Dino J. Levy

3.2k total citations · 1 hit paper
34 papers, 2.1k citations indexed

About

Dino J. Levy is a scholar working on Cognitive Neuroscience, General Decision Sciences and Cellular and Molecular Neuroscience. According to data from OpenAlex, Dino J. Levy has authored 34 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cognitive Neuroscience, 9 papers in General Decision Sciences and 8 papers in Cellular and Molecular Neuroscience. Recurrent topics in Dino J. Levy's work include Neural and Behavioral Psychology Studies (16 papers), Neural dynamics and brain function (11 papers) and Decision-Making and Behavioral Economics (9 papers). Dino J. Levy is often cited by papers focused on Neural and Behavioral Psychology Studies (16 papers), Neural dynamics and brain function (11 papers) and Decision-Making and Behavioral Economics (9 papers). Dino J. Levy collaborates with scholars based in Israel, United States and Canada. Dino J. Levy's co-authors include Paul W. Glimcher, Abraham Zangen, Ryan Webb, Ariel Telpaz, Revital Amiaz, Leon Grunhaus, Maytal Shabat-Simon, Noam Barnea‐Ygael, Uri Shalev and Yavin Shaham and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Dino J. Levy

32 papers receiving 2.1k 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.

The root of all value: a neural common currency for choice

2012 823 citations Dino J. Levy, Paul W. Glimcher profile →

Peers

Dino J. Levy

CN

CMN

ECP

GDS

SP

Ruth M. Krebs Belgium

Gerhard Jocham Germany

Nils Kolling United Kingdom

C. Nico Boehler Belgium

Soyoung Q. Park Germany

Erie D. Boorman United States

Lorena R. R. Gianotti Switzerland

Laurence T. Hunt United Kingdom

Geoffrey F. Potts United States

Christopher Trepel Canada

Ruth M. Krebs Belgium

Dino J. Levy

2.6k ×1.9

CN

429 ×1.1

CMN

621 ×1.7

ECP

226 ×0.7

GDS

267 ×1.0

SP

Citations per year, relative to Dino J. Levy Dino J. Levy (= 1×) peers Ruth M. Krebs

Countries citing papers authored by Dino J. Levy

Since Specialization

Citations

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

Fields of papers citing papers by Dino J. Levy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dino J. Levy. 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 Dino J. Levy. The network helps show where Dino J. Levy may publish in the future.

Co-authorship network of co-authors of Dino J. Levy

This figure shows the co-authorship network connecting the top 25 collaborators of Dino J. Levy. A scholar is included among the top collaborators of Dino J. Levy 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 Dino J. Levy. Dino J. Levy 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.

Sampson, Aaron L., Erik E. Emeric, Moshe Glickman, et al.. (2025). Overt Visual Attention in the Formation of Preference Between Complex Lottery Options. Computational Brain & Behavior. 8(4). 568–587.

2.

Krajbich, Ian, et al.. (2024). Valuations of target items are drawn towards unavailable decoy items due to prior expectations. PNAS Nexus. 3(7). pgae232–pgae232. 1 indexed citations

3.

Glickman, Moshe, Tal Sela, Marius Usher, & Dino J. Levy. (2023). The effect of perceptual organization on numerical and preference-based decisions shows inter-subject correlation. Psychonomic Bulletin & Review. 30(4). 1410–1421. 1 indexed citations

4.

Levy, Dino J., et al.. (2023). DeePay: deep learning decodes EEG to predict consumer’s willingness to pay for neuromarketing. Frontiers in Human Neuroscience. 17. 1153413–1153413. 10 indexed citations

5.

Lerner, Yulia, et al.. (2022). Neural and functional validation of fMRI-informed EEG model of right inferior frontal gyrus activity. NeuroImage. 266. 119822–119822. 5 indexed citations

6.

Levy, Dino J., et al.. (2020). Attraction to similar options: The Gestalt law of proximity is related to the attraction effect. PLoS ONE. 15(10). e0240937–e0240937. 3 indexed citations

7.

Sela, Tal, et al.. (2020). Item Features Interact With Item Category in Their Influence on Preferences. Frontiers in Psychology. 11. 988–988. 2 indexed citations

8.

Levy, Dino J., et al.. (2020). Contribution of self- and other-regarding motives to (dis)honesty. Scientific Reports. 10(1). 15844–15844. 9 indexed citations

9.

Louie, Kenway, et al.. (2019). Bounded rationality in C. elegans is explained by circuit-specific normalization in chemosensory pathways. Nature Communications. 10(1). 3692–3692. 14 indexed citations

10.

Glickman, Moshe, et al.. (2019). The formation of preference in risky choice. PLoS Computational Biology. 15(8). e1007201–e1007201. 27 indexed citations

11.

Levy, Dino J., et al.. (2018). Common Sense in Choice: The Effect of Sensory Modality on Neural Value Representations. eNeuro. 5(2). ENEURO.0346–17.2018. 4 indexed citations

12.

Levy, Dino J., et al.. (2013). A Computational Hypothesis for Allostasis: Delineation of Substance Dependence, Conventional Therapies, and Alternative Treatments. Frontiers in Psychiatry. 4. 167–167. 7 indexed citations

13.

Levy, Dino J., et al.. (2013). State Dependent Valuation: The Effect of Deprivation on Risk Preferences. PLoS ONE. 8(1). e53978–e53978. 54 indexed citations

14.

Levy, Dino J. & Paul W. Glimcher. (2011). Comparing Apples and Oranges: Using Reward-Specific and Reward-General Subjective Value Representation in the Brain. Journal of Neuroscience. 31(41). 14693–14707. 246 indexed citations

15.

Stehberg, Jimmy, Dino J. Levy, & Abraham Zangen. (2009). Impairment of aversive memory reconsolidation by localized intracranial electrical stimulation. European Journal of Neuroscience. 29(5). 964–969. 25 indexed citations

16.

Amiaz, Revital, et al.. (2009). Repeated high‐frequency transcranial magnetic stimulation over the dorsolateral prefrontal cortex reduces cigarette craving and consumption. Addiction. 104(4). 653–660. 223 indexed citations

17.

Shabat-Simon, Maytal, Dino J. Levy, Alon Amir, Moshe Rehavi, & Abraham Zangen. (2008). Dissociation between Rewarding and Psychomotor Effects of Opiates: Differential Roles for Glutamate Receptors within Anterior and Posterior Portions of the Ventral Tegmental Area. Journal of Neuroscience. 28(34). 8406–8416. 60 indexed citations

18.

Barnea‐Ygael, Noam, et al.. (2007). A conflict rat model of cue-induced relapse to cocaine seeking. Psychopharmacology. 194(1). 117–125. 82 indexed citations

19.

Friedman, Alexander, Eliyahu Dremencov, Dino J. Levy, et al.. (2005). Variability of the mesolimbic neuronal activity in a rat model of depression. Neuroreport. 16(5). 513–516. 20 indexed citations

20.

Dremencov, Eliyahu, Eitan Nahshoni, Dino J. Levy, et al.. (2004). Dimensional complexity of the neuronal activity in a rat model of depression. Neuroreport. 15(12). 1983–1986. 12 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.

Explore authors with similar magnitude of impact