Anatomy-Driven Brain Connectivity Mapping

Lead Research Organisation: University of Oxford
Department Name: Clinical Neurosciences

Abstract

The connectome, the comprehensive map of neural connections in the human brain, is unique in every individual. Even identical twins differ at the level of neural connectivity. Mapping the human connectome and its variability across individuals is essential in getting insight into the unknown cognitive aspects of brain function, but also into identifying dysfunctional features of the diseased brain.
For these reasons, understanding the human brain, its organisation and ultimately its function, is amongst the key scientific challenges of the 21st century. Magnetic resonance imaging (MRI) has revolutionised neuroscience by uniquely allowing both brain anatomy and function to be probed in living humans. Even if MRI allows only macroscopic features to be recovered (at the level of relatively large tissue regions, rather than individual neuronal cells), its non-invasive and in-vivo application has opened tremendous possibilities for brain research. Diffusion-weighted MRI (dMRI) is a particular modality that uniquely allows the mapping of fibre bundles, the underlying connection pathways that mediate information flow between different brain regions. The connection mapping is performed indirectly by processing dMRI images via computational algorithms referred to as tractography.
Tractography has already provided fundamental new insights into brain anatomy. The importance of brain connectivity to our understanding of the brain along, with the great potential revealed by tractography algorithms have led to large initiatives from both sides of the Atlantic. These utilise dMRI to collect state-of-the-art datasets of the healthy adult and the developing brain and map the structural connectome through tractography. They include the $30M NIH Human Connectome Project, the 15M Euros ERC Developing Human Connectome Project and the £30M UK funded Biobank Imaging. However, without state-of-the-art analysis methods, and new ways of analysing dMRI data, researchers will fail to get the most out of this vast wealth of upcoming data.
In this project, we propose new frameworks for tractography methods centred on neuroanatomy. We particularly focus on problems arising from ambiguous mapping of complex geometries (which are very common in the brain) to the dMRI measurements. These pose significant limits to the accuracy of existing approaches. We propose wholesale changes through computational and algorithmic solutions that will allow connections to be measured in-vivo with unprecedented detail, whole brain organization to be studied at a much finer scale and anatomical features -invisible to existing techniques- to be revealed. These advances will open new possibilities for neuroanatomical studies, but also set the foundations for new basic research in MRI processing and connectivity mapping. We will illustrate their potential using compelling demonstrator applications from basic and clinical neuroscience, including the assessment of benefits from using the new technology in assisting neurosurgical planning.

Planned Impact

This research provides the technological innovation that is essential for understanding and modelling human brain as an integrated network. The research output will have a transformative impact on science, from basic neuroscience to neurology, psychology and psychiatry, on pharmaceutical industry, and ultimately on the society as a whole, from the wellbeing of an individual to the care of patients suffering from neurological disorders.
There will be immediate impact on clinical and basic neuroscience researchers worldwide. The proposed advances to brain connectivity mapping open new, exciting possibilities for in vivo studies of neuroanatomy and neuropathology. For instance, differences in connectivity patterns can be used to identify functionally segregated regions; the anatomical substrate of behavior/cognition can be explored; connectivity changes may serve as disease biomarkers. Our two groups are the authors of the two leading software packages for diffusion imaging, FSL and CAMINO, ensuring the successful and timely realisation of this impact.
The impact on clinical and basic neuroscience will lead to additional impact on the downstream disciplines such as neurology, psychology and psychiatry. A better understanding of the organisation of the brain network is prerequisite to the investigation into the alteration of this network in diseased states from various brain and mental disorders. This will lead to a deeper understanding of the aetiology of these disorders.
The impact on neurology, psychology and psychiatry will in turn benefit pharmaceutical industry. Improved understanding of the aetiology of the various brain and mental disorders will allow the identification of new therapeutic approaches and targets. This creates opportunities to develop novel disease-modifying treatments.
Ultimately, the combinations of these advances will benefit the society as well. A deeper understanding of the inner workings of our brain will allow individuals to take preventive measures to ensure the long-term wellbeing of their minds. New and improved treatments for brain and mental disorders will improve patient outcome and the quality of living of themselves and their carers.

