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Ongoing (M23)
International tic partnership for advancement and alignment of neurophysiological research
FunderUK Research and Innovation
Funder Contribution £133,137.00
Duration01 Dec 2024 - 30 Nov 2026
Funded underMRC
Project codeMR/Z505055/1
Open Access mandatePublications: NoResearch data: No
Identifiers
Project timeline95.8%
Description
Tics are involuntary movements and/or vocalisations that typically happen frequently throughout the day. At least 2% of the school aged population experiences tics, which are the core clinical feature of Tourette Syndrome (TS). Tics can have dramatic, negative impacts on quality of life, psychological well-being and life expectancy. Research using brain imaging and non-invasive stimulation have led to improved understanding of the neural mechanisms that underlie tics. However, sample sizes are often low and from selective subgroups, making it difficult to properly answer fundamental and clinically meaningful questions about TS and its heterogeneity. For example, tics can improve with age and with certain treatments for some patients, but we are currently unable to predict this. Large, harmonized datasets are needed to identify clinically actionable predictors, mechanisms, and moderators of tic expression and improvement. To address this challenge, we propose to assemble a team of internationally renowned experts to create harmonized data collection and analysis systems that will enable large scale, adequately powered TS research focused on basic and applied clinical research. We propose to: 1: Create the infrastructure necessary to harmonize, organise, share and analyse existing data. Our research teams have a wealth of neurophysiological data from previous studies. This work has been impactful in its own right, leading to important insights about TS and tics; however, analytic power has been limited by small sample sizes. We will develop approaches for sharing, organising and analysing pooled data, taking inspiration from brain imaging initiatives which have successfully achieved this goal. 2: Standardize experimental methods. Protocols for data collection and analysis often vary between research groups. To optimise strategies for new collaborative data collection, unifying approaches is critical. We will achieve this by standardizing equipment and training, as well as developing best practise guidelines.
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Tics are involuntary movements and/or vocalisations that typically happen frequently throughout the day. At least 2% of the school aged population experiences tics, which are the core clinical feature of Tourette Syndrome (TS). Tics can have dramatic, negative impacts on quality of life, psychological well-being and life expectancy. Research using brain imaging and non-invasive stimulation have led to improved understanding of the neural mechanisms that underlie tics. However, sample sizes are often low and from selective subgroups, making it difficult to properly answer fundamental and clinically meaningful questions about TS and its heterogeneity. For example, tics can improve with age and with certain treatments for some patients, but we are currently unable to predict this. Large, harmonized datasets are needed to identify clinically actionable predictors, mechanisms, and moderators of tic expression and improvement. To address this challenge, we propose to assemble a team of internationally renowned experts to create harmonized data collection and analysis systems that will enable large scale, adequately powered TS research focused on basic and applied clinical research. We propose to: 1: Create the infrastructure necessary to harmonize, organise, share and analyse existing data. Our research teams have a wealth of neurophysiological data from previous studies. This work has been impactful in its own right, leading to important insights about TS and tics; however, analytic power has been limited by small sample sizes. We will develop approaches for sharing, organising and analysing pooled data, taking inspiration from brain imaging initiatives which have successfully achieved this goal. 2: Standardize experimental methods. Protocols for data collection and analysis often vary between research groups. To optimise strategies for new collaborative data collection, unifying approaches is critical. We will achieve this by standardizing equipment and training, as well as developing best practise guidelines.
