Biasing influences on the motor system during action preparation: a multimodal neuroimaging-computationally informed approach

动作准备过程中对运动系统的偏差影响：多模式神经影像计算知情方法

• 批准号: BB/F02424X/1
• 负责人: Sven Bestmann
• 金额: $ 93.85万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF02424X%2F1
• 关键词: Biasing; influences; motor; system; during

In almost every aspect of life, adequate behavior first requires the processing of incoming sensory information. We then must weigh its relevance, decide between alternative movements, and select the most appropriate behavior. For example, a goalkeeper facing a penalty kick needs to observe player and ball, estimate the likely trajectory of the ball based on experience and postural cues from the player, and finally decide in which direction to move as fast as possible. We therefore use our experience for preparing the appropriate movements, yet it is still poorly understood how information such as past experience gets funnelled into our actual movements. Previous research suggests that the processes underlying perception and movement overlap in the brain, both anatomically and in time. However, the brain activity patterns, rules and computations exchanged by different brain regions to accomplish this influence remain largely undetermined. The central goal of my proposal is to reveal how different brain regions interact with the motor system to use past experience and prior information for movement selection. In my experiments, participants prepare movements based on visual cues. These cues indicate which movement is required (e.g. button presses) when a subsequent visual go-signal is presented. When cues are reliably predicting the required movement, responses are fast. This suggests that we use our experience about the reliability of visual information available to us to prepare movements efficiently. By changing the validity of these visual cues, one can change the uncertainty about which movement will have to be performed. In this way, we can address the question how our experience about the world influences our actions, and our brain. First, non-invasive brain stimulation will measure the activation state of the motor system during movement preparation in these experiments. This safe method for causing brain activity provides a direct read-out of the state of a brain region. I will then combine this brain stimulation with neuroimaging. I have recently developed this combined technique which allows for measuring the impact of brain stimulation on activity across the entire brain with high anatomical precision. Brain regions involved in preparing movements will be stimulated. At the same time, neuroimaging will measure the resulting activity changes in connected brain regions. This will reveal the brain regions relevant for making movements based on sensory experience, and disclose the influences among them which are required to bind together our experience with our actions. Finally, Magnetoencephalography non-invasively detects electrical brain signals in humans, and will reveal the timecourse of brain activity during preparation for movements based on experience and past information. It may seem obvious that the brain uses past information to guide our future movements. However, few studies have formally tried to quantify how our experience about sensory information shapes the motor system over time. One can quantify this experience by using simple mathematical models. These provide so-called computationally informed time-evolving representations of experience, and can be applied to test for corresponding brain activity changes. Using such computationally informed representations, for example, about the uncertainty of visual information, is exciting because it overcomes one of the central limitations that has bedevilled cognitive psychology for the past 100 years: the actual computations of the brain are hidden to us, and only by formal representation can we understand the processes that the brain embellishes for specifying movements efficiently in an uncertain world.

在生活的几乎每一个方面，适当的行为首先需要处理传入的感觉信息。然后，我们必须权衡其相关性，在可供选择的动作之间做出决定，并选择最合适的行为。例如，面对点球的守门员需要观察球员和球，根据球员的经验和姿势线索估计球的可能轨迹，并最终决定尽可能快地向哪个方向移动。因此，我们利用我们的经验来准备适当的动作，但我们仍然很难理解过去的经验等信息是如何融入我们的实际动作中的。先前的研究表明，大脑中潜在的感知和运动过程在解剖学和时间上都是重叠的。然而，不同大脑区域为实现这一影响而交换的大脑活动模式、规则和计算在很大程度上仍未确定。我的建议的中心目标是揭示不同的大脑区域如何与运动系统相互作用，以利用过去的经验和先前的信息进行运动选择。在我的实验中，参与者根据视觉线索准备动作。这些提示指示当出现后续的视觉GO信号时需要哪种动作(例如，按下按钮)。当提示能够可靠地预测所需动作时，反应会很快。这表明，我们利用可获得的视觉信息的可靠性的经验来有效地准备动作。通过改变这些视觉提示的有效性，人们可以改变关于必须执行哪种动作的不确定性。通过这种方式，我们可以解决这样一个问题，即我们对世界的体验如何影响我们的行为和大脑。首先，在这些实验中，非侵入性脑刺激将测量运动准备期间运动系统的激活状态。这种引发大脑活动的安全方法可以直接读出大脑区域的状态。然后，我将把这种脑刺激与神经成像结合起来。我最近开发了这项组合技术，它允许以高解剖精度测量大脑刺激对整个大脑活动的影响。参与准备动作的大脑区域将受到刺激。与此同时，神经成像将测量大脑连接区域中由此产生的活动变化。这将揭示大脑中与基于感觉经验做出动作相关的区域，并揭示它们之间的影响，这些影响需要将我们的经验与我们的行动联系在一起。最后，脑磁图非侵入性地检测人类的大脑电信号，并将根据经验和过去的信息揭示大脑活动在准备运动期间的时间过程。大脑使用过去的信息来指导我们未来的行动，这似乎是显而易见的。然而，很少有研究正式尝试量化我们对感觉信息的体验如何随着时间的推移塑造运动系统。人们可以通过使用简单的数学模型来量化这种体验。这些提供了所谓的计算信息的时间演变经验的表征，并可用于测试相应的大脑活动变化。例如，使用这种通过计算获得信息的表征，例如关于视觉信息的不确定性，是令人兴奋的，因为它克服了过去100年来困扰认知心理学的核心限制之一：大脑的实际计算对我们是隐藏的，只有通过形式表征，我们才能理解大脑修饰的过程，以便在不确定的世界中有效地指定动作。

项目成果

Left dorsal premotor cortex and supramarginal gyrus complement each other during rapid action reprogramming.

在快速动作重编程过程中，左背前皮层和上环相互补充。

• DOI: 10.1523/jneurosci.1010-12.2012
• 发表时间: 2012-11-14
• 期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
• 作者: Hartwigsen G;Bestmann S;Ward NS;Woerbel S;Mastroeni C;Granert O;Siebner HR
• 通讯作者: Siebner HR

Relationship between physiological measures of excitability and levels of glutamate and GABA in the human motor cortex.

• DOI: 10.1113/jphysiol.2011.216978
• 发表时间: 2011-12-01
• 期刊: The Journal of physiology
• 作者: Stagg CJ;Bestmann S;Constantinescu AO;Moreno LM;Allman C;Mekle R;Woolrich M;Near J;Johansen-Berg H;Rothwell JC
• 通讯作者: Rothwell JC

Time scales of representation in the human brain: weighing past information to predict future events.

人脑中表示的时间尺度：权衡过去的信息以预测未来事件。

• DOI: 10.3389/fnhum.2011.00037
• 发表时间: 2011
• 期刊: Frontiers in human neuroscience
• 影响因子: 2.9
• 作者: Harrison LM;Bestmann S;Rosa MJ;Penny W;Green GG
• 通讯作者: Green GG

A multimodal approach to investigating human motor cortical excitability and inhibition

研究人类运动皮层兴奋性和抑制性的多模式方法

• 期刊: Journal of Physiology
• 作者: Charlotte Stagg (Co-Author)