Dr. Tijl Grootswagers

ARC DECRA Senior Research Fellow in Computational Neuroscience
The MARCS Institute for Brain, Behaviour and Development
School of Computer, Data and Mathematical Sciences
Western Sydney University, Sydney, Australia

email:    t.grootswagers@westernsydney.edu.au
homepage: https://tijl.github.io/
linktree: https://linktr.ee/tgro
scholar:  TNI8FOoAAAAJ
twitter:  @TGrootswagers
github:   github.com/Tijl
orcid:    0000-0002-7961-5002

I am a computational cognitive neuroscientist combining machine learning, neuroimaging, and behavioural data to understand how the brain represents and processes information. The focus of my research is to investigate how the brain perceives and represents visual objects, and how it uses these representations for decision making. Feel free to email me with inquiries about research opportunities in the lab.

Publications

* equal contribution

Grootswagers T.*, Robinson A.K.*, Shatek S.M., Carlson T.A. (2024). Mapping the Dynamics of Visual Feature Coding: Insights into Perception and Integration. PLoS Computational Biology, 20(1) e1011760 [doi] [pdf] [data+code]

Kennedy B., Most S., Grootswagers T., Bowden V. (2024). Memory benefits when actively, rather than passively, viewing images. Attention, Perception, & Psychophysics, 86, 1–8 [doi] [pdf] [data+code]

[PREPRINT] van Hees J., Grootswagers T., Quek G., Varlet M. (2023). Human Perception of Art in the Age of Artificial Intelligence. PsyArXiv, kvsu3 [doi] [pdf] [data+code]

[PREPRINT] Scrivener C.L., Grootswagers T., Woolgar A. (2023). Optimising analysis choices for multivariate decoding: creating pseudotrials using trial averaging and resampling. biorxiv, 2023.10.04.560678 [doi] [pdf] [code]

Sharabas D., Varlet M., Grootswagers T. (2023). An online browser-based attentional blink replication using visual objects. PLoS ONE, 18(8) e0289623 [doi] [pdf] [data+code]

Grootswagers T. (2023). Minimal condition repetitions required in rapid serial visual presentation decoding paradigms. In proceedings of the 2023 Conference on Cognitive Computational Neuroscience, 1180 [doi] [pdf] [data+code]

Hoang, Q.T., Yong, K.-T., Liu, X., Mahony, D., Chaitarvornkit, A., Cohen, A., Grootswagers, T. (2023). Detecting mild traumatic brain injury for athletes using SSVEP classification: A case study. Biomedical Signal Processing and Control, 86, 105274. [doi] [pdf]

[PREPRINT] Koenig-Robert R., Quek G., Grootswagers T., Varlet M. (2023). Movement trajectories as a window into the dynamics of emerging neural representations. biorxiv, 2023.03.15.532848 [doi] [pdf] [data+code]

[PREPRINT] Moerel D., Grootswagers T., Robinson A.K., Engeler P., Holcombe A.O., Carlson T.A. (2022). Rotation-tolerant representations elucidate the time-course of high-level object processing. PsyArXiv, wp73u [doi] [pdf] [data+code]

Shatek S.M., Robinson A.K., Grootswagers T., Carlson T.A. (2022). Capacity for movement is an organisational principle in object representations. NeuroImage, 119517 [doi] [pdf] [data+code]

Moshel M., Robinson A.K., Carlson T.A., Grootswagers T. (2022). Are you for real? Decoding realistic AI-generated faces from neural activity. Vision Research, 108079 [doi] [pdf] [data+code]

Grootswagers T., McKay H., Varlet M. (2022). Unique Contributions of Perceptual and Conceptual Humanness to Object Representations in the Human Brain. NeuroImage, 119350 [doi] [pdf] [data+code]

Moerel D., Grootswagers T., Robinson A.K., Shatek S.M., Woolgar A., Carlson T.A., Rich A.N. (2022). The time-course of feature-based attention effects dissociated from temporal expectation and target-related processes. Scientific Reports, 12, 6968 [doi] [pdf] [data+code]

Teichmann L., Moerel D., Baker C.I., Grootswagers T. (2022). An Empirically Driven Guide on Using Bayes Factors for M/EEG Decoding. Aperture Neuro, 1 (8) 1-10 [doi] [pdf] [data+code]

Grootswagers T., Zhou I., Robinson A.K., Hebart M.N., Carlson T.A. (2022). Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams. Sci Data, 9 (3) [doi] [pdf] [data+code]

[PREPRINT] Tovar D.A., Grootswagers T., Jun J., Cha O., Blake R., Wallace M.T. (2021). Getting the gist faster: Blurry images enhance the early temporal similarity between neural signals and convolutional neural networks. biorxiv, 2021.08.22.451834 [doi] [pdf]

Levitis E.*, Gould van Praag C.D.*, Gau R.*, Heunis S.*, ..., Grootswagers T., ..., Maumet C. (110 authors) (2021). Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective. GigaScience, 10 (8) [doi] [pdf]

Grootswagers T., Robinson A.K. (2021). Overfitting the Literature to One Set of Stimuli and Data. Frontiers in Human Neuroscience, 15:682661 [doi] [pdf]

Teichmann L., Grootswagers T., Moerel D., Carlson T.A., Rich A.N. (2021). Temporal dissociation of neural activity underlying synaesthetic and perceptual colours. Proceedings of the National Academy of Sciences, 118 (6) [doi] [pdf] [data+code]

Grootswagers T., Robinson A.K., Shatek S.M., Carlson T.A. (2021). The neural dynamics underlying prioritisation of task-relevant information. Neurons, Behaviour, Data Analysis, and Theory, 5(1) [doi] [pdf] [data+code] [video]

