Self-organization and optimality in neuronal networks

Our research interests lay in the area roughly situated between mathematics, physics, and neuroscience, tapping from time to time in all of those. Our goal is to uncover the origins of brain computational powers. We enjoy studying simplified models that enable the understanding of mechanisms of a system's functioning and not merely reproduce the observed statistics. I believe the self-organization on all levels is necessary for the functioning of an intelligent system (such as ourselves) in the complex world.
Often, to learn something new, we need to develop new methods to analyze existing data. We like to find new ways of looking at multidimensional neural data, complex networks, and subsampled systems.


Dr. Anna Levina
Research Group Leader

 07071 / 29-70914 

Research lines

Excitatory/Inhibitory networks

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State-dependent neural dynamics

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Network structure and subsampling

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Computation close to criticality

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Collective dynamics and emergence

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Neuronal constraints and self-organization

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New paper in PRR

Weighted directed clustering: Interpretations and requirements for heterogeneous, inferred, and…

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