Salva Ardid

1.8k total citations
21 papers, 818 citations indexed

About

Salva Ardid is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, Salva Ardid has authored 21 papers receiving a total of 818 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 6 papers in Cellular and Molecular Neuroscience and 1 paper in Molecular Biology. Recurrent topics in Salva Ardid's work include Neural dynamics and brain function (18 papers), Neural and Behavioral Psychology Studies (10 papers) and Memory and Neural Mechanisms (6 papers). Salva Ardid is often cited by papers focused on Neural dynamics and brain function (18 papers), Neural and Behavioral Psychology Studies (10 papers) and Memory and Neural Mechanisms (6 papers). Salva Ardid collaborates with scholars based in United States, Canada and Spain. Salva Ardid's co-authors include Thilo Womelsdorf, Xiao‐Jing Wang, Stephanie Westendorff, Mariann Oemisch, Paul Tiesinga, Seyed A. Hassani, Matthijs A. A. van der Meer, Albert Compte, Stefan Everling and Daniel Kaping and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

Salva Ardid

19 papers receiving 812 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Salva Ardid United States 12 490 211 117 53 40 21 818
Stephanie E. Palmer United States 14 471 1.0× 197 0.9× 140 1.2× 89 1.7× 26 0.7× 36 773
Stephanie Westendorff Germany 12 475 1.0× 132 0.6× 99 0.8× 39 0.7× 37 0.9× 21 841
Mariann Oemisch Canada 9 159 0.3× 112 0.5× 105 0.9× 26 0.5× 40 1.0× 10 525
Jeannette A. M. Lorteije Netherlands 15 593 1.2× 223 1.1× 117 1.0× 37 0.7× 10 0.3× 22 852
Paul Patton United States 14 263 0.5× 163 0.8× 51 0.4× 99 1.9× 23 0.6× 32 940
Robert A. A. Campbell United States 19 316 0.6× 407 1.9× 188 1.6× 38 0.7× 19 0.5× 36 1.1k
Robert J. Schafer United States 15 687 1.4× 153 0.7× 214 1.8× 15 0.3× 87 2.2× 32 1.1k
Fredrik Johansson Sweden 15 231 0.5× 170 0.8× 230 2.0× 22 0.4× 139 3.5× 22 779
Ahmed El Hady United States 10 147 0.3× 145 0.7× 81 0.7× 24 0.5× 25 0.6× 16 418
Xiaochen Sun China 13 184 0.4× 220 1.0× 183 1.6× 108 2.0× 66 1.6× 24 677

Countries citing papers authored by Salva Ardid

Since Specialization
Citations

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

Fields of papers citing papers by Salva Ardid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salva Ardid

This figure shows the co-authorship network connecting the top 25 collaborators of Salva Ardid. A scholar is included among the top collaborators of Salva Ardid 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 Salva Ardid. Salva Ardid 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.
Ardid, Salva, et al.. (2023). Dark matter search towards the Sun using Machine Learning reconstructions of single-line events in ANTARES. RiuNet (Politechnical University of Valencia). 1443–1443.
2.
Haß, Joachim, Salva Ardid, Jason Sherfey, & Nancy Kopell. (2022). Constraints on persistent activity in a biologically detailed network model of the prefrontal cortex with heterogeneities. Progress in Neurobiology. 215. 102287–102287. 3 indexed citations
3.
Ardid, Salva, Susanna Marquez, & M. Ardid. (2021). USE OF SOUND RECORDINGS AND ANALYSIS FOR PHYSICS LAB PRACTICES. INTED proceedings. 1. 7687–7693. 1 indexed citations
4.
5.
Sherfey, Jason, Salva Ardid, Earl K. Miller, Michael E. Hasselmo, & Nancy Kopell. (2020). Prefrontal oscillations modulate the propagation of neuronal activity required for working memory. Neurobiology of Learning and Memory. 173. 107228–107228. 16 indexed citations
6.
Ardid, Salva, Jason Sherfey, Michelle M. McCarthy, et al.. (2019). Biased competition in the absence of input bias revealed through corticostriatal computation. Proceedings of the National Academy of Sciences. 116(17). 8564–8569. 10 indexed citations
7.
Oemisch, Mariann, Stephanie Westendorff, Seyed A. Hassani, et al.. (2019). Feature-specific prediction errors and surprise across macaque fronto-striatal circuits. Nature Communications. 10(1). 176–176. 39 indexed citations
8.
Sherfey, Jason, Salva Ardid, Joachim Haß, Michael E. Hasselmo, & Nancy Kopell. (2018). Flexible resonance in prefrontal networks with strong feedback inhibition. PLoS Computational Biology. 14(8). e1006357–e1006357. 18 indexed citations
9.
Sherfey, Jason, et al.. (2018). DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation. Frontiers in Neuroinformatics. 12. 10–10. 32 indexed citations
10.
Hassani, Seyed A., Mariann Oemisch, Stephanie Westendorff, et al.. (2017). A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque. Scientific Reports. 7(1). 40606–40606. 326 indexed citations
11.
Ardid, Salva, et al.. (2015). Mapping of Functionally Characterized Cell Classes onto Canonical Circuit Operations in Primate Prefrontal Cortex. Journal of Neuroscience. 35(7). 2975–2991. 67 indexed citations
12.
Ardid, Salva, et al.. (2015). Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness. Journal of Cognitive Neuroscience. 28(2). 333–349. 15 indexed citations
13.
Womelsdorf, Thilo, Salva Ardid, Stefan Everling, & Taufik A. Valiante. (2014). Burst Firing Synchronizes Prefrontal and Anterior Cingulate Cortex during Attentional Control. Current Biology. 24(22). 2613–2621. 71 indexed citations
14.
15.
Ardid, Salva & Xiao‐Jing Wang. (2014). The “tweaking principle” for task switching. BMC Neuroscience. 15(S1). 1 indexed citations
16.
Womelsdorf, Thilo, Stephanie Westendorff, & Salva Ardid. (2013). Subnetwork selection in deep cortical layers is mediated by beta-oscillation dependent firing. Frontiers in Systems Neuroscience. 7. 25–25. 2 indexed citations
17.
Ardid, Salva & Xiao‐Jing Wang. (2013). A Tweaking Principle for Executive Control: Neuronal Circuit Mechanism for Rule-Based Task Switching and Conflict Resolution. Journal of Neuroscience. 33(50). 19504–19517. 28 indexed citations
18.
Murray, John D. & Salva Ardid. (2011). What Can Tracking Fluctuations in Dozens of Sensory Neurons Tell about Selective Attention?. Frontiers in Systems Neuroscience. 5. 35–35. 3 indexed citations
19.
Ardid, Salva, Xiao‐Jing Wang, David Gómez-Cabrero, & Albert Compte. (2010). Reconciling Coherent Oscillation with Modulationof Irregular Spiking Activity in Selective Attention:Gamma-Range Synchronization between Sensoryand Executive Cortical Areas. Journal of Neuroscience. 30(8). 2856–2870. 52 indexed citations
20.
Ardid, Salva, Xiao‐Jing Wang, & Albert Compte. (2007). An Integrated Microcircuit Model of Attentional Processing in the Neocortex. Journal of Neuroscience. 27(32). 8486–8495. 85 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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