Publications

2025

  1. Dynamically rich states in balanced networks induced by single-neuron dynamics
    Moritz Drangmeister, Rainer Engelken, Jan-Hendrik Schleimer, and Susanne Schreiber
    bioRxiv, 2025
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2024

  1. sparse-chaos.png
    Sparse chaos in cortical circuits
    Rainer Engelken, Michael Monteforte, and Fred Wolf
    2024
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  2. Understanding and Optimizing Temporal Credit Assignment in Biological and Artificial Neural Networks using Dynamical Systems Theory
    Rainer Engelken and L. F. Abbott
    In Proceedings of the Cognitive Computational Neuroscience Conference (CCN 2024), 2024
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  3. Analyzing and Improving Surrogate Gradient Training in Binary Neural Networks Using Dynamical Systems Theory
    Rainer Engelken and L. F. Abbott
    In ICML Workshop: Differentiable Almost Everything, 2024
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2023

  1. gradient-flossing.png
    Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians
    Rainer Engelken
    In Advances in Neural Information Processing Systems, 2023
    NeurIPS 2023, Poster
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  2. sparse-prop3.svg
    SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks
    Rainer Engelken
    In Advances in Neural Information Processing Systems, 2023
    NeurIPS 2023, Poster
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  3. rate-chaos2.png
    Lyapunov spectra of chaotic recurrent neural networks
    Rainer Engelken, Fred Wolf, and L. F. Abbott
    Physical Review Research, 2023
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  4. Boosting of neural circuit chaos at the onset of collective oscillations
    Agostina Palmigiano, Rainer Engelken, and Fred Wolf
    eLife, 2023
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2022

  1. A time-resolved theory of information encoding in recurrent neural networks
    Rainer Engelken and Sven Goedeke
    In Advances in Neural Information Processing Systems, 2022
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  2. Input correlations impede suppression of chaos and learning in balanced firing-rate networks
    Rainer Engelken, Alessandro Ingrosso, Ramin Khajeh, Sven Goedeke, and L. F. Abbott
    PLOS Computational Biology, 2022
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  3. Curriculum learning as a tool to uncover learning principles in the brain
    Daniel R. Kepple, Rainer Engelken, and Kanaka Rajan
    In International Conference on Learning Representations (ICLR), 2022
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2016

  1. A reanalysis of “Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons”
    Rainer Engelken, Farzad Farkhooi, David Hansel, Carl Vreeswijk, and Fred Wolf
    F1000Research, 2016
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2014

  1. Dynamical models of cortical circuits
    Fred Wolf, Rainer Engelken, Maximilian Puelma-Touzel, Juan Daniel Flórez Weidinger, and Andreas Neef
    Current Opinion in Neurobiology, 2014
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