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Posts
How likely that someone we know dies from COVID-19?
Published:
The pandemic caused by the SARS-CoV-2 virus continues to spread and dominate daily life in 2020. Yet, despite the alarming numbers reported (“X millions of cases!”) it can feel abstract. As humans, we tend to care a lot more about our tribe than about anonymous people. With that in mind, what is the probability someone we care about dies from COVID-19? Read more
2AM, somewhere over the Atlantic Ocean
Published:
I’m one of the very few not sleeping in the airplane, hopefully including the pilots. I have a window seat, and the opportunity to write under a sky full of stars over the Atlantic Ocean seemed too precious not to take. Here I am, higher than the Everest and 4x faster than an ICE train. If the airplane went a little faster there would be a bang and I would be faster than the speed of sound. If it went up a little I would confirm that, indeed, the Earth is round. A little more and the number of stars in the moonlit sky would explode. Going further, I’d be able to look down and conclude that our planet really is a pale blue dot. Maybe I will in the future, if space tourism happens in my lifetime. Read more
publications
Inhibition as a determinant of activity and criticality in dynamical networks
Published in arXiv, 2017
Recommended citation: Pinheiro Neto, J., de Aguiar, M. A. M., Brum, J. A., & Bornholdt, S. (2017). Inhibition as a determinant of activity and criticality in dynamical networks. arXiv 1712.08816
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Operating in a Reverberating Regime Enables Rapid Tuning of Network States to Task Requirements
Published in Frontiers in Systems Neuroscience, 2018
Recommended citation: Wilting, J., Dehning, J., Pinheiro Neto, J., Rudelt, L., Wibral, M., Zierenberg, J., & Priesemann, V. (2018). Operating in a Reverberating Regime Enables Rapid Tuning of Network States to Task Requirements. Frontiers in Systems Neuroscience, 12(November).
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Sampling effects and measurement overlap can bias the inference of neuronal avalanches
Published in arXiv, 2019
Recommended citation: Neto, J. P., Spitzner, F. P., & Priesemann, V. (2019). Sampling effects and measurement overlap can bias the inference of neuronal avalanches. arXiv:1911.10824.
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Inferring COVID-19 spreading rates and potential change points for case number forecasts
Published in Science, 2020
Recommended citation: Dehning, J., Zierenberg, J., Spitzner, F. P., Wibral, M., Neto, J. P., Wilczek, M., & Priesemann, V. (2020). Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions. Science, 15,eabb9789
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MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity
Published in arXiv, 2020
Recommended citation: Spitzner, F. P., Dehning, J., Wilting, J., Hagemann, A., Neto, J. P., Zierenberg, J., & Priesemann, V. (2020). MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity. http://arxiv.org/abs/2007.03367
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teaching
Network Science of Online Interactions
, University of Konstanz, SEDS Masters, 2023
Master-level course on network science focused on online interactions (6 ECTS). Read more
Social Networks
, RWTH Aachen University, CSSH Masters, 2024
Master-level course on social network analysis and theory. Read more
Micro-Degree Artificial intelligence and Society
, University of Graz, 2025
Teaching of the practical module of the Micro-Degree Artificial intelligence and Society. Read more
Arqus Summer School
, Graz University, 2025
Fundamental Lectures on AI at the “Artifical Intelligence & Digital Transformation Summer School”. Read more