Hillel Adesnik

8.7k total citations · 1 hit paper
59 papers, 5.6k citations indexed

About

Hillel Adesnik is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Hillel Adesnik has authored 59 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Cellular and Molecular Neuroscience, 36 papers in Cognitive Neuroscience and 8 papers in Molecular Biology. Recurrent topics in Hillel Adesnik's work include Photoreceptor and optogenetics research (38 papers), Neural dynamics and brain function (35 papers) and Neuroscience and Neuropharmacology Research (23 papers). Hillel Adesnik is often cited by papers focused on Photoreceptor and optogenetics research (38 papers), Neural dynamics and brain function (35 papers) and Neuroscience and Neuropharmacology Research (23 papers). Hillel Adesnik collaborates with scholars based in United States, France and Japan. Hillel Adesnik's co-authors include Roger A. Nicoll, Massimo Scanziani, David S. Bredt, Yuko Fukata, Masaki Fukata, Laura Waller, Nicolas C. Pégard, Alexander Naka, Z. Josh Huang and Hiroki Taniguchi and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Hillel Adesnik

57 papers receiving 5.5k citations

Hit Papers

A neural circuit for spat... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hillel Adesnik United States 31 3.7k 2.4k 1.9k 419 316 59 5.6k
K. Kitamura Japan 37 2.4k 0.7× 1.3k 0.5× 1.6k 0.9× 357 0.9× 452 1.4× 144 5.2k
Daniel A. Dombeck United States 28 3.6k 1.0× 2.8k 1.1× 1.3k 0.7× 378 0.9× 518 1.6× 43 5.6k
Michele Migliore Italy 40 4.0k 1.1× 3.1k 1.3× 1.7k 0.9× 117 0.3× 287 0.9× 145 5.9k
Tsai‐Wen Chen United States 18 4.3k 1.2× 2.6k 1.1× 2.3k 1.2× 482 1.2× 567 1.8× 23 7.1k
Thomas G. Oertner Germany 33 4.3k 1.2× 1.9k 0.8× 2.2k 1.2× 344 0.8× 354 1.1× 68 5.6k
Botond Roska Switzerland 50 4.7k 1.3× 1.8k 0.7× 5.0k 2.7× 386 0.9× 712 2.3× 97 8.3k
Peyman Golshani United States 38 3.2k 0.9× 3.2k 1.3× 1.6k 0.9× 321 0.8× 269 0.9× 74 6.2k
Sabine L. Renninger Portugal 9 3.3k 0.9× 1.7k 0.7× 1.9k 1.0× 511 1.2× 371 1.2× 12 5.4k
Marla B. Feller United States 47 5.7k 1.5× 2.3k 0.9× 4.7k 2.5× 573 1.4× 132 0.4× 102 8.2k
Mark Hübener Germany 41 4.4k 1.2× 4.0k 1.6× 1.9k 1.0× 332 0.8× 330 1.0× 72 6.9k

Countries citing papers authored by Hillel Adesnik

Since Specialization
Citations

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

Fields of papers citing papers by Hillel Adesnik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hillel Adesnik

