Francisco J. Vico

648 total citations
36 papers, 381 citations indexed

About

Francisco J. Vico is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Social Psychology. According to data from OpenAlex, Francisco J. Vico has authored 36 papers receiving a total of 381 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 10 papers in Artificial Intelligence and 8 papers in Social Psychology. Recurrent topics in Francisco J. Vico's work include Neural dynamics and brain function (8 papers), Evolutionary Algorithms and Applications (7 papers) and Music Therapy and Health (7 papers). Francisco J. Vico is often cited by papers focused on Neural dynamics and brain function (8 papers), Evolutionary Algorithms and Applications (7 papers) and Music Therapy and Health (7 papers). Francisco J. Vico collaborates with scholars based in Spain, United States and Italy. Francisco J. Vico's co-authors include Daniel Lobo, Alfredo Raglio, Gualberto Buela‐Casal, Alejandro de la Torre‐Luque, Rafael A. Caparrós-González, María V. Sánchez-Vives, Francisco J. Veredas, Carolina Díaz-Piedra, J.M. Bravo and Mel Slater and has published in prestigious journals such as PLoS ONE, The Journal of Physiology and Frontiers in Psychology.

In The Last Decade

Francisco J. Vico

30 papers receiving 362 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francisco J. Vico Spain 14 135 92 49 38 37 36 381
WALTER E. DANDY United States 6 99 0.7× 20 0.2× 45 0.9× 64 1.7× 13 0.4× 9 444
Xinnian Chen United States 14 141 1.0× 67 0.7× 69 1.4× 88 2.3× 7 0.2× 30 778
Shinobu Masaki Japan 13 300 2.2× 51 0.6× 6 0.1× 10 0.3× 34 0.9× 50 910
Emi Nishina Japan 10 292 2.2× 93 1.0× 7 0.1× 27 0.7× 18 0.5× 27 484
Emily Allen United States 12 457 3.4× 29 0.3× 32 0.7× 26 0.7× 76 2.1× 25 630
Jacqueline Walker Ireland 9 74 0.5× 14 0.2× 11 0.2× 36 0.9× 39 1.1× 32 371
Jasper H. Fabius Netherlands 10 327 2.4× 84 0.9× 32 0.7× 17 0.4× 27 0.7× 25 576
Benjamin G. Schultz Netherlands 12 270 2.0× 82 0.9× 4 0.1× 12 0.3× 27 0.7× 28 439
Daniel Hannon United States 9 469 3.5× 80 0.9× 58 1.2× 38 1.0× 109 2.9× 29 720
Tien-Lin Wu Taiwan 5 846 6.3× 82 0.9× 7 0.1× 31 0.8× 79 2.1× 7 975

Countries citing papers authored by Francisco J. Vico

Since Specialization
Citations

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

Fields of papers citing papers by Francisco J. Vico

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francisco J. Vico. 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 Francisco J. Vico. The network helps show where Francisco J. Vico may publish in the future.

Co-authorship network of co-authors of Francisco J. Vico

This figure shows the co-authorship network connecting the top 25 collaborators of Francisco J. Vico. A scholar is included among the top collaborators of Francisco J. Vico 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 Francisco J. Vico. Francisco J. Vico 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.
Raglio, Alfredo, et al.. (2021). Using Formal Grammars as Musical Genome. Applied Sciences. 11(9). 4151–4151. 3 indexed citations
2.
Raglio, Alfredo, Paola Baiardi, Giuseppe Vizzari, et al.. (2021). Algorithmic Music for Therapy: Effectiveness and Perspectives. Applied Sciences. 11(19). 8833–8833. 8 indexed citations
3.
Raglio, Alfredo, Daniele Bellandi, Marta Gianotti, et al.. (2019). Daily music listening to reduce work-related stress: a randomized controlled pilot trial. Journal of Public Health. 42(1). e81–e87. 24 indexed citations
4.
Raglio, Alfredo, Marcello Imbriani, Paola Baiardi, et al.. (2019). Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial. Computer Methods and Programs in Biomedicine. 185. 105160–105160. 22 indexed citations
5.
Vico, Francisco J., et al.. (2019). A CODING CURRICULUM FOR K-12 EDUCATION: THE EVIDENCE-BASED APPROACH. EDULEARN proceedings. 1. 7102–7106. 6 indexed citations
6.
Raglio, Alfredo & Francisco J. Vico. (2017). Music and Technology: The Curative Algorithm. Frontiers in Psychology. 8. 2055–2055. 15 indexed citations
7.
Caparrós-González, Rafael A., Alejandro de la Torre‐Luque, Carolina Díaz-Piedra, Francisco J. Vico, & Gualberto Buela‐Casal. (2017). Listening to Relaxing Music Improves Physiological Responses in Premature Infants. Advances in Neonatal Care. 18(1). 58–69. 34 indexed citations
8.
Torre‐Luque, Alejandro de la, et al.. (2016). Acute stress recovery through listening to Melomics relaxing music: A randomized controlled trial. Nordic Journal of Music Therapy. 26(2). 124–141. 32 indexed citations
9.
Amos, Martyn, Susan Stepney, René Doursat, Francisco J. Vico, & Steen Rasmussen. (2012). TRUCE: A Coordination Action for Unconventional Computation. International journal of unconventional computing. 8(4). 333–337. 2 indexed citations
10.
Vico, Francisco J., et al.. (2012). Complex and diverse morphologies can develop from a minimal genomic model. Repositorio Institucional de la Universidad de Málaga (University of Málaga). 553–560.
11.
Lobo, Daniel, Francisco J. Vico, & Jürgen Dassow. (2011). Graph grammars with string-regulated rewriting. Theoretical Computer Science. 412(43). 6101–6111. 13 indexed citations
12.
Vico, Francisco J., et al.. (2011). Automating the search of molecular motor templates by evolutionary methods. Biosystems. 106(2-3). 82–93. 3 indexed citations
13.
Lobo, Daniel & Francisco J. Vico. (2010). Evolution of form and function in a model of differentiated multicellular organisms with gene regulatory networks. Biosystems. 102(2-3). 112–123. 14 indexed citations
14.
Lobo, Daniel & Francisco J. Vico. (2010). Evolutionary development of tensegrity structures. Biosystems. 101(3). 167–176. 15 indexed citations
15.
Narváez, José Ángel, et al.. (2007). Robust Off- and Online Separation of Intracellularly Recorded Up and Down Cortical States. PLoS ONE. 2(9). e888–e888. 30 indexed citations
16.
Lendínez, Francisco, et al.. (2006). Serum Transferrin Receptor in Children: Usefulness for Determinating the Nature of Anemia in Infection. Journal of Pediatric Hematology/Oncology. 28(12). 809–815. 29 indexed citations
17.
Veredas, Francisco J., Francisco J. Vico, & José‐Manuel Alonso. (2004). A computational tool to simulate correlated activity in neural circuits. Journal of Neuroscience Methods. 136(1). 23–32. 1 indexed citations
18.
Vico, Francisco J., et al.. (2002). A connectionist model for local speed estimation. 2. 262–266. 1 indexed citations
19.
Vico, Francisco J., et al.. (1999). Automatic design synthesis with artificial intelligence techniques. Artificial Intelligence in Engineering. 13(3). 251–256. 13 indexed citations
20.
Bandera, César, et al.. (1996). Residual Q-Learning Applied to Visual Attention. International Conference on Machine Learning. 20–27. 18 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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