2015
DOI: 10.3389/fnins.2015.00141
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A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses

Abstract: Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network … Show more

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Cited by 554 publications
(499 citation statements)
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“…SpiNNaker [24], or the low-power analog ROLLS neuromorphic processor [26]. These platforms would be more straightforward to use in a closed-loop scenario, because networks on these chips will operate at exactly the same time scale as the brain, and recorded spikes can be injected into the network in real-time.…”
Section: Discussionmentioning
confidence: 99%
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“…SpiNNaker [24], or the low-power analog ROLLS neuromorphic processor [26]. These platforms would be more straightforward to use in a closed-loop scenario, because networks on these chips will operate at exactly the same time scale as the brain, and recorded spikes can be injected into the network in real-time.…”
Section: Discussionmentioning
confidence: 99%
“…Several platforms for neuromorphic computing have emerged, starting with the pioneering work of Carver Mead [23], up to rather recent developments like e.g. SpiNNaker [24], NeuroGrid [25], ROLLS [26], IBM's TrueNorth [27], or the systems developed at the University of Heidelberg [28], [29] (see [30] for a review). Aside from testing principles of neural computation [28], [31], [32], initial applications of neuromorphic hardware have been demonstrated for generic pattern recognition [27], [33].…”
Section: Introductionmentioning
confidence: 99%
“…One of the most recent chip designs presented in this review was developed by Qiao et al (2015). The Reconfigurable On-line Learning Spiking (ROLLS) neuromorphic processor contains 256 analog silicon neurons and a total of 131 072 synapses.…”
Section: The Rolls Neuromorphic Processormentioning
confidence: 99%
“…Like its predecessors, the ROLLS chip is able to operate in biological real-time. The power consumption in typical scenarios is 4 mW (Qiao et al, 2015). Special focus has been put on the implementation of different synaptic plasticity mechanisms, which will be discussed in Section 4.3.…”
Section: The Rolls Neuromorphic Processormentioning
confidence: 99%
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