Every day, our brains constantly and effortlessly perform object recognition. This refers to the brain’s ability to rapidly detect and classify objects (such as a fork, apple or truck) amongst many thousands of possible objects, and despite enormous variation in objects’ visual appearance, lighting, orientation and occlusion.
For example, driving to work involves a continuous need to recognise many objects, such as your own car, other cars, pedestrians, animals and traffic signs.
This ability underlies many higher cognitive functions such as memory, decision making and social interaction, and therefore is critical for most everyday tasks.
Yet we still do not fully understand how these processes work in the human brain, nor how the brain organises object information.
Dr Grootswagers is a computational cognitive neuroscientist who specialises in object recognition. His research aims to understand how the human brain recognises visual objects, and also what happens when it fails. This work can inform a wide range of applications from brain and visual disorders to artificial intelligence and informatics.
I am fascinated about the complexity of the human brain, and hope that my research will help us understand more of its workings, eventually leading to improved outcomes for brain disorders.
Dr Grootswagers’ research has significantly advanced understanding of how object recognition takes place in the brain. He has contributed to new methodologies for studying the brain that have been adopted by laboratories around the world.
Understanding the way object recognition develops in healthy populations has numerous applications for health, engineering and informatics.
For example, insights into the inner workings of the brain can help to identify and rectify neurological problems during early childhood brain development, and to diagnose, prevent and treat disorders of the mind, such as autism and schizophrenia, Alzheimer’s disease, dementia, or stroke.
I imagine a future where our brain research informs new diagnostic measures, to treat brain disorders such as dementia.
In addition, discovering how the brain performs object recognition could enable the development of machines that operate more like humans. Human-like machines can improve our interactions with intelligent technology, leading to increased productivity and safety in environments that rely on intelligent machines, such as in manufacturing and surveillance.
Understanding the brain will also inform the development of artificial intelligence, to advance engineering (e.g. robotics) and informatics (e.g. intelligent assistants).
2012 BSc Artificial Intelligence (Radboud University Nijmegen, Netherlands)
2014 MSc Artificial Intelligence (Radboud University Nijmegen, Netherlands)
2014-2017 PhD Cognitive Science (Macquarie University, Sydney)
2017-2020 Postdoc (University of Sydney)
2020-2022 Vice Chancellor's Research Fellow in Cognitive Neuroscience, MARCS Institute
2023-now Vice Chancellor's Senior Research Fellow in Cognitive Neuroscience, MARCS Institute
2023-now ARC DECRA Fellow
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 https://doi.org/10.1016/j.visres.2022.108079
Grootswagers T., McKay H., Varlet M. (2022). Unique Contributions of Perceptual and Conceptual Humanness to Object Representations in the Human Brain. NeuroImage, 119350 https://doi.org/10.1016/j.neuroimage.2022.119350
Grootswagers T. (2020). A primer on running human behavioural experiments online. Behavior Research Methods https://doi.org/10.3758/s13428-020-01395-3
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 https://doi.org/10.1016/j.neuroimage.2018.12.046
Grootswagers T, Wardle SG, Carlson TA (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 https://doi.org/10.1162/jocn_a_01068
Dr Grootswagers welcomes collaborations across academia and loves working in interdisciplinary teams that combine diverse expertise to solve bigger problems.