Reuben Rideaux

655 total citations
36 papers, 315 citations indexed

About

Reuben Rideaux is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Reuben Rideaux has authored 36 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Cognitive Neuroscience, 9 papers in Cellular and Molecular Neuroscience and 6 papers in Experimental and Cognitive Psychology. Recurrent topics in Reuben Rideaux's work include Visual perception and processing mechanisms (25 papers), Neural dynamics and brain function (22 papers) and Neural and Behavioral Psychology Studies (8 papers). Reuben Rideaux is often cited by papers focused on Visual perception and processing mechanisms (25 papers), Neural dynamics and brain function (22 papers) and Neural and Behavioral Psychology Studies (8 papers). Reuben Rideaux collaborates with scholars based in Australia, United Kingdom and United States. Reuben Rideaux's co-authors include Andrew E. Welchman, Mark Edwards, William J. Harrison, Guido Maiello, Katherine R. Storrs, Jason B. Mattingley, Mark E. Mikkelsen, Deborah Apthorp, Richard A.E. Edden and Joseph Giorgio and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

Reuben Rideaux

34 papers receiving 311 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Reuben Rideaux Australia 11 259 66 59 41 34 36 315
S. Martinez-Conde United States 2 295 1.1× 51 0.8× 30 0.5× 24 0.6× 42 1.2× 6 381
Joonyeol Lee South Korea 12 525 2.0× 137 2.1× 54 0.9× 30 0.7× 26 0.8× 30 612
Jan W. Kurzawski Italy 11 248 1.0× 32 0.5× 97 1.6× 18 0.4× 18 0.5× 18 331
Falk M. Kraemer Germany 4 323 1.2× 26 0.4× 56 0.9× 22 0.5× 29 0.9× 8 363
Nina M. Hanning Germany 13 388 1.5× 29 0.4× 26 0.4× 46 1.1× 44 1.3× 26 439
Vahe Poghosyan Japan 12 441 1.7× 36 0.5× 36 0.6× 49 1.2× 14 0.4× 21 489
Daniel Papoti United States 8 212 0.8× 60 0.9× 95 1.6× 19 0.5× 9 0.3× 13 290
NK Logothetis Germany 8 307 1.2× 55 0.8× 67 1.1× 35 0.9× 22 0.6× 112 345
Sofia Crespi Italy 10 348 1.3× 27 0.4× 47 0.8× 36 0.9× 37 1.1× 23 417
Luca Vizioli United States 10 593 2.3× 39 0.6× 184 3.1× 160 3.9× 53 1.6× 28 705

Countries citing papers authored by Reuben Rideaux

Since Specialization
Citations

This map shows the geographic impact of Reuben Rideaux's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Reuben Rideaux with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reuben Rideaux more than expected).

Fields of papers citing papers by Reuben Rideaux

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Reuben Rideaux. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Reuben Rideaux. The network helps show where Reuben Rideaux may publish in the future.

Co-authorship network of co-authors of Reuben Rideaux

This figure shows the co-authorship network connecting the top 25 collaborators of Reuben Rideaux. A scholar is included among the top collaborators of Reuben Rideaux based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Reuben Rideaux. Reuben Rideaux is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rideaux, Reuben, et al.. (2025). Energy efficiency and sensitivity benefits in a motion processing adaptive recurrent neural network. Neural Networks. 191. 107834–107834.
2.
Rideaux, Reuben, et al.. (2023). Distinct early and late neural mechanisms regulate feature-specific sensory adaptation in the human visual system. Journal of Vision. 23(9). 5187–5187. 1 indexed citations
3.
Rideaux, Reuben, et al.. (2023). Initial experiences with Direct Imaging of Neuronal Activity (DIANA) in humans. Imaging Neuroscience. 1. 7 indexed citations
4.
Harrison, William J., Paul M. Bays, & Reuben Rideaux. (2023). Neural tuning instantiates prior expectations in the human visual system. Nature Communications. 14(1). 5320–5320. 10 indexed citations
5.
Filmer, Hannah L., Timothy Ballard, Thomas B. Shaw, et al.. (2023). Individual Differences in Decision Strategy Relate to Neurochemical Excitability and Cortical Thickness. Journal of Neuroscience. 43(42). 7006–7015. 4 indexed citations
6.
Craven, Alexander R., Pallab Bhattacharyya, William T. Clarke, et al.. (2022). Comparison of seven modelling algorithms for γ‐aminobutyric acid–edited proton magnetic resonance spectroscopy. NMR in Biomedicine. 35(7). e4702–e4702. 26 indexed citations
7.
Rideaux, Reuben, Hannah L. Filmer, Jin Jin, et al.. (2022). On the relationship between GABA+ and glutamate across the brain. NeuroImage. 257. 119273–119273. 16 indexed citations
8.
Rideaux, Reuben, Mark E. Mikkelsen, & Richard A.E. Edden. (2021). Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data. NeuroImage. 232. 117900–117900. 6 indexed citations
9.
Rideaux, Reuben, Katherine R. Storrs, Guido Maiello, & Andrew E. Welchman. (2021). How multisensory neurons solve causal inference. Proceedings of the National Academy of Sciences. 118(32). 36 indexed citations
10.
Rideaux, Reuben & Andrew E. Welchman. (2020). But Still It Moves: Static Image Statistics Underlie How We See Motion. Journal of Neuroscience. 40(12). 2538–2552. 18 indexed citations
11.
Kemper, Valentin G., Ke Jia, Joseph Giorgio, et al.. (2020). Fine-scale computations for adaptive processing in the human brain. eLife. 9. 13 indexed citations
12.
Rideaux, Reuben. (2020). Temporal Dynamics of GABA and Glx in the Visual Cortex. eNeuro. 7(4). ENEURO.0082–20.2020. 14 indexed citations
13.
Rideaux, Reuben & William J. Harrison. (2019). Border ownership-dependent tilt aftereffect for shape defined by binocular disparity and motion parallax. Journal of Neurophysiology. 121(5). 1917–1923. 3 indexed citations
14.
Rideaux, Reuben, et al.. (2019). Adaptation to Binocular Anticorrelation Results in Increased Neural Excitability. Journal of Cognitive Neuroscience. 32(1). 100–110. 5 indexed citations
15.
Rideaux, Reuben, et al.. (2019). Mixed-polarity random-dot stereograms alter GABA and Glx concentration in the early visual cortex. Journal of Neurophysiology. 122(2). 888–896. 12 indexed citations
16.
Rideaux, Reuben & Andrew E. Welchman. (2019). Contextual effects on binocular matching are evident in primary visual cortex. Vision Research. 159. 76–85. 4 indexed citations
17.
Harrison, William J. & Reuben Rideaux. (2019). Voluntary control of illusory contour formation. Attention Perception & Psychophysics. 81(5). 1522–1531. 8 indexed citations
18.
Rideaux, Reuben & Mark Edwards. (2013). Information extraction during simultaneous motion processing. Vision Research. 95. 1–10. 4 indexed citations
19.
Edwards, Mark & Reuben Rideaux. (2012). How many motion directions can be simultaneously perceived?. Journal of Vision. 12(9). 152–152. 2 indexed citations
20.
Edwards, Mark & Reuben Rideaux. (2012). How many motion signals can be simultaneously perceived?. Vision Research. 76. 11–16. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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