The human brain is composed of multiple, anatomically distinct, processing units that are uniquely interconnected via white matter pathways.
Though these specialised functional regions tend to occur in similar areas of the brain, their precise location and size are highly variable among individuals. Many of these “cytoarchitectual” structures cannot be seen using routine MRI sequences.
Furthermore, accurate alignment of brain anatomy is a key requisite for many other neuroimaging analysis techniques.
The structural properties of these cytoarchitectual regions not only help support their discrete functions (e.g. vision, hearing), but can also help explain some of the observed inter-individual variability, from how people perceive and interact with the world, through to how they are affected by neurological disease.
We use neuroimaging to map the structure of the brain:
- To provide precise, reproducible, non-invasive measures of brain structure, which is fundamental to understanding the link between anatomy and function in health and disease.
- For in vivo quantification of a wide range of brain tissue microstructural properties, including measures of myelin, iron, cellular packing density, water density, diffusion, axonal diameter, regional blood flow and white matter connectivity.
- Use the intrinsic quantitative MRI (qMRI) properties to identify structures such as cortical lamina, cytoarchitectonic boundaries, subcortical nuclei and topographic gradients in individual subjects.
- To generate additional useful measures by accurately quantifying regional morphometric changes (e.g. cortical thickness).
- To gain insight into the underlying biophysical processes that contribute to any structural brain changes by characterising patterns of qMRI change.
Our goal is to provide:
Accurate, non-invasive histological maps of brain architecture at an individual subject level, in order to study:
- Organisational principles of brain structure
- Neurological and psychiatric disease
- Inter-individual variability
- Anatomical phenomics and genotype-phenotype relationships
- Develop techniques to improve the mapping, quantification and alignment of brain microarchitecture.
Damage to some of these small, difficult to define regions is seen up to 20 years before diagnosis of neurodegenerative conditions such as Alzheimer’s or Parkinson’s disease.
Improving our ability to map these regions in individual subjects will help provide:
- Earlier, more accurate diagnosis, before significant loss of brain tissue
- Non-invasive tools to monitor disease progression
- Improved safety and outcomes in neurosurgery, for example by allowing more accurate targeting of brain structures in deep brain stimulation
- Precision medicine approaches for tailoring treatments to individuals
- Greater understanding of these complex diseases.
- Techniques that facilitate the quantitative analysis of brain morphometry (voxel based morphometry) and microstructure (voxel based quantification, https://hmri-group.github.io/hMRI-toolbox/), all freely available tools in SPM
- Accurate between and within-subject diffeomorphic alignment for cross-sectional and longitudinal studies
- Techniques to map difficult to image brain regions, such as brainstem and thalamic nuclei, and topographic gradients of connectivity at an individual subject level
- Connectomic driven methods to improve surgical targeting in deep brain stimulation for tremor.
John Ashburner develops methods for computational anatomy to improve the mapping, quantification and alignment of brain microarchitecture. These techniques provide precise, reproducible, non-invasive measures of brain structure, which is fundamental to understanding the link between anatomy and function in health, disease and longitudinal studies.
Martina Callaghan develops MRI methods for non-invasive in vivo quantification of a wide range of brain tissue microstructural properties, including measures sensitive to myelin and iron content, cellular packing density, water density, diffusivity as well as connectivity. These quantitative MRI (qMRI) properties are used to identify structures such as cortical lamina, cyto– or myelo-architectonic boundaries, subcortical nuclei, and to characterise links with function and behaviour. They also provide insight into the underlying biophysical processes that contribute to structural brain changes (e.g. during neurodegeneration).
Christian Lambert develops methods using qMRI to map brain structures that are not normally visible on MRI, such as brainstem and thalamic nuclei, cortical lamina and white matter architecture. These help provide more accurate measurements of structural brain changes, and have applications in functional neurosurgical procedures such as deep brain stimulation