Unraveling Brain Complexity with fNIRS and Modelling Approaches
About the Project
Brain function arises from a highly complex network of interconnected processes that we still don’t fully understand. Functional near-infrared spectroscopy (fNIRS) is a non-invasive tool that measures changes in brain oxygenation, offering a way to monitor brain activity across different populations across all stages of life. Its ability to capture both spatial and temporal information makes it uniquely suited to reveal key features of brain complexity—such as patterns of connectivity, regional specialization, and dynamic neural adaptations.
This project aims to advance our understanding of the brain’s intricate features by developing innovative methods that combine fNIRS with computational and mathematical modelling as well as machine learning. A major focus will be on building models that capture the diverse patterns of brain neuroplasticity—the brain’s remarkable ability to change and adapt. By linking variations in oxygenation signals with underlying neural processes, these models will help clarify how the brain learns new skills, recovers from injuries, and adapts to different experiences.
To achieve these goals, the project will develop advanced signal processing algorithms to improve data quality and spatial resolution while ensuring reproducibility. The integration of machine learning techniques will enable the detection and classification of subtle, complex patterns in fNIRS data. Ultimately, this work seeks to provide a clearer picture of the dynamic processes that govern brain function and to pave the way for more effective strategies in both cognitive research and clinical applications.
The project will be based at the University of Birmingham’s Medical Imaging Lab within the School of Computer Science, although the work will be developed in different areas across the University, including the School of Psychology, School of Medicine, and Sports Exercise, along with external collaborations we currently hold in our lab. The ideal candidate should have a background in computer science, engineering, mathematics, or physics, and a passion for combining modelling and programming in applied problems in neuroscience. Other beneficial skills for this project include programming, mathematical, and communication abilities, as well as proficiency in collaborative working. Successful applicants will work in a multidisciplinary team specializing in optical neuroimaging methods, under close supervision and with opportunities to interact with collaborators from other research areas in a supportive and friendly environment.
Funding notes
Funding is awarded through a directly funded application process. Self-funded or externally sponsored students are also welcome to apply. Formal applications for research degree study should be made online through the University’s website.
For more information, please contact Dr. Rickson Mesquita (r.c.mesquita@bham.ac.uk).
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