Analog VLSI and neural systems
Analog VLSI and neural systems
Retinomorphic vision systems: reverse engineering the vertebrate retina
Retinomorphic vision systems: reverse engineering the vertebrate retina
Neural networks with dynamic synapses
Neural Computation
Reading neuronal synchrony with depressing synapses
Neural Computation
Computing and learning with dynamic synapses
Pulsed neural networks
The Retinomorphic Approach: Pixel-Parallel Adaptive Amplification,Filtering, and Quantization
Analog Integrated Circuits and Signal Processing
Modeling Selective Attention Using a Neuromorphic Analog VLSI Device
Neural Computation
Analog VLSI circuits for short-term dynamic synapses
EURASIP Journal on Applied Signal Processing
Analog VLSI circuits for short-term dynamic synapses
EURASIP Journal on Applied Signal Processing
Synaptic Dynamics in Analog VLSI
Neural Computation
Spatio-temporal spike pattern classification in neuromorphic systems
Living Machines'13 Proceedings of the Second international conference on Biomimetic and Biohybrid Systems
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We describe a model of short-term synaptic depression that is derived from a circuit implementation. The dynamics of this circuit model is similar to the dynamics of some theoretical models of short-term depression except that the recovery dynamics of the variable describing the depression is nonlinear and it also depends on the presynaptic frequency. The equations describing the steady-state and transient responses of this synaptic model are compared to the experimental results obtained from a fabricated silicon network consisting of leaky integrate-and-fire neurons and different types of short-term dynamic synapses. We also show experimental data demonstrating the possible computational roles of depression. One possible role of a depressing synapse is that the input can quickly bring the neuron up to threshold when the membrane potential is close to the resting potential.