Maya Ringli

1.7k total citations
20 papers, 1.2k citations indexed

About

Maya Ringli is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Maya Ringli has authored 20 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Cognitive Neuroscience, 7 papers in Experimental and Cognitive Psychology and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Maya Ringli's work include Sleep and Wakefulness Research (19 papers), EEG and Brain-Computer Interfaces (14 papers) and Neural dynamics and brain function (8 papers). Maya Ringli is often cited by papers focused on Sleep and Wakefulness Research (19 papers), EEG and Brain-Computer Interfaces (14 papers) and Neural dynamics and brain function (8 papers). Maya Ringli collaborates with scholars based in Switzerland, United States and Germany. Maya Ringli's co-authors include Reto Huber, Salomé Kurth, Oskar G. Jenni, Anja Geiger, Monique K. LeBourgeois, Andreas Buchmann, Peter Achermann, Daniel Brandeis, Sara Fattinger and Ines Wilhelm and has published in prestigious journals such as Journal of Neuroscience, NeuroImage and Scientific Reports.

In The Last Decade

Maya Ringli

20 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
Maya Ringli Switzerland 17 1.1k 669 310 185 147 20 1.2k
Anja Geiger Switzerland 10 842 0.8× 659 1.0× 311 1.0× 98 0.5× 89 0.6× 10 1.0k
Dominik Philip Johannes Heib Austria 20 988 0.9× 517 0.8× 190 0.6× 127 0.7× 87 0.6× 35 1.2k
P Salzarulo Italy 17 627 0.6× 436 0.7× 302 1.0× 70 0.4× 45 0.3× 59 855
Masaki Nishida Japan 14 1.2k 1.1× 799 1.2× 229 0.7× 80 0.4× 173 1.2× 36 1.4k
Bengi Baran United States 16 806 0.7× 518 0.8× 130 0.4× 104 0.6× 100 0.7× 39 983
Kim E Ono United States 11 482 0.4× 266 0.4× 67 0.2× 99 0.5× 88 0.6× 20 771
Yolanda del Río‐Portilla Mexico 16 858 0.8× 367 0.5× 137 0.4× 44 0.2× 131 0.9× 35 1.0k
Valentina Gumenyuk United States 16 800 0.7× 432 0.6× 82 0.3× 119 0.6× 28 0.2× 28 1.0k
Debo Dong China 20 946 0.9× 329 0.5× 49 0.2× 247 1.3× 61 0.4× 58 1.3k
Julie M. Gottselig Switzerland 10 526 0.5× 360 0.5× 96 0.3× 33 0.2× 55 0.4× 11 934

Countries citing papers authored by Maya Ringli

Since Specialization
Citations

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

Fields of papers citing papers by Maya Ringli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Ringli

This figure shows the co-authorship network connecting the top 25 collaborators of Maya Ringli. A scholar is included among the top collaborators of Maya Ringli 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 Maya Ringli. Maya Ringli 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.
Maric, Angelina, Sophie Guéden, Gerhard Kurlemann, et al.. (2021). Altered EEG markers of synaptic plasticity in a human model of NMDA receptor deficiency: Anti-NMDA receptor encephalitis. NeuroImage. 239. 118281–118281. 9 indexed citations
2.
3.
Jaramillo, Valeria, Carina Volk, Maya Ringli, et al.. (2019). Sleep EEG slow-wave activity in medicated and unmedicated children and adolescents with attention-deficit/hyperactivity disorder. Translational Psychiatry. 9(1). 324–324. 26 indexed citations
4.
Bernardi, Giulio, Salomé Kurth, Maya Ringli, et al.. (2018). How do children fall asleep? A high-density EEG study of slow waves in the transition from wake to sleep. NeuroImage. 178. 23–35. 27 indexed citations
5.
Fattinger, Sara, Salomé Kurth, Maya Ringli, Oskar G. Jenni, & Reto Huber. (2017). Theta waves in children’s waking electroencephalogram resemble local aspects of sleep during wakefulness. Scientific Reports. 7(1). 11187–11187. 34 indexed citations
6.
Meyer‐Heim, Andreas, et al.. (2017). High-Density Electroencephalographic Recordings During Sleep in Children and Adolescents With Acquired Brain Injury. Neurorehabilitation and neural repair. 31(5). 462–474. 10 indexed citations
7.
Hedel, Hubertus J. A. van, et al.. (2016). High-density electroencephalographic recordings during sleep in children with disorders of consciousness. NeuroImage Clinical. 11. 468–475. 18 indexed citations
8.
Lustenberger, Caroline, Noemi Tesler, Salomé Kurth, et al.. (2016). Developmental trajectories of EEG sleep slow wave activity as a marker for motor skill development during adolescence: a pilot study. Developmental Psychobiology. 59(1). 5–14. 17 indexed citations
9.
Wilhelm, Ines, Salomé Kurth, Maya Ringli, et al.. (2014). Sleep Slow-Wave Activity Reveals Developmental Changes in Experience-Dependent Plasticity. Journal of Neuroscience. 34(37). 12568–12575. 76 indexed citations
10.
Bölsterli, Bigna K., Sara Fattinger, Salomé Kurth, et al.. (2014). Spike wave location and density disturb sleep slow waves in patients with CSWS (continuous spike waves during sleep). Epilepsia. 55(4). 584–591. 52 indexed citations
11.
Ringli, Maya, Salomé Kurth, Reto Huber, & Oskar G. Jenni. (2013). The sleep EEG topography in children and adolescents shows sex differences in language areas. International Journal of Psychophysiology. 89(2). 241–245. 16 indexed citations
12.
Ringli, Maya, et al.. (2012). Topography of sleep slow wave activity in children with attention-deficit/hyperactivity disorder. Cortex. 49(1). 340–347. 78 indexed citations
13.
Kurth, Salomé, Maya Ringli, Monique K. LeBourgeois, et al.. (2012). Mapping the electrophysiological marker of sleep depth reveals skill maturation in children and adolescents. NeuroImage. 63(2). 959–965. 85 indexed citations
14.
Geiger, Anja, Reto Huber, Salomé Kurth, et al.. (2011). Sleep electroencephalography topography and children’s intellectual ability. Neuroreport. 23(2). 93–97. 24 indexed citations
15.
Geiger, Anja, Reto Huber, Salomé Kurth, et al.. (2011). The Sleep EEG as a Marker of Intellectual Ability in School Age Children. SLEEP. 34(2). 181–189. 113 indexed citations
16.
Buchmann, Andreas, Salomé Kurth, Maya Ringli, et al.. (2011). Anatomical markers of sleep slow wave activity derived from structural magnetic resonance images. Journal of Sleep Research. 20(4). 506–513. 38 indexed citations
17.
Ringli, Maya & Reto Huber. (2011). Developmental aspects of sleep slow waves. Progress in brain research. 193. 63–82. 97 indexed citations
18.
Meyer, Martin, et al.. (2011). Long-term exposure to music enhances the sensitivity of the auditory system in children. European Journal of Neuroscience. 34(5). 755–765. 43 indexed citations
19.
Buchmann, Andreas, Maya Ringli, Salomé Kurth, et al.. (2010). EEG Sleep Slow-Wave Activity as a Mirror of Cortical Maturation. Cerebral Cortex. 21(3). 607–615. 198 indexed citations
20.
Kurth, Salomé, Maya Ringli, Anja Geiger, et al.. (2010). Mapping of Cortical Activity in the First Two Decades of Life: A High-Density Sleep Electroencephalogram Study. Journal of Neuroscience. 30(40). 13211–13219. 277 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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