Jonathan S. Cant

2.0k total citations
54 papers, 1.4k citations indexed

About

Jonathan S. Cant is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Jonathan S. Cant has authored 54 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Cognitive Neuroscience, 11 papers in Computer Vision and Pattern Recognition and 8 papers in Social Psychology. Recurrent topics in Jonathan S. Cant's work include Visual perception and processing mechanisms (35 papers), Face Recognition and Perception (26 papers) and Neural dynamics and brain function (15 papers). Jonathan S. Cant is often cited by papers focused on Visual perception and processing mechanisms (35 papers), Face Recognition and Perception (26 papers) and Neural dynamics and brain function (15 papers). Jonathan S. Cant collaborates with scholars based in Canada, United States and China. Jonathan S. Cant's co-authors include Melvyn A. Goodale, Yaoda Xu, Gavin Buckingham, Stephen R. Arnott, Jason P. Gallivan, Susanne Ferber, J. Randall Flanagan, Mary‐Ellen Large, Matthew X. Lowe and Lei Mo and has published in prestigious journals such as Journal of Neuroscience, NeuroImage and Current Biology.

In The Last Decade

Jonathan S. Cant

50 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan S. Cant Canada 19 1.3k 334 332 167 83 54 1.4k
Joan López‐Moliner Spain 20 1.1k 0.8× 351 1.1× 212 0.6× 76 0.5× 117 1.4× 76 1.3k
Sergei Gepshtein United States 19 1.1k 0.9× 256 0.8× 326 1.0× 161 1.0× 68 0.8× 49 1.4k
Cathleen M. Moore United States 22 1.9k 1.5× 326 1.0× 469 1.4× 240 1.4× 133 1.6× 87 2.0k
Michiel Spapé Finland 22 978 0.8× 313 0.9× 286 0.9× 45 0.3× 104 1.3× 72 1.3k
Susan G. Wardle Australia 17 984 0.8× 162 0.5× 226 0.7× 141 0.8× 51 0.6× 42 1.2k
Nathan Faivre France 25 1.4k 1.1× 327 1.0× 434 1.3× 66 0.4× 64 0.8× 77 1.7k
Erez Freud Canada 16 821 0.6× 200 0.6× 168 0.5× 119 0.7× 44 0.5× 51 945
Johannes Burge United States 17 1.1k 0.8× 216 0.6× 244 0.7× 177 1.1× 34 0.4× 48 1.3k
Tzvi Ganel Israel 24 1.9k 1.5× 508 1.5× 606 1.8× 258 1.5× 135 1.6× 87 2.1k
Anne M. Cleary United States 23 1.1k 0.9× 354 1.1× 312 0.9× 124 0.7× 236 2.8× 69 1.3k

Countries citing papers authored by Jonathan S. Cant

Since Specialization
Citations

This map shows the geographic impact of Jonathan S. Cant'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 Jonathan S. Cant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan S. Cant more than expected).

Fields of papers citing papers by Jonathan S. Cant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan S. Cant. 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 Jonathan S. Cant. The network helps show where Jonathan S. Cant may publish in the future.

