• PhD, The University of Western Ontario

Humans are multisensory creatures, and nearly everything we do, from reading the newspaper to drinking a cup of coffee requires us to integrate information represented across multiple sensorimotor systems. I use behavioral studies, neuroimaging (fMRI) and computational models (artificial neural networks) to investigate how the brain transforms and integrates multisensory representations that are distributed among a network of (more-or-less) functionally-specialized brain regions. Because integration depends on communication among these regions, my research focuses on the properties of the networks that support these processes. Recent neuroimaging studies in my lab have found that ongoing connectivity development within the network supporting audiovisual integration predicts reading skill in typically-developing and dyslexic children. An ongoing neuroimaging study in my lab has started to explore similar ideas among individuals diagnosed with ADHD, and within typical adults engaged in multisensory imagery of common objects. Methods and computational tools developed for these studies have the potential to predict how changes to or differences in brain connectivity (e.g., following brain disease or as a consequence of learning) influence how we represent information in our minds.

• Edwards, E. S., Booth, J. R., & McNorgan, C. (2018). Dyslexia on a continuum: A complex network approach. PLoS ONE. doi: 10.1371/journal.pone.0208923
• Smith, G. J., Booth, J. R., & McNorgan, C. (2018). Longitudinal task-related functional connectivity changes predict reading development. Frontiers in Psychology, 9:1754. doi: 10.3389/fpsyg.2018.0175
• McNorgan, C., & Joanisse, M.F. (2014). A connectionist approach to mapping the human connectome permits simulations of neural activity within an artificial brain. Brain Connectivity, 4, 40 – 52. doi:10.1089/brain.2013.0174.
• McNorgan, C., Randazzo-Wagner, M., & Booth, J.R. (2013). Cross-modal integration in the brain is related to phonological awareness only in typical readers, not in those with reading difficulty. Frontiers in Human Neuroscience, 7:388. doi:10.3389/fnhum.2013.00388.
• McNorgan C. (2012) A meta-analytic review of multisensory imagery identifies the neural correlates of modality-specific and modality-general imagery. Frontiers in Human Neuroscience, 6:285. doi:10.3389/fnhum.2012.00285.
• McNorgan, C., Alvarez, A., Gayda, J., Bhullar, A., & Booth, J.R. (2011). Prediction of reading skill several years later depends on age and brain region: Implications for developmental models of reading. The Journal of Neuroscience, 31, 9641-9648. doi:10.1523/JNEUROSCI.0334-11.2011.
• McNorgan, C., Reid, J. & McRae, K. (2011). Integrating conceptual knowledge within and across representational modalities. Cognition, 118, 211 – 233. doi:10.1016/j.cognition.2010.10.017.