Multisensory Semantic Representations
- McNorgan, C., Smith, G.J., & Edwards, E.S. (2020).
Integrating functional connectivity and MVPA through a multiple constraint network analysis.
Neuroimage, 208, 116412.
- 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., 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
- Cree, G. S., McNorgan, C., & McRae, K. (2010).
Distinctive features hold a privileged status in the computation of word meaning: Implications for theories of
semantic memory. In T. A. Harley (Ed.), Sage Key Work in Psycholinguistics, Volume 5: Representation
(pp. 63-97). London: Sage. (Reprinted from Journal of Experimental Psychology: Learning, Memory, & Cognition, 32,
643-658).
- McNorgan, C., Kotack, R. A., Meehan, D. C., & McRae, K. (2007).
Feature-feature causal relations and statistical co-occurrences in object concepts.
Memory & Cognition, 35, 418-431.
doi: 10.3758/BF03193282
- Cree, G. S., McNorgan, C., & McRae, K. (2006).
Distinctive features hold a privileged status in the computation of word meaning:
Implications for theories of semantic memory.
Journal of Experimental Psychology: Learning, Memory, & Cognition, 32, 643-658. [Lead Article]
doi: 10.1037/0278-7393.32.4.643
- McRae, K., Cree, G. S., Seidenberg, M. S., & McNorgan, C. (2005).
Semantic feature production norms for a large set of living and nonliving things.
Behavior Research Methods, 37, 547-559. [Lead Article]
doi: 10.3758/BF03192726
- Cree, G. S., McRae, K., & McNorgan, C. (1999).
An attractor model of lexical conceptual processing: Simulating semantic priming.
Cognitive Science, 23, 371-414.
doi: 10.1207/s15516709cog2303_4
- McRae, K., Cree, G. S., & McNorgan, C. (1998). Semantic similarity priming without hierarchical category structure.
In Proceedings of the Twentieth Annual Conference of the Cognitive Science Society (pp. 681-686). Hillsdale NJ: Erlbaum.
Reading as a Multisensory Process
- Edwards, E.S., Burke, K., & McNorgan, C. (2018). Dyslexia on a continuum: A complex network approach.
PLoS One 13 (12), e0208923.
- Smith, G.J., Edwards, E.S., & McNorgan, C. (2018).
Longitudinal task-related functional connectivity changes predict reading development. Frontiers in Psychology, 9, 1754.
- McNorgan, C. & Booth, J.R. (2015).
Skill dependent audiovisual integration in the reading network induces repetition suppression.
Brain and Language, 141, 110-123.
- McNorgan, C., O’Young, D., Chabal, S., Lukic, S., & Booth, J.R. (2015).
Task dependent lexicality effects support interactive models of reading: A meta-analytic neuroimaging review.
Neuropsychologia, 67, 148-158.
- McNorgan, C., Awati, N., Desroches, A., & Booth, J.R. (in press).
Multimodal lexical processing in auditory cortex is literacy skill-dependent.
Cerebral Cortex.
- 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
- Brennan,C., Cao, F., Pedroarena-Leal, N., McNorgan, C. & Booth, J.R. (2013).
Learning to read reorganizes the oral language network only in
alphabetic writing systems. Human Brain Mapping, 34, 3354-3368.
- 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
Neural Connectivity and Computational Modeling
- McNorgan,C. (2021). The connectivity fingerprints of highly-skilled and disordered reading
persist across cognitive domains. Frontiers in Computational Neuroscience 15, 590093
- McNorgan, C., Judson, C., Handzlik, D., & Holden, J.D. (2020).
Linking ADHD and Behavioral Assessment Through Identification of Shared Diagnostic Task-Based Functional Connections.
Frontiers in Physiology 11, 583005
- 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.