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BP: Fachverband Biologische Physik
BP 24: Poster B: Active Biological Matter, Cell Mechanics, Systems Biology, Computational Biophysics, etc.
BP 24.30: Poster
Dienstag, 23. März 2021, 16:00–18:30, BPp
Tailored ensembles of neural networks optimize sensitivity to stimulus statistics — •Johannes Zierenberg1,2, Jens Wilting1, Viola Priesemann1,2, and Anna Levina3,4 — 1Max Planck Institute for Dynamics and Self-Organization, Am Fassberg 17, 37077 Göttingen, Germany — 2Bernstein Center for Computational Neuroscience, Am Fassberg 17, 37077 Göttingen, Germany — 3University of Tübingen, Max Planck Ring 8, 72076 Tübingen, Germany — 4Max Planck Institute for Biological Cybernetics, Max Planck Ring 8, 72076 Tübingen, Germany
The capability of a living organism to process stimuli with nontrivial intensity distributions cannot be explained by the proficiency of a single neural network. Moreover, it is not sufficient to maximize the dynamic range of the neural response; it is also necessary to tune the response to the intervals of stimulus intensities that should be reliably discriminated. We derive a class of neural networks where these intervals can be tuned to the desired interval. This allows us to tailor ensembles of networks optimized for arbitrary stimulus intensity distributions. We discuss potential applications in machine learning.