Movement perception in Functional Neurological Disorder (FND)

功能性神经障碍（FND）是一种常见的，使人衰弱的疾病，通常会导致运动和平衡问题。它是仅次于头痛的第二个转诊给神经科医生的原因，然而，人们对它的了解很少，治疗也有限，这使得FND患者的选择很少。在这个项目中，我们将从一个新的角度研究FND，这表明运动症状可能是由于大脑系统的问题而出现的，这些问题有助于我们：i）从眼睛后部（视网膜）的运动中感知环境中的运动ii）控制我们在环境中的运动。第二种活动显然需要大脑来估计我们是如何运动的，这涉及到将来自各种感官的自我运动信息（包括视觉和来自内耳的平衡信息）适当地结合起来。然而，第一项活动也依赖于对自我运动的了解--如果不首先考虑我们自己的运动，大脑就无法评估环境的其他部分是如何运动的。例如，如果我们开车经过一个交通锥，它在环境中是静止的，那么它在视网膜上就会移动，为了确定这个交通锥实际上是“世界静止的”，大脑需要考虑并补偿我们自己的运动。大脑通过快速预测/估计由于自身运动而引起的视网膜上的运动来解决这个问题，然后在解释环境的其他部分的运动之前对此进行补偿。如果没有这种能力，我们将错误地解释视网膜上的运动-环境的静止部分似乎在移动，并且类似于FND中经历的平衡和运动问题也会随之而来。考虑到这些问题，我们将测试理论表明，FND运动症状是由关于自我运动的感觉信息和/或在解释世界其他地方如何运动时对我们自我运动的估计和补偿的不适当组合引起的。我们将专注于一个亚组的FND患者持续性姿势知觉性头晕（3 PD），谁的经验特别明显的运动症状，并使用既定的实验方法来测试我们的假设。最重要的是，我们还将使用虚拟现实（VR）技术，这使我们能够打破自我运动和视网膜运动之间的关系，通常伴随着它。（对于每个个体）以下能力：i）估计自我运动和环境其他部分的运动ii）补偿自我运动; iii）联合收割机结合关于自我运动的不同感觉信息源。然后我们可以考虑这些措施在有和没有3 PD的人中有何不同，以及它们如何预测3 PD症状和日常运动任务中的问题。更好地了解导致3 PD/FND运动症状的因素，将使我们能够研究基于VR的新疗法来减轻症状。例如，我们的试点数据表明，3 PD中对自我运动的补偿较少，我们可以通过将患者暂时置于VR环境中来抵消这一点，在VR环境中，视网膜上的运动相对于通常伴随自我运动的运动略有增加，并在一段时间内逐渐将其减少到正常状态。类似地，如果我们发现FND中自我运动信息的组合发生了变化（例如过于强调视觉信息），我们可以使用VR将更多注意力集中在被忽视的信息源上。最重要的是，这些方法可以量身定制。我们预计，我们的研究将导致更好地了解FND/3 PD的原因，并随后提供更好和更有针对性的治疗。因此，我们相信这项工作可以迅速转化为未来的研究，证明对治疗选择有限的大型患者群体的直接益处。

Functional Neurological Disorder (FND) is a common, debilitating condition often causing problems with movement and balance. It is second only to headaches as a reason for referral to a neurologist, however, it is little understood and treatments are limited, leaving people with FND with few options. In this project we will study FND from a new perspective, suggesting movement symptoms might arise due to problems with the brain systems that help us to: i) Perceive movement in our environment from the motion arising on the back of the eye (the retina) ii) Control our movement through the environment. The second of these activities obviously requires the brain to estimate how we are moving, which involves combining self-movement information appropriately from a range of senses (including vision together with balance information from the inner ear). However, the first activity also relies on knowing about self-movement - the brain cannot assess how other parts of the environment are moving without taking into account our own movement first. For example, a traffic cone that is stationary in the environment will be moving on the retina if we drive past it. To establish that the cone is, in fact, 'world stationary' the brain needs to factor in and compensate for our own movement. The brain solves this this problem by rapidly predicting/estimating the motion on the retina due to self-movement and then compensating for this before interpreting the movement of other parts of the environment. Without this ability we would incorrectly interpret motion on the retina - stationary parts of the environment would seem to move and problems with balance and movement similar to those experienced in FND would follow. With these issues in mind, we will test theories suggesting that FND movement symptoms arise from inappropriate combination of sensory information about self-movement and/or estimation and compensation for our self-movement when interpreting how other parts of the world are moving. We will focus on a subgroup of FND patients with Persistent Postural-Perceptual Dizziness (3PD), who experience particularly pronounced movement symptoms and use established experimental approaches to test our hypotheses. Crucially we will also use Virtual Reality (VR) technology, which allows us to break the relationship between self-movement and the retinal movement that normally accompanies it. Using well-established methods from sensory science we will measure (for each individual) the ability to: i) estimate self-movement and movement of other parts of the environment ii) compensate for self-movement; iii) combine different sensory information sources about self-movement. We can then consider how these measures differ in those with and without 3PD and how they might predict 3PD symptoms and problems in everyday movement tasks.Having better understanding of the factors causing 3PD/FND movement symptoms, will then allow us to investigate novel VR-based therapies to reduce symptoms. For example, our pilot data suggest less compensation for self-movement in 3PD and we could counteract this by temporarily placing patients in VR environments where motion on the retina is slightly increased relative to what should normally accompany self-movement, gradually reducing this to normal over a period of time. Similarly, if we find that combination of self-movement information is altered in FND (e.g. too much emphasis placed on visual information) we could use VR to direct more attention towards the overlooked information source. Crucially, such approaches could be tailored to the individual.We anticipate that our research will lead to significantly better understanding of the causes of FND/3PD and, subsequently, better and more targeted therapies. As a consequence we are confident that this work could rapidly translate into future studies demonstrating direct benefit for a large patient group with limited treatment options.