This figure shows the co-authorship network connecting the top 25 collaborators of Hillel Adesnik. A scholar is included among the top collaborators of Hillel Adesnik 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 Hillel Adesnik. Hillel Adesnik 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.
Adesnik, Hillel, et al.. (2025). Network influence determines the impact of cortical ensembles on stimulus detection. Neuron. 113(14). 2358–2369.e5.
2.
Sadahiro, Masato, et al.. (2024). Removing direct photocurrent artifacts in optogenetic connectivity mapping data via constrained matrix factorization. PLoS Computational Biology. 20(5). e1012053–e1012053. 1 indexed citations
3.
Oldenburg, Ian Antón, William D. Hendricks, Gregory Handy, et al.. (2024). The logic of recurrent circuits in the primary visual cortex. Nature Neuroscience. 27(1). 137–147. 20 indexed citations
4.
Adesnik, Hillel, et al.. (2023). Modeling the diverse effects of divisive normalization on noise correlations. PLoS Computational Biology. 19(11). e1011667–e1011667. 4 indexed citations
5.
Sridharan, Savitha, Lamiae Abdeladim, Masato Sadahiro, et al.. (2022). High-performance microbial opsins for spatially and temporally precise perturbations of large neuronal networks. Neuron. 110(7). 1139–1155.e6. 39 indexed citations
6.
Xue, Yi, Laura Waller, Hillel Adesnik, & Nicolas C. Pégard. (2022). Three-dimensional multi-site random access photostimulation (3D-MAP). eLife. 11. 11 indexed citations
7.
Lyall, Evan H., et al.. (2021). Synthesis of a comprehensive population code for contextual features in the awake sensory cortex. eLife. 10. 13 indexed citations
8.
Sorum, Ben, et al.. (2021). Ultrasound activates mechanosensitive TRAAK K + channels through the lipid membrane. Proceedings of the National Academy of Sciences. 118(6). 112 indexed citations
9.
Ortiz, Gloria, Pei Liu, Parker E. Deal, et al.. (2021). A silicon-rhodamine chemical-genetic hybrid for far red voltage imaging from defined neurons in brain slice. RSC Chemical Biology. 2(6). 1594–1599. 10 indexed citations
10.
Adesnik, Hillel & Lamiae Abdeladim. (2021). Probing neural codes with two-photon holographic optogenetics. Nature Neuroscience. 24(10). 1356–1366. 96 indexed citations
11.
Naka, Alexander, et al.. (2019). Superficial Layers Suppress the Deep Layers to Fine-tune Cortical Coding. Journal of Neuroscience. 39(11). 2052–2064. 26 indexed citations
12.
Naka, Alexander, Julia Veit, Rebecca K. Chance, et al.. (2019). Complementary networks of cortical somatostatin interneurons enforce layer specific control. eLife. 8. 75 indexed citations
13.
Mardinly, Alan R., Ian Antón Oldenburg, Nicolas C. Pégard, et al.. (2018). Precise multimodal optical control of neural ensemble activity. Nature Neuroscience. 21(6). 881–893. 157 indexed citations
14.
Dhuey, Scott, et al.. (2018). High-density electrical and optical probes for neural readout and light focusing in deep brain tissue. Journal of Micro/Nanolithography MEMS and MOEMS. 17(2). 1–1. 13 indexed citations
15.
Pégard, Nicolas C., Alan R. Mardinly, Ian Antón Oldenburg, et al.. (2017). Three-dimensional scanless holographic optogenetics with temporal focusing (3D-SHOT). Nature Communications. 8(1). 1228–1228. 137 indexed citations
16.
Naka, Alexander & Hillel Adesnik. (2016). Inhibitory Circuits in Cortical Layer 5. Frontiers in Neural Circuits. 10. 35–35. 86 indexed citations
17.
Naka, Alexander, et al.. (2015). A direct translaminar inhibitory circuit tunes cortical output. Nature Neuroscience. 18(11). 1631–1640. 78 indexed citations
18.
Yudowski, Guillermo A., Olav Olsen, Hillel Adesnik, Kurt W. Marek, & David S. Bredt. (2013). Acute Inactivation of PSD-95 Destabilizes AMPA Receptors at Hippocampal Synapses. PLoS ONE. 8(1). e53965–e53965. 26 indexed citations
19.
Adesnik, Hillel, et al.. (2012). A neural circuit for spatial summation in visual cortex. Nature. 490(7419). 226–231. 464 indexed citations breakdown →
20.
Li, Guangnan, Hillel Adesnik, Jennifer Li, et al.. (2008). Regional Distribution of Cortical Interneurons and Development of Inhibitory Tone Are Regulated by Cxcl12/Cxcr4 Signaling. Journal of Neuroscience. 28(5). 1085–1098. 150 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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