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— The computational function of neural networks is thought to depend primarily on the learning/plasticity function carried out at the synapse. Neuromorphic circuit realizations have taken this into account by implementing a variety of synaptical processing functions, with most recent synapse circuits replicating some form of Spike Time Dependent Plasticity(More)
In this article, we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from(More)
Memristive devices have recently been proposed as efficient implementations of plastic synapses in neuromorphic systems. The plasticity in these memristive devices , i.e. their resistance change, is defined by the applied waveforms. This behavior resembles biological synapses, whose plasticity is also triggered by mechanisms that are determined by local(More)
The Bienenstock-Cooper-Munroe (BCM) rule is one of the best-established learning formalisms for neural tissue. However, as it is based on pulse rates, it can not account for recent spike-based experimental protocols that have led to spike timing dependent plasticity (STDP) rules. At the same time, STDP is being challenged by experiments exhibiting more(More)
This paper presents a hardware implementation of a fully synthesizable, technology-independent clock generator. The design is based on an ADPLL architecture described in VHDL and characterized by a digital controlled oscillator with high frequency resolution and low jitter. Frequency control is done by using a robust regulation algorithm to allow a defined(More)
A switched-capacitor (SC) neuromorphic system for closed-loop neural coupling in 28 nm CMOS is presented, occupying 600 um by 600 um. It offers 128 input channels (i.e., presynaptic terminals), 8192 synapses and 64 output channels (i.e., neurons). Biologically realistic neuron and synapse dynamics are achieved via a faithful translation of the behavioural(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: Keywords: Activity-dependent synapses Transient pulse transmission Modulated pulse(More)
Rate based (Bienenstock-Cooper-Munroe, BCM) and spike timing dependent plasticity (STDP) are the two principal learning behaviors found at cortical synapses. Some BCM induction protocols have been shown to be compatible with STDP rules, thus combining both forms of plasticity. However, we demonstrate that the majority of actual experimental BCM protocols(More)
When entering a synapse, presynaptic pulse trains are filtered according to the recent pulse history at the synapse and also with respect to their own pulse time course. Various behavioral models have tried to reproduce these complex filtering properties. In particular, the quantal model of neurotransmitter release has been shown to be highly selective for(More)
State-of-the-art large-scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an field programmable gate arrays (FPGA)-maintained environment. The(More)