Jay Hegdé

1.3k total citations
41 papers, 931 citations indexed

About

Jay Hegdé is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Cellular and Molecular Neuroscience. According to data from OpenAlex, Jay Hegdé has authored 41 papers receiving a total of 931 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cognitive Neuroscience, 11 papers in Computer Vision and Pattern Recognition and 8 papers in Cellular and Molecular Neuroscience. Recurrent topics in Jay Hegdé's work include Visual perception and processing mechanisms (23 papers), Neural dynamics and brain function (14 papers) and Face Recognition and Perception (8 papers). Jay Hegdé is often cited by papers focused on Visual perception and processing mechanisms (23 papers), Neural dynamics and brain function (14 papers) and Face Recognition and Perception (8 papers). Jay Hegdé collaborates with scholars based in United States, Bulgaria and China. Jay Hegdé's co-authors include David C. Van Essen, Daniel J. Felleman, Daniel Kersten, Evgeniy Bart, Geoffrey M. Boynton, Xin Chen, Edwin C. Stephenson, Scott O. Murray, Fang Fang and Gene R. Stoner and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and Development.

In The Last Decade

Jay Hegdé

37 papers receiving 901 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jay Hegdé United States	15	790	174	160	70	61	41	931
J.-M. Hupe France	4	948 1.2×	81 0.5×	261 1.6×	50 0.7×	31 0.5×	6	1.0k
James Gaska United States	11	729 0.9×	63 0.4×	251 1.6×	56 0.8×	25 0.4×	28	816
Ruben Coen-Cagli United States	13	679 0.9×	87 0.5×	236 1.5×	20 0.3×	74 1.2×	34	762
Robert A. Frazor United States	6	762 1.0×	178 1.0×	309 1.9×	46 0.7×	19 0.3×	8	911
Madoka Moriya Japan	6	686 0.9×	98 0.6×	130 0.8×	55 0.8×	36 0.6×	7	756
Haidong Lu China	17	1.1k 1.4×	94 0.5×	355 2.2×	83 1.2×	23 0.4×	59	1.4k
Yoav Tadmor United Kingdom	10	668 0.8×	264 1.5×	119 0.7×	96 1.4×	16 0.3×	15	858
Yasuko Sugase-Miyamoto Japan	11	837 1.1×	113 0.6×	147 0.9×	60 0.9×	61 1.0×	22	958
Akiyuki Anzai United States	13	955 1.2×	83 0.5×	312 1.9×	62 0.9×	27 0.4×	16	1.0k
Yevgeniy B. Sirotin United States	16	684 0.9×	120 0.7×	221 1.4×	105 1.5×	64 1.0×	30	1.1k

Countries citing papers authored by Jay Hegdé

Since Specialization

Citations

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

Fields of papers citing papers by Jay Hegdé

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay Hegdé. 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 Jay Hegdé. The network helps show where Jay Hegdé may publish in the future.

Co-authorship network of co-authors of Jay Hegdé

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Hegdé. A scholar is included among the top collaborators of Jay Hegdé 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 Jay Hegdé. Jay Hegdé is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Hegdé, Jay, et al.. (2022). Satisfaction of Search Can Be Ameliorated by Perceptual Learning: A Proof-of-Principle Study. Vision. 6(3). 49–49. 1 indexed citations

Hegdé, Jay, et al.. (2022). How well do practicing radiologists interpret the results of CAD technology? A quantitative characterization. Cognitive Research Principles and Implications. 7(1). 52–52.

Hegdé, Jay, et al.. (2022). Heuristic Vetoing: Top-Down Influences of the Anchoring-and-Adjustment Heuristic Can Override the Bottom-Up Information in Visual Images. Frontiers in Neuroscience. 16. 745269–745269. 1 indexed citations

Hegdé, Jay, et al.. (2021). Expert camouflage-breakers can accurately localize search targets. Cognitive Research Principles and Implications. 6(1). 27–27. 3 indexed citations

Hegdé, Jay, et al.. (2020). A Window Into Your Brain: How fMRI Helps Us Understand What Is Going on Inside Our Heads. Frontiers for Young Minds. 8. 4 indexed citations

Hegdé, Jay & Evgeniy Bart. (2018). Making Expert Decisions Easier to Fathom: On the Explainability of Visual Object Recognition Expertise. Frontiers in Neuroscience. 12. 670–670. 4 indexed citations

Hegdé, Jay, et al.. (2012). Object recognition in clutter: cortical responses depend on the type of learning. Frontiers in Human Neuroscience. 6. 170–170. 8 indexed citations

Kersten, Daniel, et al.. (2012). Creating Objects and Object Categories for Studying Perception and Perceptual Learning. Journal of Visualized Experiments. 2 indexed citations

Bart, Evgeniy & Jay Hegdé. (2012). Invariant object recognition based on extended fragments. Frontiers in Computational Neuroscience. 6. 56–56. 2 indexed citations

10.

Hegdé, Jay. (2009). How Reliable is the Pattern Adaptation Technique? A Modeling Study. Journal of Neurophysiology. 102(4). 2245–2252. 9 indexed citations

11.

Hegdé, Jay. (2007). Mental time travel sickness and a Bayesian remedy. Behavioral and Brain Sciences. 30(3). 323–324. 4 indexed citations

12.

Hegdé, Jay & David C. Van Essen. (2006). A Comparative Study of Shape Representation in Macaque Visual Areas V2 and V4. Cerebral Cortex. 17(5). 1100–1116. 129 indexed citations

13.

Hegdé, Jay & David C. Van Essen. (2006). Temporal dynamics of 2D and 3D shape representation in macaque visual area V4. Visual Neuroscience. 23(5). 749–763. 19 indexed citations

14.

Hegdé, Jay & David C. Van Essen. (2005). Role of Primate Visual Area V4 in the Processing of 3-D Shape Characteristics Defined by Disparity. Journal of Neurophysiology. 94(4). 2856–2866. 36 indexed citations

15.

Hegdé, Jay & D.J. Felleman. (2004). Modeling the observed center-surround summation in macaque visual area V1. Neurocomputing. 63. 499–525.

16.

Hegdé, Jay & David C. Van Essen. (2004). Stimulus Dependence of Disparity Coding in Primate Visual Area V4. Journal of Neurophysiology. 93(1). 620–626. 21 indexed citations

17.

Hegdé, Jay, Thomas D. Albright, & Gene R. Stoner. (2004). Second-order motion conveys depth-order information. Journal of Vision. 4(10). 1–1. 12 indexed citations

18.

Boynton, Geoffrey M. & Jay Hegdé. (2004). Visual Cortex: The Continuing Puzzle of Area V2. Current Biology. 14(13). R523–R524. 35 indexed citations

19.

Hegdé, Jay & David C. Van Essen. (2000). Selectivity for Complex Shapes in Primate Visual Area V2. Journal of Neuroscience. 20(5). RC61–RC61. 246 indexed citations

20.

Hegdé, Jay & Daniel J. Felleman. (1999). The popout in some conjunction searches is due to perceptual grouping. Neuroreport. 10(1). 143–148. 7 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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