Aaron M. Bornstein

1.6k total citations
32 papers, 842 citations indexed

About

Aaron M. Bornstein is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and General Decision Sciences. According to data from OpenAlex, Aaron M. Bornstein has authored 32 papers receiving a total of 842 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 7 papers in Experimental and Cognitive Psychology and 6 papers in General Decision Sciences. Recurrent topics in Aaron M. Bornstein's work include Memory and Neural Mechanisms (12 papers), Neural and Behavioral Psychology Studies (8 papers) and Neural dynamics and brain function (7 papers). Aaron M. Bornstein is often cited by papers focused on Memory and Neural Mechanisms (12 papers), Neural and Behavioral Psychology Studies (8 papers) and Neural dynamics and brain function (7 papers). Aaron M. Bornstein collaborates with scholars based in United States, Canada and Germany. Aaron M. Bornstein's co-authors include Nathaniel D. Daw, Kenneth A. Norman, Daphna Shohamy, Mel Win Khaw, Anthony D. Wagner, Gary H. Glover, Ben Hutchinson, Alison R. Preston, Yael Niv and Nina Rouhani and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Neuroscience.

In The Last Decade

Aaron M. Bornstein

28 papers receiving 826 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aaron M. Bornstein United States 14 661 154 131 104 94 32 842
Tarrant D.R. Cummins Australia 14 578 0.9× 169 1.1× 117 0.9× 139 1.3× 76 0.8× 28 1.0k
Payam Piray United States 13 508 0.8× 157 1.0× 186 1.4× 88 0.8× 74 0.8× 20 767
Mehdi Keramati United Kingdom 12 598 0.9× 162 1.1× 189 1.4× 116 1.1× 78 0.8× 19 874
Reka Daniel United States 8 582 0.9× 73 0.5× 142 1.1× 64 0.6× 80 0.9× 9 757
Dylan Alexander Simon United States 6 466 0.7× 98 0.6× 91 0.7× 72 0.7× 90 1.0× 8 593
Klaus Wunderlich United Kingdom 13 984 1.5× 215 1.4× 147 1.1× 111 1.1× 53 0.6× 16 1.3k
Ian C. Ballard United States 12 405 0.6× 97 0.6× 123 0.9× 93 0.9× 41 0.4× 20 589
Archy O. de Berker United Kingdom 13 746 1.1× 93 0.6× 148 1.1× 55 0.5× 42 0.4× 15 1.0k
Oren Griffiths Australia 17 705 1.1× 70 0.5× 203 1.5× 75 0.7× 155 1.6× 45 924
Michael J. Frank United States 4 513 0.8× 63 0.4× 184 1.4× 93 0.9× 59 0.6× 5 761

Countries citing papers authored by Aaron M. Bornstein

Since Specialization
Citations

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

Fields of papers citing papers by Aaron M. Bornstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aaron M. Bornstein

This figure shows the co-authorship network connecting the top 25 collaborators of Aaron M. Bornstein. A scholar is included among the top collaborators of Aaron M. Bornstein 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 Aaron M. Bornstein. Aaron M. Bornstein 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.
Peters, Megan A. K., et al.. (2025). Reasoning Goals and Representational Decisions in Computational Cognitive Neuroscience: Lessons From the Drift Diffusion Model. European Journal of Neuroscience. 61(7). e70098–e70098.
2.
Wahlheim, Christopher N., et al.. (2024). A response time model of the three-choice Mnemonic Similarity Task provides stable, mechanistically interpretable individual-difference measures. Frontiers in Human Neuroscience. 18. 1379287–1379287. 1 indexed citations
3.
Chrastil, Elizabeth R., et al.. (2024). Cognitive graphs: Representational substrates for planning.. Decision. 11(4). 537–556. 2 indexed citations
4.
Chen, Janice & Aaron M. Bornstein. (2024). The causal structure and computational value of narratives. Trends in Cognitive Sciences. 28(8). 769–781. 6 indexed citations
5.
Zhou, Dale & Aaron M. Bornstein. (2024). Expanding horizons in reinforcement learning for curious exploration and creative planning. Behavioral and Brain Sciences. 47. e118–e118. 1 indexed citations
6.
Bornstein, Aaron M., et al.. (2023). Interval Timing as a Computational Pathway From Early Life Adversity to Affective Disorders. Topics in Cognitive Science. 16(1). 92–112. 5 indexed citations
7.
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
8.
Bennett, Ilana J., et al.. (2023). Memory precision and age differentially predict the use of decision-making strategies across the lifespan. Scientific Reports. 13(1). 17014–17014. 4 indexed citations
9.
Otto, A. Ross, et al.. (2022). Context-dependent choice and evaluation in real-world consumer behavior. Scientific Reports. 12(1). 17744–17744. 13 indexed citations
10.
Ritz, Harrison, et al.. (2022). Humans can navigate complex graph structures acquired during latent learning. Cognition. 225. 105103–105103. 12 indexed citations
11.
Rouhani, Nina, Kenneth A. Norman, Yael Niv, & Aaron M. Bornstein. (2020). Reward prediction errors create event boundaries in memory. Cognition. 203. 104269–104269. 66 indexed citations
12.
Bornstein, Aaron M. & Hanna Pickard. (2020). “Chasing the first high”: memory sampling in drug choice. Neuropsychopharmacology. 45(6). 907–915. 30 indexed citations
13.
Bornstein, Aaron M., et al.. (2018). Refresh my memory: Episodic memory reinstatements intrude on working memory maintenance. Cognitive Affective & Behavioral Neuroscience. 19(2). 338–354. 22 indexed citations
14.
Millner, Alexander J., Hanneke E.M. den Ouden, Samuel J. Gershman, et al.. (2018). Suicidal thoughts and behaviors are associated with an increased decision-making bias for active responses to escape aversive states.. Journal of Abnormal Psychology. 128(2). 106–118. 38 indexed citations
15.
Bornstein, Aaron M. & Kenneth A. Norman. (2017). Reinstated episodic context guides sampling-based decisions for reward. Nature Neuroscience. 20(7). 997–1003. 105 indexed citations
16.
Bornstein, Aaron M., Mel Win Khaw, Daphna Shohamy, & Nathaniel D. Daw. (2017). Reminders of past choices bias decisions for reward in humans. Nature Communications. 8(1). 15958–15958. 132 indexed citations
17.
Bornstein, Aaron M. & Nathaniel D. Daw. (2013). Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans. PLoS Computational Biology. 9(12). e1003387–e1003387. 64 indexed citations
18.
Bornstein, Aaron M. & Nathaniel D. Daw. (2012). Dissociating hippocampal and striatal contributions to sequential prediction learning. European Journal of Neuroscience. 35(7). 1011–1023. 83 indexed citations
19.
Bornstein, Aaron M. & Nathaniel D. Daw. (2011). Multiplicity of control in the basal ganglia: computational roles of striatal subregions. Current Opinion in Neurobiology. 21(3). 374–380. 75 indexed citations
20.
Aston, Sherrell J. & Aaron M. Bornstein. (1978). An unusual complication associated with blepharoplasty. Aesthetic Plastic Surgery. 2(1). 451–453. 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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