Jacqueline M. Fulvio

975 total citations
36 papers, 593 citations indexed

About

Jacqueline M. Fulvio is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Human-Computer Interaction. According to data from OpenAlex, Jacqueline M. Fulvio has authored 36 papers receiving a total of 593 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Cognitive Neuroscience, 8 papers in Computer Vision and Pattern Recognition and 6 papers in Human-Computer Interaction. Recurrent topics in Jacqueline M. Fulvio's work include Visual perception and processing mechanisms (21 papers), Neural and Behavioral Psychology Studies (9 papers) and Neural dynamics and brain function (7 papers). Jacqueline M. Fulvio is often cited by papers focused on Visual perception and processing mechanisms (21 papers), Neural and Behavioral Psychology Studies (9 papers) and Neural dynamics and brain function (7 papers). Jacqueline M. Fulvio collaborates with scholars based in United States, Netherlands and Singapore. Jacqueline M. Fulvio's co-authors include Manish Singh, Bas Rokers, Bradley R. Postle, Laurence T. Maloney, Thomas A. Stoffregen, Kay M. Stanney, Ben D. Lawson, Cali Fidopiastis, Séamas Weech and Mark Dennison and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Child Development.

In The Last Decade

Jacqueline M. Fulvio

35 papers receiving 578 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jacqueline M. Fulvio United States 14 352 148 109 86 59 36 593
Kazumichi Matsumiya Japan 14 469 1.3× 112 0.8× 140 1.3× 85 1.0× 95 1.6× 70 634
Deborah Apthorp Australia 19 604 1.7× 168 1.1× 111 1.0× 103 1.2× 147 2.5× 44 864
Harold T. Nefs Netherlands 15 409 1.2× 292 2.0× 106 1.0× 139 1.6× 115 1.9× 37 750
Martin Jüttner Germany 11 660 1.9× 138 0.9× 245 2.2× 131 1.5× 145 2.5× 31 954
Sheryl M. Ehrlich United States 9 277 0.8× 80 0.5× 108 1.0× 85 1.0× 72 1.2× 15 440
Laura Renninger United States 7 370 1.1× 125 0.8× 303 2.8× 45 0.5× 59 1.0× 17 619
Daniel Hannon United States 9 469 1.3× 39 0.3× 109 1.0× 80 0.9× 49 0.8× 29 720
Sheena Rogers United States 8 380 1.1× 68 0.5× 99 0.9× 148 1.7× 118 2.0× 13 656
Flip Phillips United States 17 584 1.7× 62 0.4× 160 1.5× 190 2.2× 141 2.4× 50 807
Paul A. Warren United Kingdom 18 774 2.2× 74 0.5× 176 1.6× 110 1.3× 138 2.3× 60 1.1k

Countries citing papers authored by Jacqueline M. Fulvio

Since Specialization
Citations

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

Fields of papers citing papers by Jacqueline M. Fulvio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacqueline M. Fulvio. 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 Jacqueline M. Fulvio. The network helps show where Jacqueline M. Fulvio may publish in the future.

