Neural information processing with dynamical synapses /
Experimental data have consistently revealed that the neuronal connection weight, which models the efficacy of the firing of a pre-synaptic neuron in modulating the state of a post-synaptic one, varies on short time scales, ranging from hundreds to thousands of milliseconds. This is called short-ter...
Saved in:
Superior document: | Frontiers Research Topics |
---|---|
: | |
TeilnehmendeR: | |
Place / Publishing House: | France : : Frontiers Media SA,, 2014 |
Year of Publication: | 2014 |
Language: | English |
Series: | Frontiers Research Topics.
|
Physical Description: | 1 online resource (178 pages) :; illustrations, colour; digital file(s). |
Notes: | Bibliographic Level Mode of Issuance: Monograph |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
993548050104498 |
---|---|
ctrlnum |
(CKB)3710000000520134 (SSID)ssj0001683358 (PQKBManifestationID)16509273 (PQKBTitleCode)TC0001683358 (PQKBWorkID)15037834 (PQKB)10280466 (WaSeSS)IndRDA00056619 (oapen)https://directory.doabooks.org/handle/20.500.12854/54475 (EXLCZ)993710000000520134 |
collection |
bib_alma |
record_format |
marc |
spelling |
Misha Tsodyks auth Neural information processing with dynamical synapses / Frontiers Media SA 2014 France : Frontiers Media SA, 2014 1 online resource (178 pages) : illustrations, colour; digital file(s). text txt rdacontent computer c rdamedia online resource cr rdacarrier text file rda Frontiers Research Topics Bibliographic Level Mode of Issuance: Monograph Experimental data have consistently revealed that the neuronal connection weight, which models the efficacy of the firing of a pre-synaptic neuron in modulating the state of a post-synaptic one, varies on short time scales, ranging from hundreds to thousands of milliseconds. This is called short-term plasticity (STP). Two types of STP, with opposite effects on the connection efficacy, have been observed in experiments. They are short-term depression (STD) and short-term facilitation (STF).Computational studies have explored the impact of STP on network dynamics, and found that STP can generate very rich intrinsic dynamical behaviours, including damped oscillations, state hopping with transient population spikes, traveling fronts and pulses, spiral waves, rotating bump states, robust self-organized critical activities and so on. These studies also strongly suggest that STP can play many important roles in neural computation. For instances, STD may provide a dynamic control mechanism that allows equal fractional changes on rapidly and slowly firing afferents to produce post-synaptic responses, realizing Weber’s law; STD may provide a mechanism to close down network activity naturally, achieving iconic sensory memory; and STF may provide a mechanism for implementing work-memory not relying on persistent neural firing. From the computational point of view, the time scale of STP resides between fast neural signalling (in the order of milliseconds) and rapid learning (in the order of minutes or above), which is the time scale of many important temporal processes occurring in our daily lives, such as motion control and working memory. Thus, STP may serve as a substrate for neural systems manipulating temporal information on the relevant time scales. This Research Topic aims to present the recent progress in understanding the roles of STP in neural information processing. It includes, but no exclusively, the studies on investigating various computational roles of STP, the modelling studies on exploring new dynamical behaviours generated by STP, and the experimental works which help us to understand the functional roles of STP. English Psychology HILCC Social Sciences HILCC neural field model Associative Memory neural information processing phenomenological model network dynamics short-term plasticity Continuous Attractor Neural Network Wong, K. Y. Michael editor. Tsodyks, Misha editor. Wu, Si editor. Frontiers Research Topics. |
language |
English |
format |
eBook |
author |
Misha Tsodyks |
spellingShingle |
Misha Tsodyks Neural information processing with dynamical synapses / Frontiers Research Topics |
author_facet |
Misha Tsodyks Wong, K. Y. Michael Tsodyks, Misha Wu, Si |
author_variant |
m t mt |
author2 |
Wong, K. Y. Michael Tsodyks, Misha Wu, Si |
author2_variant |
k y m w kym kymw m t mt s w sw |
author2_role |
TeilnehmendeR TeilnehmendeR TeilnehmendeR |
author_sort |
Misha Tsodyks |
title |
Neural information processing with dynamical synapses / |
title_full |
Neural information processing with dynamical synapses / |
title_fullStr |
Neural information processing with dynamical synapses / |
title_full_unstemmed |
Neural information processing with dynamical synapses / |
title_auth |
Neural information processing with dynamical synapses / |
title_new |
Neural information processing with dynamical synapses / |
title_sort |
neural information processing with dynamical synapses / |
series |
Frontiers Research Topics |
series2 |
Frontiers Research Topics |
publisher |
Frontiers Media SA Frontiers Media SA, |
publishDate |
2014 |
physical |
1 online resource (178 pages) : illustrations, colour; digital file(s). |
isbn |
9782889193837 |
callnumber-first |
B - Philosophy, Psychology, Religion |
callnumber-subject |
BF - Psychology |
callnumber-label |
BF204 |
callnumber-sort |
BF 3204.5 |
illustrated |
Not Illustrated |
work_keys_str_mv |
AT mishatsodyks neuralinformationprocessingwithdynamicalsynapses AT wongkymichael neuralinformationprocessingwithdynamicalsynapses AT tsodyksmisha neuralinformationprocessingwithdynamicalsynapses AT wusi neuralinformationprocessingwithdynamicalsynapses |
status_str |
n |
ids_txt_mv |
(CKB)3710000000520134 (SSID)ssj0001683358 (PQKBManifestationID)16509273 (PQKBTitleCode)TC0001683358 (PQKBWorkID)15037834 (PQKB)10280466 (WaSeSS)IndRDA00056619 (oapen)https://directory.doabooks.org/handle/20.500.12854/54475 (EXLCZ)993710000000520134 |
carrierType_str_mv |
cr |
hierarchy_parent_title |
Frontiers Research Topics |
is_hierarchy_title |
