Project Summary/Abstract.
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.