Ştefan Mihalaş

11.3k total citations
72 papers, 2.4k citations indexed

About

Ştefan Mihalaş is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Ştefan Mihalaş has authored 72 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Cognitive Neuroscience, 32 papers in Cellular and Molecular Neuroscience and 17 papers in Electrical and Electronic Engineering. Recurrent topics in Ştefan Mihalaş's work include Neural dynamics and brain function (48 papers), Visual perception and processing mechanisms (20 papers) and Advanced Memory and Neural Computing (17 papers). Ştefan Mihalaş is often cited by papers focused on Neural dynamics and brain function (48 papers), Visual perception and processing mechanisms (20 papers) and Advanced Memory and Neural Computing (17 papers). Ştefan Mihalaş collaborates with scholars based in United States, Australia and Taiwan. Ştefan Mihalaş's co-authors include Ernst Niebur, Ramakrishnan Iyer, Christof Koch, Vijay Mohan K Namboodiri, R. von der Heydt, Yi Dong, Mary B. Kennedy, Nicholas Cain, Alfredo Kirkwood and Christopher D. Deppmann and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Ştefan Mihalaş

71 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ştefan Mihalaş United States 27 1.7k 978 440 438 200 72 2.4k
Pamela Reinagel United States 19 2.0k 1.2× 1.1k 1.2× 279 0.6× 603 1.4× 247 1.2× 31 2.6k
Tim Gollisch Germany 23 1.6k 1.0× 1.2k 1.2× 528 1.2× 859 2.0× 185 0.9× 53 2.4k
Kechen Zhang United States 19 1.8k 1.1× 1.0k 1.0× 159 0.4× 184 0.4× 110 0.6× 45 2.3k
Keith P. Purpura United States 24 2.5k 1.5× 1.1k 1.2× 286 0.7× 499 1.1× 252 1.3× 49 3.0k
Nicholas A. Steinmetz United States 28 3.5k 2.1× 1.8k 1.9× 282 0.6× 283 0.6× 131 0.7× 47 4.0k
Ulf Knoblich United States 17 2.9k 1.8× 2.5k 2.6× 193 0.4× 497 1.1× 105 0.5× 21 3.9k
Jeffrey L. Gauthier United States 21 1.8k 1.1× 1.3k 1.4× 196 0.4× 770 1.8× 175 0.9× 26 2.6k
Stephen A. Baccus United States 24 1.6k 0.9× 1.6k 1.6× 390 0.9× 1.2k 2.8× 69 0.3× 42 3.0k
Moritz Helmstaedter Germany 36 2.2k 1.3× 2.4k 2.4× 382 0.9× 1.2k 2.7× 64 0.3× 53 4.8k
Yves Frégnac France 33 3.7k 2.2× 2.5k 2.6× 468 1.1× 574 1.3× 298 1.5× 85 4.3k

