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#spikingneuralnetwork — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #spikingneuralnetwork, aggregated by home.social.

  1. Submissions (short!) due for SNUFA spiking neural networks conference in <2 weeks!

    forms.cloud.microsoft/e/XkZLav

    More info at snufa.net/2025/

    Note that we normally get around 700 participants and recordings go on YouTube and get 100s-1000s views, so it's a good place to promote your work.

    Please repost.

    #neuroscience #SpikingNeuralNetwork #SpikingNeuralNetworks #snn #snufa

  2. I recently played around with #RateModels using #NESTsimulator. Compared to #SNN, RM focus on average firing rates of #NeuronPopulations, simplifying analysis of large networks. They effectively capture collective dynamics like #oscillations and #synchronization, though they miss precise spike timing details. Thus, both approaches have their merits. Here is a brief overview:

    🌍 fabriziomusacchio.com/blog/202

    #CompNeuro #Neuroscience #Python #PythonTutorial #SpikingNeuralNetwork

  3. I recently played around with #RateModels using #NESTsimulator. Compared to #SNN, RM focus on average firing rates of #NeuronPopulations, simplifying analysis of large networks. They effectively capture collective dynamics like #oscillations and #synchronization, though they miss precise spike timing details. Thus, both approaches have their merits. Here is a brief overview:

    🌍 fabriziomusacchio.com/blog/202

    #CompNeuro #Neuroscience #Python #PythonTutorial #SpikingNeuralNetwork

  4. I recently played around with #RateModels using #NESTsimulator. Compared to #SNN, RM focus on average firing rates of #NeuronPopulations, simplifying analysis of large networks. They effectively capture collective dynamics like #oscillations and #synchronization, though they miss precise spike timing details. Thus, both approaches have their merits. Here is a brief overview:

    🌍 fabriziomusacchio.com/blog/202

    #CompNeuro #Neuroscience #Python #PythonTutorial #SpikingNeuralNetwork

  5. I recently played around with #RateModels using #NESTsimulator. Compared to #SNN, RM focus on average firing rates of #NeuronPopulations, simplifying analysis of large networks. They effectively capture collective dynamics like #oscillations and #synchronization, though they miss precise spike timing details. Thus, both approaches have their merits. Here is a brief overview:

    🌍 fabriziomusacchio.com/blog/202

    #CompNeuro #Neuroscience #Python #PythonTutorial #SpikingNeuralNetwork

  6. I recently played around with #RateModels using #NESTsimulator. Compared to #SNN, RM focus on average firing rates of #NeuronPopulations, simplifying analysis of large networks. They effectively capture collective dynamics like #oscillations and #synchronization, though they miss precise spike timing details. Thus, both approaches have their merits. Here is a brief overview:

    🌍 fabriziomusacchio.com/blog/202

    #CompNeuro #Neuroscience #Python #PythonTutorial #SpikingNeuralNetwork

  7. 📚 New preprint by Vafaii, Galor & Yates: Brain-like variational inference. They derive #SpikingNeuralNetwork dynamics directly from variational free energy minimization via online natural #GradientDescent, yielding the iterative Poisson #VAE (iP-VAE) with strong sparsity, reconstruction & #BiologicalPlausibility.

    🌍 arxiv.org/abs/2410.19315
    🧑‍💻 github.com/hadivafaii/Iterativ

    #Neuroscience #MachineLearning #SNN #CompNeuro

  8. Proud to have managed to finish a #neuromorphic manuscript, with Chiara De Luca, Mirco Tincani and Elisa Donati just before the end of the year!

    It demonstrates the benefits of using #braininspired principles of computation for achieving robust computation across multiple time-scales, despite the inherent variability of the underlying computational substrate (silicon neurons that emulate faithfully biological ones):
    A neuromorphic multi-scale approach for heart rate and state detection
    doi.org/10.21203/rs.3.rs-57373
    #neuromorphic #wearable #neuroai #SpikingNeuralNetwork