Personal website: reubenrideaux.github.io/
I conduct interdisciplinary research at the intersection of machine learning, cognitive neuroscience, and psychology. My goal is to develop bio-inspired artificial intelligence systems that explain biological neural function and disfunction. In particular, I am interested in how the brain processes, combines, and stores information from different sensory modalities, and how this information is then used to drive adaptive behaviours. To approach questions related to brain function, I employ a range of methods including deep learning, neuroimaging (EEG/fMRI/MRS), psychophysics, and eye tracking.
Craven AR, Bhattacharyya PK, Clarke WT, Dydak U, Edden RAE, Ersland L, Mandal PK, Mikkelsen M, Murdoch JB, Near J, Rideaux R, Shukla D, Wang M, Wilson M, Zöllner HJ, Hugdahl K & Oeltzschner G (2022) Comparison of seven modelling algorithms for γ-aminobutyric acid–edited proton magnetic resonance spectroscopy. NMR in Biomedicine.
Rideaux R, West KR, Wallis TSA, Bex PJ, Mattingley JB & Harrison JH (2022) Spatial structure, phase, and the contrast of natural images. Journal of Vision.
Rideaux R, Storrs KR, Maiello G & Welchman AE (2021) How multisensory neurons solve causal inference. Proceedings of the National Academy of Sciences.
Rideaux R (2021) No balance between glutamate+glutamine and GABA+ in visual or motor cortices of the human brain: A magnetic resonance spectroscopy study. NeuroImage.
Karlaftis VM, Giorgio J, Zamboni E, Frangou P, Rideaux R, Ziminski JJ & Kourtzi Z (2021) Functional interactions between sensory and memory networks for adaptive behaviour. Cerebral Cortex.
Rideaux R, Mikkelsen M & Edden RAE (2021) Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data. NeuroImage.
Rideaux R & Welchman AE (2021) Exploring and explaining properties of motion processing in biological brains using a neural network. Journal of Vision.
Rideaux R (2021) Low- and High-resolution Dynamic Analyses for Magnetic Resonance Spectroscopy Data. Bio-Protocol.
Zamboni E, Kemper VG, Goncalves NR, Jia K, Karlaftis VM, Bell SJ, Giorgio J, Rideaux R, Goebel R & Kourtzi Z (2020) Fine-scale computations for adaptive processing in the human brain. eLife.
Rideaux R (2020) Temporal dynamics of GABA and Glx in the visual cortex. eNeuro.
Rideaux R & Welchman AE (2020) But still it moves: static image statistics underlie how we see motion. Journal of Neuroscience.
Rideaux R, Michael E & Welchman AE (2020) Adaptation to binocular anticorrelation results in increased neural excitability. Journal of Cognitive Neuroscience.
Rideaux R, Goncalves NR & Welchman AE (2019) Mixed-polarity random-dot stereograms alter GABA and Glx concentration in the early visual cortex. Journal of Neurophysiology.
Rideaux R & Welchman AE (2019) Contextual effects on binocular matching are evident in primary visual cortex. Vision Research, 159, 76-85.
Rideaux R & Harrison WJ (2019) Border-ownership-dependent tilt aftereffect for shape defined by binocular disparity and motion parallax. Journal of Neurophysiology, 121(5), 1917-1923.
Harrison WJ & *Rideaux R (2019) Voluntary control of illusory contour formation. Attention, Perception, and Psychophysics, 1-10. *Joint first author.
Rideaux R & Welchman AE (2018) Proscription supports robust perceptual integration by suppression in human visual cortex. Nature Communications, 9, 1502.
Rideaux R, Baker E & Edwards M (2018) Parallel consolidation into visual working memory results in reduced precision representations. Vision Research, 149, 24-49.
Rideaux R, Johnston A, Badcock D & Edwards M (2016) Temporal synchrony is an effective cue for segmentation in the absence of form cues. Journal of Vision, 16, 1-12.
Rideaux R & Edwards M (2016) The cost of parallel consolidation into visual working memory. Journal of Vision, 16, 1-14.
Rideaux R, Apthorp D, & Edwards M (2015) Evidence for parallel consolidation of motion direction and orientation into visual short-term memory. Journal of Vision, 15, 1-12.
Rideaux R & Edwards M (2014) Information extraction during simultaneous motion processing. Vision Research, 95, 1–10.
Edwards M & Rideaux R (2013) How many motion signals can be simultaneously perceived? Vision Research, 76, 11-16.