Diane M. Beck

8.0k total citations · 1 hit paper
91 papers, 5.2k citations indexed

About

Diane M. Beck is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Diane M. Beck has authored 91 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Cognitive Neuroscience, 13 papers in Computer Vision and Pattern Recognition and 6 papers in Artificial Intelligence. Recurrent topics in Diane M. Beck's work include Visual perception and processing mechanisms (50 papers), Neural dynamics and brain function (43 papers) and Neural and Behavioral Psychology Studies (35 papers). Diane M. Beck is often cited by papers focused on Visual perception and processing mechanisms (50 papers), Neural dynamics and brain function (43 papers) and Neural and Behavioral Psychology Studies (35 papers). Diane M. Beck collaborates with scholars based in United States, United Kingdom and Italy. Diane M. Beck's co-authors include Li Fei-Fei, Monica Fabiani, Gabriele Gratton, Kyle E. Mathewson, Sabine Kästner, Nilli Lavie, Tony Ro, Christopher Baldassano, Alejandro Lleras and Dirk B. Walther and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Journal of Neuroscience.

In The Last Decade

Diane M. Beck

89 papers receiving 5.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

To See or Not to See: Prestimulus α Phase Predicts Visual Awareness

2009 748 citations Kyle E. Mathewson, Gabriele Gratton et al. profile →

Peers

Diane M. Beck

CN

ECP

CVPR

SP

CMN

Guillaume A. Rousselet United Kingdom

Dwight J. Kravitz United States

Denis Fize France

Michael H. Herzog Switzerland

John T. Serences United States

Manfred Fahle Germany

Nava Rubin United States

Jochen Braun Germany

Patrick Bennett Canada

Martin Rolfs Germany

Guillaume A. Rousselet United Kingdom

Diane M. Beck

3.8k ×0.8

CN

1.0k ×1.6

ECP

748 ×1.3

CVPR

371 ×1.0

SP

180 ×0.6

CMN

Citations per year, relative to Diane M. Beck Diane M. Beck (= 1×) peers Guillaume A. Rousselet

Countries citing papers authored by Diane M. Beck

Since Specialization

Citations

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

Fields of papers citing papers by Diane M. Beck

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Diane M. Beck

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Beck, Diane M., et al.. (2024). Image memorability is linked to facilitated perceptual and semantic processing. Imaging Neuroscience. 2. 3 indexed citations

2.

Beck, Diane M., et al.. (2024). Is attention necessary for the representational advantage of good exemplars over bad exemplars?. European Journal of Neuroscience. 59(9). 2353–2372. 5 indexed citations

3.

Gratton, Gabriele, et al.. (2024). Bypassing input to V1 in visual awareness: A TMS-EROS investigation. Neuropsychologia. 198. 108864–108864.

4.

Federmeier, Kara D., et al.. (2021). The N300: An Index for Predictive Coding of Complex Visual Objects and Scenes. Cerebral Cortex Communications. 2(2). tgab030–tgab030. 24 indexed citations

5.

Wang, Tracy H., et al.. (2021). Separation of item and context in item-method directed forgetting. NeuroImage. 235. 117983–117983. 11 indexed citations

6.

Federmeier, Kara D., et al.. (2017). Evidence for similar patterns of neural activity elicited by picture- and word-based representations of natural scenes. NeuroImage. 155. 422–436. 16 indexed citations

7.

Baldassano, Christopher, Diane M. Beck, & Li Fei-Fei. (2016). Human–Object Interactions Are More than the Sum of Their Parts. Cerebral Cortex. 27(3). bhw077–bhw077. 47 indexed citations

8.

Baldassano, Christopher, Andre Esteva, Li Fei-Fei, & Diane M. Beck. (2016). Two Distinct Scene-Processing Networks Connecting Vision and Memory. eNeuro. 3(5). ENEURO.0178–16.2016. 106 indexed citations

9.

Greene, Michelle R., et al.. (2016). Typicality sharpens category representations in object-selective cortex. NeuroImage. 134. 170–179. 27 indexed citations

10.

Parks, Nathan A., Chiara Mazzi, Evelina Tapia, et al.. (2015). The influence of posterior parietal cortex on extrastriate visual activity: A concurrent TMS and fast optical imaging study. Neuropsychologia. 78. 153–158. 17 indexed citations

11.

Baldassano, Christopher, Diane M. Beck, & Li Fei-Fei. (2014). Supervoxel parcellation of visual cortex connectivity. Journal of Vision. 14(10). 1080–1080. 1 indexed citations

12.

Lleras, Alejandro, et al.. (2014). No masked priming of shape in metacontrast and object substitution masking paradigms without attention. Journal of Vision. 14(10). 1058–1058.

13.

Baldassano, Christopher, Diane M. Beck, & Li Fei-Fei. (2013). Differential Connectivity Within the Parahippocampal Place Area. Journal of Vision. 13(9). 1096–1096. 44 indexed citations

14.

Greene, Michelle R., et al.. (2012). Neural Representations of Object Categories at Multiple Taxonomic Levels. Journal of Vision. 12(9). 1105–1105. 1 indexed citations

15.

Beck, Diane M., et al.. (2011). The effects of dividing attention on target enhancement and distractor inhibition. Journal of Vision. 11(11). 104–104. 1 indexed citations

16.

Mathewson, Kyle E., Alejandro Lleras, Diane M. Beck, et al.. (2011). Pulsed Out of Awareness: EEG Alpha Oscillations Represent a Pulsed-Inhibition of Ongoing Cortical Processing. Frontiers in Psychology. 2. 99–99. 370 indexed citations

17.

Yao, Bangpeng, Dirk B. Walther, Diane M. Beck, & Li Fei-Fei. (2009). Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions. Neural Information Processing Systems. 22. 2178–2186. 12 indexed citations

18.

Walther, Dirk B., et al.. (2009). Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis. Neural Information Processing Systems. 22. 270–278. 51 indexed citations

19.

Beck, Diane M. & Sabine Kästner. (2008). Top-down and bottom-up mechanisms in biasing competition in the human brain. Vision Research. 49(10). 1154–1165. 314 indexed citations

20.

Ehrlich, Sheryl M., Diane M. Beck, James A. Crowell, Tom C. A. Freeman, & Martin S. Banks. (1998). Depth information and perceived self-motion during simulated gaze rotations. Vision Research. 38(20). 3129–3145. 48 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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