Dr. M.D. (Michael) Nunez PhD
Faculty of Social and Behavioural Sciences
Programme group Psychological Methods
Visiting address
- Nieuwe Achtergracht 129
- Room number: G0.32
Postal address
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Postbus 15906
1001 NK Amsterdam
Contact details
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Profile
I am a Cognitive Neuroscientist who uses mathematical modeling to understand the brain and mind. I currently have two main research trends: 1) to further understanding of decision making and cognitive differences across individuals and 2) to develop modeling techniques that better test "neurocognitive" theories with real data. I evaluate electrical signals recorded from the brain while also evaluating human behavior during experiments. To answer specific scientific questions with this data, I often use Bayesian hierarchical statistical modeling and signal processing methods.
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Publications
2024
- Nunez, M. D., Fernandez, K., Srinivasan, R., & Vandekerckhove, J. (2024). A tutorial on fitting joint models of M/EEG and behavior to understand cognition. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02331-x
- Vo, K., Sun, Q. J., Nunez, M. D., Vandekerckhove, J., & Srinivasan, R. (2024). Deep latent variable joint cognitive modeling of neural signals and human behavior. NeuroImage, 291, Article 120559. Advance online publication. https://doi.org/10.1016/j.neuroimage.2024.120559
2023
Ghaderi-Kangavari, A., Parand, K., Ebrahimpour, R., Nunez, M. D., & Rad, J. A. (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. https://doi.org/10.1080/20445911.2023.2187714 [details]- Ghaderi-Kangavari, A., Rad, J. A., & Nunez, M. D. (2023). A General Integrative Neurocognitive Modeling Framework to Jointly Describe EEG and Decision-making on Single Trials. Computational Brain and Behavior, 6(3), 317–376. https://doi.org/10.1007/s42113-023-00167-4
2022
- Ghaderi-Kangavari, A., Rad, J. A., Parand, K., & Nunez, M. D. (2022). Neuro-cognitive models of single-trial EEG measures describe latent effects of spatial attention during perceptual decision making. Journal of Mathematical Psychology, 111, Article 102725. https://doi.org/10.1016/j.jmp.2022.102725 [details]
- Nunez, M. D., Charupanit, K., Sen-Gupta, I., Lopour, B. A., & Lin, J. J. (2022). Beyond rates: time-varying dynamics of high frequency oscillations as a biomarker of the seizure onset zone. Journal of Neural Engineering, 19(1), Article 016034. Advance online publication. https://doi.org/10.1088/1741-2552/ac520f [details]
- Sun, Q. J., Vo, K., Lui, K., Nunez, M., Vandekerckhove, J., & Srinivasan, R. (2022). Decision SincNet: Neurocognitive models of decision making that predict cognitive processes from neural signals. In 2022 International Joint Conference on Neural Networks (IJCNN): 2022 conference proceedings (pp. 5258-5266). IEEE. https://doi.org/10.1109/IJCNN55064.2022.9892272 [details]
2021
- Jun, E. J., Bautista, A. R., Nunez, M. D., Allen, D. C., Tak, J. H., Alvarez, E., & Basso, M. A. (2021). Causal role for the primate superior colliculus in the computation of evidence for perceptual decisions. Nature Neuroscience, 24(8), 1121-1131. https://doi.org/10.1038/s41593-021-00878-6
- Lui, K. K., Nunez, M. D., Cassidy, J. M., Vandekerckhove, J., Cramer, S. C., & Srinivasan, R. (2021). Timing of Readiness Potentials Reflect a Decision-making Process in the Human Brain. Computational Brain & Behavior, 4(3), 264-283. https://doi.org/10.1007/s42113-020-00097-5 [details]
2019
- Nunez, M. D., Gosai, A., Vandekerckhove, J., & Srinivasan, R. (2019). The latency of a visual evoked potential tracks the onset of decision making. NeuroImage, 197, 93-108. https://doi.org/10.1016/j.neuroimage.2019.04.052
- Nunez, P. L., Nunez, M. D., & Srinivasan, R. (2019). Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review. Brain Topography, 32(2), 193-214. https://doi.org/10.1007/s10548-019-00701-3
- Schubert, A. L., Nunez, M. D., Hagemann, D., & Vandekerckhove, J. (2019). Individual Differences in Cortical Processing Speed Predict Cognitive Abilities: a Model-Based Cognitive Neuroscience Account. Computational Brain and Behavior, 2(2), 64-84. https://doi.org/10.1007/s42113-018-0021-5
2018
- Bridwell, D. A., Cavanagh, J. F., Collins, A. G. E., Nunez, M. D., Srinivasan, R., Stober, S., & Calhoun, V. D. (2018). Moving beyond ERP components: A selective review of approaches to integrate EEG and behavior. Frontiers in Human Neuroscience, 12, Article 106. https://doi.org/10.3389/fnhum.2018.00106
- Charupanit, K., Nunez, M. D., Bernardo, D., Bebin, M., Krueger, D. A., Northrup, H., Sahin, M., Wu, J. Y., & Lopour, B. A. (2018). Automated Detection of High Frequency Oscillations in Human Scalp Electroencephalogram. In 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 (pp. 3116-3119). Article 8513033 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2018.8513033
2017
- Nunez, M. D., Vandekerckhove, J., & Srinivasan, R. (2017). How attention influences perceptual decision making: Single-trial EEG correlates of drift-diffusion model parameters. Journal of Mathematical Psychology, 76, 117-130. https://doi.org/10.1016/j.jmp.2016.03.003
2016
- Nunez, M. D., Nunez, P. L., & Srinivasan, R. (2016). Electroencephalography (EEG): neurophysics, experimental methods, and signal processing. In Handbook of Neuroimaging Data Analysis (1st ed.). https://doi.org/10.13140/rg.2.2.12706.63687
2015
- Nunez, M. D., Srinivasan, R., & Vandekerckhove, J. (2015). Individual differences in attention influence perceptual decision making. Frontiers in Psychology, 6, Article 18. https://doi.org/10.3389/fpsyg.2015.00018
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Ancillary activities
No ancillary activities
Ghaderi-Kangavari, A., Parand, K., Ebrahimpour, R., Nunez, M. D., & Rad, J. A. (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.