(PS2-69) Characterizing Autogenous and Reactive Obsessions Using Theta and Beta Oscillations Under Inhibitory Demands

Obsessive-Compulsive Disorder (OCD) is believed to be driven by inhibitory failures in cognitive inhibition and behavioral inhibition (Chamberlain et al., 2005). Cognitive inhibition refers to the ability to suppress competing task-irrelevant details to resolve relevant task problems (e.g., Flanker task; interference), and behavioral inhibition refers to the ability to suppress an already initiated motorized response (e.g., stop-signal task; action cancellation; Chamberlain et al., 2005). Within OCD is a two-factor subtype model for obsessions known as autogenous- and reactive-obsessions (AO; RO; Lee & Kwon, 2003). AO are characterized by poorly controlled repulsive mental intrusions that may have aggressive sexual or religious themes (Lee et al., 2005), and may be more strongly associated with cognitive inhibition failures. In contrast, RO are characterized by thoughts occurring in response to distressing external stimuli or triggers (Lee et al., 2005), and may be more strongly associated with behavioral inhibition failures. Electroencephalography (EEG) is one method that can be used to distinguish the unique inhibitory deficits within AO and RO. Specifically, oscillatory activity within the theta band has been shown to be more associated with interference control during cognitive inhibition demands (Haciahmet et al., 2021), whereas oscillatory activity within the beta band has been shown to be more associated with action cancellation during behavioral inhibition (Fonken et al., 2016). The goal of the present study was to characterize AO and RO using theta and beta band oscillations during a flanker and stop-signal task. Young adults (N=63, M age = 22.3 years, 53 women) completed a flanker and stop-signal task and questionnaires about AO and RO (Revised obsessional intrusion inventory). During both tasks 32-channel EEG was acquired, and theta and beta band power at frontal-central electrodes Fz and Cz were calculated. The association between AO symptom severity and theta power during cognitive inhibition (theta CI), and the association between RO symptom severity and beta power during behavioral inhibition (beta BI) was examined. Additionally, these associations were controlled for age, sex, treatment history, ethnicity, race, worry, anxiety, stress, and depression. With AO as the dependent variable, covariates and beta BI were entered in step 1, and theta CI was entered as a predictor in step 2 of a hierarchical regression model. The model was significant (p = .018, R² = .620, ΔR² = .053). Theta CI was a significant predictor of AO severity (p = .018, β = .287), whereas beta BI did not predict AO severity (p = .996, β = .000). Additionally, with RO as the dependent variable, covariates and theta CI were entered in step 1, and beta BI was entered as a predictor in step 2. The model was significant (p = .034, R² = .525, ΔR² = .044). Beta BI significantly predicted RO severity (p = .034, β = .221), whereas theta CI did not predict RO severity (p = .413, β = .099). As expected, AO is primarily associated with theta CI, whereas RO is primarily associated with beta BI. Future research can seek to further characterize theta and beta as neural biomarkers to address the heterogeneity within OCD.