People

Structural brain ageing

White matter disease

Cognitive ageing

Stroke

Image Analysis

Alzheimer's disease and other dementias

We focus on processing biomedical signals and images in clinical applications.

Our main aim is to reveal the subtle changes that major diseases (e.g., Alzheimer's and epilepsy) cause in the brain activity and how this changes in different conditions and mental states.

In collaboration with researchers at Edinburgh, across the UK and overseas, we are currently working in the processing and analysis of biomedical signals, particularly human brain activity. By applying advanced mathematics, we aim at increasing our understanding of how several brain conditions progress. Of particular interest is the evaluation of brain functional connectivity in both neurodevelopmental and neurodegenerative diseases to understand how they affect the way in which different brain regions interact with each other. We are also interested in the interplay between structure and function in the brain and in the application of pattern recognition techniques to highly-dimensional clinical datasets to support decision making. Finally, we also work in the development of non-invasive methods for rehabilitation purposes, being either the dexterous controls prostheses for amputees or brain-computer interfaces.

For additional information, please see: http://www.research.ed.ac.uk/portal/jescuder

I am interested in all forms of brain imaging, primarily structural MRI, and currently working on multicentre, normative brain imaging and stroke.

My research is mainly focused on investigating the cognitive and neural correlates of a range of neuropsychiatric symptoms (e.g., delusions, sleep disorder, depression, apathy).

I am interested in improving the diagnosis/detection of Alzheimer’s disease and other types of dementia (especially in the earliest stages) through customised assessment methods or through the use of multivariate markers.  Variants of these markers could also be used to stratify patients or as outcome measures for clinical drug trials.  Relatedly, I have interests in developing methods to speed drug development.

I have projects underway to develop serum blood-based biomarkers for the dementias (in combination with other methods), to investigate the diagnostic utility of customised neuropsychological tests (and analysis methods), and in the near future hope to begin a project that will utilise electrophysiological methods.

I have an additional research line that focuses on understanding the neural bases of hypnosis and suggestibility. By targeting individual differences suggestion can be used to study elements of psychosis, changes in agency, and other interesting psychological and behavioural phenomena.

Within my research I use structural magnetic resonance imaging techniques (voxel-based morphometry and cortical thickness assessment), functional magnetic resonance imaging (brain activity and connectivity analyses), electrophysiological methods, and neuropsychological assessment.

Assessing neurodegeneration of the retina and brain with ultra-widefield retinal images.

Philosophers have often described the eye as the window to the soul. This can also be addressed on the scientific basis that the retina is a direct window into the health of the brain (or CNS). My focus is on the development of automatic detection algorithms of biomarkers for Age-related macular degeneration (AMD) and Alzheimer’s disease (AD) in retinal images. AMD is often characterised by the presence of drusen, small deposits of cellular debris, in retinal images appearing as bright white/yellow spots. The hallmark of AD is the presence of Aβ-amyloid which has also been shown to be present in drusen. There are currently no treatments for late AMD, therefore early diagnosis and detection of drusen could provide timely treatment. Additionally, the potential of drusen as an early biomarker of AD will be explored. My methods focus on image analysis and quantification of fundus and OptoMap images (Optos) and application of machine learning algorithms as an automatic detection strategy.

• Hippocampal atrophy
• Cognitive ageing
• Stroke
• Brain tumours