Mya C. Schiess

3.0k total citations · 1 hit paper
72 papers, 1.6k citations indexed

About

Mya C. Schiess is a scholar working on Neurology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Mya C. Schiess has authored 72 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Neurology, 20 papers in Cellular and Molecular Neuroscience and 16 papers in Cognitive Neuroscience. Recurrent topics in Mya C. Schiess's work include Parkinson's Disease Mechanisms and Treatments (40 papers), Neurological disorders and treatments (21 papers) and Botulinum Toxin and Related Neurological Disorders (11 papers). Mya C. Schiess is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (40 papers), Neurological disorders and treatments (21 papers) and Botulinum Toxin and Related Neurological Disorders (11 papers). Mya C. Schiess collaborates with scholars based in United States, Italy and Germany. Mya C. Schiess's co-authors include Albert J. Fenoy, Vicki M. Soukup, Jessika Suescun, Ashley J. Hood, Haring J. W. Nauta, Timothy M. Ellmore, Anne B. Sereno, Zheng He, Roger J. Bick and Erin Furr‐Stimming and has published in prestigious journals such as PLoS ONE, Neurology and Scientific Reports.

In The Last Decade

Mya C. Schiess

69 papers receiving 1.6k citations

Hit Papers

Fecal microbiota transplantation in Parkinson's disease—A... 2023 2026 2024 2025 2023 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mya C. Schiess United States 24 1.0k 420 378 203 197 72 1.6k
Yasushi Shimo Japan 22 943 0.9× 450 1.1× 392 1.0× 254 1.3× 210 1.1× 90 1.8k
Fumihito Yoshii Japan 24 693 0.7× 291 0.7× 520 1.4× 202 1.0× 266 1.4× 92 1.8k
Darrin J. Lee United States 24 912 0.9× 746 1.8× 560 1.5× 320 1.6× 141 0.7× 80 1.8k
Katia Longo Italy 30 2.0k 1.9× 420 1.0× 494 1.3× 238 1.2× 164 0.8× 58 2.5k
Bertrand Degos France 29 1.3k 1.3× 976 2.3× 430 1.1× 354 1.7× 284 1.4× 96 2.3k
Martin Südmeyer Germany 30 1.4k 1.4× 560 1.3× 727 1.9× 380 1.9× 183 0.9× 88 2.4k
Francesca Assogna Italy 26 967 0.9× 240 0.6× 485 1.3× 160 0.8× 131 0.7× 55 1.8k
Katie Kompoliti United States 24 979 0.9× 521 1.2× 234 0.6× 179 0.9× 223 1.1× 56 1.9k
S. J. Huber United States 20 1.7k 1.6× 506 1.2× 381 1.0× 179 0.9× 164 0.8× 31 2.2k
Amit Batla United Kingdom 23 843 0.8× 429 1.0× 292 0.8× 218 1.1× 153 0.8× 60 1.5k

Countries citing papers authored by Mya C. Schiess

Since Specialization
Citations

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

Fields of papers citing papers by Mya C. Schiess

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mya C. Schiess. 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 Mya C. Schiess. The network helps show where Mya C. Schiess may publish in the future.