Robinson A.K., Grootswagers T., Shatek S.M., Gerboni J., Holcombe, A.O., Carlson T.A. (2021). Overlapping neural representations for the position of visible and invisible objects. Neurons, Behaviour, Data Analysis, and Theory, 4(1) [doi] [pdf] [data+code]

Teichmann L., Quek G.L., Robinson A.K., Grootswagers T., Carlson T.A., Rich A.N. (2020). The Influence of Object-Color Knowledge on Emerging Object Representations in the Brain. The Journal of Neuroscience, 40 (35), 6779-6789 [doi] [pdf]

Petit S., Badcock N.A., Grootswagers T., Rich A.N., Brock J., Nickels L., Moerel D., Dermody N., Yau S., Schmidt E., Woolgar A. (2020). Toward an Individualized Neural Assessment of Receptive Language in Children. Journal of Speech, Language, and Hearing Research, 63 (7), 2361-2385 [doi] [pdf]

Petit S., Badcock N.A., Grootswagers T., Woolgar A. (2020). Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children. Scientific Reports, 10, 10849 [doi] [pdf] [data+code]

Carlson T.A., Grootswagers T., Robinson A.K. (2020). An introduction to time-resolved decoding analysis for M/EEG. in: (Gazzaniga, Mangun, & Poeppel, eds.) The Cognitive Neurosciences, 6th Edition [doi] [pdf]

Grootswagers T. (2020). A primer on running human behavioural experiments online. Behavior Research Methods [doi] [pdf] [featuredcontent.psychonomic.org]

[PREPRINT] Whyte C.J., Robinson A.K., Grootswagers T., Hogendoorn H., Carlson T.A. (2020). Decoding Predictions and Violations of Object Position and Category in Time-resolved EEG. biorxiv, 032888 [doi] [pdf]

Contini E.W., Goddard E., Grootswagers T., Williams M., Carlson T.A. (2020). A humanness dimension to visual object coding in the brain. NeuroImage, 117139 [doi] [pdf] [data+code]

Shatek S.M., Grootswagers T., Robinson A.K., Carlson T.A. (2019). Decoding images in the mind's eye: The temporal dynamics of visual imagery. Vision, 3 (4), 53 [doi] [pdf]

[PREPRINT] Carlson T., Grootswagers T., Robinson A.K. (2019). An introduction to time-resolved decoding analysis for M/EEG. arxiv, 1905.04820 [doi] [pdf]

Grootswagers T., Robinson A.K., Shatek S.M., Carlson T.A. (2019). Untangling featural and conceptual object representations. NeuroImage, 202, 116083 [doi] [pdf] [data+code]

Teichmann L., Grootswagers T., Carlson T.A., Rich A.N. (2019). Seeing versus Knowing: The Temporal Dynamics of Real and Implied Colour Processing in the Human Brain. NeuroImage, 200, 373-381 [doi] [pdf]

Robinson A.K.*, Grootswagers T.*, Carlson T.A. (2019). The influence of image masking on object representations during rapid serial visual presentation. NeuroImage, 197, 224-231 [doi] [pdf] [data+code]

Mai A., Grootswagers T., Carlson T.A. (2019). In Search of Consciousness: Examining the Temporal Dynamics of Conscious Visual Perception using MEG time-series data. Neuropsychologia, 129, 310-317 [doi] [pdf]

Grootswagers T.*, Robinson A.K.*, Carlson T.A. (2019). The representational dynamics of visual objects in rapid serial visual processing streams. NeuroImage, 188, 668-679 [doi] [pdf] [data+code]

Grootswagers T., Cichy R.M., Carlson T.A. (2018). Finding decodable information that can be read out in behaviour. NeuroImage, 179, 252-262 [doi] [pdf]

Teichmann L., Grootswagers T., Carlson T.A., Rich A.N. (2018). Decoding digits and dice with Magnetoencephalography: Evidence for a shared representation of magnitude. Journal of Cognitive Neuroscience, 30 (7), 999-1010 [doi] [pdf]

Grootswagers T.*, Kennedy B.L.*, Most S.L., Carlson T.A. (2017). Neural signatures of dynamic emotion constructs in the human brain. Neuropsychologia [doi] [pdf] [osf]

Grootswagers T., Wardle S.G., Carlson T.A. (2017). Decoding dynamic brain patterns from evoked responses: A tutorial on multivariate pattern analysis applied to time-series neuroimaging data. Journal of Cognitive Neuroscience, 29(4), 677-697 [doi] [pdf] [data+code]

Grootswagers T., Ritchie J.B., Wardle S.G., Heathcote A., Carlson T.A. (2017). Asymmetric compression of representational space for object animacy categorization under degraded viewing conditions. Journal of Cognitive Neuroscience, 29(12), 1995-2010 [doi] [pdf] [data+code]

de Wit B., Badcock N.A., Grootswagers T., Hardwick K., Teichmann L., Wehrman J., Williams M., Kaplan D.M. (2017). Neurogaming technology meets neuroscience education: A cost-effective, scalable, and highly portable undergraduate teaching laboratory for neuroscience. Journal of Undergraduate Neuroscience Education, 15(2), A104-A109 [doi] [pdf]

Wardle S.G., Kriegeskorte N., Grootswagers T., Khaligh-Razavi S., Carlson T.A. (2016). Perceptual similarity of visual patterns predicts dynamic neural activation patterns measured with MEG. NeuroImage, 132, 59-70 [doi] [pdf]