Zhijun Yang

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We use a mathematical model of the calyx of Held to explore information transmission at this giant glutamatergic synapse. The significant depression of the postsynaptic response to repeated stimulation in vitro is a result of various activity-dependent processes in multiple timescales, which can be reproduced by multiexponential functions in this model.(More)
We propose a simplified depth-from-motion vision model based on leaky integrate-and-fire (LIF) neurons for edge detection and two-dimensional depth recovery. In the model, every LIF neuron is able to detect the irradiance edges passing through its receptive field in an optical flow field, and respond to the detection by firing a spike when the neuron's(More)
— To localize a seen object, the superior colliculus of the barn owl integrates the visual and auditory localization cues which are accessed from the sensory system of the brain. These cues are formed as visual and auditory maps, thus the alignment between visual and auditory maps is very important for accurate localization in prey behavior. Blindness or(More)
The visual and auditory map alignment in the Superior Colliculus (SC) of barn owl is important for its accurate localization for prey behavior. Prism learning or Blindness may interfere this alignment and cause loss of the capability of accurate prey. However, juvenile barn owl could recover its sensory map alignment by shifting its auditory map. The(More)
Neural oscillation is one of the most extensively investigated topics of artificial neural networks. Scientific approaches to the functionalities of both natural and artificial intelligences are strongly related to mechanisms underlying oscillatory activities. This paper concerns itself with the assumption of the existence of central pattern generators(More)
This paper presents a novel approach to the emulation of locomotor central pattern generators (CPGs) of legged animals. Based on Scheduling by Multiple Edge Reversal (SMER), a simple but powerful distributed algorithm, it is shown how oscillatory building blocks (OBBs) can be created and how OBB-based networks can be implemented as asymmetric Hopfield-like(More)
We present a large-scale Neuromorphic model based on integrate-and-fire (IF) neurons that analyses objects and their depth within a moving visual scene. A feature-based algorithm builds a luminosity receptor field as an artificial retina, in which the IF neurons act both as photoreceptors and processing units. We show that the IF neurons can trace an(More)