ArticleFrontiers in neuroscience2022
The BrainScaleS-2 Accelerated Neuromorphic System With Hybrid Plasticity.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- Spike-based alignment learning solves the weight transport problem.Nature communications · 2026Article
- A Wilson-Cowan reservoir computer for interpretable spatiotemporal vision.Scientific reports · 2026Article
- Event-Based Vision at the Edge: A Review.Brain sciences · 2026Review
- Higher-order neuromorphic Ising machines-autoencoders and Fowler-Nordheim annealers are all you need for scalability.Nature communications · 2026Article
- A highly energy-efficient multi-core neuromorphic architecture for training deep spiking neural networks.Nature communications · 2026Article
- Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Advancing neuroengineering with Neuromorphic Twins.Nature communications · 2026Review
- Bioinspired spiking architecture enables energy constrained touch encoding.Nature communications · 2026Article
- Bridging the neuro-AI chasm: a framework for scalable, contextually adaptive training resources in large-scale brain data science.Frontiers in psychology · 2026Article
- Can neuromorphic computing help reduce AI's high energy cost?Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Modeling macroscopic brain dynamics with brain-inspired computing architecture.Nature communications · 2025Article
- Article
- Designing nonlinearity in a current-starved ring oscillator for reservoir computing hardware.Scientific reports · 2025Article
- Wafer-scale fabrication of memristive passive crossbar circuits for brain-scale neuromorphic computing.Nature communications · 2025Article
- DelGrad: exact event-based gradients for training delays and weights on spiking neuromorphic hardware.Nature communications · 2025Article
- A neuromorphic processor with on-chip learning for beyond-CMOS device integration.Nature communications · 2025Article
- Spiking Neural Networks for Multimodal Neuroimaging: A Comprehensive Review of Current Trends and the NeuCube Brain-Inspired Architecture.Bioengineering (Basel, Switzerland) · 2025Review
- Memristive Ion Dynamics to Enable Biorealistic Computing.Chemical reviews · 2025Review
- Decoupling model descriptions from execution: a modular paradigm for extensible neurosimulation with EDEN.Frontiers in neuroinformatics · 2025Article
- Efficient spiking convolutional neural networks accelerator with multi-structure compatibility.Frontiers in neuroscience · 2025Article
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10 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Since the beginning of information processing by electronic components, the nervous system has served as a metaphor for the organization of computational primitives. Brain-inspired computing today encompasses a class of approaches ranging from using novel nano-devices for computation to research into large-scale neuromorphic architectures, such as TrueNorth, SpiNNaker, BrainScaleS, Tianjic, and Loihi. While implementation details differ, spiking neural networks-sometimes referred to as the third generation of neural networks-are the common abstraction used to model computation with such systems. Here we describe the second generation of the BrainScaleS neuromorphic architecture, emphasizing applications enabled by this architecture. It combines a custom analog accelerator core supporting the accelerated physical emulation of bio-inspired spiking neural network primitives with a tightly coupled digital processor and a digital event-routing network.
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