Robert S. Raike

1.5k total citations
28 papers, 659 citations indexed

About

Robert S. Raike is a scholar working on Cellular and Molecular Neuroscience, Neurology and Molecular Biology. According to data from OpenAlex, Robert S. Raike has authored 28 papers receiving a total of 659 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Cellular and Molecular Neuroscience, 22 papers in Neurology and 7 papers in Molecular Biology. Recurrent topics in Robert S. Raike's work include Neurological disorders and treatments (20 papers), Parkinson's Disease Mechanisms and Treatments (16 papers) and Genetic Neurodegenerative Diseases (16 papers). Robert S. Raike is often cited by papers focused on Neurological disorders and treatments (20 papers), Parkinson's Disease Mechanisms and Treatments (16 papers) and Genetic Neurodegenerative Diseases (16 papers). Robert S. Raike collaborates with scholars based in United States, Netherlands and France. Robert S. Raike's co-authors include Ellen J. Hess, H. A. Jinnah, Catherine J.C. Weisz, Christopher M. Gómez, Randall M. Thompson, Arn M. J. M. van den Maagdenberg, Michael S. Okun, Maureen Riedl, Jacob Eliet and Pierre Charnet and has published in prestigious journals such as Journal of Neuroscience, Brain and Neurology.

In The Last Decade

Robert S. Raike

27 papers receiving 650 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert S. Raike United States 15 500 401 225 96 49 28 659
Jennifer Stanic Italy 12 358 0.7× 241 0.6× 211 0.9× 68 0.7× 49 1.0× 15 535
Jacques Audin France 8 547 1.1× 527 1.3× 170 0.8× 109 1.1× 154 3.1× 8 840
Eileanoir B. Johnson United Kingdom 19 511 1.0× 383 1.0× 343 1.5× 42 0.4× 89 1.8× 29 708
Nathaniel R. Whaley United States 11 342 0.7× 545 1.4× 103 0.5× 75 0.8× 64 1.3× 12 670
Jens Claaßen Germany 12 273 0.5× 223 0.6× 196 0.9× 229 2.4× 57 1.2× 22 601
Yaimeé Vázquez‐Mojena Cuba 16 362 0.7× 214 0.5× 258 1.1× 82 0.9× 36 0.7× 31 475
Laura Orsi Italy 13 231 0.5× 127 0.3× 222 1.0× 123 1.3× 69 1.4× 25 448
Marta Panzeri Italy 10 230 0.5× 103 0.3× 209 0.9× 71 0.7× 32 0.7× 17 355
J. Andrich Germany 9 461 0.9× 330 0.8× 255 1.1× 35 0.4× 43 0.9× 13 563
Nalia Canales‐Ochoa Cuba 13 389 0.8× 236 0.6× 282 1.3× 85 0.9× 36 0.7× 22 474

Countries citing papers authored by Robert S. Raike

Since Specialization
Citations

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

Fields of papers citing papers by Robert S. Raike

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert S. Raike. 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 Robert S. Raike. The network helps show where Robert S. Raike may publish in the future.