Publications

10 25 50
 
Description We have developed a number of new computational frameworks that push the technology for accurate connectivity mapping of the living human brain. These developments meet the project's objectives and include:

1) A new way to perform anatomical connectivity mapping has been devised (Bastiani et al, NeuroImage 2017), which further allows a more precise mapping of brain connections, particularly in regions of the human brain with very complex structure, such as bending and fanning structures. This has been a long standing limitation of current technologies and we have provided a comprehensive framework that provides a novel solution. We have driven the developments and validated this framework using microscopy techniques, which can achieve much higher imaging resolution than MRI. However microscopy can be used only in post-mortem brains, contrary to our technology.

2) A data fusion approach has been developed (Sotiropoulos et al, NeuroImage 2016) that integrates complementary in neuroimaging datasets (for instance data with different spatial resolution and contrast) to improve brain connection estimation near the cortex. A case study was performed showing the benefits in data from the Human Connectome Project and illustrating the reduction in biases obtained from previous approaches. This approach improves accuracy by addressing typical image acquisition trade-offs, which would otherwise dominate the results.

3) We have developed a new framework which permits enhancement of MRI data obtained with short-duration scans in the clinic, using state-of-the-art data obtained using bespoke scanners and very long scans. This way, the amount of information contained in a clinical scan can be increased using features from one of the best MRI datasets available nowadays (Human Connectome Project data), without the need for additional scan time or additional hardware. This development was led by our partners at UCL (Alexander et al, NeuroImage 2017) and we have contributed to illustrating its benefits for tractography and reconstruction of very thin pathways that would have been otherwise invisible in standard clinical datasets.

4) We have devised a number of validation protocols for comparing the developed connectivity mapping technologies. These include direct comparisons (Donahue et al, Journal of Neurosciece 2016) with traditional ground-truth neuroanatomy measurements (chemical tracing), which are however performed post-mortem using very labour intensive approaches. We also performed indirect validation, by confirming the benefits of our methods in assisting neurosurgical planning. Specifically, we confirmed the predictive power of our methods for assessing the efficacy of potential target locations in deep brain stimulation surgery (Akram et al, NeuroImage 2017), a technique commonly used for instance to suppress the symptoms of Parkinson's disease. Finally, we used estimates of anatomical connectivity maps in a neuroscience application. Anatomical connections were used to build the backbone of whole-brain mechanistic models that aim to explain spontaneous activity recorded in the human brain (Abeysuriya et al, Plos Computational Biology, 2018), (Hadida et al, NeuroImage 2018).

5) As brain mapping can be very computationally demanding, we have developed a number of toolboxes based on Graphics Processing Units (GPUs) to allow considerably faster computations. A tractography toolbox which allows higher precision via using anatomy-driven constraints has been developed. A generic library for biophysical modelling of microstructure and fibre patterns has been also devised and implemented (Hernandez et al, Neuroimage 2019). These approaches allow speed-ups of more than two orders of magnitude, changing the perspective of what is computationally feasible in diffusion MRI. Journal publications are in preparation for this work and these toolboxes are already heavily used by large international consortia that aim to map brain connectivity in large cohorts, including the Human Connectome Project (Glasser et al, Nature Neuroscience 2016) and the UK Biobank (Miller et al, Nature Neuroscience 2016)

6) We have used histology and microscopy to learn anatomical features of connections in the vicinity of white matter/grey matter boundary on a whole-brain scale. We have used these features to create a new coordinate system that allow us to navigate throughout the brain in a more anatomically consistent manner (Cottaar et al, NeuroImage 2018). We have also utilised these features to map more accurately connectivity, developing a framework that allows quantitative constraints to be imposed on estimation. We are preparing a manuscript for this last methodological innovation.

