Scott Stanslaski

1.7k total citations
36 papers, 1.2k citations indexed

About

Scott Stanslaski is a scholar working on Cellular and Molecular Neuroscience, Neurology and Cognitive Neuroscience. According to data from OpenAlex, Scott Stanslaski has authored 36 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Cellular and Molecular Neuroscience, 28 papers in Neurology and 22 papers in Cognitive Neuroscience. Recurrent topics in Scott Stanslaski's work include Neuroscience and Neural Engineering (34 papers), Neurological disorders and treatments (27 papers) and EEG and Brain-Computer Interfaces (21 papers). Scott Stanslaski is often cited by papers focused on Neuroscience and Neural Engineering (34 papers), Neurological disorders and treatments (27 papers) and EEG and Brain-Computer Interfaces (21 papers). Scott Stanslaski collaborates with scholars based in United States, United Kingdom and Ireland. Scott Stanslaski's co-authors include Timothy Denison, Paul H. Stypulkowski, Randy Jensen, Peng Cong, Pedram Afshar, Al-Thaddeus Avestruz, Jonathon E. Giftakis, Wesley Santa, David Carlson and Gregory F. Molnar and has published in prestigious journals such as Neurology, Journal of Neurophysiology and Brain Research.

In The Last Decade

Scott Stanslaski

35 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Scott Stanslaski United States 16 943 757 581 168 161 36 1.2k
Chadwick Boulay Canada 10 557 0.6× 456 0.6× 730 1.3× 137 0.8× 84 0.5× 20 1.1k
Ro’ee Gilron United States 15 549 0.6× 710 0.9× 378 0.7× 33 0.2× 60 0.4× 22 912
Gregory F. Molnar United States 14 403 0.4× 441 0.6× 266 0.5× 35 0.2× 113 0.7× 24 739
Peng Cong United States 12 477 0.5× 336 0.4× 310 0.5× 106 0.6× 154 1.0× 30 698
Mattia Arlotti Italy 12 528 0.6× 449 0.6× 413 0.7× 24 0.1× 100 0.6× 17 952
Alexis M. Kuncel United States 10 730 0.8× 759 1.0× 246 0.4× 48 0.3× 56 0.3× 12 916
David J. Guggenmos United States 13 432 0.5× 120 0.2× 400 0.7× 166 1.0× 165 1.0× 36 686
Bryan Lad Howell United States 20 488 0.5× 542 0.7× 321 0.6× 43 0.3× 143 0.9× 32 904
Nicholas L. Opie Australia 16 446 0.5× 142 0.2× 391 0.7× 181 1.1× 150 0.9× 45 743
Gábor Kozák Hungary 11 364 0.4× 142 0.2× 448 0.8× 42 0.3× 122 0.8× 20 805

Countries citing papers authored by Scott Stanslaski

Since Specialization
Citations

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

Fields of papers citing papers by Scott Stanslaski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Scott Stanslaski

This figure shows the co-authorship network connecting the top 25 collaborators of Scott Stanslaski. A scholar is included among the top collaborators of Scott Stanslaski 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 Scott Stanslaski. Scott Stanslaski 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.
Hageman, Kristin N., Paul H. Stypulkowski, & Scott Stanslaski. (2024). Characterization of subthalamic nucleus deep brain stimulation evoked resonant neural activity in a large animal model: A pilot study. Brain Research. 1846. 149233–149233.
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.
4.
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
5.
Goyal, Abhinav, Scott Stanslaski, Yoonbae Oh, et al.. (2020). The development of an implantable deep brain stimulation device with simultaneous chronic electrophysiological recording and stimulation in humans. Biosensors and Bioelectronics. 176. 112888–112888. 66 indexed citations
6.
Pulliam, Christopher L., Scott Stanslaski, & Timothy Denison. (2020). Industrial perspectives on brain-computer interface technology. Handbook of clinical neurology. 168. 341–352. 14 indexed citations
7.
Herron, Jeffrey A., et al.. (2018). Embedding adaptive stimulation algorithms for a new implantable deep-brain stimulation research tool. 32. 1–4. 4 indexed citations
8.
Stanslaski, Scott, Jeffrey A. Herron, Enrico Opri, et al.. (2018). Creating neural “co-processors” to explore treatments for neurological disorders. 4 indexed citations
9.
Stypulkowski, Paul H., Scott Stanslaski, & Jonathon E. Giftakis. (2017). Modulation of hippocampal activity with fornix Deep Brain Stimulation. Brain stimulation. 10(6). 1125–1132. 24 indexed citations
10.
11.
Connolly, Allison T., Abirami Muralidharan, Claudia Hendrix, et al.. (2015). Local field potential recordings in a non-human primate model of Parkinsons disease using the Activa PC + S neurostimulator. Journal of Neural Engineering. 12(6). 66012–66012. 31 indexed citations
12.
Ryapolova-Webb, Elena, Pedram Afshar, Scott Stanslaski, et al.. (2014). Chronic cortical and electromyographic recordings from a fully implantable device: preclinical experience in a nonhuman primate. Journal of Neural Engineering. 11(1). 16009–16009. 47 indexed citations
13.
Lipski, Witold, Scott Stanslaski, Arun Antony, et al.. (2014). Sensing-enabled hippocampal deep brain stimulation in idiopathic nonhuman primate epilepsy. Journal of Neurophysiology. 113(4). 1051–1062. 10 indexed citations
14.
Stypulkowski, Paul H., Scott Stanslaski, Randy Jensen, Timothy Denison, & Jonathon E. Giftakis. (2014). Brain Stimulation for Epilepsy – Local and Remote Modulation of Network Excitability. Brain stimulation. 7(3). 350–358. 67 indexed citations
15.
16.
Stypulkowski, Paul H., Scott Stanslaski, Timothy Denison, & Jonathon E. Giftakis. (2013). Chronic Evaluation of a Clinical System for Deep Brain Stimulation and Recording of Neural Network Activity. Stereotactic and Functional Neurosurgery. 91(4). 220–232. 49 indexed citations
17.
Stanslaski, Scott, Pedram Afshar, Peng Cong, et al.. (2012). Design and Validation of a Fully Implantable, Chronic, Closed-Loop Neuromodulation Device With Concurrent Sensing and Stimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 20(4). 410–421. 230 indexed citations
18.
Rouse, Adam G., Scott Stanslaski, Peng Cong, et al.. (2011). A chronic generalized bi-directional brain–machine interface. Journal of Neural Engineering. 8(3). 36018–36018. 117 indexed citations
19.
Stanslaski, Scott, et al.. (2011). Emerging technology for advancing the treatment of epilepsy using a dynamic control framework. PubMed. 2011. 753–756. 3 indexed citations
20.
Stanslaski, Scott, Peng Cong, David Carlson, et al.. (2009). An implantable Bi-directional brain-machine interface system for chronic neuroprosthesis research. PubMed. 1 3. 5494–5497. 40 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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