Co-authorship network of co-authors of Jacqueline M. Fulvio

This figure shows the co-authorship network connecting the top 25 collaborators of Jacqueline M. Fulvio. A scholar is included among the top collaborators of Jacqueline M. Fulvio 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 Jacqueline M. Fulvio. Jacqueline M. Fulvio 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.
Ardalan, Adel, et al.. (2024). Representing Context and Priority in Working Memory. Journal of Cognitive Neuroscience. 36(7). 1374–1394. 2 indexed citations
2.
Fulvio, Jacqueline M., Saskia Haegens, & Bradley R. Postle. (2024). Single-pulse Transcranial Magnetic Stimulation Affects Working-memory Performance via Posterior Beta-band Oscillations. Journal of Cognitive Neuroscience. 36(9). 1827–1846. 1 indexed citations
3.
Fulvio, Jacqueline M., Bas Rokers, & Jason Samaha. (2023). Task feedback suggests a post-perceptual component to serial dependence. Journal of Vision. 23(10). 6–6. 6 indexed citations
4.
Fulvio, Jacqueline M., Qing Yu, & Bradley R. Postle. (2023). Strategic control of location and ordinal context in visual working memory. Cerebral Cortex. 33(13). 8821–8834. 4 indexed citations
5.
Fulvio, Jacqueline M., et al.. (2020). Gender (Im)balance in Citation Practices in Cognitive Neuroscience. Journal of Cognitive Neuroscience. 33(1). 3–7. 82 indexed citations
6.
Cai, Ying, et al.. (2020). The Role of Location-Context Binding in Nonspatial Visual Working Memory. eNeuro. 7(6). ENEURO.0430–20.2020. 13 indexed citations
7.
Fulvio, Jacqueline M. & Bradley R. Postle. (2020). Cognitive Control, Not Time, Determines the Status of Items in Working Memory. Journal of Cognition. 3(1). 8–8. 13 indexed citations
8.
Rokers, Bas, Jacqueline M. Fulvio, Jonathan W. Pillow, & Emily A. Cooper. (2018). Systematic misperceptions of 3-D motion explained by Bayesian inference. Journal of Vision. 18(3). 23–23. 10 indexed citations
9.
Fulvio, Jacqueline M. & Bas Rokers. (2018). Sensitivity to Sensory Cues Predicts Motion Sickness in Virtual Reality. Journal of Vision. 18(10). 1066–1066. 4 indexed citations
10.
Plate, Rista C., Jacqueline M. Fulvio, Kristin Shutts, C. Shawn Green, & Seth D. Pollak. (2017). Probability Learning: Changes in Behavior Across Time and Development. Child Development. 89(1). 205–218. 15 indexed citations
11.
Fulvio, Jacqueline M., Laurence T. Maloney, & Paul Schrater. (2015). Revealing individual differences in strategy selection through visual motion extrapolation. Cognitive Neuroscience. 6(4). 169–179. 3 indexed citations
12.
Fulvio, Jacqueline M., et al.. (2015). Sensory uncertainty leads to systematic misperception of the direction of motion in depth. Attention Perception & Psychophysics. 77(5). 1685–1696. 15 indexed citations
13.
Fulvio, Jacqueline M., Michelle Wang, & Bas Rokers. (2015). Head tracking in virtual reality displays reduces the misperception of 3D motion. Journal of Vision. 15(12). 1180–1180. 4 indexed citations
14.
Fulvio, Jacqueline M., Michelle Wang, & Bas Rokers. (2015). Head tracking in virtual reality displays reduces the misperception of 3D motion. 15(12). 1180–1180. 2 indexed citations
15.
Fulvio, Jacqueline M., C. Shawn Green, & Paul Schrater. (2014). Task-Specific Response Strategy Selection on the Basis of Recent Training Experience. PLoS Computational Biology. 10(1). e1003425–e1003425. 16 indexed citations
16.
Fulvio, Jacqueline M., et al.. (2013). Specificity in learning: Blame the paradigm. Journal of Vision. 13(9). 246–246. 1 indexed citations
17.
Singh, Manish & Jacqueline M. Fulvio. (2007). Bayesian contour extrapolation: Geometric determinants of good continuation. Vision Research. 47(6). 783–798. 28 indexed citations
18.
Fulvio, Jacqueline M. & Manish Singh. (2006). Surface geometry influences the shape of illusory contours. Acta Psychologica. 123(1-2). 20–40. 25 indexed citations
19.
Fulvio, Jacqueline M., Manish Singh, & Laurence T. Maloney. (2006). Combining achromatic and chromatic cues to transparency. Journal of Vision. 6(8). 1–1. 20 indexed citations
20.
Singh, Manish & Jacqueline M. Fulvio. (2005). Visual extrapolation of contour geometry. Proceedings of the National Academy of Sciences. 102(3). 939–944. 53 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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