Aaron Newman

Education

BA(hons) University of Winnipeg
MSc University of Oregon
PhD University of Oregon
PDF University of Rochester

Research Interests

My research examines relationships between brain activity and thought (particularly language) using a variety neuroimaging tools. I direct the NeuroCognitive Imaging Lab (NCIL), where I train students in cognitive neuroscience research as we study how experience affects the brain in contexts such as second language learning and reading development. We also work on developing brain-computer interface technology with applications in learning, gaming, and assistive tech. Our lab also maintains an active collaboration with Dr. Colin Conrad in Dalhousie’s School of Information Management, taking a Neuro Information Systems approach to studying topics such as trust in AI and online learning. I am the author of two textbooks: Research Methods in Cognitive Neuroscience and Neural Data Science in Python.

Another facet of my work is training scientists at all levels to be more creative and critical thinkers, to understand design thinking and entrepreneurship, and to find and solve important problems within and beyond academia. I do this through the SURGE Innovation Sandbox at Dalhousie, where I develop and deliver classes, workshops, hackathons, and other programming.  

About My Lab

The NeuroCognitive Imaging Lab (NCIL) is a multimodal neuroimaging lab equipped with several EEG systems as well as fNIRS and eye tracking. We support trainees at all levels from undergraduate through postdoctoral, in an inclusive and supportive environment that encourages trainees to develop scientific and critical thinking abilities, as well as professional skills that position them for careers in both academia and industry. For more information on joining our lab and the opportunities available, please visit the NCIL website.

Selected Publications

• Douglas, C., Tremblay, A., and Newman, A.. (2023).  A two for one special: EEG hyperscanning using a single-person EEG recording setup. MethodsX 10, 102019 DOI: 10.1016/j.mex.2023.102019
• Galilee, A., Beck, L.J., Lownie, C., Veinot, J., Mimeau, C., Dempster, T.,  Elliott, L., Deacon, S.H., & Newman,  A.J.. (2024) Ortho-Semantic Learning of Novel Words: An event-related potential study of grade 3 children. Frontiers in Developmental Psychology. DOI: 10.3389/fdpys.2024.1340383
• Nissen, A, Seeber, I., Conrad, C., and Newman, A.J. (2025). Why Do We Follow Virtual Influencer Recommendations? Three Theoretical Explanations from Brain Data Tested with Self-Reports Journal of the Association for Information Systems. 26(4), 1042-1080. DOI: doi.org/10.17705/1jais.00930
• Bailey, L.M., , Matheson, H., Fawcett, J.M., Bodner, G.E., & Newman, A.J.. (2025). Differential weighting of information during aloud and silent reading: Evidence from representational similarity analysis of fMRI data. Imaging Neuroscience, 3: imag_a_00428. doi.org/10.1162/imag_a_00428
• Conrad, C., Nissen, A., Masoumi-Ravandi, K., Ramchandani, M., Fecury Braga, R., and Newman, AJ.. (2025). Can You Trust an AI Politician? Cognitive Assessments of Artificially Generated Political Image Perceptions and Truthfulness Notifications. Computers in Human Behavior: Artificial Humans. 5, 100185. ​​doi.org/10.1016/j.chbah.2025.100185
• Bode, D., Rankaduwa, S., Elliott, L.M., Newman, A.J.. (2026). fNIRS in the examination of neural areas underlying childhood reading development: A scoping review. Brain and Development.. 48(2), 104507. doi.org/10.1016/j.braindev.2026.104507
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• Hallal, L, Rhinelander, J., Venkat, R., and Newman, A.. (2026)  Efficient Feature Extraction for EEG-Based Classification: A Comparative Review of Deep Learning Models. AI. 7(2),  50. doi.org/10.3390/ai7020050
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• Douglas, C.L., Tremblay, A., Newman, A.J.. (2026). Context Matters: Hyperscanning the N400 Lexical Frequency Effect During Conversation and Passive Listening. Journal of Cognitive Neuroscience. Accepted March 19, 2026. doi.org/10.1162/JOCN.a.2595
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