7) We used our new brain mapping technologies to develop whole-brain models that can predict and simulate the dynamics of the human cortex more accurately than before (Demirtas et al, Neuron 2019). These can provide insight into the brain's functional organisation, in health and disease and highlight its relationships with neuro-anatomy/structure (Tewarie et al, Neuroimage 2019), (Hadida et al, Neuroimage 2018), (Abeysuriya et al, Plos Computational Biology, 2018).
Exploitation Route FSL and Camino (our flagship software packages developed by our groups in Oxford and UCL) are used to make the frameworks available to the wider community. A number of related tools will be available in the next public release of FSL, including the GPU-based libraries for biophysical modelling and tractography with anatomical constraints, as well as new quality assessment and quality control tools aimed to assist in brain connectivity studies (particularly in studies with non-compliant subjects, such as patients or older subjects who tend to move more). These packages are already adopted and used by large international consortia (the NIH Human Connectome Project throughout the Lifespan and the ERC developing Human Connectome Project). Furthermore, we have Matlab code for the new asymmetric tractography algorithms and we will be porting this into FSL soon.
Sectors Healthcare,Pharmaceuticals and Medical Biotechnology

 
Description Our accelerated, surface-constrained connection mapping toolbox (probtrackx2 in FSL) is been used both in Oxford and in UCL to assist pre-surgical planning. In Oxford, patients with tumours undergo a scan before surgery and the surgeon can extract the connections around the tumour to establish the best possible strategies for approaching the tumour and resecting it, without however damaging pathways that provide vital functionality to the patient. Our tools (and optimised diffusion MRI scan protocols) are used for mapping the connections with higher accuracy and faster than before. In UCL, Parkinson's patients with tremor undergo Deep Brain stimulation via an implanted electrode, a technique which alleviates the disease symptoms. Finding the most efficacious site for the electrode implantation is a challenging task for the surgeons, which includes trial attempts during surgery. Neurosurgeons have found that using our connectivity toolboxes can predict better and more efficiently the target location for implanting the electrode, with the potential therefore to reduce the time of the operation. More impact is expected in the coming years. The Connectome projects focused on brain disorders are ongoing. The UK Biobank is the largest ever population-level imaging study. We are naturally positioned so that our technological developments are rapidly uptaken by these consortiums. There is therefore a potential for identifying latent connectivity signatures as disease markers, something which would have immediate impact into medical technology companies. We are also involved in the Connectome projects throughout the Lifespan (development and aging), which will also allow our technologies to impact the exploration of brain aging and mental health, for instance within the context of dementia.
First Year Of Impact 2016
Sector Healthcare
 
Description SS Invited contributor to ESPRC -Wellcome scoping event Bioelectronics solutions for neuromodulation
Geographic Reach National 
Policy Influence Type Membership of a guideline committee
 
Description Centre grant to establish Wellcome Centre for Integrative Neuroimaging (Behrens, Co-I)
Amount £11,463,085 (GBP)
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 04/2017 
End 04/2022
 
Description Confidence in Concept - Explaining cognitive impairment in multiple sclerosis through integrated structural and functional networks (Sotiropoulos, Co-I)
Amount £97,000 (GBP)
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 02/2018 
End 02/2019
 
Description Data-driven approaches for estimating multi-modal connectivity in the developing brain
Amount £60,000 (GBP)
Funding ID 1796154 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2016 
End 09/2020
 
Description IMPACT Doctoral Studentship - Unravelling the associations between multi-modal brain connectivity, genetic factors and behaviour (Sotiropoulos)
Amount £75,000 (GBP)
Funding ID 1912956 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 10/2017 
End 03/2021
 
Description LIFESPAN HUMAN CONNECTOME PROJECT in DEVELOPMENT and AGING ($2x14m across 9 centres)
Amount $1,000,000 (USD)
Organisation National Institutes of Health (NIH) 
Sector Public
Country United States
Start 05/2016 
End 05/2020
 
Description Learning the associations between cognitive decline and ageing through brain imaging (Sotiropoulous)
Amount £40,000 (GBP)
Organisation Birmingham-Nottingham Strategic Collaboration Fund 
Sector Academic/University
Country United Kingdom
Start 03/2018 
End 09/2019
 
