Search results for "spike"
showing 10 items of 106 documents
Adaptive-threshold neural spike detection by noise-envelope tracking
2007
A new method for adaptive threshold setting is implemented and used in two threshold-based spike detectors: simple threshold and nonlinear energy operator. Detection quality assessment is performed using both a set of artificially generated signals and a real neural recording. Receiver operating curves are obtained and results show that, compared to fix threshold, adaptive threshold setting yields performance improvement.
Information – theoretic characterization of concurrent activity of neural spike trains
2021
The analysis of massively parallel spike train recordings facilitates investigation of communications and synchronization in neural networks. In this work we develop and evaluate a measure of concurrent neural activity, which is based on intrinsic firing properties of the recorded neural units. An overall single neuron activity is unfolded in time and decomposed into working and non-firing state, providing a coarse, binary representation of the neurons functional state. We propose a modified measure of mutual information to reflect the degree of simultaneous activation and concurrency in neural firing patterns. The measure is shown to be sensitive to both correlations and anti-correlations,…
Hardware-accelerated spike train generation for neuromorphic image and video processing
2014
Recent studies concerning Spiking Neural Networks show that they are a powerful tool for multiple applications as pattern recognition, image tracking, and detection tasks. The basic functional properties of SNN reside in the use of spike information encoding as the neurons are specifically designed and trained using spike trains. We present a novel and efficient frequency encoding algorithm with Gabor-like receptive fields using probabilistic methods and targeted to FPGA for online pro-cessing. The proposed encoding is versatile, modular and, when applied to images, it is able to perform simple image transforms as edge detection, spot detection or removal, and Gabor-like filtering without a…
FPGA implementation of Spiking Neural Networks supported by a Software Design Environment
2011
Abstract This paper is focused on the creation of Spiking Neural Networks (SNN) in hardware due to their advantages for certain problem solving and their similarity to biological neural system. One of the main uses of this neural structure is pattern classification. The chosen model for the spiking neuron is the Spike Response Model (SRM). For SNN design and implementation, a software application has been developed to provide easy creation, simulation and automatic generation of the hardware model. VHDL was used for the hardware model. This paper describes the functionality of SNN and the design procedure followed to obtain a working neural system in both software and hardware. Designed VHD…
Noise-assisted persistence and recovery of memory state in a memristive spiking neuromorphic network
2021
Abstract We investigate the constructive role of an external noise signal, in the form of a low-rate Poisson sequence of pulses supplied to all inputs of a spiking neural network, consisting in maintaining for a long time or even recovering a memory trace (engram) of the image without its direct renewal (or rewriting). In particular, this unique dynamic property is demonstrated in a single-layer spiking neural network consisting of simple integrate-and-fire neurons and memristive synaptic weights. This is carried out by preserving and even fine-tuning the conductance values of memristors in terms of dynamic plasticity, specifically spike-timing-dependent plasticity-type, driven by overlappi…
Fast spiking neural network architecture for low-cost FPGA devices
2012
Spiking Neural Networks (SNN) consist of fully interconnected computation units (neurons) based on spike processing. This type of networks resembles those found in biological systems studied by neuroscientists. This paper shows a hardware implementation for SNN. First, SNN require the inputs to be spikes, being necessary a conversion system (encoding) from digital values into spikes. For travelling spikes, each neuron interconnection is characterized by weights and delays, requiring an internal neuron processing by a Postsynaptic Potential (PSP) function and membrane potential threshold evaluation for a postsynaptic output spike generation. In order to model a real biological system by arti…
Frequency spike encoding using Gabor-like receptive fields
2014
Abstract Spiking Neural Networks (SNN) are a popular field of study. For a proper development of SNN algorithms and applications, special encoding methods are required. Signal encoding is the first step since signals need to be converted into spike trains as the primary input to an SNN. We present an efficient frequency encoding system using receptive fields. The proposed encoding is versatile and it can provide simple image transforms like edge detection, spot detection or removal, or Gabor-like filtering. The proposed encoding can be used in many application areas as image processing and signal processing for detection and classification.
Modelling and Simulation of Ego-Noise of Unmanned Aerial Vehicles
2020
In this paper, we develop a simulation model for the ego-noise of unmanned aerial vehicles (UAVs). The ego-noise is composed of spike noise and background noise. The spike noise is modelled by a finite sum of sinusoids, while the background noise is modelled by a coloured Gaussian stationary process. The main property of our model is that it only depends on physical characteristics of the UAV and it does not need real-time audio inputs to be developed. This model is very useful for training novel noise cancelling algorithms and for evaluating their performance. To validate the proposed model, we compare the statistical properties of the ego-noise simulated using our model with actual ego-no…
Molecular study of porcine transmissible gastroenteritis virus after serial animal passages revealed point mutations in S protein
2010
Porcine respiratory coronavirus is related genetically to porcine transmissible gastroenteritis virus with a large deletion in S protein. The respiratory virus is a mutated form that may be a consequence of the gastroen- teritis virus's evolution. Intensive passages of the virus in its natural host may enhance the appearance of mutations and therefore may contribute to any attenuated form of the virus. The objective of this study was to characterize the porcine transmissible gastroenteritis virus TMK22 strain after passages in piglets from 1992 until 2007. A typical experimental infection, molecular characterization, and serological analysis were also carried out to further char- acterize a…
Unisexual flowers as a robust synapomorphy in Cariceae (Cyperaceae)? Evidence for bisexual flowers in Schoenoxiphium
2012
Abstract Cariceae, the largest tribe within Cyperaceae, comprises about 2000 species in five genera. Cariceae is usually considered to be distinct from other Cyperaceae by the presence of exclusively unisexual flowers and by the arrangement of the pistillate flowers in single-flowered spikelets that are enclosed by the flask-like spikelet prophyll (utricle or perigynium). The nature of several morphological features of the Cariceae inflorescence remains controversial. The staminate reproductive units, as well as earlier reported bisexual reproductive units in Schoenoxiphium have been considered to be reduced partial inflorescences, or flowers. Aims of this study are to test both interpretat…