Countries citing papers authored by Ştefan Mihalaş

Since Specialization
Citations

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

Fields of papers citing papers by Ştefan Mihalaş

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ştefan Mihalaş

This figure shows the co-authorship network connecting the top 25 collaborators of Ştefan Mihalaş. A scholar is included among the top collaborators of Ştefan Mihalaş 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 Ştefan Mihalaş. Ştefan Mihalaş 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.
Kuśmierz, Łukasz, et al.. (2025). Hierarchy of Chaotic Dynamics in Random Modular Networks. Physical Review Letters. 134(14). 148402–148402.
2.
Shea‐Brown, Eric, et al.. (2023). A biologically inspired architecture with switching units can learn to generalize across backgrounds. Neural Networks. 168. 615–630. 1 indexed citations
3.
Jeong, Huijeong, et al.. (2022). Mesolimbic dopamine release conveys causal associations. Science. 378(6626). eabq6740–eabq6740. 100 indexed citations
4.
Jeong, Huijeong, et al.. (2022). Mesolimbic dopamine release conveys causal associations. Zenodo (CERN European Organization for Nuclear Research). 12 indexed citations
5.
Shi, Jianghong, et al.. (2022). MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex. PLoS Computational Biology. 18(9). e1010427–e1010427. 11 indexed citations
6.
Smith, Stephen J, et al.. (2021). Cell-type–specific neuromodulation guides synaptic credit assignment in a spiking neural network. Proceedings of the National Academy of Sciences. 118(51). 14 indexed citations
7.
Hu, Brian, Marina Garrett, Peter A. Groblewski, et al.. (2021). Adaptation supports short-term memory in a visual change detection task. PLoS Computational Biology. 17(9). e1009246–e1009246. 12 indexed citations
8.
Dai, Kael, Sergey L. Gratiy, Yazan N. Billeh, et al.. (2020). Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits. PLoS Computational Biology. 16(11). e1008386–e1008386. 31 indexed citations
9.
Knox, Joseph E., Kameron Decker Harris, Nile Graddis, et al.. (2018). High-resolution data-driven model of the mouse connectome. Network Neuroscience. 3(1). 217–236. 58 indexed citations
10.
Teeter, Corinne, Ramakrishnan Iyer, Vilas Menon, et al.. (2018). Generalized leaky integrate-and-fire models classify multiple neuron types. Nature Communications. 9(1). 709–709. 129 indexed citations
11.
Gao, Ming, Shiyong Huang, Angela Lee, et al.. (2017). Experience-dependent homeostasis of ‘noise’ at inhibitory synapses preserves information coding in adult visual cortex. Philosophical Transactions of the Royal Society B Biological Sciences. 372(1715). 20160156–20160156. 20 indexed citations
12.
Billeh, Yazan N., Alexander V. Rodriguez, Michele Bellesi, et al.. (2016). Effects of Chronic Sleep Restriction during Early Adolescence on the Adult Pattern of Connectivity of Mouse Secondary Motor Cortex. eNeuro. 3(2). ENEURO.0053–16.2016. 18 indexed citations
13.
Cain, Nicholas, Ramakrishnan Iyer, Christof Koch, & Ştefan Mihalaş. (2016). The Computational Properties of a Simplified Cortical Column Model. PLoS Computational Biology. 12(9). e1005045–e1005045. 27 indexed citations
14.
Harris, Kameron Decker, Ştefan Mihalaş, & Eric Shea‐Brown. (2016). Nonnegative spline regression of incomplete tracing data reveals high resolution neural connectivity. arXiv (Cornell University). 1 indexed citations
15.
Namboodiri, Vijay Mohan K, Joshua M. Levy, Ştefan Mihalaş, David Sims, & Marshall G. Hussain Shuler. (2016). Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework. Proceedings of the National Academy of Sciences. 113(31). 8747–8752. 23 indexed citations
16.
Mihalaş, Ştefan, et al.. (2014). Local spectral anisotropy is a valid cue for figure–ground organization in natural scenes. Vision Research. 103. 116–126. 12 indexed citations
17.
Namboodiri, Vijay Mohan K, Ştefan Mihalaş, & Marshall G. Hussain Shuler. (2014). Rationalizing Decision-Making: Understanding the Cost and Perception of Time. PubMed. 1(1). 1–40. 16 indexed citations
18.
Mihalaş, Ştefan, et al.. (2013). A model of proto-object based saliency. Vision Research. 94. 1–15. 69 indexed citations
19.
Iyer, Ramakrishnan, Vilas Menon, Michael A. Buice, Christof Koch, & Ştefan Mihalaş. (2013). The Influence of Synaptic Weight Distribution on Neuronal Population Dynamics. PLoS Computational Biology. 9(10). e1003248–e1003248. 57 indexed citations
20.
Deppmann, Christopher D., Ştefan Mihalaş, Nikhil Sharma, et al.. (2008). A Model for Neuronal Competition During Development. Science. 320(5874). 369–373. 131 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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