Zvi Israel

5.9k total citations · 1 hit paper
115 papers, 3.9k citations indexed

About

Zvi Israel is a scholar working on Neurology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Zvi Israel has authored 115 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Neurology, 57 papers in Cellular and Molecular Neuroscience and 32 papers in Cognitive Neuroscience. Recurrent topics in Zvi Israel's work include Neurological disorders and treatments (64 papers), Parkinson's Disease Mechanisms and Treatments (48 papers) and Neuroscience and Neural Engineering (25 papers). Zvi Israel is often cited by papers focused on Neurological disorders and treatments (64 papers), Parkinson's Disease Mechanisms and Treatments (48 papers) and Neuroscience and Neural Engineering (25 papers). Zvi Israel collaborates with scholars based in Israel, United States and France. Zvi Israel's co-authors include Hagai Bergman, Adam Zaidel, Eilon Vaadia, Suzanne N. Haber, Michal Rivlin‐Etzion, Boris Rosin, Maya Slovik, Rea Mitelman, Hermona Soreq and Lilach Soreq and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Neuron.

In The Last Decade

Zvi Israel

112 papers receiving 3.8k citations

Hit Papers

Closed-Loop Deep Brain St... 2011 2026 2016 2021 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zvi Israel Israel 33 2.6k 2.1k 1.1k 426 388 115 3.9k
Jan Vesper Germany 35 2.1k 0.8× 1.2k 0.6× 640 0.6× 596 1.4× 276 0.7× 133 4.0k
Nobuhiro Mikuni Japan 36 1.4k 0.5× 1.2k 0.6× 1.8k 1.6× 372 0.9× 320 0.8× 270 4.6k
Alain Bouthillier Canada 32 824 0.3× 792 0.4× 855 0.8× 635 1.5× 439 1.1× 110 3.7k
S. Blond France 36 3.3k 1.3× 1.7k 0.8× 421 0.4× 496 1.2× 251 0.6× 163 4.8k
Peter C. Reinacher Germany 28 1.3k 0.5× 648 0.3× 420 0.4× 914 2.1× 284 0.7× 136 3.1k
Bradley Lega United States 34 648 0.2× 1.2k 0.6× 2.3k 2.0× 250 0.6× 250 0.6× 98 3.4k
Giuseppe Moretto Italy 30 1.2k 0.5× 646 0.3× 250 0.2× 389 0.9× 514 1.3× 84 2.6k
Pál Barzó Hungary 26 1.4k 0.6× 1.2k 0.6× 745 0.7× 253 0.6× 847 2.2× 114 3.3k
Dario J. Englot United States 47 1.9k 0.7× 1.9k 0.9× 2.4k 2.1× 974 2.3× 364 0.9× 177 6.5k
Kurtis I. Auguste United States 34 910 0.4× 1.1k 0.6× 695 0.6× 696 1.6× 882 2.3× 68 4.3k

Countries citing papers authored by Zvi Israel

Since Specialization
Citations

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

Fields of papers citing papers by Zvi Israel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zvi Israel. 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 Zvi Israel. The network helps show where Zvi Israel may publish in the future.

