Unravelling the associations between multi-modal brain connectivity, genetic factors and behaviours
Lead Research Organisation:
University of Nottingham
Department Name: School of Medicine
Abstract
Understanding the workings of the human brain is one of the most outstanding challenges of our time. In particular, determining factors that contribute to the individual signature of integrated cognitive function and eventually behavior is of genuine interest to neuroscience, but also of paramount importance for neurological applications; characterising the "normal" brain structure and function is key for characterizing abnormalities and approaching disease mechanisms. Non-invasive and in-vivo imaging can uniquely shed light to these questions. The project will use magnetic resonance imaging (MRI) to map brain connections and organisation and explore their associations with behavior and genetics.
More specifically, we will capitalise on advances and data offered by the cornerstone Human Connectome Project (HCP) (www.humanconnectome.org), for which the principal supervisor has been a major contributor. We will build and augment computational methodology for estimating connections and characterising their (micro)structure and functional relevance, through signal and image processing techniques. We will use modelling to identify latent multivariate associations between behaviour and brain organisation and explore heritability of connections to identify features that are strongly influenced by genetics. This would further allow the extraction of summary imaging-derived measures with certain contextual associations that could comprise potential markers for subsequently exploring pathology-induced abnormalities.
More specifically, we will capitalise on advances and data offered by the cornerstone Human Connectome Project (HCP) (www.humanconnectome.org), for which the principal supervisor has been a major contributor. We will build and augment computational methodology for estimating connections and characterising their (micro)structure and functional relevance, through signal and image processing techniques. We will use modelling to identify latent multivariate associations between behaviour and brain organisation and explore heritability of connections to identify features that are strongly influenced by genetics. This would further allow the extraction of summary imaging-derived measures with certain contextual associations that could comprise potential markers for subsequently exploring pathology-induced abnormalities.
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| MR/N013913/1 | 01/10/2016 | 30/09/2025 | |||
| 1957092 | Studentship | MR/N013913/1 | 01/10/2017 | 31/03/2021 | Shaun Warrington |
| Description | Graduate School/MRC IMPACT DTP Flexible Funding Award |
| Amount | £7,000 (GBP) |
| Organisation | University of Nottingham |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 11/2018 |
| End | 09/2019 |
| Description | International Society for Magnetic Resonance in Medicine New Entrants Stipend |
| Amount | $875 (USD) |
| Organisation | International Society for Magnetic Resonance in Medicine (ISMRM) |
| Sector | Charity/Non Profit |
| Country | United States |
| Start | 02/2018 |
| End | 06/2018 |
| Description | MRC IMPACT DTP Flexible Funding Award |
| Amount | £1,274 (GBP) |
| Organisation | MRC Doctoral Training Program |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 07/2019 |
| End | 07/2019 |
| Description | MRC IMPACT DTP Flexible Funding Award |
| Amount | £1,300 (GBP) |
| Organisation | MRC Doctoral Training Program |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 03/2018 |
| End | 06/2018 |
| Title | XTRACT - tool for tractography |
| Description | An automated method for performing tractography (FSL's XTRACT) and a library of standardised tractography protocols (42) for application in the human and macaque. |
| Type Of Material | Model of mechanisms or symptoms - human |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | The paper currently under review and available via bioRxiv (see 'Publications') describes a processing toolbox and tractography protocols which allow for the robust generation of white matter tracts across individuals whilst capturing individual variation. Importantly, the protocols are defined such that we able to reconstruct homologues of each tracts in humans and macaques, allowing for comparative anatomy studies. The toolbox and protocols also aim to help standardise the methods used in performing and reporting tractography, thus increasing reproducibility. The protocols and toolbox are freely available via FSL. |
| URL | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/XTRACT |
| Title | HCP1065 standard-space DTI templates |
