Regensburg 2019 – wissenschaftliches Programm
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BP: Fachverband Biologische Physik
BP 15: Focus session: Collective Dynamics in Neural Networks
BP 15.8: Vortrag
Mittwoch, 3. April 2019, 11:45–12:00, H11
Homeostatic plasticity and external input shape neural network dynamics — •Johannes Zierenberg1,2, Jens Wilting1, and Viola Priesemann1,2 — 1Max-Planck-Institut für Dynamik und Selbstorganisation, Göttingen — 2Bernstein Center for Computational Neuroscience, Göttingen
In vitro and in vivo spiking activity clearly differ. Whereas networks in vitro develop strong bursts separated by periods of silence, in vivo cortical networks show continuous activity. This is puzzling as both networks presumably share similar single-neuron dynamics and plasticity rules. We propose that the defining difference between in vitro and in vivo dynamics is the strength of external input. In vitro, networks are virtually isolated, whereas in vivo every brain area receives continuous input. We analyze a model of spiking neurons in which the input strength, mediated by spike rate homeostasis, determines the characteristics of the dynamical state. Our analytical and numerical results on various network topologies show that under increasing input, homeostatic plasticity generates distinct dynamic states, from bursting, to close-to-critical, reverberating and irregular states. This implies that the dynamic state of neural networks can readily adapt to the input strengths. Our results match experimental spike recordings: in vitro bursts are consistent with a state generated by very low network input (< 0.1%), whereas in vivo activity suggests that on the order of 1% recorded spikes are input-driven, resulting in reverberating dynamics. This implies that one could impose in vivo-like activity in in vitro preparations by exposition to weak long-term stimulation.