Co-authorship network of co-authors of Jonathan S. Cant

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan S. Cant. A scholar is included among the top collaborators of Jonathan S. Cant 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 Jonathan S. Cant. Jonathan S. Cant 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.
Nestor, Adrian, et al.. (2025). Attention and stimulus structure interact during ensemble encoding of facial expression. Scientific Reports. 15(1). 18632–18632.
2.
3.
Fukuda, Keisuke, et al.. (2023). Testing the flexibility of ensemble coding: Limitations in cross-modal ensemble perception.. Journal of Experimental Psychology General. 153(1). 56–69.
4.
Srikanthan, Dilakshan, et al.. (2021). Global and local interference effects in ensemble encoding are best explained by interactions between summary representations of the mean and the range. Attention Perception & Psychophysics. 83(3). 1106–1128. 7 indexed citations
5.
Cant, Jonathan S. & Yaoda Xu. (2020). One bad apple spoils the whole bushel: The neural basis of outlier processing. NeuroImage. 211. 116629–116629. 14 indexed citations
6.
Nemrodov, Dan, et al.. (2019). A multivariate investigation of visual word, face, and ensemble processing: Perspectives from EEG‐based decoding and feature selection. Psychophysiology. 57(3). e13511–e13511. 7 indexed citations
7.
Cant, Jonathan S., et al.. (2019). Elucidating the Neural Representation and the Processing Dynamics of Face Ensembles. Journal of Neuroscience. 39(39). 7737–7747. 14 indexed citations
8.
Barense, Morgan D., et al.. (2017). Erasing and blurring memories: The differential impact of interference on separate aspects of forgetting.. Journal of Experimental Psychology General. 146(11). 1606–1630. 37 indexed citations
9.
Stevenson, Ryan A., et al.. (2016). Seeing the Forest and the Trees: Default Local Processing in Individuals with High Autistic Traits Does Not Come at the Expense of Global Attention. Journal of Autism and Developmental Disorders. 48(4). 1382–1396. 30 indexed citations
10.
Wen, Xue, Yanhui Xiang, Jonathan S. Cant, et al.. (2016). The neural correlates of internal and external comparisons: an fMRI study. Brain Structure and Function. 222(1). 563–575. 11 indexed citations
11.
Cant, Jonathan S., et al.. (2015). Automatic capture of attention by conceptually generated working memory templates. Attention Perception & Psychophysics. 77(6). 1841–1847. 10 indexed citations
12.
Wang, Tingting, Lei Mo, Oshin Vartanian, Jonathan S. Cant, & Gerald C. Cupchik. (2015). An investigation of the neural substrates of mind wandering induced by viewing traditional Chinese landscape paintings. Frontiers in Human Neuroscience. 8. 1018–1018. 18 indexed citations
13.
Lowe, Matthew X., Ryan A. Stevenson, Kristin Wilson, et al.. (2015). Sensory processing patterns predict the integration of information held in visual working memory.. Journal of Experimental Psychology Human Perception & Performance. 42(2). 294–301. 9 indexed citations
14.
Cant, Jonathan S. & Yaoda Xu. (2014). The Impact of Density and Ratio on Object-Ensemble Representation in Human Anterior-Medial Ventral Visual Cortex. Cerebral Cortex. 25(11). 4226–4239. 26 indexed citations
15.
Gallivan, Jason P., Jonathan S. Cant, Melvyn A. Goodale, & J. Randall Flanagan. (2014). Representation of Object Weight in Human Ventral Visual Cortex. Current Biology. 24(16). 1866–1873. 91 indexed citations
16.
Cant, Jonathan S. & Yaoda Xu. (2012). Object Ensemble Processing in Human Anterior-Medial Ventral Visual Cortex. Journal of Neuroscience. 32(22). 7685–7700. 103 indexed citations
17.
Cant, Jonathan S. & Melvyn A. Goodale. (2011). Scratching Beneath the Surface: New Insights into the Functional Properties of the Lateral Occipital Area and Parahippocampal Place Area. Journal of Neuroscience. 31(22). 8248–8258. 97 indexed citations
18.
Connolly, Jason D., Melvyn A. Goodale, Jonathan S. Cant, & Douglas P. Munoz. (2006). Effector-specific fields for motor preparation in the human frontal cortex. NeuroImage. 34(3). 1209–1219. 41 indexed citations
19.
Cant, Jonathan S. & Melvyn A. Goodale. (2006). Attention to Form or Surface Properties Modulates Different Regions of Human Occipitotemporal Cortex. Cerebral Cortex. 17(3). 713–731. 233 indexed citations
20.
Cant, Jonathan S., David A. Westwood, Kenneth F. Valyear, & Melvyn A. Goodale. (2005). No evidence for visuomotor priming in a visually guided action task. Neuropsychologia. 43(2). 216–226. 40 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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