Luca Aquili

794 total citations
33 papers, 529 citations indexed

About

Luca Aquili is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Neurology. According to data from OpenAlex, Luca Aquili has authored 33 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cognitive Neuroscience, 12 papers in Cellular and Molecular Neuroscience and 9 papers in Neurology. Recurrent topics in Luca Aquili's work include Alzheimer's disease research and treatments (6 papers), Neural dynamics and brain function (5 papers) and Transcranial Magnetic Stimulation Studies (5 papers). Luca Aquili is often cited by papers focused on Alzheimer's disease research and treatments (6 papers), Neural dynamics and brain function (5 papers) and Transcranial Magnetic Stimulation Studies (5 papers). Luca Aquili collaborates with scholars based in Hong Kong, Australia and Malaysia. Luca Aquili's co-authors include Lee Wei Lim, Adam Z. Weitemier, Joshua P. Johansen, Thomas J. McHugh, Akira Uematsu, Jaydeep Roy, Boon Chin Heng, Kah-Hui Wong, Charlotte J. Stagg and Man Lung Fung and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Luca Aquili

31 papers receiving 523 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luca Aquili Hong Kong 13 226 185 97 96 93 33 529
Grasielle C. Kincheski Brazil 11 160 0.7× 141 0.8× 89 0.9× 62 0.6× 126 1.4× 14 456
Surajit Sahu India 13 146 0.6× 106 0.6× 94 1.0× 74 0.8× 43 0.5× 17 398
Wei Zong United States 13 164 0.7× 101 0.5× 82 0.8× 103 1.1× 83 0.9× 28 500
Wladimir A. Medrano Brazil 7 165 0.7× 175 0.9× 37 0.4× 89 0.9× 83 0.9× 7 491
Amber T. Levine United States 13 332 1.5× 279 1.5× 96 1.0× 188 2.0× 212 2.3× 17 830
N Naghdi Iran 15 268 1.2× 321 1.7× 121 1.2× 141 1.5× 176 1.9× 26 733
Christina L. Ruby United States 15 164 0.7× 263 1.4× 55 0.6× 118 1.2× 114 1.2× 20 611
Karienn S. Montgomery United States 11 298 1.3× 316 1.7× 100 1.0× 89 0.9× 90 1.0× 15 696
Margarita Martı́-Nicolovius Spain 19 381 1.7× 365 2.0× 88 0.9× 95 1.0× 53 0.6× 50 735
Salar Vaseghi Iran 19 378 1.7× 192 1.0× 81 0.8× 116 1.2× 107 1.2× 71 866

Countries citing papers authored by Luca Aquili

Since Specialization
Citations

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

Fields of papers citing papers by Luca Aquili

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luca Aquili

This figure shows the co-authorship network connecting the top 25 collaborators of Luca Aquili. A scholar is included among the top collaborators of Luca Aquili 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 Luca Aquili. Luca Aquili 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.
Zhang, Jingyi, Luca Aquili, Kah-Hui Wong, et al.. (2025). Data Mining Approach to Melatonin Treatment in Alzheimer’s Disease: New Gene Targets MMP2 and NR3C1. International Journal of Molecular Sciences. 26(1). 338–338. 1 indexed citations
2.
Liu, Yanzhi, Luca Aquili, Kah-Hui Wong, Zhi-Liang Lu, & Lee Wei Lim. (2025). Past, present, and future of serotonin-targeting therapeutics for Alzheimer’s disease: Perspectives from DNA methylation. Ageing Research Reviews. 108. 102755–102755.
3.
4.
Lim, Wei Ling, Luca Aquili, Anna Chung-Kwan Tse, et al.. (2023). Prelimbic Cortical Stimulation Induces Antidepressant-like Responses through Dopaminergic-Dependent and -Independent Mechanisms. Cells. 12(11). 1449–1449. 1 indexed citations
5.
Roy, Jaydeep, K. Y. Wong, Luca Aquili, et al.. (2022). Role of melatonin in Alzheimer’s disease: From preclinical studies to novel melatonin-based therapies. Frontiers in Neuroendocrinology. 65. 100986–100986. 42 indexed citations
6.
7.
Poon, Chi Him, Yanzhi Liu, Robert Chunhua Zhao, et al.. (2022). Prelimbic Cortical Stimulation with L-methionine Enhances Cognition through Hippocampal DNA Methylation and Neuroplasticity Mechanisms. Aging and Disease. 14(1). 112–112. 5 indexed citations
8.
Roy, Jaydeep, Kah-Hui Wong, Лей Ши, et al.. (2022). Distribution and inter-regional relationship of amyloid-beta plaque deposition in a 5xFAD mouse model of Alzheimer’s disease. Frontiers in Aging Neuroscience. 14. 964336–964336. 26 indexed citations
9.
Poon, Chi Him, et al.. (2021). Functional Roles of Neuronal Nitric Oxide Synthase in Neurodegenerative Diseases and Mood Disorders. Current Alzheimer Research. 18(10). 831–840. 6 indexed citations
10.
Roy, Jaydeep, K. Y. Wong, Luca Aquili, et al.. (2020). Therapeutic potential of neurogenesis and melatonin regulation in Alzheimer's disease. Annals of the New York Academy of Sciences. 1478(1). 43–62. 36 indexed citations
11.
Tan, Shawn Zheng Kai, Yasin Temel, Arjan Blokland, et al.. (2020). Serotonergic treatment normalizes midbrain dopaminergic neuron increase after periaqueductal gray stimulation. Brain Structure and Function. 225(7). 1957–1966. 5 indexed citations
12.
Aquili, Luca, Eric Bowman, & Robert Schmidt. (2020). Occasion setters determine responses of putative DA neurons to discriminative stimuli. Neurobiology of Learning and Memory. 173. 107270–107270. 3 indexed citations
13.
Thirkettle, Martin, et al.. (2019). Dissociable Effects of Tryptophan Supplementation on Negative Feedback Sensitivity and Reversal Learning. Frontiers in Behavioral Neuroscience. 13. 127–127. 8 indexed citations
14.
Soranzo, Alessandro & Luca Aquili. (2019). Fear expression is suppressed by tyrosine administration. Scientific Reports. 9(1). 16073–16073. 6 indexed citations
15.
Lim, Lee Wei, et al.. (2019). Tyrosine negatively affects flexible-like behaviour under cognitively demanding conditions. Journal of Affective Disorders. 260. 329–333. 5 indexed citations
16.
Lim, Lee Wei, et al.. (2019). Dopamine depletion effects on cognitive flexibility as modulated by tDCS of the dlPFC. Brain stimulation. 13(1). 105–108. 34 indexed citations
17.
Uematsu, Akira, et al.. (2018). A dopaminergic switch for fear to safety transitions. Nature Communications. 9(1). 2483–2483. 131 indexed citations
18.
Riby, Leigh M., et al.. (2017). Impulsiveness, postprandial blood glucose, and glucoregulation affect measures of behavioral flexibility. Nutrition Research. 48. 65–75. 12 indexed citations
19.
Ong, Derek Lai Teik, et al.. (2016). Ginseng and Ginkgo Biloba Effects on Cognition as Modulated by Cardiovascular Reactivity: A Randomised Trial. PLoS ONE. 11(3). e0150447–e0150447. 34 indexed citations
20.
Aquili, Luca, et al.. (2014). Behavioral flexibility is increased by optogenetic inhibition of neurons in the nucleus accumbens shell during specific time segments. Learning & Memory. 21(4). 223–231. 19 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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2026