Laboratories

Focused ultrasound, acoustic simulation and experimental biophysics connect physical stimulation with biological responses. Research develops methods for blood–brain barrier modulation, targeted delivery and neuromodulation. Imaging, cavitation monitoring and histological measurements support the modelling and control of ultrasound exposure, alongside work on magnetic nanomaterials and wireless neural interfaces.

• Focused ultrasound and acoustic modelling
• Cavitation monitoring and predictive control
• Barrier transport and targeted delivery
• Neuromodulation and wireless interfaces

Machine learning methods connect images, language and sound with neural recordings and other complex data. Research combines generative models, representation learning and multimodal alignment to develop neural encoding and decoding. Graph and geometric learning, model interpretability and uncertainty quantification support robust analysis across datasets, participants and recording modalities.

• Neural encoding and decoding
• Generative and multimodal learning
• Graph and geometric deep learning
• Interpretability and uncertainty quantification

Biological principles guide the design of neural architectures and learning systems. Research develops spiking networks, reservoir computing and wiring rules inspired by genetic organisation and spatial structure. Studies of excitation, inhibition and memory connect network dynamics with computational performance, while mismatch-tolerant learning explores how neural computation can remain robust under device variability.

• Spiking networks and reservoir computing
• Bioinspired wiring and network topology
• Learning dynamics and computational memory
• Mismatch-tolerant neuromorphic learning

Physical models and computational analysis turn imaging signals into quantitative measurements of structure, physiology and metabolism. Research spans MRI physics, diffusion and perfusion analysis, PET tracer kinetics and multimodal image fusion. Method development examines reconstruction, parameter estimation and reproducibility, linking measurements across complementary imaging modalities and scales.

• MRI physics, diffusion and perfusion
• PET quantification and tracer kinetics
• Multimodal image analysis and radiomics
• Parameter estimation and reproducibility

Mathematical models and physiological recordings reveal interactions within the brain and between brain and body. Research combines nonlinear dynamics, Bayesian inference, directed connectivity and graph analysis to study changing neural networks. Biophysical modelling and signal processing connect neural activity, cardiovascular regulation and behaviour, including responses to multisensory and virtual environments.

• Nonlinear dynamics and Bayesian inference
• Brain networks and directed connectivity
• Physiological signals and brain–body coupling
• Behavioural and multisensory measurements

Molecular and cellular measurements connect biological mechanisms with material design and quantitative analysis. Research develops aptamer-based detection, fluorescence assays and approaches to studying extracellular vesicles and engineered nanocarriers. Microscopy, histology and computational modelling help characterise biological interactions, transport and material effects, including predictive methods for nanomaterial safety and environmental exposure.

• Aptamers and molecular detection
• Fluorescence assays and extracellular vesicles
• Nanocarriers and material–cell interactions
• Nanoinformatics and exposure modelling