Michael A. Buice

3.7k total citations
25 papers, 989 citations indexed

About

Michael A. Buice is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics. According to data from OpenAlex, Michael A. Buice has authored 25 papers receiving a total of 989 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cognitive Neuroscience, 11 papers in Cellular and Molecular Neuroscience and 6 papers in Statistical and Nonlinear Physics. Recurrent topics in Michael A. Buice's work include Neural dynamics and brain function (20 papers), Visual perception and processing mechanisms (6 papers) and stochastic dynamics and bifurcation (6 papers). Michael A. Buice is often cited by papers focused on Neural dynamics and brain function (20 papers), Visual perception and processing mechanisms (6 papers) and stochastic dynamics and bifurcation (6 papers). Michael A. Buice collaborates with scholars based in United States, China and Canada. Michael A. Buice's co-authors include Carson C. Chow, Jack D. Cowan, Robin Hayman, Kijung Yoon, Ila Fiete, Caswell Barry, Neil Burgess, Eric Shea‐Brown, Christof Koch and Gabriel Koch Ocker and has published in prestigious journals such as Cell, Physical Review Letters and Nature Communications.

In The Last Decade

Michael A. Buice

25 papers receiving 970 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael A. Buice United States 16 763 397 261 132 126 25 989
Roman Borisyuk United Kingdom 22 865 1.1× 454 1.1× 280 1.1× 303 2.3× 106 0.8× 87 1.3k
Susanne Schreiber Germany 19 902 1.2× 669 1.7× 273 1.0× 79 0.6× 216 1.7× 53 1.3k
Duane Q. Nykamp United States 13 876 1.1× 386 1.0× 365 1.4× 133 1.0× 153 1.2× 33 1.0k
Adrián Ponce‐Alvarez Spain 21 1.7k 2.3× 375 0.9× 176 0.7× 121 0.9× 88 0.7× 37 1.9k
Jan Benda Germany 22 1.1k 1.5× 694 1.7× 418 1.6× 103 0.8× 304 2.4× 59 1.7k
Kanaka Rajan United States 14 1.2k 1.5× 515 1.3× 246 0.9× 90 0.7× 325 2.6× 28 1.6k
Lyle Muller Canada 17 1.1k 1.4× 476 1.2× 149 0.6× 150 1.1× 135 1.1× 54 1.2k
Sharon Crook United States 16 609 0.8× 295 0.7× 123 0.5× 122 0.9× 136 1.1× 57 1.0k
Aaditya V. Rangan United States 15 475 0.6× 228 0.6× 320 1.2× 124 0.9× 100 0.8× 46 641
Christian W. Eurich Germany 17 633 0.8× 203 0.5× 212 0.8× 113 0.9× 119 0.9× 36 942

Countries citing papers authored by Michael A. Buice

Since Specialization
Citations

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

Fields of papers citing papers by Michael A. Buice

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael A. Buice

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Buice. A scholar is included among the top collaborators of Michael A. Buice 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 A. Buice. Michael A. Buice 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.
Ledochowitsch, Peter, Joshua H. Siegle, Daniel J. Denman, et al.. (2025). Deciphering neuronal variability across states reveals dynamic sensory encoding. Nature Communications. 16(1). 1768–1768. 5 indexed citations
2.
Ledochowitsch, Peter, et al.. (2023). Saccade-Responsive Visual Cortical Neurons Do Not Exhibit Distinct Visual Response Properties. eNeuro. 10(9). ENEURO.0051–23.2023. 1 indexed citations
3.
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
4.
Ocker, Gabriel Koch & Michael A. Buice. (2021). Tensor decompositions of higher-order correlations by nonlinear Hebbian plasticity. neural information processing systems. 34. 1 indexed citations
5.
Ocker, Gabriel Koch & Michael A. Buice. (2020). Flexible neural connectivity under constraints on total connection strength. PLoS Computational Biology. 16(8). e1008080–e1008080. 2 indexed citations
6.
Millman, Daniel, Gabriel Koch Ocker, Shiella Caldejon, et al.. (2020). VIP interneurons in mouse primary visual cortex selectively enhance responses to weak but specific stimuli. eLife. 9. 39 indexed citations
7.
Shi, Jianghong, Eric Shea‐Brown, & Michael A. Buice. (2019). Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex. arXiv (Cornell University). 32. 5764–5774. 4 indexed citations
8.
Recanatesi, Stefano, Gabriel Koch Ocker, Michael A. Buice, & Eric Shea‐Brown. (2019). Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity. PLoS Computational Biology. 15(7). e1006446–e1006446. 42 indexed citations
9.
Brinkman, Braden A. W., Fred Rieke, Eric Shea‐Brown, & Michael A. Buice. (2018). Predicting how and when hidden neurons skew measured synaptic interactions. PLoS Computational Biology. 14(10). e1006490–e1006490. 20 indexed citations
10.
Ocker, Gabriel Koch, Krešimir Josić́, Eric Shea‐Brown, & Michael A. Buice. (2017). Linking structure and activity in nonlinear spiking networks. PLoS Computational Biology. 13(6). e1005583–e1005583. 35 indexed citations
11.
Chow, Carson C. & Michael A. Buice. (2015). Path Integral Methods for Stochastic Differential Equations. PubMed. 5(1). 8–8. 59 indexed citations
12.
Koch, Christof & Michael A. Buice. (2015). A Biological Imitation Game. Cell. 163(2). 277–280. 10 indexed citations
13.
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
14.
Buice, Michael A. & Carson C. Chow. (2013). Beyond mean field theory: statistical field theory for neural networks. Journal of Statistical Mechanics Theory and Experiment. 2013(3). P03003–P03003. 38 indexed citations
15.
Buice, Michael A. & Carson C. Chow. (2013). Dynamic Finite Size Effects in Spiking Neural Networks. PLoS Computational Biology. 9(1). e1002872–e1002872. 36 indexed citations
16.
Buice, Michael A. & Carson C. Chow. (2011). Effective stochastic behavior in dynamical systems with incomplete information. Physical Review E. 84(5). 51120–51120. 4 indexed citations
17.
Buice, Michael A. & Jack D. Cowan. (2009). Statistical mechanics of the neocortex. Progress in Biophysics and Molecular Biology. 99(2-3). 53–86. 48 indexed citations
18.
Buice, Michael A. & Carson C. Chow. (2007). Correlations, fluctuations, and stability of a finite-size network of coupled oscillators. Physical Review E. 76(3). 31118–31118. 41 indexed citations
19.
Hildebrand, Eric, Michael A. Buice, & Carson C. Chow. (2007). Kinetic Theory of Coupled Oscillators. Physical Review Letters. 98(5). 54101–54101. 40 indexed citations
20.
Buice, Michael A. & Jack D. Cowan. (2007). Field-theoretic approach to fluctuation effects in neural networks. Physical Review E. 75(5). 51919–51919. 114 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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