Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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Dr. Viola Priesemann

Group: Neural Dynamics and Information Processing
Projects: Self-Organized Criticality in the Activity Dynamics of Neural Networks
Address:  Am Fassberg 17
37077 Göttingen
Office: 3.124
Phone: +49-(0)551-5176-405
Email: send email
  • Bernstein Fellow
  • Max Planck Research Group Leader "Neural Systems Theory"
  • Fellow of the Schiemann-Kolleg


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The human brain has amazing information processing capacities, which rely on the coordinated activity of 80 billion neurons, each of them interacting with thousands of other neurons. With the aim to understand how the collective neural dynamics ultimately gives rise to the brain’s information processing capacities, I work on a class of collective states, i.e. critical states, because these maximize information processing capacities in models. In this context I recently provided the first evidence that the human brain operates not in a critical state, but keeps a distance to criticality [Priesemann et al. 2013], despite the computational advantages of criticality. I confirmed these results for highly parallel spike recordings from rats, cats, and monkeys [Priesemann et al. 2014]. This indicates that maximizing information processing is not the only goal function for the brain. Based on these results, I suggest that the brain only tunes itself closer to criticality when strictly necessary for information processing. Else the brain maintains a larger safety margin, thereby losing processing capacity, but avoiding instability. In the near future, I want to reveal how the brain should allocate its resources and tune its distance to criticality for a given task. In the far future, this will provide insight of how information processing emerges from the collective neural dynamics in nervous systems.


Selected Publications

Link to the full list:

J. Zierenberg, J. Wilting & V. Priesemann, "Homeostatic Plasticity and External Input Shape Neural Netw", Physical Review X, 2018.

J. Wilting & V. Priesemann, "Inferring Collective Dynamical States from Widely Unobserved Systems", Nature Communications, 2018.

A. Levina & V. Priesemann, "Subsampling Scaling", Nature Communications, 2017.

M. Wibral, J. Lizier, V. Priesemann, "Bits from Brains for Biologically Inspried Computing", Front. Robotics and AI, 2015.

V. Priesemann, et al., “Spike avalanches in vivo suggest a driven, slightly subcritical brain state,” Front. Syst. Neurosci., 2014.

Publications (chronological - click here to see all publications)