Neural signature of the (in)ability to turn physical activity intentions into actions

将体育活动意图转化为行动的（不）能力的神经特征

• 批准号: RGPIN-2021-03153
• 负责人: Boisgontier, Matthieu
• 金额: $ 2.04万
• 依托单位: University of Ottawa
• 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=742404
• 关键词: Neural; signature; ability; turn; physical

What if a fundamental principle of evolution that leads us to minimize effort had been neglected in the neuropsychology of physical activity behavior? While the rewarding value of physical activity has been widely studied, behaviors minimizing physical effort have been neglected in this regard. Yet, effort minimization has been critical during evolution. Moreover, this principle has been evidenced in multiple domains such as motor control, biomechanics, and evolutionary biology. Therefore, it is difficult to conceive of physical effort minimization differently than as an essential factor in the regulation of physical activity behavior. Within the scope of my program, theoretical and experimental work has already been initiated and supports the automatic attraction to effort minimization in physical activity. To further test this hypothesis, the objectives of this grant cycle are to investigate i) whether reward-related brain activity is associated with the automatic attraction towards physical effort minimization, ii) whether neural processes counteract this automatic attraction, and iii) which factors influence the aforementioned association and processes (e.g., sex, age, reward sensitivity, recent and real-time energy expenditure). To ensure that the constructs under investigation are exclusively related to physical effort variations, an associative conditioning paradigm will be conducted to systematically associate neutral geometrical figures with different effort patterns: increasing, decreasing, and constant. The resulting conditioned stimuli will be used in neurobehavioral paradigms crossing neuroimaging and neurostimulation techniques with behavioral tasks assessing the automatic evaluation of effort-related cues. Findings from this grant cycle will contribute to the long-term objectives of the program aiming at modifying the mechanisms supporting the automatic attraction towards effort minimization through training. During this grant cycle, a diverse and inclusive group of undergraduate and graduate highly qualified personnel will be trained to i) conceive robust neurobehavioral experimental paradigms, ii) generate knowledge and develop expertise in behavioral methods related to the psychology of physical activity and the physiology of exercise, iii) collect and analyze neuroimaging and neurophysiological data (electroencephalography, magnetic resonance imaging, transcranial magnetic stimulation), iv) conduct and understand advanced statistics (e.g., mixed effects models), and v) gain advanced scientific writing skills. Knowledge that will emerge from the conceptual and methodological innovations of this program merging neuroscience, psychology, and physiology will significantly enhance our understanding of the brain processes governing the automatic evaluation of effort-related stimuli, which will ultimately lead to a better understanding of the mechanisms underlying the (in)ability to turn physical activity intentions into actions.

如果进化的一个基本原则，导致我们最大限度地减少努力已经被忽视的神经心理学的身体活动行为？虽然身体活动的奖励价值已经被广泛研究，但在这方面，最小化身体努力的行为却被忽视了。然而，在进化过程中，努力最小化是至关重要的。此外，这一原则已在多个领域得到证明，如运动控制，生物力学和进化生物学。因此，很难想象体力最小化不同于作为一个重要因素，在调节身体活动行为。在我的计划范围内，理论和实验工作已经启动，并支持在体力活动中努力最小化的自动吸引力。为了进一步测试这一假设，该授权周期的目标是调查i）与奖励相关的大脑活动是否与朝向身体努力最小化的自动吸引相关联，ii）神经过程是否抵消这种自动吸引，以及iii）哪些因素影响上述关联和过程（例如，性别、年龄、奖励敏感度、最近和实时能量消耗）。为了确保研究中的结构只与体力变化相关，将进行关联条件反射范式，以系统地将中性几何图形与不同的努力模式相关联：增加，减少和恒定。由此产生的条件刺激将被用于神经行为范例交叉神经成像和神经刺激技术与行为任务评估的自动评估的努力相关的线索。从这个赠款周期的调查结果将有助于该计划的长期目标，旨在修改的机制，支持自动吸引到努力最小化通过培训。在这个资助周期内，一个多元化和包容性的本科生和研究生高素质人才群体将接受培训，i）构思强大的神经行为实验范式，ii）产生知识和发展与身体活动心理学和运动生理学相关的行为方法的专业知识，iii）收集和分析神经成像和神经生理学数据（脑电图、磁共振成像、经颅磁刺激），iv）进行和理解高级统计学（例如，混合效应模型），以及v）获得先进的科学写作技能。知识将出现在这个程序的概念和方法创新融合神经科学，心理学和生理学将显着提高我们的大脑过程的理解，管理自动评估的努力相关的刺激，这将最终导致更好地了解潜在的机制（在）能力把身体活动的意图变成行动。