Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / / topic editors, Julie Wall and Cornelius Glackin.
The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication be...
Saved in:
: | |
---|---|
TeilnehmendeR: | |
Place / Publishing House: | [Lausanne, Switzerland] : : Frontiers Media SA,, 2014. |
Year of Publication: | 2014 |
Language: | English |
Series: | Frontiers Research Topics,
|
Physical Description: | 1 online resource (123 pages). |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
993547293104498 |
---|---|
ctrlnum |
(CKB)3710000000504553 (WaSeSS)IndRDA00058309 (oapen)https://directory.doabooks.org/handle/20.500.12854/59844 (EXLCZ)993710000000504553 |
collection |
bib_alma |
record_format |
marc |
spelling |
Cornelius Glackin auth Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / topic editors, Julie Wall and Cornelius Glackin. Frontiers Media SA 2014 [Lausanne, Switzerland] : Frontiers Media SA, 2014. 1 online resource (123 pages). text txt rdacontent computer c rdamedia online resource cr rdacarrier Frontiers Research Topics, 1664-8714 Includes bibliographical references. Description based on: online resource; title from pdf title page (frontiers, viewed Jun. 23, 2016). The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain's neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena. English Neurons. Neural receptors. Learning cell assembly sensory processing spike timing connectivity biological neurons Spiking Neural network 2-88919-239-3 Wall, Julie, editor. Glackin, Cornelius, editor. |
language |
English |
format |
eBook |
author |
Cornelius Glackin |
spellingShingle |
Cornelius Glackin Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / Frontiers Research Topics, |
author_facet |
Cornelius Glackin Wall, Julie, Glackin, Cornelius, |
author_variant |
c g cg |
author2 |
Wall, Julie, Glackin, Cornelius, |
author2_variant |
j w jw c g cg |
author2_role |
TeilnehmendeR TeilnehmendeR |
author_sort |
Cornelius Glackin |
title |
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / |
title_full |
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / topic editors, Julie Wall and Cornelius Glackin. |
title_fullStr |
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / topic editors, Julie Wall and Cornelius Glackin. |
title_full_unstemmed |
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / topic editors, Julie Wall and Cornelius Glackin. |
title_auth |
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / |
title_new |
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / |
title_sort |
spiking neural network connectivity and its potential for temporal sensory processing and variable binding / |
series |
Frontiers Research Topics, |
series2 |
Frontiers Research Topics, |
publisher |
Frontiers Media SA Frontiers Media SA, |
publishDate |
2014 |
physical |
1 online resource (123 pages). |
isbn |
2-88919-239-3 |
issn |
1664-8714 |
callnumber-first |
Q - Science |
callnumber-subject |
QP - Physiology |
callnumber-label |
QP363 |
callnumber-sort |
QP 3363 |
illustrated |
Not Illustrated |
work_keys_str_mv |
AT corneliusglackin spikingneuralnetworkconnectivityanditspotentialfortemporalsensoryprocessingandvariablebinding AT walljulie spikingneuralnetworkconnectivityanditspotentialfortemporalsensoryprocessingandvariablebinding AT glackincornelius spikingneuralnetworkconnectivityanditspotentialfortemporalsensoryprocessingandvariablebinding |
status_str |
n |
ids_txt_mv |
(CKB)3710000000504553 (WaSeSS)IndRDA00058309 (oapen)https://directory.doabooks.org/handle/20.500.12854/59844 (EXLCZ)993710000000504553 |
carrierType_str_mv |
cr |
is_hierarchy_title |
Spiking neural network connectivity and its potential for temporal sensory processing and variable binding / |
author2_original_writing_str_mv |
noLinkedField noLinkedField |
_version_ |
1796649024535658496 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01510nam a2200325 i 4500</leader><controlfield tag="001">993547293104498</controlfield><controlfield tag="005">20160624143059.0</controlfield><controlfield tag="006">m o u </controlfield><controlfield tag="007">cr |||||||||||</controlfield><controlfield tag="008">160624s2014 sz |||||o|||||||||||eng d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)3710000000504553</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(WaSeSS)IndRDA00058309</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/59844</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)993710000000504553</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">WaSeSS</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="c">WaSeSS</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QP363</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Cornelius Glackin</subfield><subfield code="4">auth</subfield></datafield><datafield tag="245" ind1="0" ind2="0"><subfield code="a">Spiking neural network connectivity and its potential for temporal sensory processing and variable binding /</subfield><subfield code="c">topic editors, Julie Wall and Cornelius Glackin.</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="b">Frontiers Media SA</subfield><subfield code="c">2014</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Lausanne, Switzerland] :</subfield><subfield code="b">Frontiers Media SA,</subfield><subfield code="c">2014.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (123 pages).</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Frontiers Research Topics,</subfield><subfield code="x">1664-8714</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on: online resource; title from pdf title page (frontiers, viewed Jun. 23, 2016).</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain's neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Neurons.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Neural receptors.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">cell assembly</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">sensory processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">spike timing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">connectivity</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">biological neurons</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Spiking Neural network</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">2-88919-239-3</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wall, Julie,</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Glackin, Cornelius,</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-02-22 20:13:51 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2015-11-22 13:16:40 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&portfolio_pid=5338460490004498&Force_direct=true</subfield><subfield code="Z">5338460490004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338460490004498</subfield></datafield></record></collection> |