Neural information processing with dynamical synapses / |
container_title |
Frontiers Research Topics |
author2_original_writing_str_mv |
noLinkedField noLinkedField noLinkedField |
_version_ |
1787548700966387712 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03937nam a2200541 i 4500</leader><controlfield tag="001">993548050104498</controlfield><controlfield tag="005">20230621135733.0</controlfield><controlfield tag="006">m o u </controlfield><controlfield tag="007">cr#||#||||||||</controlfield><controlfield tag="008">160829s2014 fr ob 000 | eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9782889193837</subfield><subfield code="q">(ebook)</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)3710000000520134</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SSID)ssj0001683358</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PQKBManifestationID)16509273</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PQKBTitleCode)TC0001683358</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PQKBWorkID)15037834</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PQKB)10280466</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(WaSeSS)IndRDA00056619</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/54475</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)993710000000520134</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">PQKB</subfield><subfield code="b">eng</subfield><subfield code="d">UkMaJRU</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">BF204.5</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Misha Tsodyks</subfield><subfield code="4">auth</subfield></datafield><datafield tag="245" ind1="0" ind2="0"><subfield code="a">Neural information processing with dynamical synapses /</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="b">Frontiers Media SA</subfield><subfield code="c">2014</subfield></datafield><datafield tag="264" ind1="3" ind2="1"><subfield code="a">France :</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 (178 pages) :</subfield><subfield code="b">illustrations, colour; digital file(s).</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="347" ind1=" " ind2=" "><subfield code="a">text file</subfield><subfield code="2">rda</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Frontiers Research Topics</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Bibliographic Level Mode of Issuance: Monograph</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Experimental data have consistently revealed that the neuronal connection weight, which models the efficacy of the firing of a pre-synaptic neuron in modulating the state of a post-synaptic one, varies on short time scales, ranging from hundreds to thousands of milliseconds. This is called short-term plasticity (STP). Two types of STP, with opposite effects on the connection efficacy, have been observed in experiments. They are short-term depression (STD) and short-term facilitation (STF).Computational studies have explored the impact of STP on network dynamics, and found that STP can generate very rich intrinsic dynamical behaviours, including damped oscillations, state hopping with transient population spikes, traveling fronts and pulses, spiral waves, rotating bump states, robust self-organized critical activities and so on. These studies also strongly suggest that STP can play many important roles in neural computation. For instances, STD may provide a dynamic control mechanism that allows equal fractional changes on rapidly and slowly firing afferents to produce post-synaptic responses, realizing Weber’s law; STD may provide a mechanism to close down network activity naturally, achieving iconic sensory memory; and STF may provide a mechanism for implementing work-memory not relying on persistent neural firing. From the computational point of view, the time scale of STP resides between fast neural signalling (in the order of milliseconds) and rapid learning (in the order of minutes or above), which is the time scale of many important temporal processes occurring in our daily lives, such as motion control and working memory. Thus, STP may serve as a substrate for neural systems manipulating temporal information on the relevant time scales. This Research Topic aims to present the recent progress in understanding the roles of STP in neural information processing. It includes, but no exclusively, the studies on investigating various computational roles of STP, the modelling studies on exploring new dynamical behaviours generated by STP, and the experimental works which help us to understand the functional roles of STP.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Psychology</subfield><subfield code="2">HILCC</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Social Sciences</subfield><subfield code="2">HILCC</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">neural field model</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Associative Memory</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">neural information processing</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">phenomenological model</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">network dynamics</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">short-term plasticity</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Continuous Attractor Neural Network</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wong, K. Y. Michael</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tsodyks, Misha</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wu, Si</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Frontiers Research Topics.</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2023-06-25 11:06:38 Europe/Vienna</subfield><subfield code="d">00</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2015-12-12 16:57:58 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=5338717520004498&Force_direct=true</subfield><subfield code="Z">5338717520004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338717520004498</subfield></datafield></record></collection> |