Research

UKRI BBSRC Pioneer Awards

"Brain Mechanisms underlying Emotional Processing in Infants"

This project aims to use a cutting-edge brain imaging technique called Optically Pumped Magnetometers (OPMs) to explore the earliest origins of emotional processing in human infants. Since Darwin’s account of the evolutionary origins of emotion over 150 years ago, researchers have searched for early markers of emotion processing in human infants. The outcomes have been inconsistent: Most studies indicate that infants can discriminate basic emotions from facial expressions after 5 months of age, but a few reports suggest sensitivity in younger infants or newborns. By combining OPMs with advanced statistical methods, we aim to provide the most sensitive understanding yet of emotional processing in infants. OPM-MEG offers high resolution without the limitations of other imaging methods, making it well-suited for studying infants. We'll expose infants to emotional and non-emotional stimuli while recording their brain activity to reveal the neural mechanisms underlying emotional processing at different ages. This study will focus on infants aged newborn, 4 months, and 8 months, using both auditory and visual stimuli to capture early emotional development. 

SMQB Seedcorn Project

"Developing Early Diagnostic Methods for Autism using MEG and Novel Graph Neural Network"

Autism Spectrum Conditions (ASC) is prevalent, and early conditions are crucial to help manage the condition from childhood. Currently, ASD diagnosis is only based on behavioural information. While ASD diagnoses based on brain imaging data studies have been extensive, they are not suitable for young children who need to remain still and in specific positions during the procedure. Consequently, magnetoencephalography (MEG) is a more suitable neuroimaging technique for children, which provides a more comfortable recording environment and accurate temporal data than other types of brain imaging. However, there is a lack of ASC diagnostic research using MEG. 

In this study, we aim to use novel mathematical and computational techniques to analyse MEG data that is more appropriate for young children. Specifically, we will use network analysis and artificial intelligence to estimate how MEG data correlates with behavioural information. This research holds significant importance as it seeks to advance the understanding of brain activity in children with ASC and to investigate a method to diagnose ASD in young children using a more child-friendly neuroimaging technique.

IGI/IAS Pump-priming Funding

"Neural mechanisms of iconicity and cross-sensory metaphor "

In this project, we aim to investigate how the brain processes iconicity and metaphor in written and spoken language. We will use cutting-edge magnetoencephalography (MEG) to observe brain activity as participants comprehend iconic words and cross-sensory metaphorical expressions, compared to literal controls. By pinpointing brain dynamics during lexical processing, we aim to uncover the neural mechanisms underlying meaning-making through iconicity and metaphor. This pilot study will lay the groundwork for a larger-scale MEG study, with potential implications for understanding linguistic creativity and autism.