The main goal of our research group (Neural Oscillations in Multisensory Communication Group at the Centre for Human Brain Health (CHBH), University of Birmingham) is to understand the brain’s information processing in human communication. We are particularly interested in how brain rhythms (also known as neural oscillations) interact with audiovisual speech rhythms when we listen to natural speech (perception) [1-3] as well as in a conversation (interaction between speech perception and production) in our daily lives.
To study this, we use Magnetoencephalography (MEG) and Optically Pumped Magnetometers (OPM), a neuroimaging method that allows for investigating the brain with excellent temporal and good spatial resolution. We aim to study how brain rhythms track speech rhythms (reactive process) as well as predict upcoming speech inputs (proactive process) from diverse perspectives, such as:
1) Local/global brain network within- and cross-frequency in order to identify feedforward and feedback (top-down) information processing using connectivity/causality measures. In addition, its relationship to the anatomical brain network (e.g. data acquired by Diffusion-Weighted Imaging).
2) In combination with neuromodulation techniques, e.g., sensory (via rapid frequency tagging) and/or ultrasound stimulation methods, to understand the causal/modulatory mechanism.
3) Analysis of brain signals in combination with Machine Learning (ML) based Natural Language Processing (NLP) algorithms in order to identify feature representations in the brain [4][5].
4) Also, we plan to extend the study to identify diagnostic and prognostic biomarkers for patients with (age-related) hearing loss and mild/moderate traumatic brain injury (mTBI) in order to find new approaches to effective intervention and develop rehabilitation programmes for the patients.
5) Our research aims to investigate the neural mechanisms underlying audiovisual speech tracking and semantic processing across various developmental stages, spanning from childhood to late adulthood. Through this investigation, we aim to identify potential interventions for neurodevelopmental disorders, including but not limited to dyslexia, developmental language disorders, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD).
The PhD project will be well suited to candidates ideally having experience in electrophysiology, cognitive neuroimaging, computational neuroscience, psychology, computer science or similar disciplines. The research project requires the acquisition of MEG data and analysis of neural oscillations and their relationship to behaviour. Therefore, experience with MEG/EEG/OPM, spectral analysis, programming skills (Matlab, Python, or R), and Machine Learning/Deep Learning skills is highly desirable.
Lab webpage: https://www.neureca.org/