过度估计波动性是双相I型障碍异常决策的基础

Background Bipolar disorder (BD) is marked by extreme mood fluctuations, yet the computational mechanisms underlying this instability remain poorly understood. Recent computational accounts suggest that mood instability may arise from altered reward prediction error (RPE) processing, yet little is known about the factors that modulate this process. Volatility inference—the ability to track environmental change—may be particularly relevant as it modulates the influence of prediction errors on belief updating. However, it remains unclear whether BD is characterized by altered volatility inferenc