Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron Experiment

The experimental study of neural networks requires simultaneous measurements of a massive number of neurons, while monitoring properties of the connectivity, synaptic strengths and delays. Current technological barriers make such a mission unachievable. In addition, as a result of the enormous numbe...

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Main Authors: Amir eGoldental, Pinhas eSabo, Shira eSardi, Roni eVardi, Ido eKanter
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-01-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00508/full
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spelling doaj-ac3c8e29509d45b78ce624af314149dc2020-11-25T00:30:57ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2016-01-01910.3389/fnins.2015.00508174492Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron ExperimentAmir eGoldental0Pinhas eSabo1Shira eSardi2Roni eVardi3Ido eKanter4Bar Ilan UniversityBar Ilan UniversityBar Ilan UniversityBar Ilan UniversityBar Ilan UniversityThe experimental study of neural networks requires simultaneous measurements of a massive number of neurons, while monitoring properties of the connectivity, synaptic strengths and delays. Current technological barriers make such a mission unachievable. In addition, as a result of the enormous number of required measurements, the estimated network parameters would differ from the original ones. Here we present a versatile experimental technique, which enables the study of recurrent neural networks activity while being capable of dictating the network connectivity and synaptic strengths. This method is based on the observation that the response of neurons depends solely on their recent stimulations, a short-term memory. It allows a long-term scheme of stimulation and recording of a single neuron, to mimic simultaneous activity measurements of neurons in a recurrent network. Utilization of this technique demonstrates the spontaneous emergence of cooperative synchronous oscillations, in particular the coexistence of fast gamma and slow delta oscillations, and opens the horizon for the experimental study of other cooperative phenomena within large-scale neural networks.http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00508/fullNeuronal Plasticityneural networksIn-vitroneuronal response latencyneuronal response failures
collection DOAJ
language English
format Article
sources DOAJ
author Amir eGoldental
Pinhas eSabo
Shira eSardi
Roni eVardi
Ido eKanter
spellingShingle Amir eGoldental
Pinhas eSabo
Shira eSardi
Roni eVardi
Ido eKanter
Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron Experiment
Frontiers in Neuroscience
Neuronal Plasticity
neural networks
In-vitro
neuronal response latency
neuronal response failures
author_facet Amir eGoldental
Pinhas eSabo
Shira eSardi
Roni eVardi
Ido eKanter
author_sort Amir eGoldental
title Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron Experiment
title_short Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron Experiment
title_full Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron Experiment
title_fullStr Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron Experiment
title_full_unstemmed Mimicking Collective Firing Patterns of Hundreds of Connected Neurons using a Single-Neuron Experiment
title_sort mimicking collective firing patterns of hundreds of connected neurons using a single-neuron experiment
publisher Frontiers Media S.A.
series Frontiers in Neuroscience
issn 1662-453X
publishDate 2016-01-01
description The experimental study of neural networks requires simultaneous measurements of a massive number of neurons, while monitoring properties of the connectivity, synaptic strengths and delays. Current technological barriers make such a mission unachievable. In addition, as a result of the enormous number of required measurements, the estimated network parameters would differ from the original ones. Here we present a versatile experimental technique, which enables the study of recurrent neural networks activity while being capable of dictating the network connectivity and synaptic strengths. This method is based on the observation that the response of neurons depends solely on their recent stimulations, a short-term memory. It allows a long-term scheme of stimulation and recording of a single neuron, to mimic simultaneous activity measurements of neurons in a recurrent network. Utilization of this technique demonstrates the spontaneous emergence of cooperative synchronous oscillations, in particular the coexistence of fast gamma and slow delta oscillations, and opens the horizon for the experimental study of other cooperative phenomena within large-scale neural networks.
topic Neuronal Plasticity
neural networks
In-vitro
neuronal response latency
neuronal response failures
url http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00508/full
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