Individual differences in associative learning / / topic editors, Robin A. Murphy and Rachel M. Msetf.
Theories of associative learning have a long history in advancing the psychological account of behavior via cognitive representation. There are many components and variations of associative theory but at the core is the idea that links or connections between stimuli or responses describe important a...
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 (112 pages). |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
993547662304498 |
---|---|
ctrlnum |
(CKB)3710000000526110 (WaSeSS)IndRDA00058980 (oapen)https://directory.doabooks.org/handle/20.500.12854/50144 (EXLCZ)993710000000526110 |
collection |
bib_alma |
record_format |
marc |
spelling |
Rachel M. Msetfi auth Individual differences in associative learning / topic editors, Robin A. Murphy and Rachel M. Msetf. Frontiers Media SA 2014 [Lausanne, Switzerland] : Frontiers Media SA, 2014. 1 online resource (112 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 Jul. 13, 2016). Theories of associative learning have a long history in advancing the psychological account of behavior via cognitive representation. There are many components and variations of associative theory but at the core is the idea that links or connections between stimuli or responses describe important aspects of our psychological experience. This Frontiers Topic considers how variations in association formation can be used to account for differences between people, elaborating the differences between males and females, differences over the life span, understanding of psychopathologies or even across cultural contexts. A recent volume on the application of learning theory to clinical psychology is one example of this emerging application (e.g., Hazelgrove & Hogarth, 2012). The task for students of learning has been the development, often with mathematically defined explanations, of the parameters and operators that determine the formation and strengths of associations. The ultimate goal is to explain how the acquired representations influence future behavior. This approach has recently been influential in the field of neuroscience where one such learning operator, the error correction principle, has unified the understanding of the conditions which facilitate neuron activation with the computational goals of the brain with properties of learning algorithms (e.g., Rescorla & Wagner, 1972). In this Frontiers Research Topic, we are interested in a similar but currently developing aspect to learning theory, which is the application of the associative model to our understanding of individual differences, including psychopathology. In general, learning theories are monolithic, the same theory applies to the rat and the human, and within people the same algorithm is applied to all individuals. If so this might be thought to suggest that there is little that learning theory can tell us about the how males and females differ, how we change over time or why someone develops schizophrenia for instance. However, these theories have wide scope for developing our understanding of when learning occurs and when it is interfered with, along with a variety of methods of predicting these differences. We received contributions from researchers studying individual differences, including sex differences, age related changes and those using analog or clinical samples of personality and psychopathological disorders where the outcomes of the research bear directly on theories of associative learning. This Research Topic brings together researchers studying basic learning and conditioning processes but in which the basic emotional, attentional, pathological or more general physiological differences between groups of people are modeled using associative theory. This work involves varying stimulus properties and temporal relations or modeling the differences between groups. English Paired-association learning. Learning conditioning Computational Psychopathology Associationism individual differences 2-88919-290-3 Murphy, Robin A., editor. Rachel M. Msetf, editor. |
language |
English |
format |
eBook |
author |
Rachel M. Msetfi |
spellingShingle |
Rachel M. Msetfi Individual differences in associative learning / Frontiers Research Topics, |
author_facet |
Rachel M. Msetfi Murphy, Robin A., Rachel M. Msetf, |
author_variant |
r m m rmm |
author2 |
Murphy, Robin A., Rachel M. Msetf, |
author2_variant |
r a m ra ram r m m rmm |
author2_role |
TeilnehmendeR TeilnehmendeR |
author_sort |
Rachel M. Msetfi |
title |
Individual differences in associative learning / |
title_full |
Individual differences in associative learning / topic editors, Robin A. Murphy and Rachel M. Msetf. |
title_fullStr |
Individual differences in associative learning / topic editors, Robin A. Murphy and Rachel M. Msetf. |
title_full_unstemmed |
Individual differences in associative learning / topic editors, Robin A. Murphy and Rachel M. Msetf. |
title_auth |
Individual differences in associative learning / |
title_new |
Individual differences in associative learning / |
title_sort |
individual differences in associative learning / |
series |
Frontiers Research Topics, |
series2 |
Frontiers Research Topics, |
publisher |
Frontiers Media SA Frontiers Media SA, |
publishDate |
2014 |
physical |
1 online resource (112 pages). |
isbn |
2-88919-290-3 |
issn |
1664-8714 |
callnumber-first |
L - Education |
callnumber-subject |
LB - Theory and Practice of Education |
callnumber-label |
LB1064 |
callnumber-sort |
LB 41064 |
illustrated |
Not Illustrated |
work_keys_str_mv |
