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Lateral prefrontal model-based signatures are reduced in healthy individuals with high trait impulsivity

机译:具有特质冲动的健康个体减少基于前额叶模型的外侧特征

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摘要

High impulsivity is an important risk factor for addiction with evidence from endophenotype studies. In addiction, behavioral control is shifted toward the habitual end. Habitual control can be described by retrospective updating of reward expectations in ‘model-free' temporal-difference algorithms. Goal-directed control relies on the prospective consideration of actions and their outcomes, which can be captured by forward-planning ‘model-based' algorithms. So far, no studies have examined behavioral and neural signatures of model-free and model-based control in healthy high-impulsive individuals. Fifty healthy participants were drawn from the upper and lower ends of 452 individuals, completing the Barratt Impulsiveness Scale. All participants performed a sequential decision-making task during functional magnetic resonance imaging (fMRI) and underwent structural MRI. Behavioral and fMRI data were analyzed by means of computational algorithms reflecting model-free and model-based control. Both groups did not differ regarding the balance of model-free and model-based control, but high-impulsive individuals showed a subtle but significant accentuation of model-free control alone. Right lateral prefrontal model-based signatures were reduced in high-impulsive individuals. Effects of smoking, drinking, general cognition or gray matter density did not account for the findings. Irrespectively of impulsivity, gray matter density in the left dorsolateral prefrontal cortex was positively associated with model-based control. The present study supports the idea that high levels of impulsivity are accompanied by behavioral and neural signatures in favor of model-free behavioral control. Behavioral results in healthy high-impulsive individuals were qualitatively different to findings in patients with the same task. The predictive relevance of these results remains an important target for future longitudinal studies.
机译:根据内表型研究的证据,高冲动性是成瘾的重要危险因素。在成瘾中,行为控制已转向习惯性目的。习惯控制可以通过对“无模型”时差算法中的奖励期望进行回顾性更新来描述。以目标为导向的控制依赖于对行为及其结果的前瞻性考虑,这可以通过预先计划“基于模型”的算法来捕获。到目前为止,还没有研究检查健康高冲动个体中无模型和基于模型的控制的行为和神经特征。从452个人的上下两端抽取了50名健康参与者,完成了Barratt冲动量表。所有参与者均在功能磁共振成像(fMRI)期间执行了顺序决策任务,并接受了结构MRI。通过反映无模型和基于模型的控制的计算算法来分析行为和fMRI数据。两组在无模型控制和基于模型的控制的平衡方面没有差异,但是冲动性高的人仅对无模型控制表现出微妙而重要的强调。在高冲动的个体中,基于右侧前额叶模型的签名减少了。吸烟,饮酒,一般认知或灰质密度的影响并未解释这一发现。与冲动无关,左背外侧前额叶皮层的灰质密度与基于模型的控制呈正相关。本研究支持这样的想法,即高冲动性伴随着行为和神经签名,有利于无模型行为控制。健康的高冲动个体的行为结果在质量上与任务相同的患者不同。这些结果的预测相关性仍然是未来纵向研究的重要目标。

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