神经性厌食症患者体重恢复的模拟类别学习和设置转移赤字
Simulating Category Learning and Set Shifting Deficits in Patients Weight-Restored from Anorexia Nervosa
关键词:厌食;行为;临床医学;计算
摘 要:To examine set shifting in a group of women previously diagnosed with anorexia nervosa (AN) who are now weight-restored (AN-WR) and a control group and then apply a biologically-based computational model (Competition between Verbal and Implicit Systems; COVIS) to simulate the pattern of category learning and set shifting performances observed in the AN-CW group. Method: Nineteen AN-WR women and 35 control women (CW) were administered an explicit category learning task that required the initial acquisition of a rule, and after a certain number of trials, a set shift following a rule change. COVIS was first fit to the behavioral results of the controls and then parameters of the model theoretically relevant to AN were altered to mimic the behavioral results. Results: Relative to CW, the AN-WR group displayed steeper learning curves (i.e., hyper learning) prior to the rule shift, but greater difficulty in learning the new categories after the rule shift (i.e., a deficit in set shifting). Hyper learning and set shifting deficits in the AN-CW group were not associated and demonstrated a different pattern of correlations with clinical measures. Hyper learning in the AN-WR group was simulated by increasing the model parameter that represents sensitivity to negative feedback (parameter), whereas the deficit in set shifting was simulated by altering the parameters that represent changes in rule selection and flexibility (and parameters, respectively), processes dependent on dopamine levels. Conclusions: These simulations suggest that multiple factors can impact category learning and set shifting in AN-WR individuals (e.g., alterations in sensitivity to negative feedback, rule selection deficits, and inflexibility) and provide an important starting point to further investigate this pervasive deficit in adult AN.