Research directions
The work sits where imaging physics, signal processing and clinical neuroscience meet. Seven strands, held together by a single question: what can a measured signal tell us about the brain that produced it?
SIGNALS
The acronym is the map of the lab.
The voice as a clinical signal
Paralinguistic feature extraction, prosody and timing analysis, and the statistical treatment of speech for distinct mental health conditions. Applied in the Speech Health Lab.
MRI, fMRI, diffusion and flow
Sequence physics and acquisition trade-offs, structural and functional analysis pipelines, diffusion modelling, and 4D flow. Grounded in NMR physics.
Brain connectivity
Structural and functional connectomes, graph-theoretic description of network organisation, and the methodological question of how much of a connectome is biology and how much is pipeline a computational framework.
Systems and neurophysiology
The anatomy and physiology that any imaging result has to be reconciled with. The brain atlas came out of this strand. Many more to come in future across Preclinical domain.
Modelling and computational psychiatry
Statistical modelling for psychology and psychiatry, multimodal biomarkers, and the application of machine learning and medical language models to clinical data with attention to software development for long term sustainability.
Teaching and tooling
Open educational resources on MRI and NMR foundations, statistics and coding, and research communication alongside simulation work that makes the underlying physics visible. Still a work in progress, but the brain atlas is a first step.
Publications
A current list of publications is maintained on ORCID and ResearchGate.