Description Seed Award in Science: Unified modelling of structural and functional imaging for accurate brain connectivity mapping in health and disease
Amount £100,000 (GBP)
Funding ID 217266/Z/19/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 01/2020 
End 01/2022
 
Description Senior Research Fellowship - Neural mechanisms of behavioural control (Behrens)
Amount £1,968,459 (GBP)
Funding ID 104765/Z/14/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 10/2015 
End 09/2019
 
Title A GPU library for biophysical modeling using brain MRI 
Description We have developed a GPU library that allows users with no GPU/CUDA programming to create GPU binaries for biophysical model fitting and estimation. These executables allow more than two orders of magnitude accelerations in computation times and change the perception of what is feasible, both for model building/exploration and for data analysis. Without these accelerations certain types of stateo-of-the-art models are impractical to use, as they may require more than ten days to be fitted to a single dataset (normally neuroscience studies have many tens to hundreds - and recently thousands of - datasets) 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact A first abstract at ISMRM describes these contributions and we are in the process of preparing a journal paper. The new toolbox will become part of FSL and form the backbone for a number of processing steps used in the UK Biobank Imaging pipelines that are used to create the database with imaging-derived phenotypes. It also has the potential to be used in the recently launched Lifespan Connectome Projects. 
URL https://users.fmrib.ox.ac.uk/~moisesf/cudimot/
 
Title Automatic Quality Assessment and Control for brain connectivity data 
Description We have developed an automated pipeline for assessing quality and performing quality control in large imaging cohorts with diffusion MRI data. 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact ISMRM abstract published. Journal paper to be submitted and pipeline to be made freely available through FSL. The pipeline is already used in a number of large-scale projects, including the ERC-funded developing human connectome project and the NIH-funded Lifespan Human Connectome (in development and aging). 
 
Title GPU-based software for analysis of diffusion MRI 
Description Software for estimating fibre orientations from diffusion MR images. The tool is built up on our previous work, but now supports a family of models and allows massive accelerations in computations using graphics processing units (GPUs). 
Type Of Material Improvements to research infrastructure 
Year Produced 2014 
Provided To Others? Yes  
Impact Massive accelerations allow processing of large databases in realistic time frames. The tool is now in use by cornerstone projects, such as the NIH Human Connectome Project, the UK Biobank and the ERC developing Human Connectome Project. 
 
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 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
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 Human Connectome Project 
Organisation Washington University in St Louis
Department Department of Neuroscience
Country United States 
Sector Academic/University 
PI Contribution Our team is the backbone of methods development for this vast project. We develop software tools that will be used to study brain connections in a large cohort of subjects with unprecedented data quality
Collaborator Contribution Provide state of the art data Provide expertise in brain anatomy
Impact Publication 21908183, 27071694, 27571196, 26260428, 23702418, 23668970. Software release of the HCP pipelines: https://github.com/Washington-University/Pipelines. Development of state of the art approach for correcting distortions in neuroimaging data. Publications: 26481672, 27393418 Software release of relevant toolbox: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddy
Start Year 2010
 
Description UCL Institute of Neurology - DBS 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution Tools for MRI analysis and connection mapping
Collaborator Contribution Provide functional neurosurgery data on efficacy of stimulation sites
Impact This collaboration translates the methodology we develop to the clinic. We use connectivity mapping to predict efficacious targets for deep brain stimulation, prior to surgery and assist surgical planning. A database with patient Neuroimaging data has been developed along with pipelines to analyse them. The structural connectivity profiles of potential target regions have been estimated and used to predict the efficacy of stimulation. A journal publication has arisen from this work, showing that connectivity mapping improves the ability for presurgical planning and target selection: Pubmed: 28711737
Start Year 2014
 
