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This paper uses a simple optogenetic model to compare the timing distortion between a randomly-generated target spike sequence and an externally-stimulated neuron spike sequence. Optogenetics is an emerging field of neuroscience where…

Neurons and Cognition · Quantitative Biology 2020-04-24 Adam Noel , Dimitrios Makrakis , Andrew W. Eckford

Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from…

Methodology · Statistics 2016-12-23 Xi Luo , Steven Gee , Vikaas S. Sohal , Dylan S. Small

The effects of spike timing precision and dynamical behavior on error correction in spiking neurons were investigated. Stationary discharges -- phase locked, quasiperiodic, or chaotic -- were induced in a simulated neuron by presenting…

Neurons and Cognition · Quantitative Biology 2007-05-23 Michael Stiber

Background: In neurophysiological data, latency refers to a global shift of spikes from one spike train to the next, either caused by response onset fluctuations or by finite propagation speed. Such systematic shifts in spike timing lead to…

Optogenetics has emerged as an exciting tool for manipulating neural activity, which in turn, can modulate behavior in live organisms. However, detecting the response to the optical stimulation requires electrophysiology with physical…

We derive a synaptic weight update rule for learning temporally precise spike train to spike train transformations in multilayer feedforward networks of spiking neurons. The framework, aimed at seamlessly generalizing error backpropagation…

Neural and Evolutionary Computing · Computer Science 2016-01-11 Arunava Banerjee

Photonic Spiking Neural Networks (PSNN) composed of the co-integrated CMOS and photonic elements can offer low loss, low power, highly-parallel, and high-throughput computing for brain-inspired neuromorphic systems. In addition,…

Systems and Control · Electrical Eng. & Systems 2023-11-28 Yun-Jhu Lee , Mehmet Berkay On , Luis El Srouji , Li Zhang , Mahmoud Abdelghany , S. J. Ben Yoo

This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a…

Neurons and Cognition · Quantitative Biology 2018-09-06 Adam Noel , Shayan Monabbati , Dimitrios Makrakis , Andrew W. Eckford

A single neuron is known to generate almost identical spike trains when the same fluctuating input is repeatedly applied. Here, we study the reliability of spike firing in a pulse-coupled network of oscillator neurons receiving fluctuating…

Adaptation and Self-Organizing Systems · Physics 2015-05-13 Jun-nosuke Teramae , Tomoki Fukai

Spiking neural networks (SNN) hold the promise of being a more biologically plausible, low-energy alternative to conventional artificial neural networks. Their time-variant nature makes them particularly suitable for processing…

Machine Learning · Computer Science 2025-04-10 Jan Debus , Charlotte Debus , Günther Dissertori , Markus Götz

Objective. Long-term potentiation (LTP) is a fundamental mechanism underlying learning and memory, yet its investigation at the network level in vitro remains challenging, particularly when optogenetic stimulation is used. The objective of…

Biological Physics · Physics 2026-02-13 Matteo Dominici , Ilya Auslender , Clara Zaccaria , Yasaman Heydari , Lorenzo Pavesi

This article investigates the emergence of phase synchronization in a network of randomly connected neurons by chemical synapses. The study uses the classic Hodgkin-Huxley model to simulate the neuronal dynamics under the action of a train…

The majority of inherited retinal degenerations are due to photoreceptor cell death. In many cases ganglion cells are spared making it possible to stimulate them to restore visual function. Several studies (Bi et al., 2006; Lin et al.,…

Optical computing could reduce the energy cost of artificial intelligence by leveraging the parallelism and propagation speed of light. However, implementing nonlinear activation, essential for machine learning, remains challenging in…

Optics · Physics 2026-01-01 Bahadır Utku Kesgin , Gülsüm Yaren Durdu , Uğur Teğin

Today, machine learning tools, particularly artificial neural networks, have become crucial for diverse applications. However, current digital computing tools to train and deploy artificial neural networks often struggle with massive data…

Emerging Technologies · Computer Science 2025-02-14 Bora Çarpınlıoğlu , Uğur Teğin

Biotechnology can benefit from dynamic control to improve production efficiency. In this context, optogenetics enables modulation of gene expression using light as an external input, allowing fine-tuning of protein levels to unlock dynamic…

Systems and Control · Electrical Eng. & Systems 2026-05-11 Sebastián Espinel-Ríos

Neuroprosthesis, as one type of precision medicine device, is aiming for manipulating neuronal signals of the brain in a closed-loop fashion, together with receiving stimulus from the environment and controlling some part of our brain/body.…

Neurons and Cognition · Quantitative Biology 2020-01-14 Zhaofei Yu , Jian K. Liu , Shanshan Jia , Yichen Zhang , Yajing Zheng , Yonghong Tian , Tiejun Huang

We investigate the evolution of coherence property of noise-seeded Stokes wave in short (< 1 ps) and long pulse (> 1 ps) regimes. Nonlinear equations expressing the evolution of pump and Stokes wave are solved numerically for both the…

Optics · Physics 2019-05-22 Partha Mondal , Shailendra K. Varshney

Spike-sorting techniques attempt to classify a series of noisy electrical waveforms according to the identity of the neurons that generated them. Existing techniques perform this classification ignoring several properties of actual neurons…

Quantitative Methods · Quantitative Biology 2007-05-23 Christophe Pouzat

This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a…

Neurons and Cognition · Quantitative Biology 2020-04-24 Adam Noel , Shayan Monabbati , Dimitrios Makrakis , Andrew W. Eckford
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