| Description | A collection of brain atlases derived from a range of diffusion MRI metrics available in v6.0 of FMRIB's FSL software. These atlases are superb quality representations of the average appearance of the healthy young adult's brain. They were constructed using high-quality data made available through the young adult Human Connectome Project (HCP). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | These atlases are high-quality representations of the typical brain and offer significant improvement over the quality of the previous DTI atlases available via FSL. The atlases may be used to compare normally or abnormally appearing diffusion images against to ensure quality data collection and processing. Tract-based spatial statistics may be applied to the templates and used to compare subjects to the template. They may be used to perform advanced spatial normalisation, by, for example, making use of the greater amount of information available in diffusion tensor images compared to standard anatomical images. |
| URL | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases |
| Title | XTRACT WM Tract Probabilistic Atlases |
| Description | A collection of brain white matter tract atlases derived using the tractography toolkit XTRACT. These atlases are currently available on GitHub and are due to be released in FMRIB's FSL software. These atlases are superb quality representations of the average appearance of the healthy young adult's brain. They were constructed using high-quality data made available through the young adult Human Connectome Project (HCP). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | These atlases are high-quality representations of the typical brain and offer significant improvement over the quality of the previous WM tract atlases available via FSL. The tract atlases will be particularly useful for education of early career researchers/clinicians/neuroanatomists. Researchers may use the probabilistic atlases to explore brain disconnectivity or tract-based differences in healthy or patient groups. They may be used to compare normal/abnormal appearing tracts to in order to identify subject-wise difference in connectivity. |
| URL | http://github.com/SPMIC-UoN/XTRACT_atlases |
| Description | Analysis group in FMRIB, Oxford |
| Organisation | University of Oxford |
| Department | Oxford Centre for Functional MRI of the Brain (FMRIB) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | FMRIB developed and continue to develop FSL - a brain image analysis software package. I am currently testing and helping develop new tractography protocols and demonstrating the potential of an automated tractography toolkit (autoPtx - see working paper). I am also performing image processing on the UK Biobank diffusion MRI data and will feed this back to the analysis group at FMRIB who are leading MR image analysis for the UK Biobank. I also contributed the HCP1065 DTI templates to FMRIB's FSL. We are currently drafting a paper and have submitted a conference abstract in collaboration. |
| Collaborator Contribution | The testing and development of tractography protocols is a collaborative process with the development being performed by FMRIB using feedback from my testing. The group have contributed image processing techniques and code (some via open-source avenues). We are currently drafting a paper and have submitted a conference abstract in collaboration. FMRIB have particularly offered unique insight into the methods in the paper. |
| Impact | The conference abstract submitted to OHBM 2019 - see details in 'Publications' The working paper on the topic of standardised and automated tractography - see details in 'Publications' This is a multi-disciplinary collaboration which expertise in physics, computer programming, biomedial engineering, image analysis, neuroimaging, neuroanatomy, computational neuroimaging, statistics and more. |
| Start Year | 2018 |
| Description | Defining White Matter and Tractography International Collaboration |
| Organisation | University of Oxford |
| Department | Oxford Centre for Functional MRI of the Brain (FMRIB) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We (a collaboration between Nottingham and the Analysis Group at FMRIB, Oxford University) have provided tractography results for a small subset of HCP subjects using the XTRACT toolbox. |
| Collaborator Contribution | The collaborators have organised a large-scale collaborative effort to capture the variance in how white matter and tractography are defined with the end goal of seeking some standardisation of the terminology used in the field. The collaborators plan to collate submissions from many groups and define and describe how the field describes white matter and tractography. |
| Impact | Outcomes yet to be reached |
| Start Year | 2019 |
| Description | Defining White Matter and Tractography International Collaboration |
| Organisation | University of Sheffield |
| Department | Department of Computer Science |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We (a collaboration between Nottingham and the Analysis Group at FMRIB, Oxford University) have provided tractography results for a small subset of HCP subjects using the XTRACT toolbox. |
| Collaborator Contribution | The collaborators have organised a large-scale collaborative effort to capture the variance in how white matter and tractography are defined with the end goal of seeking some standardisation of the terminology used in the field. The collaborators plan to collate submissions from many groups and define and describe how the field describes white matter and tractography. |
