ArticleFrontiers in neuroscience2014
Real-time million-synapse simulation of rat barrel cortex.
Article in Frontiers in neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Cortical Representation of Touch in Silico.Neuroinformatics · 2022Article
- A model of lateral interactions as the origin of multiwhisker receptive fields in rat barrel cortex.Journal of computational neuroscience · 2022Article
- Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model.Frontiers in neuroscience · 2018Article
- GPUs Outperform Current HPC and Neuromorphic Solutions in Terms of Speed and Energy When Simulating a Highly-Connected Cortical Model.Frontiers in neuroscience · 2018Article
- Connecting the Brain to Itself through an Emulation.Frontiers in neuroscience · 2017Article
- Synapse-Centric Mapping of Cortical Models to the SpiNNaker Neuromorphic Architecture.Frontiers in neuroscience · 2016Article
- Large-Scale Simulations of Plastic Neural Networks on Neuromorphic Hardware.Frontiers in neuroanatomy · 2016Article
- Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations.PLoS computational biology · 2015Article
- NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors.Frontiers in neuroscience · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Simulations of neural circuits are bounded in scale and speed by available computing resources, and particularly by the differences in parallelism and communication patterns between the brain and high-performance computers. SpiNNaker is a computer architecture designed to address this problem by emulating the structure and function of neural tissue, using very many low-power processors and an interprocessor communication mechanism inspired by axonal arbors. Here we demonstrate that thousand-processor SpiNNaker prototypes can simulate models of the rodent barrel system comprising 50,000 neurons and 50 million synapses. We use the PyNN library to specify models, and the intrinsic features of Python to control experimental procedures and analysis. The models reproduce known thalamocortical response transformations, exhibit known, balanced dynamics of excitation and inhibition, and show a spatiotemporal spread of activity though the superficial cortical layers. These demonstrations are a significant step toward tractable simulations of entire cortical areas on the million-processor SpiNNaker machines in development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.