Description UCL Microstructure Modelling 
Organisation University College London
Department Department of Computer Science
Country United Kingdom 
Sector Academic/University 
PI Contribution Provide tools and expertise in brain connectivity estimation
Collaborator Contribution Provide tools and expertise in tissue microstructure modeling
Impact Two new methods for analysis of diffusion MRI have arisen from this collaboration, both published in a top neuroimaging journal. Asymmetric deconvolution - PMID: 28669902 and Image quality transfer - PMID: 28263925. We have also used this successful collaboration within the efforts of a large consortium, the UK Biobank Imaging, which has also led to another journal publication - PMID: 29079522. Finally. another journal paper is been prepared on model selection for a taxonomy of biophysical models, which will be soon submitted.
Start Year 2014
 
Description WashU - Histology and Tracers in the non-human primate brain 
Organisation Washington University in St Louis
Department Department of Neuroscience
Country United States 
Sector Academic/University 
PI Contribution We develop new computational frameworks for more accurate mapping of connections to the cortex using MRI.
Collaborator Contribution Provide histological data (myelin staining) and expertise in primate anatomy that we use to guide our model development
Impact Three conference presentations (Cottaar et al 2015, Cottaar et al 2016, Bastiani et al 2016). One review article published in Nature Neurosciece (Jbabdi et al, 2015), PMID: 26505566 One journal publication on new histology-driven methodology (Bastiani et al 2017), PMID: 28669902 . One journal publication on validation of tractography-based connectivity mapping using macaque tracing, PMID: 27335406 Another journal publication is under Revision and will appear in Neuroimage, 2018.
Start Year 2014
 
Description White matter anatomy of the macaque brain 
Organisation University of Rochester
Department University of Rochester Medical Centre
Country United States 
Sector Academic/University 
PI Contribution Ongoing collaboration to validate white matter anatomy inferred by imaging in macaques with chemical tracing. My expertise in tractography is a central part of this collaboration
Collaborator Contribution Provide ground-truth mappings of white matter tracts using tracers
Impact Publications 23407972 and 23283687
Start Year 2012
 
Description Yale Medical School - Brain Connectivity in Mental Health 
Organisation Yale University
Country United States 
Sector Academic/University 
PI Contribution Provide expertise and pipelines for mapping the brain connections in large patient cohorts (schizophrenia)
Collaborator Contribution Provide expertise on computational modelling of mechanisms of mental health disorders. Access to unique data, amongst the first HCP-like patient data.
Impact The collaboration is still very active. The first pilots have given rise to two NIH-funded projects, http://grantome.com/grant/NIH/R01-MH112189-01 & http://grantome.com/grant/NIH/R01-MH108590-01
Start Year 2016
 
Title FSL - Brain Mapping Software 
Description FSL is our group's software toolbox, which have been developed for more than 15 years. The developments from this particular grant have already appeared in new minor versions of FSL v.5 (diffusion toolboxes in 5.09 & 5.010 - https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/WhatsNew#anchor1) and will also appear in the FSL version 6, which is prepared top be released in 2018. 
IP Reference  
Protection Copyrighted (e.g. software)
Year Protection Granted
Licensed Yes
Impact FSL in total has had a huge impact in neurosciences. It is one of the de-facto standard software packages used in research environments for brain MRI analysis, currently by more than 5000 users in more than 500 institutions worldwide.
 
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
 
Description SES Case study 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Our research became one of the showcase studies for the UK Science and Engineering South consortium, illustrating how new computational technologies can provide solutions for practical neuroscience problems. Given that the technologies are based on GP-GPUs and corresponding programming architectures, there was interest raised by researchers and industry as well (NVIDIA in particular).
Year(s) Of Engagement Activity 2015
URL https://www.ses.ac.uk/2015/10/03/imaging-software-bring-the-brain-into-fuller-focus/
 
Description Talk at the Science Museum in London 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact I contributed to a talk that Tim Behrens gave about our joint work at the Science Museum. This was part of the Blavatnik series.
Year(s) Of Engagement Activity 2019
URL https://www.nyas.org/events/2019/blavatnik-awards-for-young-scientists-in-the-uk-inaugural-science-s...