Maria Waltmann, Nadine Herzog, Andrea M F Reiter, Arno Villringer, Annette Horstmann, Lorenz Deserno
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Obese participants with BED, obese participants without BED, and healthy normal-weight participants (n = 96) performed a probabilistic reversal learning task during functional imaging, with different blocks focused on obtaining wins or avoiding losses. They were reinvited for a 6-month follow-up assessment.</p><p><strong>Results: </strong>Analyses informed by computational models of reinforcement learning showed that unlike obese participants with BED, obese participants without BED performed worse in the win than in the loss condition. Computationally, this was explained by differential learning sensitivities in the win versus loss conditions in the groups. In the brain, this was echoed in differential neural learning signals in the ventromedial prefrontal cortex per condition. The differences were subtle but scaled with BED symptoms, such that more severe BED symptoms were associated with increasing bias toward improved learning from wins versus losses. Across conditions, obese participants with BED switched more between choice options than healthy normal-weight participants. This was reflected in diminished representation of choice certainty in the ventromedial prefrontal cortex.</p><p><strong>Conclusions: </strong>Our study highlights the importance of distinguishing between obesity with and without BED to identify unique neurocomputational alterations underlying different styles of maladaptive eating behavior.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. 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引用次数: 0
摘要
背景:暴饮暴食症(BED)被认为是一种认知控制障碍,但有关其神经认知机制的证据尚无定论。以往研究的主要局限性在于,BED的影响与肥胖之间缺乏一致的区分,而且忽视了自我报告的证据,这些证据表明,神经认知的改变可能主要出现在避免损失或伤害的情况下:为了弥补这些不足,这项纵向研究调查了行为灵活性及其在寻求奖赏和避免损失情境下的潜在神经计算过程。有肥胖症的参与者(BED)、无肥胖症的参与者(OB)和体重正常的健康参与者(NW)(总人数=96)在功能成像过程中执行了一项概率反转学习任务,不同的区块侧重于获得胜利或避免损失。他们被再次邀请进行为期6个月的随访:结果:根据强化学习计算模型进行的分析表明,与 BED 不同,OB 在获胜条件下的表现比失败条件下差。从计算角度看,这是因为不同组别在获胜与失败条件下的学习敏感性不同。在大脑中,每种条件下腹外侧前额叶皮层(vmPFC)的不同神经学习信号也反映了这一点。这种差异是微妙的,但会随着 BED 症状的变化而变化。在所有条件下,OB 比 NW 更多地在选择选项之间切换。这反映在大脑前部皮质中枢(vmPFC)对选择确定性的表征减弱:我们的研究强调了区分肥胖症伴有和不伴有BED的重要性,以确定不同风格的适应不良饮食行为背后独特的神经计算改变。
Neurocomputational Mechanisms Underlying Differential Reinforcement Learning From Wins and Losses in Obesity With and Without Binge Eating.
Background: Binge-eating disorder (BED) is thought of as a disorder of cognitive control, but evidence regarding its neurocognitive mechanisms is inconclusive. Key limitations of previous research include a lack of consistent separation between effects of BED and obesity and a disregard for self-report evidence suggesting that neurocognitive alterations may emerge primarily in loss- or harm-avoidance contexts.
Methods: To address these gaps, in this longitudinal study we investigated behavioral flexibility and its underlying neurocomputational processes in reward-seeking and loss-avoidance contexts. Obese participants with BED, obese participants without BED, and healthy normal-weight participants (n = 96) performed a probabilistic reversal learning task during functional imaging, with different blocks focused on obtaining wins or avoiding losses. They were reinvited for a 6-month follow-up assessment.
Results: Analyses informed by computational models of reinforcement learning showed that unlike obese participants with BED, obese participants without BED performed worse in the win than in the loss condition. Computationally, this was explained by differential learning sensitivities in the win versus loss conditions in the groups. In the brain, this was echoed in differential neural learning signals in the ventromedial prefrontal cortex per condition. The differences were subtle but scaled with BED symptoms, such that more severe BED symptoms were associated with increasing bias toward improved learning from wins versus losses. Across conditions, obese participants with BED switched more between choice options than healthy normal-weight participants. This was reflected in diminished representation of choice certainty in the ventromedial prefrontal cortex.
Conclusions: Our study highlights the importance of distinguishing between obesity with and without BED to identify unique neurocomputational alterations underlying different styles of maladaptive eating behavior.