding the neural features driving avoidance symptomatology in affective disorders.
The proposed research is relevant to public health because a characterization of the role of the amygdala and prefrontal cortex in avoidance will provide a valuable biomarker for the targeted treatment to alleviate clinical symptomatology in affective disorders such as post-traumatic stress disorder, generalized anxiety disorder and major depressive disorder. Thus, the proposed research is relevant to the part of NIH's mission that pertains to developing fundamental knowledge that will help to reduce the burdens of human illness and disability.
