Bernstein Seminar

December 19, 2017

Freiburg i. Br. (Germany)




Tuesday, 19 december 2017 - 17:15 hours


"Self-organization of neuronal networks and its assessment under subsampling"

Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network.

In real-world applications, observations are often constrained to a small fraction of a system. For example, reconstruction of the cortical network topology and statistics, as one we attempted to mimic in the model from the first part of the talk, is based only on a tiny fraction of all synaptic connections. Such spatial subsampling can be caused by the inaccessibility or the sheer size of the system, and cannot be overcome by longer sampling. Spatial subsampling can strongly bias inferences about a system’s aggregated properties. To overcome the bias, we derive analytically a subsampling scaling framework that is applicable to different observables, including distributions of neuronal avalanches, of number of people infected during an epidemic outbreak, and of node degrees. We demonstrate how to infer the correct distributions of the underlying full system, how to apply it to distinguish critical from subcritical systems, and how to disentangle subsampling and finite size effects. Lastly, we apply subsampling scaling to neuronal avalanche models and to recordings from developing neural networks. We show that only mature, but not young networks follow power-law scaling, indicating self-organization to criticality during development.


Hosted by Stefan Rotter.



16-01-2018           Prof. Andreas Draguhn (Heidelberg University) "Oscillating hippocampal networks – patterns, mechanisms and potential ‘meaning’ of cooperative neuronal activity"

31-01-2018           Prof. Matthew Rushworth (University of Oxford, UK)

13-02-2018           Prof. Julijana Gjorgjieva (MPI Brain Research)

13-03-2018           Prof. Siegrid Löwel (Göttingen University) "The dynamic architecture of the adult visual cortex: how to keep my brain young?"

27-03-2018           Prof. Tomislav Milekovic (University of Geneve) "Neuroprostheses based on intracortical recordings of neural activity for restoration of movement and communication of people with paralysis"



Tuesday, 19 december 2017

17:15 hours

Lecture Hall (ground floor)
Bernstein Center Freiburg
Hansastraße 9a
79104 Freiburg