• New Article: An alternative to classic deep learning datasets!
  • New article in eLife: how natural-gradient descent enable efficient synaptic plasticity!
  • Kreutzer2022 EKeLife
    "Natural-gradient learning for spiking neurons".
    See Publications

  • DEEP MINDS Podcast (in German) - Info
  • From Cortical Microcircuits to Consciousness Symposium - Apr 11-13 - Info
  • Nicolas Deperrois presented the Poster "Learning cortical representations through perturbed and adversarial dreaming"

  • New contribution to eLife: Learning across three different global brain states!
  • From Neuroscience to Artificially Intelligent Systems (NAISys) - Apr 5-9 - Info
  • Paul Haider presented the Poster "Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons"

  • Now in PCB: How cortical oscillations shape spike-based probabilistic inference in the brain!
  • PCB2022
    "Cortical oscillations support sampling-based computations in spiking neural networks.
    See Publications

  • NICE Conference - Mar 29-Apr 1 - Info
    Three talks from Team NeuroTMA! Respectively, on March 29, 31 and April 1
    Well done Andi for receiving the Best Early Researcher
    Presentation Award from NEUROTECH!!

  • Happy to have contributed to shaping the course of neuroscience in the last HBP position paper! - Info
  • COSYNE Conference & Workshop - Mar 17-22 - Info
  • Swiss Computational Neuroscience Retreat 2022 - Mar 2-4 - Info
  • Jakob, Paul, Mihai and Walter had a great time in Crans-Montana among fellow computational neuroscientists and got to present some of our latest research:
    talked about "Cortical representation learning & Bayes-optimal cue integration"
    and Paul about "Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons"

  • SIAM Conference on Parallel Processing for Scientific Computing - Feb 23-26 - Info
  • 6th HBP Student Conference on Interdisciplinary Brain Research - Feb. 22-25 - Info
  • New Preprint: a dataset of abstract paintings and nonfigurative art objects!
    "DELAUNAY: a dataset of abstract art for psychophysical and machine learning research".
    See Publications

  • New Article in SciPost Physics: our first demonstration of representing entangled quantum states on BrainScaleS!
  • SciPost2022
    "Spiking neuromorphic chip learns entangled quantum states".
    See Publication


  • Our group leader speaks his mind!
  • Logo
    Read the Interview that Mihai gave to Uniaktuell - the online magazine of the University of Bern - on Science and Politics.

  • New Article in NeurIPS: Learning with slow neurons is not a problem anymore!
    And this awesome work was selected for an oral presentation at the 35th Conference on Neural Information Processing Systems (NeurIPS 2021)!
    Paul Haider 's Talk (Oral session 1) was scheduled on Tuesday, December 7 followed by a Poster presentation (session 3) on Wednesday, December 8 - Info
  • LEnews
    "Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons".
    See Publication - Press Release

  • New lab member (December)
  • Very Happy that Timo Gierlich , previously one of our Master's students,
    decided to pursue his work as a PhD student with us!

  • Another news article on our Fast&Deep work in Singularity Hub!
    Singularity Hub offers daily news coverage, feature articles, analysis, and insights on key breakthroughs and future trends in science and technology.
  • wrote a news article on our latest Fast&Deep work!
    This magazine is Germany's first and largest online magazine for mixed reality and the future of computers.
  • New Article in eLife: Evolving to Learn!
  • Our NMI article featured on Tech Xplore!
    The News website Tech Xplore covers the latest engineering, electronics and technology advances. Following the recent publication in Nature Machine Intelligence, Ingrid Fadelli of Tech Xplore reached out to us.
    The resulting interview includes a short overview of our study.
  • ACAIN 2021 - 1st International Advanced Course & Symposium on Artificial Intelligence & Neuroscience - Oct. 5-8 - Info
  • Four oral presentations:
    - Jakob Jordan "Learning Bayes-optimal dendritic opinion pooling".
    - Julian Göltz and Laura Kriener "Fast and energy-efficient neuromorphic deep learning with first-spike times".
    - Henrik Mettler "Evolving to Learn: Automating the search for interpretable, biologically plausible synaptic plasticity rules".
    - Agnes Korcsak-Gorzo "Cortical oscillations support sampling-based computations in spiking neural network".

  • New Preprint! Approximating the ground states of quantum spin models.
  • quantum2021
    "Variational learning of quantum ground states on spiking neuromorphic hardware".
    See Publications - Blog post

  • Bernstein Conference - Sep. 22 - Info
  • Now in Nature Machine Intelligence!
  • 2nd PhD and Postdoc Retreat of the Department of Physiology - Sep. 10 - Info
  • Congrats to Henrik and Jakob for winning two of the Idorsia prizes for academic excellence for best presentations, respectively, for best Long talk - Early PhDs and Popular Vote!


  • New Preprint! Learning across three different global brain states.
  • NDarXivFigbig
    "Memory semantization through perturbed and adversarial dreaming".
    See Publications

  • MESEC - MEditerranean SEminar For Consciousness - Sep. 9 - Info
  • As an invited speaker, Mihai Petrovici talked about "Aspects of cortical computation".

  • New lab member (September)
  • GECCO 2021 - The Genetic and Evolutionary Computation Conference
    July 12 - Info
  • Henrik Mettler presented the Poster "Evolving Neuronal Plasticity Rules using Cartesian Genetic Programming".

  • Read our Success Story on using the Fenix Supercomputing Infrastructure!
  • fenix
    "HPC Simulations Support Fast and Energy Efficient Deep Neuromorphic Learning"
    See Article

  • CNS*2021 - Computational Neuroscience Meeting - July 4 - Info
  • NeuroFrance 2021 Satellite Workshop - May 18 - Info
  • Julian Göltz talked about "Fast and deep: energy-efficient neuromorphic learning with first-spike times" at the NeuroFrance 2021 satellite workshop "Neuroscience and Artificial Intelligence" -> Abstract

  • New Preprint! Single neurons perform bayes-optimal cue integration.
  • pool
    "Learning Bayes-optimal dendritic opinion pooling".
    See Publications

  • NEUROTECH Education Programme: day 6 - Apr. 13 - Info

    To answer this question, Laura Kriener presented her work on "Fast and deep: energy-efficient neuromorphic learning with first-spike times" -> Recording

    We contributed three articles to the special issue "Brain-inspired Computing" of the European Research Consortium for Informatics and Mathematics Magazine (ERCIM).