Kenneth A. Norman

21.4k total citations · 5 hit papers
140 papers, 12.0k citations indexed

About

Kenneth A. Norman is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Kenneth A. Norman has authored 140 papers receiving a total of 12.0k indexed citations (citations by other indexed papers that have themselves been cited), including 119 papers in Cognitive Neuroscience, 26 papers in Artificial Intelligence and 18 papers in Experimental and Cognitive Psychology. Recurrent topics in Kenneth A. Norman's work include Memory and Neural Mechanisms (69 papers), Memory Processes and Influences (50 papers) and Neural dynamics and brain function (43 papers). Kenneth A. Norman is often cited by papers focused on Memory and Neural Mechanisms (69 papers), Memory Processes and Influences (50 papers) and Neural dynamics and brain function (43 papers). Kenneth A. Norman collaborates with scholars based in United States, Italy and United Kingdom. Kenneth A. Norman's co-authors include Sean M. Polyn, Randall C. O’Reilly, Greg Detre, Daniel L. Schacter, James V. Haxby, Uri Hasson, Nicholas B. Turk‐Browne, Wilma Koutstaal, Jonathan D. Cohen and Michael J. Kahana and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Kenneth A. Norman

140 papers receiving 11.8k citations

Hit Papers

Beyond mind-reading: multi-voxel pattern analysis of fMRI... 1998 2026 2007 2016 2006 2003 1998 2017 2016 500 1000 1.5k

Peers

Kenneth A. Norman
Eric Maris Netherlands
Lila Davachi United States
Mark A. Gluck United States
Tim Curran United States
Uri Hasson United States
Randall C. O’Reilly United States
George R. Mangun United States
Floris P. de Lange Netherlands
Kenneth A. Norman
Citations per year, relative to Kenneth A. Norman Kenneth A. Norman (= 1×) peers Nicholas B. Turk‐Browne

Countries citing papers authored by Kenneth A. Norman

Since Specialization
Citations

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

Fields of papers citing papers by Kenneth A. Norman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kenneth A. Norman. 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 Kenneth A. Norman. The network helps show where Kenneth A. Norman may publish in the future.

Co-authorship network of co-authors of Kenneth A. Norman

This figure shows the co-authorship network connecting the top 25 collaborators of Kenneth A. Norman. A scholar is included among the top collaborators of Kenneth A. Norman 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 Kenneth A. Norman. Kenneth A. Norman 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.
Collin, Silvy, et al.. (2025). Neural codes track prior events in a narrative and predict subsequent memory for details. Communications Psychology. 3(1). 26–26. 1 indexed citations
2.
Michelmann, Sebastian, M. Kumar, Kenneth A. Norman, & Mariya Toneva. (2025). Large language models can segment narrative events similarly to humans. Behavior Research Methods. 57(1). 39–39. 3 indexed citations
3.
Lu, Qihong, et al.. (2025). Towards large language models with human-like episodic memory. Trends in Cognitive Sciences. 29(10). 928–941. 1 indexed citations
4.
Wammes, Jeffrey D., et al.. (2024). Inducing representational change in the hippocampus through real-time neurofeedback. Philosophical Transactions of the Royal Society B Biological Sciences. 379(1915). 20230091–20230091. 3 indexed citations
5.
Norman, Kenneth A., et al.. (2024). Sculpting new visual categories into the human brain. Proceedings of the National Academy of Sciences. 121(50). e2410445121–e2410445121. 1 indexed citations
6.
Goldstein, Ariel, Uri Hasson, Kenneth A. Norman, et al.. (2024). Shared functional specialization in transformer-based language models and the human brain. Nature Communications. 15(1). 5523–5523. 12 indexed citations
7.
Zhang, Robert, Étienne Serbe, Matthias Meier, et al.. (2024). Study while you sleep: using targeted memory reactivation as an independent research project for undergraduates. AJP Advances in Physiology Education. 49(1). 1–10. 1 indexed citations
8.
Brooks, Paula P., et al.. (2024). Eye tracking evidence for the reinstatement of emotionally negative and neutral memories. PLoS ONE. 19(5). e0303755–e0303755. 1 indexed citations
9.
Rier, Lukas, Sebastian Michelmann, Harrison Ritz, et al.. (2023). Test-retest reliability of the human connectome: An OPM-MEG study. Imaging Neuroscience. 1. 9 indexed citations
10.
Goldstein, Ariel, et al.. (2023). Bayesian Surprise Predicts Human Event Segmentation in Story Listening. Cognitive Science. 47(10). e13343–e13343. 8 indexed citations
11.
Michelmann, Sebastian, Uri Hasson, & Kenneth A. Norman. (2023). Evidence That Event Boundaries Are Access Points for Memory Retrieval. Psychological Science. 34(3). 326–344. 24 indexed citations
12.
Bornstein, Aaron M., Mariam Aly, Samuel F. Feng, et al.. (2023). Associative memory retrieval modulates upcoming perceptual decisions. Cognitive Affective & Behavioral Neuroscience. 23(3). 645–665. 5 indexed citations
13.
Margulis, Elizabeth Hellmuth, Samuel A. Nastase, Janice Chen, et al.. (2022). High-Order Areas and Auditory Cortex Both Represent the High-Level Event Structure of Music. Journal of Cognitive Neuroscience. 34(4). 699–714. 18 indexed citations
14.
Chang, Claire H. C., et al.. (2021). Relating the Past with the Present: Information Integration and Segregation during Ongoing Narrative Processing. Journal of Cognitive Neuroscience. 33(6). 1106–1128. 27 indexed citations
15.
Michelmann, Sebastian, Amy Price, Bobbi Aubrey, et al.. (2021). Moment-by-moment tracking of naturalistic learning and its underlying hippocampo-cortical interactions. Nature Communications. 12(1). 5394–5394. 28 indexed citations
16.
Schechtman, Eitan, et al.. (2021). Multiple memories can be simultaneously reactivated during sleep as effectively as a single memory. Communications Biology. 4(1). 25–25. 34 indexed citations
17.
Schapiro, Anna C., Elizabeth A. McDevitt, Timothy T. Rogers, Sara C. Mednick, & Kenneth A. Norman. (2018). Human hippocampal replay during rest prioritizes weakly learned information and predicts memory performance. Nature Communications. 9(1). 3920–3920. 148 indexed citations
18.
Poppenk, Jordan & Kenneth A. Norman. (2017). Multiple-object Tracking as a Tool for Parametrically Modulating Memory Reactivation. Journal of Cognitive Neuroscience. 29(8). 1339–1354. 3 indexed citations
19.
Schapiro, Anna C., Nicholas B. Turk‐Browne, Matthew Botvinick, & Kenneth A. Norman. (2016). Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning. Philosophical Transactions of the Royal Society B Biological Sciences. 372(1711). 20160049–20160049. 264 indexed citations
20.
O’Reilly, Randall C., Kenneth A. Norman, & James L. McClelland. (1997). A Hippocampal Model of Recognition Memory. Neural Information Processing Systems. 10. 73–79. 30 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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