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Aberrant Computational Mechanisms of Social Learning and Decision-Making in Schizophrenia and Borderline Personality Disorder.

PLoS Computational Biology(2020)CCF BSCI 2区

Max Planck Inst Psychiat | Univ Basel | Kbo Isar Amper Klinikum Munich East | Ludwig Maximilians Univ Munchen | Univ Zurich

Cited 46|Views45
Abstract
Psychiatric disorders are ubiquitously characterized by debilitating social impairments. These difficulties are thought to emerge from aberrant social inference. In order to elucidate the underlying computational mechanisms, patients diagnosed with major depressive disorder (N = 29), schizophrenia (N = 31), and borderline personality disorder (N = 31) as well as healthy controls (N = 34) performed a probabilistic reward learning task in which participants could learn from social and non-social information. Patients with schizophrenia and borderline personality disorder performed more poorly on the task than healthy controls and patients with major depressive disorder. Broken down by domain, borderline personality disorder patients performed better in the social compared to the non-social domain. In contrast, controls and major depressive disorder patients showed the opposite pattern and schizophrenia patients showed no difference between domains. In effect, borderline personality disorder patients gave up a possible overall performance advantage by concentrating their learning in the social at the expense of the non-social domain. We used computational modeling to assess learning and decision-making parameters estimated for each participant from their behavior. This enabled additional insights into the underlying learning and decision-making mechanisms. Patients with borderline personality disorder showed slower learning from social and non-social information and an exaggerated sensitivity to changes in environmental volatility, both in the non-social and the social domain, but more so in the latter. Regarding decision-making the modeling revealed that compared to controls and major depression patients, patients with borderline personality disorder and schizophrenia showed a stronger reliance on social relative to non-social information when making choices. Depressed patients did not differ significantly from controls in this respect. Overall, our results are consistent with the notion of a general interpersonal hypersensitivity in borderline personality disorder and schizophrenia based on a shared computational mechanism characterized by an over-reliance on beliefs about others in making decisions and by an exaggerated need to make sense of others during learning specifically in borderline personality disorder.
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Borderline Personality Disorder,Neuropsychological Performance,Social Cognition,Emotion Dysregulation
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要点】:研究揭示了精神分裂症和边缘型人格障碍患者在社会学习和决策中的异常计算机制,表现为对他人信念的过度依赖和对于社会信息的敏感性。

方法】:采用概率性奖励学习任务,结合计算建模分析学习与决策参数。

实验】:患者组(包括精神分裂症、边缘型人格障碍、重度抑郁症)和健康对照组参与实验,使用了计算模型分析行为数据,结果表明边缘型人格障碍和 schizophrenia 患者在社会和非社会信息学习上表现较差,且在社会领域中给予过多关注,数据集名称未提及。