Better understanding of the neurocognitive mechanisms that contribute to variation in children's development will help guide where best to target assessment and support for children who need it. Evidence-based supports will ensure all children are able to thrive and reach their full potential. We take a variety of approaches towards this overarching goal - see below for more information.
We believe that our research should seek to answer questions that are relevant to people with lived experience. To this end, we regularly seek input on our ideas and implementation of research, to ensure projects are accessible and reflect stakeholder priorities. Our Engagement page has some examples of previous stand-alone engagement projects, but this is an ethos we seek to embed in everything we do.
We also think it's important to feedback our findings to people outside of academia, if you are interested in having us present at your organisation or group, get in touch.
Although many models of psychopathology assume a one-to-one mapping of cause-effect, this is probably far too simplistic a model of human brain development. We use multi-method and multi-informant measurement to get a fine-grained and in-depth picture of a child's cognitive functioning, their family dynamics, and the environments they interact with. We are particularly interested in delineating the interacting effects of risk and resilience factors as this may offer new targets for supporting children in their development.
Early childhood is a time of dynamic brain development. Understanding the mechanisms that underpin individual variation in development requires methods to robustly capture (individual) change over time.
We combine repeated measures of neurocognitive features (such as cognitive task performance, eye-tracking, or EEG markers) with structural equation modelling techniques which can handle complex longitudinal data. This approach allows us to model individual trajectories during key developmental periods.
Although diagnostic categories are useful tools, there is evidence of substantial co-occurrence between diagnoses, and significant overlap in biological and cognitive features.
Therefore, we try and think about mechanisms from a transdiagnostic viewpoint, focusing on links between profiles of neurocognitive functioning and domains of characteristics/symptoms, rather than binary categories.
For example, although differences in sensory processing are highly prevalent in autistic people, new evidence suggests these differences can also occur in people without a diagnosis of autism. We are interested in what might drive individual variation in this domain, regardless of a person's diagnostic status.
