Elı́as Manjarrez

1.9k total citations
72 papers, 1.5k citations indexed

About

Elı́as Manjarrez is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics. According to data from OpenAlex, Elı́as Manjarrez has authored 72 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Cognitive Neuroscience, 20 papers in Cellular and Molecular Neuroscience and 19 papers in Statistical and Nonlinear Physics. Recurrent topics in Elı́as Manjarrez's work include Neural dynamics and brain function (34 papers), stochastic dynamics and bifurcation (19 papers) and Ecosystem dynamics and resilience (11 papers). Elı́as Manjarrez is often cited by papers focused on Neural dynamics and brain function (34 papers), stochastic dynamics and bifurcation (19 papers) and Ecosystem dynamics and resilience (11 papers). Elı́as Manjarrez collaborates with scholars based in Mexico, Germany and Spain. Elı́as Manjarrez's co-authors include Ignacio Méndez‐Balbuena, Amira Flores, Agustín L. Herrera‐May, Óscar Arias-Carrión, Pedro J. García-Ramírez, L. A. Aguilera-Cortés, José Adán Miguel‐Puga, Sérgio Machado, Cláudio R. Mirasso and Rumyana Kristeva and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Elı́as Manjarrez

67 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Elı́as Manjarrez Mexico 20 817 327 324 261 200 72 1.5k
Brian N. Lundstrom United States 26 1.6k 2.0× 90 0.3× 430 1.3× 990 3.8× 183 0.9× 94 3.0k
Miguel Valencia Spain 32 2.1k 2.6× 150 0.5× 206 0.6× 1.4k 5.2× 89 0.4× 96 3.6k
Chi‐Sang Poon United States 30 1.1k 1.3× 509 1.6× 137 0.4× 340 1.3× 300 1.5× 136 3.3k
Roberto F. Galán United States 23 1.1k 1.4× 103 0.3× 473 1.5× 545 2.1× 100 0.5× 46 1.8k
Vernon L. Towle United States 30 2.0k 2.4× 161 0.5× 40 0.1× 716 2.7× 295 1.5× 97 3.2k
Lionel G. Nowak France 24 2.7k 3.4× 170 0.5× 196 0.6× 2.2k 8.3× 343 1.7× 41 3.5k
Victoria Booth United States 20 904 1.1× 72 0.2× 204 0.6× 521 2.0× 61 0.3× 80 1.2k
Thomas C. Ferrée United States 16 1.2k 1.5× 193 0.6× 50 0.2× 229 0.9× 224 1.1× 29 1.8k
Sarang S. Dalal United States 34 4.3k 5.2× 212 0.6× 82 0.3× 1.2k 4.6× 112 0.6× 62 4.9k
David B. Grayden Australia 36 3.3k 4.1× 297 0.9× 204 0.6× 1.7k 6.7× 738 3.7× 258 4.4k

Countries citing papers authored by Elı́as Manjarrez

Since Specialization
Citations

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

Fields of papers citing papers by Elı́as Manjarrez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elı́as Manjarrez

This figure shows the co-authorship network connecting the top 25 collaborators of Elı́as Manjarrez. A scholar is included among the top collaborators of Elı́as Manjarrez 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 Elı́as Manjarrez. Elı́as Manjarrez 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.
Manjarrez, Elı́as, et al.. (2024). Power spectral density and similarity analysis of COVID-19 mortality waves across countries. Heliyon. 10(15). e35546–e35546.
2.
Manjarrez, Elı́as, et al.. (2022). Absence of Neuroplastic Changes in the Bilateral H-Reflex Amplitude following Spinal Manipulation with Activator IV. Medicina. 58(11). 1521–1521. 1 indexed citations
3.
Manjarrez, Elı́as, et al.. (2021). Low-field thoracic magnetic stimulation increases peripheral oxygen saturation levels in coronavirus disease (COVID-19) patients. Medicine. 100(40). e27444–e27444. 1 indexed citations
4.
Manjarrez, Elı́as, et al.. (2021). Potential role of noise to improve intracortical microstimulation in tactile neuroprostheses. Neural Regeneration Research. 16(8). 1533–1533. 1 indexed citations
5.
6.
Méndez‐Balbuena, Ignacio, et al.. (2018). Augmenting EEG-global-coherence with auditory and visual noise. Medicine. 97(35). e12008–e12008. 10 indexed citations
7.
Canto-Bustos, Martha, Emanuel Loeza‐Alcocer, David Elı́as-Viñas, et al.. (2017). Tonically Active α5GABAA Receptors Reduce Motoneuron Excitability and Decrease the Monosynaptic Reflex. Frontiers in Cellular Neuroscience. 11. 283–283. 6 indexed citations
8.
Treviño, Mario, et al.. (2017). Optogenetic noise-photostimulation on the brain increases somatosensory spike firing responses. Neuroscience Letters. 664. 51–57. 15 indexed citations
9.
Flores, Amira, et al.. (2016). Stochastic resonance in the synaptic transmission between hair cells and vestibular primary afferents in development. Neuroscience. 322. 416–429. 21 indexed citations
10.
Flores, Gonzalo, et al.. (2015). Transition of pattern generation: The phenomenon of post-scratching locomotion. Neuroscience. 288. 156–166. 8 indexed citations
11.
Franco, Luis M., et al.. (2015). Differential frequency-dependent antidromic resonance of the Schaffer collaterals and mossy fibers. Brain Structure and Function. 221(4). 1793–1807. 5 indexed citations
12.
Herrera‐May, Agustín L., et al.. (2014). Improved Detection of Magnetic Signals by a MEMS Sensor Using Stochastic Resonance. PLoS ONE. 9(10). e109534–e109534. 5 indexed citations
13.
Linares, P., et al.. (2014). Spinal neurons bursting in phase with fictive scratching are not related to spontaneous cord dorsum potentials. Neuroscience. 266. 66–79. 3 indexed citations
14.
Trenado, Carlos, Elı́as Manjarrez, Ignacio Méndez‐Balbuena, et al.. (2014). Broad-band Gaussian noise is most effective in improving motor performance and is most pleasant. Frontiers in Human Neuroscience. 8. 22–22. 21 indexed citations
15.
Vázquez‐Roque, Rubén Antonio, Israel Camacho‐Abrego, Kurt L. Hoffman, et al.. (2014). Histological correlates of N40 auditory evoked potentials in adult rats after neonatal ventral hippocampal lesion: animal model of schizophrenia. Schizophrenia Research. 159(2-3). 450–457. 10 indexed citations
16.
Herrera‐May, Agustín L., et al.. (2013). Respiratory Magnetogram Detected with a MEMS Device. International Journal of Medical Sciences. 10(11). 1445–1450. 10 indexed citations
17.
Herrera‐May, Agustín L., et al.. (2010). Sistemas nanoelectromecánicos: origen, aplicaciones y desafíos. Interciencia. 35(3). 163–170. 1 indexed citations
18.
Manjarrez, Elı́as, et al.. (2007). Computing the center of mass for traveling alpha waves in the human brain. Brain Research. 1145. 239–247. 15 indexed citations
19.
Manjarrez, Elı́as, Pablo Balenzuela, Jordi García‐Ojalvo, et al.. (2006). Phantom reflexes: Muscle contractions at a frequency not physically present in the input stimuli. Biosystems. 90(2). 379–388. 6 indexed citations
20.
Manjarrez, Elı́as, et al.. (2002). Absence of coherence between cervical and lumbar spinal cord dorsal surface potentials in the anaesthetized cat. Neuroscience Letters. 328(1). 37–40. 7 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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