Beta and High Gamma Oscillations in the Cortico-striatal Network Reflect Reward Certainty on a Probabilistic Reversal Learning Task.

IF 4 2区 医学 Q1 NEUROSCIENCES
Miranda F Koloski, Morteza Salimi, Sidharth Hulyalkar, Tianzhi Tang, Sam A Barnes, Joyti Mishra, Dhakshin S Ramanathan
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引用次数: 0

Abstract

Behavioral outcomes are rarely certain, requiring subjects to discriminate between available choices by using feedback to guide future decisions. Probabilistic reversal learning (PRL) tasks test subjects' ability to learn and flexibly adapt to changes in reward contingencies. Cortico-striatal circuitry has been broadly implicated in flexible decision-making-though what role these circuits play remains complicated. In this study we leveraged the fast temporal dynamics of local field potentials to precisely identify the role that cortico-striatal networks play during PRL reward feedback. We measured widespread (32-CH) local field potential activity of male Long-Evans rats during a PRL task wherein a target response delivered reward on 80% of trials while a non-target response delivered reward on 20% of trials. When subjects learned those reward probabilities, contingencies were reversed. We found that reward-evoked oscillations at beta (15-30 Hz) and high gamma (>70 Hz) frequencies marked positive reward valence and reflected probability of reward. Activity and connectivity at beta frequencies between orbitofrontal cortex, anterior insula, medial prefrontal cortex, and ventral striatum during expected rewards were correlated with behavioral performance and specific aspects of value/exploitative behavior as defined by a reinforcement learning computational model. Finally, we found that modulating beta activity in orbitofrontal cortex with optogenetic (20 Hz) stimulation promoted maladaptive behavior when stimulation was provided during non-target responses, consistent with our data and computational model predictions. Reward-evoked beta oscillations may reflect a crucial component underlying reward learning, and erroneous elevations in this physiological signal may contribute to maladaptive task performance and behavioral disruptions.

皮质纹状体网络的β和高γ振荡反映了概率反转学习任务的奖励确定性。
行为结果很少是确定的,这要求受试者通过使用反馈来指导未来的决策,区分可用的选择。概率反转学习(PRL)任务是测试对象学习和灵活适应奖励随因变化的能力。皮质纹状体回路广泛涉及灵活的决策,尽管这些回路的作用仍然很复杂。在这项研究中,我们利用局部场电位的快速时间动态来精确识别皮质纹状体网络在PRL奖励反馈过程中发挥的作用。在PRL任务中,我们测量了雄性Long-Evans大鼠广泛的(32-CH)局部场电位活动,其中80%的试验是目标反应,而20%的试验是非目标反应。当实验对象了解到这些奖励概率时,偶然性发生了逆转。我们发现,在beta (15-30Hz)和高gamma (> - 70Hz)频率下,奖励诱发振荡标志着积极的奖励价,反映了奖励的可能性。在期望奖励期间,眶额皮质、脑岛前部、内侧前额叶皮质和腹侧纹状体之间的β -频率活动和连通性与行为表现和价值/剥削行为的特定方面相关,这是由强化学习计算模型定义的。最后,我们发现,在非目标反应期间,通过光遗传(20Hz)刺激调节眶额叶皮层的β活动会促进适应不良行为,这与我们的数据和计算模型预测一致。奖励诱发的β振荡可能反映了奖励学习的一个关键组成部分,这种生理信号的错误升高可能导致任务表现不适应和行为中断。我们研究了当奖励传递不确定时,皮质纹状体区域的振荡动力学如何代表奖励价值。β和高伽马振荡标志着积极的奖励价,反映了奖励的可能性,并显示出在成功完成任务时皮质纹状体网络区域之间更大的连通性。眼窝额叶皮质在β频率(20赫兹)的光遗传刺激调节任务的表现基于试验(高或低的奖励概率)。总之,我们的研究结果表明,皮质纹状体网络中的β振荡代表了习得的奖励价值,这在不确定或变化的奖励偶然性条件下可能特别重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Neuroscience
Journal of Neuroscience 医学-神经科学
CiteScore
9.30
自引率
3.80%
发文量
1164
审稿时长
12 months
期刊介绍: JNeurosci (ISSN 0270-6474) is an official journal of the Society for Neuroscience. It is published weekly by the Society, fifty weeks a year, one volume a year. JNeurosci publishes papers on a broad range of topics of general interest to those working on the nervous system. Authors now have an Open Choice option for their published articles
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