Computer simulation of neural matter is a promising methodology for understanding the function of the brain. Recent anatomical studies have mapped the intricate structure of cortex, and these data have been exploited in numerous simulations attempting to explain its function. However, the largest of these models run inconveniently slowly and require vast amounts of electrical power, which hinders useful experimentation. SpiNNaker is a novel computer architecture designed to address these problems using low-power microprocessors and custom communication hardware. We use four SpiNNaker chips (of a planned fifty thousand) to simulate, in real-time, a cortical circuit of ten thousand spiking neurons and four million synapses. In this simulation...
To understand and mimic the working mechanism of the brain, neuroscientists rely on brain simulation...
The SpiNNaker project aims to develop parallel computer systems with more than a million embedded pr...
simulating a billion spiking neurons in real time. Fortunately, such an application is an ideal cand...
SpiNNaker is a digital neuromorphic hardware designed to reduce simulation time and power consumptio...
The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale ...
The modelling of large systems of spiking neurons is computationally very demanding in terms of proc...
The modelling of large systems of spiking neurons is computationally very demanding in terms of proc...
Abstract—The modelling of large systems of spiking neurons is computationally very demanding in term...
While the adult human brain has approximately 8.8 × 1010 neurons, this number is dwarfed by its 1 × ...
SpiNNaker (Spiking Neural Network Architecture) is a specialized computing engine, intended for real...
The cortical microcircuit is a building block of the mammalian brain. In a model of the network belo...
Neurobiologically realistic, large-scale cortical and sub-cortical simulations are bound to play a k...
We present a biologically-inspired and scalable model of the Basal Ganglia (BG) simulated on the Spi...
By building and simulating neural systems we hope to understand how the brain may work and use this ...
This article employs the new IBM INC-3000 prototype FPGA-based neural supercomputer to implement a w...
To understand and mimic the working mechanism of the brain, neuroscientists rely on brain simulation...
The SpiNNaker project aims to develop parallel computer systems with more than a million embedded pr...
simulating a billion spiking neurons in real time. Fortunately, such an application is an ideal cand...
SpiNNaker is a digital neuromorphic hardware designed to reduce simulation time and power consumptio...
The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale ...
The modelling of large systems of spiking neurons is computationally very demanding in terms of proc...
The modelling of large systems of spiking neurons is computationally very demanding in terms of proc...
Abstract—The modelling of large systems of spiking neurons is computationally very demanding in term...
While the adult human brain has approximately 8.8 × 1010 neurons, this number is dwarfed by its 1 × ...
SpiNNaker (Spiking Neural Network Architecture) is a specialized computing engine, intended for real...
The cortical microcircuit is a building block of the mammalian brain. In a model of the network belo...
Neurobiologically realistic, large-scale cortical and sub-cortical simulations are bound to play a k...
We present a biologically-inspired and scalable model of the Basal Ganglia (BG) simulated on the Spi...
By building and simulating neural systems we hope to understand how the brain may work and use this ...
This article employs the new IBM INC-3000 prototype FPGA-based neural supercomputer to implement a w...
To understand and mimic the working mechanism of the brain, neuroscientists rely on brain simulation...
The SpiNNaker project aims to develop parallel computer systems with more than a million embedded pr...
simulating a billion spiking neurons in real time. Fortunately, such an application is an ideal cand...