Sarah Hescham

1.0k total citations
31 papers, 737 citations indexed

About

Sarah Hescham is a scholar working on Neurology, Cellular and Molecular Neuroscience and Neurology. According to data from OpenAlex, Sarah Hescham has authored 31 papers receiving a total of 737 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Neurology, 19 papers in Cellular and Molecular Neuroscience and 14 papers in Neurology. Recurrent topics in Sarah Hescham's work include Neurological disorders and treatments (20 papers), Transcranial Magnetic Stimulation Studies (13 papers) and Neuroscience and Neural Engineering (13 papers). Sarah Hescham is often cited by papers focused on Neurological disorders and treatments (20 papers), Transcranial Magnetic Stimulation Studies (13 papers) and Neuroscience and Neural Engineering (13 papers). Sarah Hescham collaborates with scholars based in Netherlands, Germany and United States. Sarah Hescham's co-authors include Yasin Temel, Ali Jahanshahi, Arjan Blokland, Lee Wei Lim, Lauriston Kellaway, Kishor Bugarith, Polina Anikeeva, Vivienne A. Russell, Harry W.M. Steinbusch and Jos Prickaerts and has published in prestigious journals such as Nature Communications, Scientific Reports and Neuroscience & Biobehavioral Reviews.

In The Last Decade

Sarah Hescham

29 papers receiving 727 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sarah Hescham Netherlands 15 398 306 167 151 83 31 737
Martin T. Woodlee United States 12 227 0.6× 255 0.8× 125 0.7× 168 1.1× 81 1.0× 13 709
Katherine W. Scangos United States 11 353 0.9× 234 0.8× 625 3.7× 179 1.2× 109 1.3× 26 1.1k
Galit Pelled United States 21 473 1.2× 197 0.6× 348 2.1× 256 1.7× 166 2.0× 53 1.2k
Florian Klinker Germany 15 194 0.5× 140 0.5× 200 1.2× 314 2.1× 78 0.9× 25 711
Étienne Pralong Switzerland 20 868 2.2× 507 1.7× 362 2.2× 90 0.6× 232 2.8× 53 1.4k
Jacqueline R. Kane United States 8 229 0.6× 186 0.6× 93 0.6× 59 0.4× 51 0.6× 8 576
Mark R. Witcher United States 10 459 1.2× 112 0.4× 252 1.5× 170 1.1× 119 1.4× 33 793
Maxime Cazorla France 13 765 1.9× 202 0.7× 145 0.9× 81 0.5× 408 4.9× 16 1.1k
Nagheme Thomas United States 10 327 0.8× 94 0.3× 338 2.0× 267 1.8× 104 1.3× 24 868
Nobuhiko Hatanaka Japan 13 232 0.6× 199 0.7× 434 2.6× 145 1.0× 38 0.5× 29 693

Countries citing papers authored by Sarah Hescham

Since Specialization
Citations

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

Fields of papers citing papers by Sarah Hescham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sarah Hescham

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Hescham. A scholar is included among the top collaborators of Sarah Hescham 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 Sarah Hescham. Sarah Hescham 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.
Heidari, Hadi, et al.. (2025). Biocompatible PVDF Nanofibers with Embedded Magnetite Nanodiscs Enable Wireless Magnetoelectric Stimulation in Premotor Cortex. Advanced Healthcare Materials. 14(32). e03082–e03082. 2 indexed citations
2.
3.
Hescham, Sarah, et al.. (2023). Wireless stimulation of the subthalamic nucleus with nanoparticles modulates key monoaminergic systems similar to contemporary deep brain stimulation. Behavioural Brain Research. 444. 114363–114363. 7 indexed citations
4.
Hescham, Sarah, et al.. (2022). Magnetic nanomaterials for wireless thermal and mechanical neuromodulation. iScience. 25(11). 105401–105401. 14 indexed citations
5.
Temel, Yasin, et al.. (2022). High-frequency stimulation of the subthalamic nucleus induces a sustained inhibition of serotonergic system via loss of cell phenotype. Scientific Reports. 12(1). 14011–14011. 10 indexed citations
6.
Hescham, Sarah, Po‐Han Chiang, Danijela Gregureć, et al.. (2021). Magnetothermal nanoparticle technology alleviates parkinsonian-like symptoms in mice. Nature Communications. 12(1). 5569–5569. 85 indexed citations
7.
Hescham, Sarah & Yasin Temel. (2021). Electrical stimulation of the fornix for the treatment of brain diseases. Handbook of clinical neurology. 180. 447–454.
8.
Temel, Yasin, et al.. (2020). The effect of fornix deep brain stimulation in brain diseases. Cellular and Molecular Life Sciences. 77(17). 3279–3291. 17 indexed citations
9.
Hescham, Sarah, et al.. (2019). Progress in neuromodulation of the brain: A role for magnetic nanoparticles?. Progress in Neurobiology. 177. 1–14. 59 indexed citations
10.
Temel, Yasin, et al.. (2018). Fornix deep brain stimulation induces reduction of hippocampal synaptophysin levels. Journal of Chemical Neuroanatomy. 96. 34–40. 10 indexed citations
11.
Hescham, Sarah, et al.. (2018). Deep brain stimulation for Alzheimer's Disease: An update. Surgical Neurology International. 9(1). 58–58. 37 indexed citations
12.
Ackermans, Linda, Mayke Oosterloo, R. Jeroen Vermeulen, et al.. (2017). Infections in deep brain stimulation: Shaving versus not shaving. Surgical Neurology International. 8(1). 249–249. 8 indexed citations
13.
Hescham, Sarah, Ali Jahanshahi, Céline Mériaux, et al.. (2015). Behavioral effects of deep brain stimulation of different areas of the Papez circuit on memory- and anxiety-related functions. Behavioural Brain Research. 292. 353–360. 29 indexed citations
14.
Kocabıçak, Ersoy, et al.. (2014). Deep brain stimulation of the rat subthalamic nucleus induced inhibition of median raphe serotonergic and dopaminergic neurotransmission. Turkish Neurosurgery. 25(5). 721–7. 14 indexed citations
15.
Hescham, Sarah, Bryan A. Adriaanse, Harry W.M. Steinbusch, et al.. (2014). Increased number of TH-immunoreactive cells in the ventral tegmental area after deep brain stimulation of the anterior nucleus of the thalamus. Brain Structure and Function. 220(5). 3061–3066. 12 indexed citations
16.
Jahanshahi, Ali, Marcus L.F. Janssen, Sarah Hescham, et al.. (2013). Electrical stimulation of the motor cortex enhances progenitor cell migration in the adult rat brain. Experimental Brain Research. 231(2). 165–177. 26 indexed citations
17.
Hescham, Sarah, Lee Wei Lim, Ali Jahanshahi, Arjan Blokland, & Yasin Temel. (2013). Deep brain stimulation in dementia-related disorders. Neuroscience & Biobehavioral Reviews. 37(10). 2666–2675. 55 indexed citations
18.
Hescham, Sarah, Lee Wei Lim, Ali Jahanshahi, et al.. (2012). Deep brain stimulation of the forniceal area enhances memory functions in experimental dementia: The role of stimulation parameters. Brain stimulation. 6(1). 72–77. 88 indexed citations
19.
Temel, Yasin, Sarah Hescham, Ali Jahanshahi, et al.. (2012). Neuromodulation in Psychiatric Disorders. International review of neurobiology. 107. 283–314. 28 indexed citations
20.
Hescham, Sarah, et al.. (2009). Effect of exercise on learning and memory in a rat model of developmental stress. Metabolic Brain Disease. 24(4). 643–657. 65 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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