AT rachelmmsetfi individualdifferencesinassociativelearning AT murphyrobina individualdifferencesinassociativelearning AT rachelmmsetf individualdifferencesinassociativelearning |
status_str |
n |
ids_txt_mv |
(CKB)3710000000526110 (WaSeSS)IndRDA00058980 (oapen)https://directory.doabooks.org/handle/20.500.12854/50144 (EXLCZ)993710000000526110 |
carrierType_str_mv |
cr |
is_hierarchy_title |
Individual differences in associative learning / |
author2_original_writing_str_mv |
noLinkedField noLinkedField |
_version_ |
1796648777818308608 |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01327nam a2200313 i 4500</leader><controlfield tag="001">993547662304498</controlfield><controlfield tag="005">20160713131703.0</controlfield><controlfield tag="006">m o u </controlfield><controlfield tag="007">cr |||||||||||</controlfield><controlfield tag="008">160713s2014 sz |||||o|||||||||||eng d</controlfield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)3710000000526110</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(WaSeSS)IndRDA00058980</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/50144</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)993710000000526110</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">LB1064</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Rachel M. Msetfi</subfield><subfield code="4">auth</subfield></datafield><datafield tag="245" ind1="0" ind2="0"><subfield code="a">Individual differences in associative learning /</subfield><subfield code="c">topic editors, Robin A. Murphy and Rachel M. Msetf.</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 (112 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 Jul. 13, 2016).</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Theories of associative learning have a long history in advancing the psychological account of behavior via cognitive representation. There are many components and variations of associative theory but at the core is the idea that links or connections between stimuli or responses describe important aspects of our psychological experience. This Frontiers Topic considers how variations in association formation can be used to account for differences between people, elaborating the differences between males and females, differences over the life span, understanding of psychopathologies or even across cultural contexts. A recent volume on the application of learning theory to clinical psychology is one example of this emerging application (e.g., Hazelgrove & Hogarth, 2012). The task for students of learning has been the development, often with mathematically defined explanations, of the parameters and operators that determine the formation and strengths of associations. The ultimate goal is to explain how the acquired representations influence future behavior. This approach has recently been influential in the field of neuroscience where one such learning operator, the error correction principle, has unified the understanding of the conditions which facilitate neuron activation with the computational goals of the brain with properties of learning algorithms (e.g., Rescorla & Wagner, 1972). In this Frontiers Research Topic, we are interested in a similar but currently developing aspect to learning theory, which is the application of the associative model to our understanding of individual differences, including psychopathology. In general, learning theories are monolithic, the same theory applies to the rat and the human, and within people the same algorithm is applied to all individuals. If so this might be thought to suggest that there is little that learning theory can tell us about the how males and females differ, how we change over time or why someone develops schizophrenia for instance. However, these theories have wide scope for developing our understanding of when learning occurs and when it is interfered with, along with a variety of methods of predicting these differences. We received contributions from researchers studying individual differences, including sex differences, age related changes and those using analog or clinical samples of personality and psychopathological disorders where the outcomes of the research bear directly on theories of associative learning. This Research Topic brings together researchers studying basic learning and conditioning processes but in which the basic emotional, attentional, pathological or more general physiological differences between groups of people are modeled using associative theory. This work involves varying stimulus properties and temporal relations or modeling the differences between groups.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">English</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Paired-association learning.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Learning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">conditioning</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Computational Psychopathology</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Associationism</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">individual differences</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">2-88919-290-3</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Murphy, Robin A.,</subfield><subfield code="e">editor.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rachel M. Msetf,</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 20:28:19 Europe/Vienna</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=5338611250004498&Force_direct=true</subfield><subfield code="Z">5338611250004498</subfield><subfield code="b">Available</subfield><subfield code="8">5338611250004498</subfield></datafield></record></collection> |