Michael D. Nunez

851 total citations
19 papers, 388 citations indexed

About

Michael D. Nunez is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Michael D. Nunez has authored 19 papers receiving a total of 388 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 4 papers in Experimental and Cognitive Psychology and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Michael D. Nunez's work include Neural dynamics and brain function (12 papers), Neural and Behavioral Psychology Studies (12 papers) and EEG and Brain-Computer Interfaces (11 papers). Michael D. Nunez is often cited by papers focused on Neural dynamics and brain function (12 papers), Neural and Behavioral Psychology Studies (12 papers) and EEG and Brain-Computer Interfaces (11 papers). Michael D. Nunez collaborates with scholars based in United States, Netherlands and Germany. Michael D. Nunez's co-authors include Ramesh Srinivasan, Joachim Vandekerckhove, Paul L. Nunez, Vince D. Calhoun, David A. Bridwell, James F. Cavanagh, Sebastian Stober, Anne Collins, Michele A. Basso and Anna‐Lena Schubert and has published in prestigious journals such as Nature Neuroscience, NeuroImage and Frontiers in Psychology.

In The Last Decade

Michael D. Nunez

17 papers receiving 376 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 D. Nunez United States 9 337 59 52 33 27 19 388
Aurelio Cortese Japan 12 451 1.3× 70 1.2× 14 0.3× 26 0.8× 45 1.7× 28 544
Vincent Adam United Kingdom 5 343 1.0× 93 1.6× 31 0.6× 38 1.2× 32 1.2× 8 423
Debbie Yee United States 9 249 0.7× 72 1.2× 53 1.0× 47 1.4× 36 1.3× 15 353
Kinjan Parikh United States 3 385 1.1× 76 1.3× 46 0.9× 17 0.5× 42 1.6× 4 454
Steven Miletić Netherlands 12 266 0.8× 59 1.0× 63 1.2× 43 1.3× 23 0.9× 26 385
Norman H. Lam United States 7 190 0.6× 35 0.6× 17 0.3× 15 0.5× 14 0.5× 11 258
Arman Abrahamyan Australia 10 289 0.9× 33 0.6× 13 0.3× 22 0.7× 23 0.9× 14 344
Anil Cherian United States 5 395 1.2× 41 0.7× 42 0.8× 13 0.4× 22 0.8× 6 425
Zhe Qu China 13 433 1.3× 119 2.0× 61 1.2× 7 0.2× 43 1.6× 27 515
Ruben S. van Bergen Netherlands 7 366 1.1× 67 1.1× 9 0.2× 23 0.7× 24 0.9× 10 409

Countries citing papers authored by Michael D. Nunez

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. Nunez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael D. Nunez

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

All Works

19 of 19 papers shown
1.
Nunez, Michael D., Anna‐Lena Schubert, Gidon T. Frischkorn, & Klaus Oberauer. (2025). Cognitive models of decision-making with identifiable parameters: Diffusion decision models with within-trial noise. Journal of Mathematical Psychology. 125. 102917–102917.
2.
Nunez, Michael D., et al.. (2024). A tutorial on fitting joint models of M/EEG and behavior to understand cognition. Behavior Research Methods. 56(6). 6020–6050. 7 indexed citations
3.
Nunez, Michael D., et al.. (2024). Deep latent variable joint cognitive modeling of neural signals and human behavior. NeuroImage. 291. 120559–120559.
4.
Rad, Jamal Amani, et al.. (2023). A General Integrative Neurocognitive Modeling Framework to Jointly Describe EEG and Decision-making on Single Trials. Computational Brain & Behavior. 6(3). 317–376. 8 indexed citations
5.
Parand, Kourosh, et al.. (2023). How spatial attention affects the decision process: looking through the lens of Bayesian hierarchical diffusion model & EEG analysis. Journal of Cognitive Psychology. 35(4). 456–479. 4 indexed citations
6.
Nunez, Michael D., et al.. (2022). Beyond rates: time-varying dynamics of high frequency oscillations as a biomarker of the seizure onset zone. Journal of Neural Engineering. 19(1). 16034–16034. 6 indexed citations
7.
Rad, Jamal Amani, et al.. (2022). Neuro-cognitive models of single-trial EEG measures describe latent effects of spatial attention during perceptual decision making. Journal of Mathematical Psychology. 111. 102725–102725. 6 indexed citations
8.
Nunez, Michael D., et al.. (2021). Causal role for the primate superior colliculus in the computation of evidence for perceptual decisions. Nature Neuroscience. 24(8). 1121–1131. 47 indexed citations
9.
Nunez, Michael D., et al.. (2020). Timing of Readiness Potentials Reflect a Decision-making Process in the Human Brain. Computational Brain & Behavior. 4(3). 264–283. 10 indexed citations
10.
Nunez, Paul L., Michael D. Nunez, & Ramesh Srinivasan. (2019). Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review. Brain Topography. 32(2). 193–214. 29 indexed citations
11.
Nunez, Michael D., et al.. (2019). The latency of a visual evoked potential tracks the onset of decision making. NeuroImage. 197. 93–108. 32 indexed citations
12.
Bridwell, David A., James F. Cavanagh, Anne Collins, et al.. (2018). Moving Beyond ERP Components: A Selective Review of Approaches to Integrate EEG and Behavior. Frontiers in Human Neuroscience. 12. 106–106. 58 indexed citations
13.
Schubert, Anna‐Lena, Michael D. Nunez, Dirk Hagemann, & Joachim Vandekerckhove. (2018). Individual differences in cortical processing speed predict cognitive abilities: A model-based cognitive neuroscience account. eScholarship (California Digital Library). 1 indexed citations
14.
Schubert, Anna‐Lena, Michael D. Nunez, Dirk Hagemann, & Joachim Vandekerckhove. (2018). Individual Differences in Cortical Processing Speed Predict Cognitive Abilities: a Model-Based Cognitive Neuroscience Account. Computational Brain & Behavior. 2(2). 64–84. 24 indexed citations
15.
Nunez, Michael D., Martina Bebin, Darcy A. Krueger, et al.. (2018). Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. PubMed. 2018. 3116–3119. 6 indexed citations
16.
Nunez, Paul L., Michael D. Nunez, & Ramesh Srinivasan. (2018). Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review. bioRxiv (Cold Spring Harbor Laboratory). 2 indexed citations
17.
Nunez, Michael D., Joachim Vandekerckhove, & Ramesh Srinivasan. (2016). How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters. Journal of Mathematical Psychology. 76(Pt B). 117–130. 85 indexed citations
18.
Nunez, Michael D., Paul L. Nunez, & Ramesh Srinivasan. (2016). Electroencephalography (EEG): neurophysics, experimental methods, and signal processing. eScholarship (California Digital Library). 14 indexed citations
19.
Nunez, Michael D.. (2015). Individual differences in attention influence perceptual decision making. Frontiers in Psychology. 6. 18–18. 49 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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