- Brain connectivity modelling
I am a postdoctoral researcher in FMRIB Analysis Group, working on population and individual-level modelling of brain connectivity based on functional Magnetic Resonance Imaging (fMRI), and its application for prediction of non-imaging phenotypes. To that end, I am working as the developer of Probabilistic Functional Modes (PROFUMO) project. Recently, we developed stochastic PROFUMO (sPROFUMO), that is designed to simultaneously and hierarchically estimate brain networks for big populations (e.g. UK Biobank with expected 100,000 subjs) and every individual therein. Links to paper and code repository.
Before joining FMRIB in 2018, I did my PhD in Brain Imaging Methods for Neuroscience at MRC CBU, Cambridge University. My project, funded by Cambridge International Scholarship Scheme, was aimed at investigating the dynamic meaning comprehension networks in the human brain using novel approaches for Electro-/Magnetoencephalography connectivity. Prior to that, I did my undergraduate and master's studies in Biomedical Engineering- Bioelectrics at AmirKabir University of Technology.
Task modulation of spatiotemporal dynamics in semantic brain networks: An EEG/MEG study
Rahimi S. et al, (2022), NeuroImage, 246, 118768 - 118768
Distinct Roles for the Anterior Temporal Lobe and Angular Gyrus in the Spatiotemporal Cortical Semantic Network
Farahibozorg S-R. et al, (2022), Cerebral Cortex
Hierarchical modelling of functional brain networks in population and individuals from big fMRI data
Farahibozorg S-R. et al, (2021), NeuroImage, 243, 118513 - 118513
The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants.
Fitzgibbon SP. et al, (2020), Neuroimage, 223
Modelling subject variability in the spatial and temporal characteristics of functional modes.
Harrison SJ. et al, (2020), Neuroimage, 222