| Impact | Outcomes yet to be reached |
| Start Year | 2019 |
| Description | Defining White Matter and Tractography International Collaboration |
| Organisation | Vanderbilt University |
| Department | Medical image Analysis and Statistical Interpretation (MASI) |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | We (a collaboration between Nottingham and the Analysis Group at FMRIB, Oxford University) have provided tractography results for a small subset of HCP subjects using the XTRACT toolbox. |
| Collaborator Contribution | The collaborators have organised a large-scale collaborative effort to capture the variance in how white matter and tractography are defined with the end goal of seeking some standardisation of the terminology used in the field. The collaborators plan to collate submissions from many groups and define and describe how the field describes white matter and tractography. |
| Impact | Outcomes yet to be reached |
| Start Year | 2019 |
| Description | Nottingham BRC |
| Organisation | University of Nottingham |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This collaboration consists of working closely with a colleague to develop and evaluate multi-variate analysis methods (e.g. CCA and PLS) to find latent associations between imaging and behavioural data. My primary input is to provide brain connectivity and behavioural features and to evaluate and report on analysis techniques. |
| Collaborator Contribution | Ali-reza Mohammadi-Nejad has developed several multivariate analysis techniques and continues to develop techniques in accordance with our analysis needs. In addition, their expertise is vital in understanding which analysis techniques in the literature are applicable to our data and how they should be applied. |
| Impact | As of yet there are no formal outputs. We continue to collaborate to evaluate and compare multiple multivariate analysis techniques. These evaluations will form the basis of a thesis chapter and a paper for publication. |
| Start Year | 2018 |
| Description | Nottingham-Yale CCA collaboration |
| Organisation | Yale University |
| Department | School of Medicine |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | I completed a 2 month placement at the Anticevic Lab in the Department of Psychiatry at Yale. During this time, I started investigations in how canonical correlation analysis (CCA) may be applied to real data to explore brain-behaviour associations using data from the Human Connectome Project (HCP). This work has led to the submission of an abstract to an international conference (OHBM 2020). |
| Collaborator Contribution | Collaborators at Yale have provided expertise in both psychiatry and statistical analysis, leading to a more targeted exploration of the pitfalls of CCA when applied to data typical of that used in the field of neuroimaging. Collaborators at Yale are focussing on the exploration of the behaviour of CCA via data simulations, leading to the submission of another abstract to an international conference (OHBM 2020). |
| Impact | Shaun Warrignton, Markus Helmer, Jie Lisa Ji, Ali-Reza Mohammadi-Nejad, Alan Anticevic, John Murray, Stamatios Sotiropoulos, 'Exploring the stability of canonical correlation analysis between imaging and non-imaging datasets', OHBM 2020 abstract submitted Markus Helmer, Shaun Warrington, Jie Lisa Ji, Alan Anticevic, Stamatios Sotiropoulos, John Murray, 'On discovery of brain-phenotype relationships: detection, estimation, and prediction', OHBM 2020 abstract submitted |
| Start Year | 2019 |
| Title | GitHub code repository |
| Description | A GitHub repository of code designed to perform an array of MRI brain connectivity processing pipelines in Unix (bash) and Matlab scripting languages. |
| Type Of Technology | Software |
| Year Produced | 2019 |
| Impact | This repository allows for version control and public sharing. Sections of this repository are publicly available. |
| URL | https://github.com/swarrington1?tab=repositories |
| Title | XTRACT |
| Description | Tool for automated and standardised tractography in the human and macaque brain freely available via FSL, see https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/XTRACT and https://www.biorxiv.org/content/10.1101/804641v1 for details. |
| Type Of Technology | Software |
| Year Produced | 2019 |
| Impact | The development of this toolbox has led to the submission of a journal paper (currently under review). Researchers around the world have already started to use the software to investigate their own research questions. The tool is also being used as a part of the "Defining WM and tractography" collaborative project. |
| URL | https://www.biorxiv.org/content/10.1101/804641v1 |
| Title | XTRACT_viewer |
| Description | An "add-on" to the XTRACT software package for quick and easy viewing of the results obtained by running XTRACT. |
| Type Of Technology | Software |
| Year Produced | 2019 |
| Impact | This software is linked to the XTRACT software. |
| URL | https://www.biorxiv.org/content/10.1101/804641v1 |