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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Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00508/full |
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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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