Robust graph analysis of brain connectivity
Lead Research Organisation:
University College London
Department Name: Institute of Child Health
Abstract
A broad range of neurological diseases and disorders have been linked with pathological alterations in the connectivity of the brain. However, robust methods for identifying and characterising abnormalities in connectivity, their evolution over time and response to treatments, are lacking; and addressing this omission represents a pressing clinical need. In this proposal we aim to meet this need using novel methods based on medical imaging and graph theory, a well-established mathematical framework with which to describe and characterise interconnected systems. To establish a clear baseline, we will characterise the typical "normal" connectivity network, and model statistically its variability in a healthy population. We will also investigate approaches to classifying graphs into groups, and identify common factors underlying structural and functional connectivity, to be used as new biomarkers. We will use magnetic resonance imaging (MRI) and electroencephalography (EEG) to obtain connectivity information in the living brain; and childhood epilepsy and autism spectrum disorders will be investigated as neurological disorders which can display altered brain connectivity. Our developments will also be applicable to other data which can be represented graphically. This work will provide major novel tools for graph analysis of brain connectivity, thereby driving connectivity network methods towards reliable and routine clinical application. Through our close links with clinical colleagues we will ensure that our developments are well positioned for wide-ranging applicability, elucidating connectivity failures in disease and their recovery with treatment.
Planned Impact
The primary opportunity for impact outside academia in the work described in this proposal lies in its contribution to the understanding of "disconnection syndromes". We highlight childhood epilepsy and autism spectrum disorders (ASDs) as two specific areas in which we expect a significant clinical impact, but disconnection between brain regions is thought to be a major contributing factor to a broad range of neurological deficits that collectively impose a huge health and economic burden on society. Since we also aim to elucidate the changes in connectivity in response to drug treatments, commercial exploitation of some of the developments arising from the project may also be a medium-to-long-term possibility in the pharmaceutical sector. Open access to the methods developed during the project, as well as clear summaries of the ideas embodied in it, will ensure that a very wide, international audience can benefit from them as quickly as possible.
Publications
Deligianni F
(2014)
Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.
in Frontiers in neuroscience
Clayden JD
(2013)
Imaging connectivity: MRI and the structural networks of the brain.
in Functional neurology
Parker CS
(2018)
Structural and effective connectivity in focal epilepsy.
in NeuroImage. Clinical
Parker CS
(2014)
Consensus between pipelines in structural brain networks.
in PloS one
Deligianni F
(2016)
NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity.
in PloS one
Clayden JD
(2013)
Principal networks.
in PloS one
Deligianni F
(2013)
Multimodal Brain Image Analysis
Description | We have developed techniques for identifying important subnetworks in the living brain using medical imaging data, and a framework for relating functional and structural measures of brain connectivity. We have discovered that EEG data is better at predicting fMRI-based functional connectivity than vice-versa, and found evidence that sophisticated structural models may be helpful in unravelling the complex relationship between structure and function. In addition, we continue to investigate the normal variability in brain connectivity features, both in adults and children. |
Exploitation Route | We have been involved in a number of applications in clinical and nonclinical neuroscience, demonstrating our developments' wide applicability. Areas of application that we have directly collaborated on include normal childhood development (including structural and functional differences between monolingual and bilingual children), multiple sclerosis, autism and sickle cell disease. Clinical and neurolinguistic collaborators have been very positive about the approach. |
Sectors | Digital/Communication/Information Technologies (including Software) Healthcare |
URL | http://www.homepages.ucl.ac.uk/~sejjjd2/research.html#multimodal-brain-networks |
Description | Our work on identifying important subnetworks in brain connectivity graphs has been applied to the study of functional connectivity in young children, and to structural connectivity in multiple sclerosis. Further medical applications of our brain connectivity ideas in paediatric epilepsy and sickle cell disease are in various stages of development, with the enthusiastic support of clinical colleagues. This work has also influenced new efforts to develop connectivity mapping approaches that are tailored for intra-operative neurosurgical use in nearby hospitals; again, with the collaboration of the relevant clinical specialities. Through all of these initiatives, and their gradual influence on medical policy and practice, impact is being realised in the healthcare sector. |
First Year Of Impact | 2013 |
Sector | Healthcare |
Impact Types | Policy & public services |
Description | Research Project Grant |
Amount | £305,748 (GBP) |
Funding ID | RPG-2017-403 |
Organisation | The Leverhulme Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2018 |
End | 03/2021 |
Description | Royal Society-Newton Mobility Grant |
Amount | £4,700 (GBP) |
Funding ID | NI160219 |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2017 |
End | 03/2018 |
Description | IoE |
Organisation | University College London |
Department | Institute of Education (IOE) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Originator and co-investigator on jointly held research grant (see Additional Funding) |
Collaborator Contribution | Lead investigator on jointly held research grant |
Impact | This collaboration is still in the relatively early stages, and has not produced any outputs yet. It is multidisciplinary (linguistics, education, imaging science, computer science). |
Start Year | 2017 |
Description | IoN |
Organisation | University College London |
Department | Institute of Neurology |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Provision of software and expertise in tractography and network-based analysis of brain connectivity |
Collaborator Contribution | Access to manpower and data |
Impact | Several journal and conference publications have been submitted on this work. This collaboration is multidisciplinary (computer science, physics, neuroscience, medicine). |
Start Year | 2012 |
Title | TractoR |
Description | TractoR is a flexible and integrated package for medical image analysis based on the open-source R platform for statistical computing. It provides interfaces for technical and less technical users, to allow them to perform image manipulation and brain connectivity analyses on their own data. It is also the context in which our methodological work is first developed and made publicly available to the community. The software is being updated on a rolling basis during the course of the project, to include the methodological advances arising from it. |
Type Of Technology | Software |
Year Produced | 2014 |
Open Source License? | Yes |
Impact | The availability and maturity of this software has been a significant factor in many established and new collaborative partnerships. |
URL | http://www.tractor-mri.org.uk |
Description | School visit (Birmingham) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | I gave a talk to 100-200 A-level pupils at my former school, covering my career and recent research, and answered their questions. This was a careers event, timed to inform their applications to undergraduate degrees. |
Year(s) Of Engagement Activity | 2020 |