Dr Reza Shoorangiz
BSc, MSc, PhD
Research Fellow
New Zealand Brain Research Institute, Christchurch
Deputy Director
Christchurch Neurotechnology Research Programme, Christchurch
Adjunct Fellow
Department of Electrical and Computer Engineering, University of Canterbury, Christchurch
Honorary Senior Research Fellow
Department of Medicine, University of Otago, Christchurch
This person is no longer at the institute and this page is for historical access to their publications only
Publications
Provided on request for non-commercial personal use by researchers.
2024
(2024). Conscious but not thinking—Mind‐blanks during visuomotor tracking: An fMRI study of endogenous attention lapses. Human Brain Mapping, 45(11), e26781. 10.1002/hbm.26781
2023
(2023). Extracellular vesicle biomarkers for cognitive impairment in Parkinson’s disease. Brain, 146(1), 195–208. 10.1093/brain/awac258
(2023). Cognitive and arginine metabolic correlates of temporal dysfunction in the MIA rat model of schizophrenia risk. Behavioral Neuroscience, 137(1), 67–77. 10.1037/bne0000540
(2023). The New Zealand Parkinson’s Progression Programme. Journal of the Royal Society of New Zealand, 53, 466-488. 10.1080/03036758.2022.2111448
(2023). Progressive MRI brain volume changes in ovine models of CLN5 and CLN6 neuronal ceroid lipofuscinosis. Brain Communications, 5(1). 10.1093/braincomms/fcac339
(2023). Increased cerebral activity during microsleeps reflects an unconscious drive to re-establish consciousness. International Journal of Psychophysiology, 189, 57-65. 10.1016/j.ijpsycho.2023.05.349
2021
(2021). Classification of alcoholic EEG signals using wavelet scattering transform-based features. Computers in Biology and Medicine, 139 (104969), 1-10. 10.1016/j.compbiomed.2021.104969
(2021). Neuropsychiatric symptoms are associated with dementia in Parkinson’s disease but not predictive of it. Movement Disorders Clinical Practice, 8, 390-399. 10.1002/mdc3.13151
(2021). EEG-Based Machine Learning: Theory and Applications. , In N. V. Thakor (Ed.) Handbook of Neuroengineering. Springer, Singapore.. 10.1007/978-981-15-2848-4_70-1
2020
(2020). Childbirth and delayed Parkinson’s onset: a reproducible non-biological artefact of societal change. Movement Disorders, 35, 1268-1271. 10.1002/mds.28135
(2020). Test-retest reliability and sample size estimates after MRI scanner relocation. Neuroimage 211, 116608. 10.1016/j.neuroimage.2020.116608
2018
(2018). Stress-evoking emotional stimuli exaggerate deficits in motor function in Parkinson’s disease. Neuropsychologia, 112, 66-76. 10.1016/j.neuropsychologia.2018.03.006
(2018). Predicting microsleep states using EEG inter-channel relationships. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26, 2260 - 2269. 10.1109/TNSRE.2018.2878587
2013
(2013). Complex neuro-fuzzy system for function approximation. International Journal of Applied Electronics in Physics & Robotics, 1(2), 1 (2), 5–9. 10.7575/aiac.ijaepr.v.1n.2p.5
(2013). Effects of the number of rules on the quality of fuzzy logic control of induction motor. International Journal of Applied Electronics in Physics & Robotics, 1(1), 14-17. 10.7575/aiac.ijaepr.v.1n.1p.14
Abstracts and Short papers
2021
(2021). Investigating the neural signature of microsleeps using EEG. Proceedings of International Conference of IEEE Engineering in Medicine and Biology Society, 43, 6293-6296.
2020
(2020). Neuropsychiatric symptoms are associated with dementia in Parkinson’s disease but not predictive of it. MedRxiv, 2020, 09, 01, 20186312. https://doi.org/10.1101/2020.09.01.20186312
(2020). Neural correlates of attention lapses during continuous tasks. Proceedings of International Conference of IEEE Engineering in Medicine and Biology Society, 42, 3196-3199.
2019
(2019). Deep learning with convolutional neural network for detecting microsleep states from EEG: A comparison between the oversampling technique and cost-based learning. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society, 41, 4152-4155.
(2019). Detection and prediction of microsleeps from EEG using spatio-temporal patterns. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society, 41, 522-525.
2018
(2018). Ensemble learning based on overlapping clusters of subjects to predict microsleep states from EEG. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society, 40, 3036-3039.
2017
(2017). Bayesian multi-subject factor analysis to predict microsleeps from EEG power spectral features. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society, 39, 4183-4186.
2016
(2016). Prediction of microsleeps from EEG: preliminary results. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society, Orlando, 38, 4650-4653.