Ty Lees

Ty Lees is a post-doctoral scholar working under the direction of Lisa Kopp on the Family Life Project (Early Life Stress and the Environmental Origins of Disease: a Population-based Prospective Longitudinal Study of Children in Rural Poverty), funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). His current research focus is examining brain activity to understand reward processing and development as they relate to internalizing and externalizing behaviors and disorders. 

He holds a Ph.D. in Neuroscience and Neurophysiology from the University of Technology Sydney. His doctoral dissertation focused on “The impact of stress and anxiety on the neurocognitive performance of Australian nurses,” and his research interests primarily lie in cognitive neuroscience and electrophysiological biomarkers.

Developmental changes in external and internal performance monitoring across middle childhood: an ERP study

Lees, T., Fry, C.M., Terrel, S., Jetha, M.K., Segalowitz, S.J., & Gatzke-Kopp, L.M. (2021). Developmental changes in external and internal performance monitoring across middle childhood: an ERP study. International Journal of Psychophysiology, 169. https://doi.org/10.1016/j.ijpsycho.2021.09.002

Association between EEG asymmetry and the error-related negativity across middle childhood

Lees, T., Fry, C.M., Jetha, M.K., Segalowitz, S.J., & Gatzke-Kopp, L.M. (2021). Association between EEG Asymmetry and the Error-related Negativity across Middle Childhood. Biological Psychology, 163. https://doi.org/10.1016/j.biopsycho.2021.108137

Heart rate variability as a potential non-invasive marker of blood glucose level

Jarman, L., Elliott, J.L., Lees, T., Clifton-Bligh, R., Simpson, A.M., Nassif, N., & Lal, S. (2021). Heart rate variability as a potential non-invasive marker of blood glucose level. Human Physiology, 47. https://doi.org/10.1134/S0362119721020031

Classifying multi-level stress responses from brain cortical EEG in nurses and non-health professionals using machine learning auto encoder

Akella, A., Singh A.K., Leong, D., Lal, S., Newton, P.J., Clifton-Bligh, R., McLachlan, C.S., Gustin, S.M., Maharaj, S., Lees, T., Cao, Z., & Lin C.T. (2021). Classifying multi-level stress responses from brain cortical EEG in nurses and non-health professionals using machine learning auto encoder. IEEE Journal of Translational Engineering in Health & Medicine, 9. https://doi.org/10.1109/JTEHM.2021.3077760

Electrophysiological brain-cardiac coupling in train drivers during monotonous driving

Lees. T., Chalmers, T., Burton, D., Zilberg, E., Penzel, T., Lal, S., & Lal S. (2021). Electrophysiological brain-cardiac coupling in train drivers during monotonous driving. International Journal of Environmental Research and Public Health, 18(7). https://dx.doi.org/10.3390%2Fijerph18073741

Electroencephalographic prediction of global and domain specific cognitive performance of clinically active Australian nurses

Lees, T., Maharaj, S., Kalatzis, G., Nassif, N., Newton, P.J., & Lal, S. (2020). Electroencephalographic prediction of global and domain specific cognitive performance of clinically active Australian nurses. Physiological Measurement, 41(9). https://doi.org/10.1088/1361-6579/abb12a

Impact of acute stress on cognitive-cardiac coupling in Australian nurses

Chalmers, T., Maharaj, S., Lees, T., Lin, C.T., Newton, P.J., Clifton-Bligh, R., McLachlan, C.S., Gustin, S.M., & Lal, S. (2020). Impact of acute stress on cognitive-cardiac coupling in Australian nurses. Journal of Integrative Neuroscience, 19(2).https://doi.org/10.31083/j.jin.2020.02.74