Hughes Natasha C, Qian Helen, 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
bioRxiv. 2024 Apr 11:2024.04.10.588629. doi: 10.1101/2024.04.10.588629.
Risk taking behavior 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 by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking. Eleven patients with pharmacoresistant epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula, and/or anterior cingulate participated. Patients participated in 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 cluster-based permutation testing to identify reward prediction error signals by comparing oscillatory power following unexpected and expected rewards. We also used cluster-based permutation testing to compare power preceding high and low bets in high-risk (<50% chance of winning) trials and two-way ANOVA with bet and risk level to identify signals associated with risky, risk averse, and optimized decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials, and a linear regression model for associations between risky decision signal power and Barratt Impulsiveness Scale scores for each patient. Reward prediction error signals were identified in the amygdala (p=0.0066), anterior cingulate (p=0.0092), and orbitofrontal cortex (p=6.0E-4, p=4.0E-4). Risky decisions were predicted by increased oscillatory power in high-gamma frequency range during card presentation in the orbitofrontal cortex (p=0.0022), and by increased power following bet cue presentation across the theta-to-beta range in the orbitofrontal cortex ( =0.0022), high-gamma in the anterior cingulate ( =0.0004), and high-gamma in the insula ( =0.0014). Risk averse decisions were predicted by decreased orbitofrontal cortex gamma power ( =2.0E-4). Optimized decisions that maximized earnings were preceded by decreases within the theta to beta range in orbitofrontal cortex ( =2.0E-4), broad frequencies in amygdala ( =2.0E-4), and theta to low-gamma in insula ( =4.0E-4). Insula risky decision power was associated with orbitofrontal cortex high-gamma reward prediction error signal ( =0.0048) and with patient impulsivity ( =0.00478). Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings 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一种症状,且往往缺乏有效的治疗方法。神经影像学研究表明,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。在人类中,这些区域与冒险行为相关的电生理活动尚未得到充分了解。进一步表征冒险行为背后的神经信号,可能会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研究,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。患者参与了一项赌博任务,他们押注一张可见的扑克牌高于一张隐藏的牌,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。我们使用基于聚类的置换检验,通过比较意外奖励和预期奖励后的振荡功率来识别奖赏预测误差信号。我们还使用基于聚类的置换检验,比较高风险(获胜几率<50%)试验中高赌注和低赌注之前的功率,并使用赌注和风险水平的双向方差分析来识别与冒险、规避风险和优化决策相关的信号。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冒险决策信号之间的关系,并使用线性回归模型来评估每个患者冒险决策信号功率与巴拉特冲动性量表得分之间的关联。在杏仁核(p=0.0066)、前扣带回(p=0.0092)和眶额皮质(p=6.0E-4,p=4.0E-4)中识别出了奖赏预测误差信号。在眶额皮质中,牌面展示期间高伽马频率范围内振荡功率增加可预测冒险决策(p=0.0022),在眶额皮质中,赌注提示呈现后,整个θ到β频率范围内功率增加也可预测冒险决策(p=0.0022),在前扣带回中高伽马频率范围内功率增加(p=0.0004)以及在脑岛中高伽马频率范围内功率增加(p=0.0014)也可预测冒险决策。眶额皮质伽马功率降低可预测规避风险决策(p=2.0E-4)。在眶额皮质中,θ到β频率范围内功率降低(p=2.0E-4)、杏仁核中广泛频率范围内功率降低(p=2.0E-4)以及脑岛中θ到低伽马频率范围内功率降低(p=4.0E-4)之前会出现使收益最大化的优化决策。脑岛冒险决策功率与眶额皮质高伽马奖赏预测误差信号相关(p=0.0048),也与患者冲动性相关(p=0.00478)。我们的研究结果识别并有助于表征预测人类冒险行为的奖赏回路活动。这些发现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。