Reward circuit local field potential modulations precede risk taking

Risk-taking behaviour is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula and anterior cingulate have been implicated in risk-taking, but electrophysiological activity predictive of risk taking in these regions is not well understood in humans. Identifying local field potential frequency signatures of risk-taking may provide therapeutic insight into disorders associated with risk-taking.

Eleven patients with medically refractory epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula and/or anterior cingulate participated in this experiment. Patients completed a gambling task where they wagered on a visible playing card being higher than a hidden card, betting $5 or $20 on this outcome, while local field potentials were recorded from implanted electrodes. We used linear regression models and cluster-based permutation testing to identify oscillatory power modulations associated with reward prediction error signal. We also computed a risk-taking value for each trial using card number and bet choice and similarly used linear regression and cluster-based permutation testing to identify power changes associated with risk-taking value. We then used two-way ANOVA with bet and risk level to identify power clusters predictive of risky decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials.

Time-frequency clusters associated with reward prediction error were identified in the amygdala (two clusters: all P < 0.001) and orbitofrontal cortex (four clusters: all P < 0.001). Risky decisions were predicted by increased oscillatory power in theta-to-beta frequency range during card presentation in the orbitofrontal cortex (P = 0.00053; η2bet = 0.15, η2risk = 0.27, η2bet*risk = 0.017) and by high beta power in the insula (P = 0.0003; η2bet = 0.15, η2risk = 0.20, η2bet*risk = 0.0018). Subsequent analysis localized these signals to lateral orbitofrontal cortex and posterior insula respectively. The power within an insula cluster associated with risky decisions was associated with a theta-alpha reward prediction error signal in the orbitofrontal cortex (P = 0.023). In addition, an amygdala reward prediction error signal was associated with overall percentage of high bets (P = 0.0015) and a lateral orbitofrontal cortex risky decision signal was associated with high bets in risky scenarios (P = 0.028).

Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings identify oscillatory power signatures within these regions preceding risky decisions, which may serve as potential biomarkers to inform the development of novel treatment strategies such as closed loop neuromodulation for disorders of risk taking.