Developing novel neuroimaging approaches to investigate the neural antecedents of tics and brain correlates of premonitory urges in Tourette syndrome

多发性抽动症(TS)是一种以运动和声带痉挛为特征的儿童期发病的神经系统疾病。许多(约90%)的TS患者报告说，他们的抽搐之前会有一种先兆冲动(PU)，这种冲动被描述为身体的不适感觉，被认为是强烈的抽搐冲动。体验过PU的人经常报告说，如果他们没有经历过PU，他们就不会表现出抽搐。基于这些原因，我们认为使用功能磁共振成像(FMRI)和脑磁图(MEG)等脑成像技术来研究TS患者抽动的脑机制是及时和非常重要的。不幸的是，使用传统的fMRI和MEG方法扫描TS患者是极其困难的，因为他们不想要的运动，这通常会导致非常高的(50%-75%)的数据丢失。如果个体在被扫描时实际上被要求表达他们的抽搐(即，在传统的fMRI分析中，抽搐实际上发生是必要的，以便可以对与产生抽搐相关联的大脑活动的时间进程进行建模)，则该问题会加剧。然而，大多数TS患者可以相当有效地抑制他们的抽动：尽管抽动抑制与增加的不适程度有关，这是一种强烈的抽动冲动。这表明，如果我们要求TS患者在接受扫描期间抑制他们的抽搐，我们可能会成功扫描许多TS患者。该项目的目标是开发新的方法，以成像PU和抽动的神经前驱在TS。一种方法是基于用于分析功能磁共振成像(FMRI)数据的另一种数据驱动的框架，该框架被称为“多回波稀疏范式自由映射”(ME-SPFM)，在该框架中，我们获得与出现在TS中的PU相关的fMRI测量，而不需要TIC表达。使用这种方法，我们将准确和可靠地识别在抽动被有效抑制的情况下(即没有抽搐可用作外部计时事件)与PU发生相关的功能性大脑活动。第二种方法涉及我们使用一种全新的可穿戴式脑磁图设备，该设备由诺丁汉大学开发。脑磁图是一种非侵入性的脑成像技术，它比功能磁共振成像有优势：尤其是它允许在毫秒级测量正在进行的大脑活动。使用该设备将允许我们记录与PU相关的大脑活动，以及抽搐之前的大脑活动，即使在TS患者执行大型头部或身体运动时也是如此。我们将开展的脑磁图研究的一个关键焦点是，它们将使我们能够调查瞬时同步的大脑网络是如何组装起来的，将与行动冲动体验相关的大脑区域与参与行动启动的大脑网络联系起来。再一次，这些分析将使用新颖的、最先进的、数据驱动的方法来研究大脑区域之间功能连接的变化。

Tourette syndrome (TS) is a neurological condition of childhood onset that is characterised by motor and vocal tics. Many (~90%) people with TS report that their tics are preceded by a 'premonitory urge' (PU) that is described as uncomfortable bodily sensations that is experienced as a strong urge-to-tic. People who experience PU often report that they would not exhibit tics if they did not experience PU. For these reasons, we consider it timely and highly important to investigate the brain mechanisms that give rise to the urge to tic in TS using brain imaging techniques such as functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG).Unfortunately, scanning individuals with TS using conventional fMRI and MEG methods is extremely difficult due to their unwanted movements, which often lead to a very high (50-75%) loss of data. This problem is exacerbated if the individual is actually required to express their tic while being scanned (i.e., in conventional fMRI analyses it is necessary that tics actually occur so that the time course of the brain activity associated with producing the tic can be modelled). However, most TS patients can suppress their tics quite effectively: although tic suppression is associated with increasing levels of discomfort which is experienced as a strong urge-to-tic. This suggests that we might successfully scan many TS patients if we asked them to suppress their tics throughout the period they were being scanned. The objective of this project is to develop new approaches to imaging PU and the neural antecedents of tics in TS. One approach is based upon an alternative, data-driven, framework for the analysis of functional magnetic resonance imaging (fMRI) data, termed 'Multi-echo Sparse Paradigm Free Mapping' (ME-SPFM), in which we obtain fMRI measurements associated with PU that occur in TS without the necessity for tic expression. Using this approach, we will accurately and reliably identify functional brain activity that is associated with the occurrence of PU in circumstances where tics are effectively suppressed (i.e. there is no tic to use as an external timing event). The second approach involves our using an entirely novel form of wearable MEG device, developed at the University of Nottingham. MEG is a non-invasive brain imaging technique that has advantages over fMRI: not least it allows the measurement of ongoing brain activity at the millisecond scale. Using this device will allow us to record brain activity associated with PU, and the brain activity that precedes a tic, in patients with TS even when they are executing large head or body movements. A key focus of the MEG studies that we will carry out are that they will allow us to investigate how transiently-synchronising brain networks are assembled linking brain regions associated with the experience of the urge-for-action with brain networks involved in the initiation of action. Once again, these analyses will be conducted using novel, state-of-the-art, data-driven approaches to investigating changes in functional connectivity between brain areas.