Michael Doron

597 total citations
9 papers, 265 citations indexed

About

Michael Doron is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Biophysics. According to data from OpenAlex, Michael Doron has authored 9 papers receiving a total of 265 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cognitive Neuroscience, 5 papers in Cellular and Molecular Neuroscience and 4 papers in Biophysics. Recurrent topics in Michael Doron's work include Neural dynamics and brain function (6 papers), Neuroscience and Neuropharmacology Research (4 papers) and Cell Image Analysis Techniques (3 papers). Michael Doron is often cited by papers focused on Neural dynamics and brain function (6 papers), Neuroscience and Neuropharmacology Research (4 papers) and Cell Image Analysis Techniques (3 papers). Michael Doron collaborates with scholars based in United States, Israel and Switzerland. Michael Doron's co-authors include Aditya Pratapa, Juan Carlos Caicedo, Idan Segev, Eilif Müller, Henry Markram, Giuseppe Chindemi, Hanbo Chen, Larry Abbott, Yujie Li and Heike Blockus and has published in prestigious journals such as Nature Communications, Neuron and Journal of Neuroscience.

In The Last Decade

Michael Doron

8 papers receiving 265 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Doron United States	6	135	135	55	51	41	9	265
Alessandro Motta Germany	6	137 1.0×	155 1.1×	57 1.0×	83 1.6×	31 0.8×	6	338
Sahil Loomba Germany	3	117 0.9×	132 1.0×	52 0.9×	67 1.3×	27 0.7×	3	289
Marcel Beining Germany	8	168 1.2×	137 1.0×	71 1.3×	65 1.3×	36 0.9×	9	335
Benedikt Staffler Germany	4	84 0.6×	91 0.7×	42 0.8×	81 1.6×	25 0.6×	4	243
Claudio Moretti Italy	8	237 1.8×	193 1.4×	77 1.4×	79 1.5×	27 0.7×	12	443
Oscar Hernandez United States	8	163 1.2×	171 1.3×	40 0.7×	137 2.7×	36 0.9×	9	391
Jacob Duijnhouwer Netherlands	7	152 1.1×	217 1.6×	42 0.8×	38 0.7×	17 0.4×	16	302
Ching‐Lung Hsu United States	7	192 1.4×	165 1.2×	84 1.5×	96 1.9×	41 1.0×	9	346
Andreas Herzog Germany	9	164 1.2×	120 0.9×	87 1.6×	25 0.5×	27 0.7×	26	337
Jae-eun Kang Miller United States	6	283 2.1×	301 2.2×	47 0.9×	125 2.5×	43 1.0×	7	484

Countries citing papers authored by Michael Doron

Since Specialization

Citations

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

Fields of papers citing papers by Michael Doron

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Doron

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

All Works

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9 of 9 papers shown

1.

Moutakanni, Théo, Camille Couprie, Michael Doron, et al.. (2025). Cell-DINO: Self-supervised image-based embeddings for cell fluorescent microscopy. PLoS Computational Biology. 21(12). e1013828–e1013828.

2.

Balcioglu, Aygul, Michael Doron, Taeyun Ku, et al.. (2023). Mapping thalamic innervation to individual L2/3 pyramidal neurons and modeling their ‘readout’ of visual input. Nature Neuroscience. 26(3). 470–480. 9 indexed citations

3.

Pernice, Wolfgang M., et al.. (2023). Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy. 4326–4335. 5 indexed citations

4.

Chindemi, Giuseppe, Marwan Abdellah, Oren Amsalem, et al.. (2022). A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex. Nature Communications. 13(1). 3038–3038. 41 indexed citations

5.

Pratapa, Aditya, Michael Doron, & Juan Carlos Caicedo. (2021). Image-based cell phenotyping with deep learning. Current Opinion in Chemical Biology. 65. 9–17. 65 indexed citations

6.

Doron, Michael, et al.. (2021). Synaptic Input and ACh Modulation Regulate Dendritic Ca²⁺Spike Duration in Pyramidal Neurons, Directly Affecting Their Somatic Output. Journal of Neuroscience. 42(7). 1184–1195. 3 indexed citations

7.

Iascone, Daniel Maxim, Yujie Li, Uygar Sümbül, et al.. (2020). Whole-Neuron Synaptic Mapping Reveals Spatially Precise Excitatory/Inhibitory Balance Limiting Dendritic and Somatic Spiking. Neuron. 106(4). 566–578.e8. 95 indexed citations

8.

Doron, Michael, Idan Segev, & Dafna Shahaf. (2019). Discovering Unexpected Local Nonlinear Interactions in Scientific Black-box Models. 425–435. 4 indexed citations

9.

Doron, Michael, Giuseppe Chindemi, Eilif Müller, Henry Markram, & Idan Segev. (2017). Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons. Cell Reports. 21(6). 1550–1561. 43 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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