Hughes Natasha C, Qian Helen, Doss Derek J, Makhoul Ghassan S, Zargari Michael, Zhao Zixiang, Singh Balbir, Wang Zhengyang, Fulton Jenna N, Johnson Graham W, Li Rui, Dawant Benoit M, Englot Dario J, Constantinidis Christos, Roberson Shawniqua Williams, Bick Sarah K
Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
Brain. 2025 Mar 18. doi: 10.1093/brain/awaf107.
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 (2 clusters: all p<0.001) and orbitofrontal cortex (4 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, η2betrisk=0.017), and by high beta power in the insula (p=0.0003; η2bet=0.15, η2risk=0.20, η2betrisk=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 OFC 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.
冒险行为是多种神经精神疾病的症状,且往往缺乏有效的治疗方法。包括杏仁核、眶额皮质、脑岛和前扣带回在内的奖赏回路区域与冒险行为有关,但人类对这些区域中预测冒险行为的电生理活动了解并不充分。识别冒险行为的局部场电位频率特征可能为与冒险行为相关的疾病提供治疗思路。11名药物难治性癫痫患者参与了本实验,他们接受了立体定向脑电图检查,电极植入在杏仁核、眶额皮质、脑岛和/或前扣带回。患者完成了一项赌博任务,他们押注一张可见的扑克牌比一张隐藏的牌大,在此结果上押注5美元或20美元,同时从植入电极记录局部场电位。我们使用线性回归模型和基于聚类的置换检验来识别与奖赏预测误差信号相关的振荡功率调制。我们还使用牌面数字和押注选择为每个试验计算了一个冒险值,并同样使用线性回归和基于聚类的置换检验来识别与冒险值相关的功率变化。然后我们使用双向方差分析,结合押注和风险水平,来识别预测风险决策的功率聚类。我们使用线性混合效应模型来评估奖赏预测误差与各试验中风险决策信号之间的关系。在杏仁核(2个聚类:所有p<0.001)和眶额皮质(4个聚类:所有p<0.001)中识别出了与奖赏预测误差相关的时频聚类。在眶额皮质中,牌面展示期间θ至β频率范围内振荡功率增加可预测风险决策(p=0.00053;η2押注=0.15,η2风险=0.27,η2押注风险=0.017),而在脑岛中,高β功率可预测风险决策(p=0.0003;η2押注=0.15,η2风险=0.20,η2押注风险=0.0018)。随后的分析将这些信号分别定位到外侧眶额皮质和脑岛后部。与风险决策相关的脑岛聚类内的功率与眶额皮质中的θ-α奖赏预测误差信号相关(p=0.023)。此外,杏仁核奖赏预测误差信号与高押注的总体百分比相关(p=0.0015),外侧眶额皮质风险决策信号与风险情境中的高押注相关(p=0.028)。我们的研究结果识别并有助于表征人类中预测冒险行为的奖赏回路活动。这些结果识别出了这些区域内风险决策之前的振荡功率特征,这可能作为潜在的生物标志物,为开发新的治疗策略提供信息,如用于冒险行为障碍的闭环神经调节。