Uncovering the drivers of human sensorimotor learning: EEG oscillatory manifestations of error, repetition and reward processing.

揭示人类感觉运动学习的驱动因素：错误、重复和奖励处理的脑电图振荡表现。

• 批准号: RGPIN-2019-05786
• 负责人: Bernier, PierreMichel
• 金额: $ 3.64万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=738514
• 关键词: Uncovering; drivers; human; sensorimotor; learning

Sensorimotor learning is at the heart of humans' capacity to acquire and maintain efficient motor behaviour across the lifespan. Computational modeling work has highlighted the contributions of sensory prediction errors and target errors to the acquisition of a new motor behaviour, as well as the contributions of movement repetitions and rewards to the long-term retention of motor memories. Still, there remains an important gap in our understanding of how these processes manifest in the brain, and in particular how functional interactions between brain regions change during learning. In this light, the long-term objective of my research is to study learning-related neuroplasticity at the systems levels within the human sensorimotor network. Interestingly, there is growing evidence that rhythmic brain activity plays a key role in computations involved in learning and plasticity. Specifically, neural oscillations in the theta-band (3-7 Hz) have been shown to be modulated by sensory prediction errors and target errors, whereas oscillations in the beta-band (15-30 Hz) have been shown to be modulated by movement repetitions and rewards. The short-term objective of my program is to test the hypothesis that theta and beta oscillations instantiate functional communication in distinct brain networks mediating errors vs. repetitions and rewards, with the important implication that they respectively relate to acquisition and retention of motor behaviours. In Theme 1, experiments will test the hypothesis that theta-band oscillations i) covary with the size of sensory prediction errors, ii) causally relate to acquisition of a new motor behaviour, and iii) depend upon the cerebellum. In Theme 2, experiments will test the hypothesis that beta-band oscillations i) reflect the degree of plasticity induced by repetitions and rewards, ii) causally relate to retention of a new motor behaviour, and iii) are modulated by sensory prediction errors. A key element is to bridge the gap between brain and behaviour, relating neural responses incurred by errors, repetitions and rewards to rates of acquisition and retention of motor memories. Paradigms of visuomotor adaptation of goal-directed reaching movements will be used while electroencephalography (EEG) is recorded. To establish a causal link between neural responses and motor behaviour, non-invasive brain stimulation techniques will be used to influence cortical activity, including single-pulse transcranial magnetic stimulation (TMS), repetitive TMS (rTMS) and transcranial alternating current stimulation (tACS). At a time where we are garnering the tools to alter neural rhythms in a circumscribed manner through non-invasive neuromodulatory interventions, there is a need for fundamental research to provide reliable biomarkers of known mediators of learning. The present research looks to fill that gap, with the ultimate hope of optimizing motor learning and performance in both healthy and brain-injured populations.

感觉运动学习是人类在整个生命周期中获得和保持有效运动行为的能力的核心。计算建模工作强调了感觉预测错误和目标错误对获得新运动行为的贡献，以及运动重复和奖励对长期保持运动记忆的贡献。尽管如此，我们对这些过程如何在大脑中表现的理解仍然存在重要差距，特别是在学习过程中大脑区域之间的功能性相互作用如何变化。在这种情况下，我的研究的长期目标是在人类感觉运动网络的系统水平上研究与学习相关的神经可塑性。 有趣的是，越来越多的证据表明，有节奏的大脑活动在涉及学习和可塑性的计算中起着关键作用。具体而言，θ波段（3-7 Hz）的神经振荡已被证明是由感觉预测误差和目标误差调制的，而β波段（15-30 Hz）的振荡已被证明是由运动重复和奖励调制的。我的项目的短期目标是检验以下假设：θ和β振荡在不同的大脑网络中例示了功能性通信，这些网络介导错误与重复和奖励，重要的是它们分别与运动行为的获得和保持有关。 在主题1中，实验将测试以下假设：θ波段振荡i）与感觉预测错误的大小协变，ii）与新运动行为的获得有因果关系，iii）取决于小脑。在主题2中，实验将测试以下假设：β-波段振荡i）反映了重复和奖励诱导的可塑性程度，ii）与新运动行为的保留有因果关系，iii）受到感官预测错误的调制。一个关键因素是弥合大脑和行为之间的差距，将错误、重复和奖励引起的神经反应与运动记忆的获得和保持率联系起来。 在记录脑电图（EEG）的同时，将使用目标导向的到达运动的视觉适应范例。为了建立神经反应和运动行为之间的因果关系，将使用非侵入性脑刺激技术来影响皮层活动，包括单脉冲经颅磁刺激（TMS），重复TMS（rTMS）和经颅交流电刺激（tACS）。 在我们通过非侵入性神经调节干预以有限的方式获得改变神经节律的工具的时候，需要进行基础研究，以提供已知学习介质的可靠生物标志物。目前的研究希望填补这一空白，最终希望在健康和脑损伤人群中优化运动学习和表现。