Prof. Dr. Anna Levina (Martius)

Contact

University of Tübingen
Maria von Linden Str. 6,
2^nd floor
Email-address: anna.levinaspam prevention@uni-tuebingen.de

Main research:

Self-organization of neuronal activity
Critical dynamics in neuronal networks
Excitation/Inhibition balance in cortical circuits
Mathematics of criticality
Complex networks

Research Projects

Short CV

2024 -

Permanent group leader, apl. Prof (equivalent of Ass. Prof.)

University of Tübingen

2018-2024

Assistant Professor for Computational Neuroscience

University of Tübingen

2017-2018

Group leader

University of Tübingen

20015-2017

IST Fellow

Institute of Science and Technology Austria

2011-2015

Associated researcher

Max Plank Institute for Mathematics in the Sciences

2011-2015

Postdoc and PI

Bernstein Center for Computational Neuroscience

2008-2011

Postdoc

Max Plank Institute for Dynamics and Self-Organization Göttingen

2008

Ph.D. in Mathematics

University of Göttingen

2003

Diploma in Mathematics

St. Petersburg State University, Russia

Selected publications:

Journal articles

Spieler, A., Martius, G., & Levina, A. (2026). Scaling laws and tradeoffs in recurrent networks of expressive neurons. Advances in Neural Information Processing Systems (NeurIPS 2026). link
Barretto-Bittar, J., Levina, A., Giannakakis, E., & Zeraati, R. (2026). Diffusion of neuromodulators for temporal credit assignment. Proceedings of the National Academy of Sciences, 123(38), e2608831123. link
Zeraati, R., Levina, A., Macke, J. H., & Gao, R. (2026). Neural timescales from a computational perspective. Nature Neuroscience, 29(7), 1534–1547. link
Azizpour, S., Priesemann, V., Zierenberg, J., & Levina, A. (2026). Finite integration time can shift optimal sensitivity away from criticality. Communications Physics, 9, 119. link
Giannakakis, E., Vinogradov, O., Buendía, V., & Levina, A. (2024). Structural influences on synaptic plasticity: The role of presynaptic connectivity in the emergence of E/I co-tuning. PLoS Computational Biology, 20(10), e1012510. link
Safavi, S., Chalk, M., Logothetis, N. K., & Levina, A. (2024). Signatures of criticality in efficient coding networks. Proceedings of the National Academy of Sciences, 121(41), e2302730121. link
Spieler, A., Rahaman, N., Martius, G., Schölkopf, B., & Levina, A. (2024). The expressive leaky memory neuron: An efficient and expressive phenomenological neuron model can solve long-horizon tasks. The Twelfth International Conference on Learning Representations (ICLR 2024). link
Zeraati, R., Shi, Y.-L., Steinmetz, N. A., Gieselmann, M. A., Thiele, A., Moore, T., Levina, A., & Engel, T. A. (2023). Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity. Nature Communications, 14, 1858. link
Levina, A., Priesemann, V., & Zierenberg, J. (2022). Tackling the subsampling problem to infer collective properties from limited data. Nature Reviews Physics, 4, 770–784. link
Zeraati, R., Engel, T. A., & Levina, A. (2022). A flexible Bayesian framework for unbiased estimation of timescales. Nature Computational Science, 2, 193–204. link
Sukenik, N., Vinogradov, O., Weinreb, E., Segal, M., Levina, A., & Moses, E. (2021). Neuronal circuits overcome imbalance in excitation and inhibition by adjusting connection numbers. Proceedings of the National Academy of Sciences, 118(12), e2018459118. link
Fardet, T., & Levina, A. (2020). Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions. PLoS Computational Biology, 16(12), e1008503. link
Zierenberg, J., Wilting, J., Priesemann, V., & Levina, A. (2020). Tailored ensembles of neural networks optimize sensitivity to stimulus statistics. Physical Review Research, 2, 013115. link
Das, A., & Levina, A. (2019). Critical neuronal models with relaxed timescale separation. Physical Review X, 9, 021062. link
Levina, A., & Priesemann, V. (2017). Subsampling scaling. Nature Communications, 8, 15140. link
Effenberger, F., Jost, J., & Levina, A. (2015). Self-organization in balanced state networks by STDP and homeostatic plasticity. PLoS Computational Biology, 11(9), e1004420. link
Nagler, J., Levina, A., & Timme, M. (2011). Impact of single links in competitive percolation. Nature Physics, 7, 265–270. link
Levina, A., Herrmann, J. M., & Geisel, T. (2009). Phase transitions towards criticality in a neural system with adaptive interactions. Physical Review Letters, 102, 118110. link
Levina, A., Herrmann, J. M., & Geisel, T. (2007). Dynamical synapses causing self-organized criticality in neural networks. Nature Physics, 3, 857–860. link

Book chapters

Priesemann V., Levina A., Wilting J. (2019) Assessing Criticality in Experiments. In: Tomen N., Herrmann J., Ernst U. (eds) The Functional Role of Critical Dynamics in Neural Systems. Springer Series on Bio- and Neurosystems, vol 11. Springer.
Levina A, Herrmann JM, Geisel T. Theoretical neuroscience of self-organized criticality: from formal approaches to realistic models. Criticality in Neural Systems. 2014.

Functions and memberships:

Equality officer, Department of Computer Science
Board member of the Bernstein Center Tübingen
Board member of CIN