Movement perception in Functional Neurological Disorder (FND)
Lead Research Organisation:
University of Manchester
Department Name: School of Biological Sciences
Abstract
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.
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.
Technical Summary
Recent research on Persistent Perceptual Postural Dizziness (3PD), a subtype of Functional Neurological Disorder (FND), highlights two sensory information processing abnormalities. The first concerns a general change in predictive processing and/or interplay between feedforward and feedback sensory information. The second concerns altered sensory integration and, more specifically, suggests that atypical visual processing might be over-weighted when integrated with vestibular information. Crucially, prediction and integration mechanisms are vital for two ubiquitous perceptual tasks, namely estimating: i) self-movement (SM); ii) scene-relative movement (SRM) of other parts of the environment. We hypothesise that errors in prediction and integration supporting either or both of these tasks drive 3PD symptoms and will test these hypotheses using established methods from perceptual psychophysics together with Virtual Reality (VR) and Motion Capture technologies. In four work packages (WPs) we will:
WP1 - Characterise performance in 3PD relative to control participants in both SM and SRM visual estimation tasks.
WP2 - Investigate integration of visual and vestibular self-movement information for recovery of SM and SRM estimates using a standard cue conflict paradigm and compare this to optimal integration observed in healthy control participants.
WP3 - Investigate which metrics recovered in WP1-2 predict functional performance in a VR-based task involving avoiding obstacles in a cluttered virtual scene.
WP4 - Use what we have learned in WP1-3 to develop and test theoretically motivated targeted Virtual Reality (VR)-based therapies harnessing VR's power to break the natural relationship between observer movement and its visual consequences.
This work should lead to a step change in our understanding of the causal factors underpinning 3PD (& FND more generally) and highlight novel routes to targeted therapy.
WP1 - Characterise performance in 3PD relative to control participants in both SM and SRM visual estimation tasks.
WP2 - Investigate integration of visual and vestibular self-movement information for recovery of SM and SRM estimates using a standard cue conflict paradigm and compare this to optimal integration observed in healthy control participants.
WP3 - Investigate which metrics recovered in WP1-2 predict functional performance in a VR-based task involving avoiding obstacles in a cluttered virtual scene.
WP4 - Use what we have learned in WP1-3 to develop and test theoretically motivated targeted Virtual Reality (VR)-based therapies harnessing VR's power to break the natural relationship between observer movement and its visual consequences.
This work should lead to a step change in our understanding of the causal factors underpinning 3PD (& FND more generally) and highlight novel routes to targeted therapy.