Co-authorship network of co-authors of Mya C. Schiess

This figure shows the co-authorship network connecting the top 25 collaborators of Mya C. Schiess. A scholar is included among the top collaborators of Mya C. Schiess 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 Mya C. Schiess. Mya C. Schiess 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
3.
Schiess, Mya C., et al.. (2024). Role of alpha-synuclein seed amplification assay in Parkinson’s disease clinical trials: A case of misdiagnosis. Clinical Parkinsonism & Related Disorders. 11. 100274–100274. 2 indexed citations
4.
Adams, Christopher, et al.. (2023). Updated Parkinson's disease motor subtypes classification and correlation to cerebrospinal homovanillic acid and 5-hydroxyindoleacetic acid levels. Clinical Parkinsonism & Related Disorders. 8. 100187–100187. 10 indexed citations
5.
Ellmore, Timothy M., Jessika Suescun, Richard J. Castriotta, & Mya C. Schiess. (2020). A Study of the Relationship Between Uric Acid and Substantia Nigra Brain Connectivity in Patients With REM Sleep Behavior Disorder and Parkinson's Disease. Frontiers in Neurology. 11. 815–815. 17 indexed citations
6.
Schiess, Mya C., Sam Eldabe, Peter E. Konrad, et al.. (2020). Intrathecal Baclofen for Severe Spasticity: Longitudinal Data From the Product Surveillance Registry. Neuromodulation Technology at the Neural Interface. 23(7). 996–1002. 19 indexed citations
7.
DuPont, Herbert L., Jessika Suescun, Zhi‐Dong Jiang, et al.. (2020). Microbiome characterization and reversal of dysbiosis in Parkinson’s disease by Fecal Microbiota Transplantation (1825). Neurology. 94(15_supplement). 3 indexed citations
8.
Barman, Arko, et al.. (2019). Quantifying Neurodegenerative Progression With DeepSymNet, an End-to-End Data-Driven Approach. Frontiers in Neuroscience. 13. 1053–1053. 8 indexed citations
9.
Reddy, Sujan, Albert J. Fenoy, Erin Furr‐Stimming, Mya C. Schiess, & Raja Mehanna. (2016). Does the Use of Intraoperative Microelectrode Recording Influence the Final Location of Lead Implants in the Ventral Intermediate Nucleus for Deep Brain Stimulation?. The Cerebellum. 16(2). 421–426. 6 indexed citations
10.
Riecke, Jenny, Chunyan Cai, Farhaan Vahidy, et al.. (2015). A Meta-Analysis of Mesenchymal Stem Cells in Animal Models of Parkinson's Disease. Stem Cells and Development. 24(18). 2082–2090. 25 indexed citations
11.
Gayed, Isis, et al.. (2015). The Impact of DaTscan in the Diagnosis of Parkinson Disease. Clinical Nuclear Medicine. 40(5). 390–393. 23 indexed citations
12.
Doursout, Marie–Françoise, et al.. (2013). Inflammatory Cells and Cytokines in the Olfactory Bulb of a Rat Model of Neuroinflammation; Insights into Neurodegeneration?. Journal of Interferon & Cytokine Research. 33(7). 376–383. 21 indexed citations
14.
Ellmore, Timothy M., Qiaoli Liang, Jessika Suescun, et al.. (2012). Region of Interest Measurements of Structural Volumes in Patients with Parkinson's Disease, Atypical Parkinsonism, and REM Sleep Behavior Disorder: Baseline Measurements from a Prospective Longitudinal Study (P06.076). Neurology. 78(Meeting Abstracts 1). P06.076–P06.076. 1 indexed citations
16.
Hood, Ashley J., et al.. (2006). Levodopa slows prosaccades and improves antisaccades: an eye movement study in Parkinson's disease. Journal of Neurology Neurosurgery & Psychiatry. 78(6). 565–570. 122 indexed citations
17.
Hood, Ashley J., et al.. (2005). Dissociating cognitive deficits involved in voluntary eye movement dysfunctions in Parkinson's disease patients. Neuropsychologia. 44(8). 1475–1482. 66 indexed citations
18.
Bick, Roger J., Brian J. Poindexter, & Mya C. Schiess. (2004). Localization of calcitonin gene-related peptide in cardiomyocytes: comparison of neonatal and dedifferentiating cells to adult myocytes. Peptides. 26(2). 331–336. 8 indexed citations
19.
Schiess, Mya C., et al.. (2000). Parkinson's disease subtypes: clinical classification and ventricular cerebrospinal fluid analysis. Parkinsonism & Related Disorders. 6(2). 69–76. 146 indexed citations
20.
Soukup, Vicki M., et al.. (1997). Cognitive Sequelae of Unilateral Posteroventral Pallidotomy. Archives of Neurology. 54(8). 947–950. 60 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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