Co-authorship network of co-authors of Robert S. Raike

This figure shows the co-authorship network connecting the top 25 collaborators of Robert S. Raike. A scholar is included among the top collaborators of Robert S. Raike 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 Robert S. Raike. Robert S. Raike 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.
Thompson, John A., et al.. (2025). Unipolar recordings of beta power inform initial programming of the subthalamic nucleus in Parkinson's disease. Parkinsonism & Related Disorders. 141. 108078–108078.
2.
Stanslaski, Scott, Rebekah L. S. Summers, Lisa Tonder, et al.. (2024). Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease (ADAPT-PD) clinical trial. npj Parkinson s Disease. 10(1). 174–174. 26 indexed citations
3.
Kramer, Daniel R., et al.. (2024). Comparison of beta peak detection algorithms for data-driven deep brain stimulation programming strategies in Parkinson’s disease. npj Parkinson s Disease. 10(1). 150–150. 1 indexed citations
4.
5.
Wong, Joshua K., Wei Hu, Jon B. Toledo, et al.. (2023). Double blind, nonrandomized crossover study of active recharge biphasic deep brain stimulation for primary dystonia. Parkinsonism & Related Disorders. 109. 105328–105328. 1 indexed citations
6.
Ojemann, Steven, et al.. (2023). Pilot Study to Investigate the Use of In-Clinic Sensing to Identify Optimal Stimulation Parameters for Deep Brain Stimulation Therapy in Parkinson’s Disease. Neuromodulation Technology at the Neural Interface. 27(3). 509–519. 10 indexed citations
7.
Stanslaski, Scott, et al.. (2022). Long Term Performance of a Bi-Directional Neural Interface for Deep Brain Stimulation and Recording. Frontiers in Human Neuroscience. 16. 916627–916627. 6 indexed citations
8.
Jesus, Sol De, Michael S. Okun, Kelly D. Foote, et al.. (2019). Square Biphasic Pulse Deep Brain Stimulation for Parkinson’s Disease: The BiP-PD Study. Frontiers in Human Neuroscience. 13. 368–368. 12 indexed citations
9.
Almeida, Leonardo, Daniel Martínez-Ramírez, Bilal Ahmed, et al.. (2017). A pilot trial of square biphasic pulse deep brain stimulation for dystonia: The BIP dystonia study. Movement Disorders. 32(4). 615–618. 15 indexed citations
10.
Jesus, Sol De, Leonardo Almeida, Leili Shahgholi, et al.. (2017). Square biphasic pulse deep brain stimulation for essential tremor: The BiP tremor study. Parkinsonism & Related Disorders. 46. 41–46. 20 indexed citations
11.
Raike, Robert S., Ellen J. Hess, & Hyder A. Jinnah. (2015). Dystonia and cerebellar degeneration in the leaner mouse mutant. Brain Research. 1611. 56–64. 13 indexed citations
12.
Yu, Xin, Ann K. Heinzer, Xueliang Fan, et al.. (2015). A new knock-in mouse model of l-DOPA-responsive dystonia. Brain. 138(10). 2987–3002. 43 indexed citations
13.
Lentz, Linnea, et al.. (2015). Motor behaviors in the sheep evoked by electrical stimulation of the subthalamic nucleus. Experimental Neurology. 273. 69–82. 6 indexed citations
14.
Raike, Robert S., Carolyn Pizoli, Catherine J.C. Weisz, et al.. (2012). Limited regional cerebellar dysfunction induces focal dystonia in mice. Neurobiology of Disease. 49. 200–210. 55 indexed citations
15.
Raike, Robert S., Catherine J.C. Weisz, Freek E. Hoebeek, et al.. (2012). Stress, caffeine and ethanol trigger transient neurological dysfunction through shared mechanisms in a mouse calcium channelopathy. Neurobiology of Disease. 50. 151–159. 21 indexed citations
16.
Todorov, Boyan, Reinald Shyti, Elize D. Haasdijk, et al.. (2011). Purkinje Cell-Specific Ablation of CaV2.1 Channels is Sufficient to Cause Cerebellar Ataxia in Mice. The Cerebellum. 11(1). 246–258. 36 indexed citations
17.
Raike, Robert S., Holly Kordasiewicz, Randall M. Thompson, & Christopher M. Gómez. (2006). Dominant-negative suppression of Cav2.1 currents by α12.1 truncations requires the conserved interaction domain for β subunits. Molecular and Cellular Neuroscience. 34(2). 168–177. 22 indexed citations
18.
Raike, Robert S., H. A. Jinnah, & Ellen J. Hess. (2005). Animal models of generalized dystonia. PubMed. 2(3). 504–512. 56 indexed citations
19.
Weisz, Catherine J.C., et al.. (2005). Potassium Channel Blockers Inhibit the Triggers of Attacks in the Calcium Channel Mouse Mutanttottering. Journal of Neuroscience. 25(16). 4141–4145. 52 indexed citations
20.
Subramony, S. H., et al.. (2003). Novel CACNA1A mutation causes febrile episodic ataxia with interictal cerebellar deficits. Annals of Neurology. 54(6). 725–731. 31 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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