Co-authorship network of co-authors of Zvi Israel

This figure shows the co-authorship network connecting the top 25 collaborators of Zvi Israel. A scholar is included among the top collaborators of Zvi Israel 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 Zvi Israel. Zvi Israel 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.
Israel, Zvi, Omer Zarchi, Idit Tamir, et al.. (2025). Is the Subthalamic Nucleus Sleeping Under Nitrous Oxide–Ketamine General Anesthesia?. European Journal of Neuroscience. 61(5). e70039–e70039. 1 indexed citations
2.
Romito, Luigi, Nico Golfrè Andreasi, Sara Rinaldo, et al.. (2025). Genetic Etiology Influences the Low‐Frequency Components of Globus Pallidus Internus Electrophysiology in Dystonia. European Journal of Neurology. 32(3). e70098–e70098.
3.
Andreasi, Nico Golfrè, Sara Rinaldo, Zvi Israel, et al.. (2025). Spiking Patterns in the Globus Pallidus Highlight Convergent Neural Dynamics across Diverse Genetic Dystonia Syndromes. Annals of Neurology. 97(5). 826–844. 3 indexed citations
5.
Pal, Gian, Daniel M. Corcos, Leo Verhagen Metman, et al.. (2023). Cognitive Effects of Subthalamic Nucleus Deep Brain Stimulation in Parkinson's Disease with GBA1 Pathogenic Variants. Movement Disorders. 38(12). 2155–2162. 6 indexed citations
6.
Linetsky, Eduard, et al.. (2023). The Genetic Etiology of Parkinson's Disease Does Not Robustly Affect Subthalamic Physiology. Movement Disorders. 38(3). 484–489. 4 indexed citations
7.
Mor‐Shaked, Hagar, Simona Ben‐Haim, Zvi Israel, et al.. (2021). Levodopa-responsive dystonia caused by biallelic PRKN exon inversion invisible to exome sequencing. Brain Communications. 3(3). fcab197–fcab197. 9 indexed citations
8.
Deffains, Marc, Odeya Marmor, Rony Paz, et al.. (2021). Modulation of dopamine tone induces frequency shifts in cortico-basal ganglia beta oscillations. Nature Communications. 12(1). 7026–7026. 52 indexed citations
10.
Arkadir, David, Eduard Linetsky, Atira Bick, et al.. (2019). Theta‐alpha Oscillations Characterize Emotional Subregion in the Human Ventral Subthalamic Nucleus. Movement Disorders. 35(2). 337–343. 29 indexed citations
11.
Blackwell, Kim T., et al.. (2019). Real-time machine learning classification of pallidal borders during deep brain stimulation surgery. Journal of Neural Engineering. 17(1). 16021–16021. 25 indexed citations
12.
Soreq, Lilach, Nathan Salomonis, Zvi Israel, Hagai Bergman, & Hermona Soreq. (2015). Analyzing alternative splicing data of splice junction arrays from Parkinson patients' leukocytes before and after deep brain stimulation as compared with control donors. Genomics Data. 5. 340–343. 7 indexed citations
13.
Soreq, Lilach, Nathan Salomonis, Alessandro Guffanti, et al.. (2014). Whole transcriptome RNA sequencing data from blood leukocytes derived from Parkinson's disease patients prior to and following deep brain stimulation treatment. Genomics Data. 3. 57–60. 20 indexed citations
14.
Eitan, Renana, Reuben R. Shamir, Eduard Linetsky, et al.. (2013). Asymmetric right/left encoding of emotions in the human subthalamic nucleus. Frontiers in Systems Neuroscience. 7. 69–69. 60 indexed citations
15.
Adler, Avital, et al.. (2012). Temporal Convergence of Dynamic Cell Assemblies in the Striato-Pallidal Network. Journal of Neuroscience. 32(7). 2473–2484. 67 indexed citations
16.
Zaidel, Adam, et al.. (2010). Subthalamic span of   oscillations predicts deep brain stimulation efficacy for patients with Parkinson's disease. Brain. 133(7). 2007–2021. 231 indexed citations
17.
Arce‐McShane, Fritzie I., et al.. (2010). Combined Adaptiveness of Specific Motor Cortical Ensembles Underlies Learning. Journal of Neuroscience. 30(15). 5415–5425. 27 indexed citations
18.
Constantini, Shlomi, et al.. (2001). Safety of perioperative minidose heparin in patients undergoing brain tumor surgery: a prospective, randomized, double-blind study. Journal of neurosurgery. 94(6). 918–921. 68 indexed citations
19.
Israel, Zvi, John M. Gomori, Shlomo Dotan, et al.. (2000). Rathke’s Cleft Cyst Abscess. Pediatric Neurosurgery. 33(3). 159–161. 22 indexed citations
20.
Gural, Alexander, et al.. (1998). Massive Intracranial Bleeding Requiring Emergency Splenectomy in a Patient with CMV-Associated Thrombocytopenia. Pathophysiology of Haemostasis and Thrombosis. 28(5). 250–255. 16 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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