Brendan T. Johns

Research Areas:

Cognition & Cognitive Neuroscience

Research Summary:

My research focuses on the development of large-scale computational models of cognition, with a specific emphasis on understanding the computational mechanisms that support the acquisition and representation of semantic information from naturalistic big data, as well as how this knowledge is used in online natural language processing and memory retrieval. The goal of this research is to develop cognitively plausible machine learning models that can further our understanding of human cognition. Additionally, my research involves using these models to gain a better understanding of the effects of lifelong learning on cognitive aging, bilingualism, and memory and language disorders.

Selected References:

Johns, B. T., Dye, M., & Jones, M. N. (in press). Estimating the prevalence and diversity of words in written language. Quarterly Journal of Experimental Psychology.

Qui, M. & Johns, B. T. (in press). Semantic diversity in paired-associate learning: Further evidence for the information accumulation perspective of cognitive aging. Psychonomic Bulletin & Review.

Taler, V., Johns, B. T., & Jones, M. N. (in press). A large scale semantic analysis of verbal fluency across the aging spectrum: Data from the Canadian longitudinal study on aging. Journal of Gerontology: Psychological Sciences.

Johns, B. T., Mewhort, D. J. K., & Jones, M. N. (2019). The role of negative information in distributional semantic learning. Cognitive Science, 43, e12730.

Johns, B. T. & Jamieson, R. K. (2019). The influence of time and place on lexical behavior: A distributional analysis. Behavior Research Methods, 51, 2438-2453.

Johns, B. T. & Dye, M. (2019). Gender bias at scale: Evidence from the usage of personal names. Behavior Research Methods, 51, 1601-1618.

Johns, B. T., Jones, M. N., & Mewhort, D. J. K. (2019). Using experiential optimization to build lexical representations. Psychonomic Bulletin & Review, 26, 103-126.

Johns, B. T. (2019). Mining a crowdsourced dictionary to understand consistency and preference in word meanings. Frontiers in Psychology, 10, 268.