Dr Delshad Vaghari

University position

Research Associate

Departments

Department of Psychology

Email

dv315@cam.ac.uk

Home page

https://www.abg.psychol.cam.ac.uk/

Research Themes

Systems and Computational Neuroscience

Clinical and Veterinary Neuroscience

The Cambridge Neuroscience Community

Interests

I am a post-doctoral research associate at the Adaptive Brain Lab (Prof Zoe Kourtzi's Lab). My primary interest concerns how to leverage the use of machine learning to study neurodegenerative diseases. I use neuroimaging techniques such as electro- and magneto- encephalography (EEG/MEG), structural and functional magnetic resonance imaging (f/MRI), positron emission tomography (PET), etc to examine changes in the brain due to dementia. I develop machine-learning models for the early detection of Alzheimer's disease and other subtypes of dementia.

Research Focus

Keywords

Machine Learning

Prognostic trajectories

Neuroimaging

Clinical conditions

Alzheimer's disease

Cognitive impairment

Dementia

Equipment

Computational modelling

Cross-sectional and cohort studies

Electroencephalography (EEG)

Magnetic resonance imaging (MRI)

Positron Emission Tomography (PET)

Collaborators

No collaborators listed

Associated News Items


    Key publications

    Delshad Vaghari, Ehsanollah Kabir, Richard N Henson (2022), “Late Combination shows that MEG adds to MRI in classifying MCI versus Controls” NeuroImage

    Delshad Vaghari, Ricardo Bruna, Laura E Hughes, David Nesbitt, Roni Tibon, James B Rowe, Fernando Maestu, Richard N Henson (2022), “A multi-site, multi-participant magnetoencephalography resting-state dataset to study dementia: The BioFIND dataset” NeuroImage

    Publications

    2022

    Ricardo Bruņa, Delshad Vaghari, Andrea Greve, Elisa Cooper, Marius O Mada, Richard N Henson (2022), “Modified MRI anonymization (de-facing) for improved MEG coregistration” Bioengineering