Alfred B. Yu

1.5k total citations · 1 hit paper
17 papers, 837 citations indexed

About

Alfred B. Yu is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Developmental and Educational Psychology. According to data from OpenAlex, Alfred B. Yu has authored 17 papers receiving a total of 837 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 5 papers in Experimental and Cognitive Psychology and 5 papers in Developmental and Educational Psychology. Recurrent topics in Alfred B. Yu's work include Neural dynamics and brain function (5 papers), Child and Animal Learning Development (5 papers) and Neuroscience and Neural Engineering (4 papers). Alfred B. Yu is often cited by papers focused on Neural dynamics and brain function (5 papers), Child and Animal Learning Development (5 papers) and Neuroscience and Neural Engineering (4 papers). Alfred B. Yu collaborates with scholars based in United States. Alfred B. Yu's co-authors include Jean M. Vettel, Danielle S. Bassett, Scott T. Grafton, Ari E. Kahn, Fabio Pasqualetti, Matthew Cieslak, Qawi K. Telesford, Shi Gu, Michael B. Miller and John D. Medaglia and has published in prestigious journals such as Nature Communications, Journal of Experimental Psychology Human Perception & Performance and Memory & Cognition.

In The Last Decade

Alfred B. Yu

16 papers receiving 829 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Controllability of structural brain networks

2015 536 citations Shi Gu, Fabio Pasqualetti et al. Nature Communications profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Alfred B. Yu	535	150	143	101	72	17	837
Mukesh Dhamala	907 1.7×	113 0.8×	161 1.1×	152 1.5×	111 1.5×	52	1.1k
Stavros I. Dimitriadis	1.5k 2.8×	92 0.6×	255 1.8×	202 2.0×	73 1.0×	72	1.8k
Thomas F. Collura	1.2k 2.3×	67 0.4×	71 0.5×	114 1.1×	182 2.5×	43	1.4k
Andreas Spiegler	1.2k 2.2×	95 0.6×	354 2.5×	73 0.7×	186 2.6×	23	1.3k
Jérémie Lefebvre	681 1.3×	129 0.9×	85 0.6×	24 0.2×	254 3.5×	50	931
Juliane Britz	1.9k 3.5×	89 0.6×	138 1.0×	236 2.3×	88 1.2×	28	2.0k
Simo Monto	1.4k 2.5×	46 0.3×	112 0.8×	131 1.3×	176 2.4×	15	1.5k
Lihui Cai	575 1.1×	75 0.5×	37 0.3×	49 0.5×	69 1.0×	35	742
Vadim V. Nikouline	1.4k 2.5×	454 3.0×	82 0.6×	100 1.0×	191 2.7×	15	1.6k

Countries citing papers authored by Alfred B. Yu

Since Specialization

Citations

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

Fields of papers citing papers by Alfred B. Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alfred B. Yu. 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 Alfred B. Yu. The network helps show where Alfred B. Yu may publish in the future.

Co-authorship network of co-authors of Alfred B. Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Alfred B. Yu. A scholar is included among the top collaborators of Alfred B. Yu 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 Alfred B. Yu. Alfred B. Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

1.

Mullins, Teagan S., et al.. (2021). Baseline Differences in Anxiety Affect Attention and tDCS-Mediated Learning. Frontiers in Human Neuroscience. 15. 541369–541369. 3 indexed citations

2.

Cox, Patrick, et al.. (2021). Moving Beyond the Keypress: As Technology Advances, so Should Psychology Response Time Measurements. Perception. 50(6). 555–565. 3 indexed citations

3.

Brunyé, Tad T., Tracy Jill Doty, Erika K. Hussey, et al.. (2020). A Review of US Army Research Contributing to Cognitive Enhancement in Military Contexts. Journal of Cognitive Enhancement. 4(4). 453–468. 33 indexed citations

4.

Badran, Bashar W., Alfred B. Yu, Devin Adair, et al.. (2019). Laboratory Administration of Transcutaneous Auricular Vagus Nerve Stimulation (taVNS): Technique, Targeting, and Considerations. Journal of Visualized Experiments. 70 indexed citations

5.

Crone, Joshua C., et al.. (2019). Enabling Large-Scale Simulations With the GENESIS Neuronal Simulator. Frontiers in Neuroinformatics. 13. 69–69. 3 indexed citations

6.

Mullins, Teagan S., et al.. (2019). Transcranial direct current stimulation facilitates category learning. Brain stimulation. 13(2). 393–400. 13 indexed citations

7.

Badran, Bashar W., Alfred B. Yu, Devin Adair, et al.. (2019). Laboratory Administration of Transcutaneous Auricular Vagus Nerve Stimulation (taVNS): Technique, Targeting, and Considerations. Journal of Visualized Experiments. 26 indexed citations

8.

Geuss, Michael N., et al.. (2019). Intelligent squad weapon: challenges to displaying and interacting with artificial intelligence in small arms weapon systems. 29–29. 1 indexed citations

9.

Sanguinetti, Joseph L., Bashar W. Badran, Alfred B. Yu, et al.. (2018). Increased Excitability Induced in the Primary Motor Cortex by Transcranial Ultrasound Stimulation. Frontiers in Neurology. 9. 1007–1007. 70 indexed citations

10.

Felton, Melvin, et al.. (2018). Resonance Analysis as a Tool for Characterizing Functional Division of Layer 5 Pyramidal Neurons. Frontiers in Computational Neuroscience. 12. 29–29. 3 indexed citations

11.

Yu, Alfred B., et al.. (2017). Impact of Neuronal Membrane Damage on the Local Field Potential in a Large-Scale Simulation of Cerebral Cortex. Frontiers in Neurology. 8. 236–236. 9 indexed citations

12.

Yu, Alfred B. & Jeffrey M. Zacks. (2017). Transformations and representations supporting spatial perspective taking. Spatial Cognition and Computation. 17(4). 304–337. 15 indexed citations

13.

Crone, Joshua C., et al.. (2016). Study of Neocortex Simulations with GENESIS on High Performance Computing Resources. 924–931.

14.

Gu, Shi, Fabio Pasqualetti, Matthew Cieslak, et al.. (2015). Controllability of structural brain networks. Nature Communications. 6(1). 8414–8414. 536 indexed citations breakdown →

15.

Yu, Alfred B. & Jeffrey M. Zacks. (2015). How are bodies special? Effects of body features on spatial reasoning. Quarterly Journal of Experimental Psychology. 69(6). 1210–1226. 6 indexed citations

16.

Yu, Alfred B., Richard A. Abrams, & Jeffrey M. Zacks. (2014). Limits on action priming by pictures of objects.. Journal of Experimental Psychology Human Perception & Performance. 40(5). 1861–1873. 31 indexed citations

17.

Yu, Alfred B. & Jeffrey M. Zacks. (2010). The role of animacy in spatial transformations. Memory & Cognition. 38(7). 982–993. 15 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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