Mechanisms of implicit learning: What sort of structures can be implicitly learnt?

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Mechanisms of implicit learning: What sort of structures can be implicitly learnt? (What sort of model would allow such learning?)

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Mechanisms of implicit learning: What sort of structures can be implicitly learnt? (What sort of model would allow such learning?). 1. [0] -> M[1] 2. [1] -> T[1] 3. [1] -> Q[2] 4. [2] -> B[1] [2] -> ε [0], [1], [2] are non- terminals Finite state grammar. Example string; M[1] - PowerPoint PPT Presentation

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Mechanisms of implicit learning:

What sort of structures can be implicitly learnt?

(What sort of model would allow such learning?)

1. [0] -> M[1]2. [1] -> T[1]3. [1] -> Q[2]4. [2] -> B[1][2] ->

[0], [1], [2] are non-terminals

Finite state grammarExample string;M[1]-> MT[1]-> MTT[1]-> MTTQ[2]-> MTTQMTTQ

People learn:

Chunks: MT, TT, TQ, MTT, TTQ

Whole items: MTTQ

Repetition structure: 1223 (so they can classify KXXV as grammatical)

Cross serial dependency/ inversionCentre embedding/ retrogradeA1 A2 A3 - B1 B2 B3

mirrorA1A2A3B1B2B3

mirror

A1 A2 A3 - B3 B2 B1Retrograde symmetry:

A1A2A3-B3B2B1

1. [0] -> Ai[0]Bi2. [0] ->

(where [0] is a non-terminal)

Context free grammar

Inverse symmetry:

A1A2A3-B1B2B3

1. S-> Ai S] Ti 2. S-> 3. Ai Tj -> Ai Bj4. Bj Ti -> Ti Bj

(where Ti and S are non-terminals)

Context-sensitive grammar

Kuhn and Dienes 2005Grammatical Tune showing inversion

Contour -3 +6 +1 +3 -6 -1Kuhn & Dienes 2005

Liking ratingsClassification performanceKuhn and Dienes 2008SRN learns fixed length long distance associations.

Have either subjects or SRN learnt a symmetry?

Need to show generalisation to new lengths.

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Tang poetry:Divides Chinese tones (1-4) into two categories: ping (1,2) and ze (3,4)And specifies an inversion relation in successive lines:

People can implicitly learn tonal inversions and retrogrades.

chunks and repetition structure are rigorously controlled.

People only learn when ping-ze classification is used

People can generalise from lines of 5 words to both 4 and 6 words BUT with a major decrement

SRN characteristically shows all the above!!

Questions:

Can people be trained on different lengths so as to generalise with facility to longer poems? Can the SRN? (This is crucial for show the symmetry as such can be learnt)

Brain regions involved in learning symmetry versus chunking?

Cross cultural differences?

Can we induce symmetry learning in body movement and eye movements?

Chart55.06365740755.11226851840.10946737250.10946737250.14306171980.14306171984.87847222225.18287037040.10384219670.10384219670.13521192920.1352119292

G = GrammaticalU = UngrammaticalExperimentalControlMean liking Ratings

exp 2GroupExemplarFragmentAbstractGroupExemplarFragmentAbstractExperimental0.56770833320.58854166660.5156250001Experimental56.77083332558.854166662551.5625000062Control0.53645833320.54166666660.453125Control53.64583332554.166666662545.31250.02631568790.02252399270.0260208252.63156879412.2523992692.60208249910.01568276350.02439750180.02185018441.56827635372.4397501842.1850184391

exp 256.77083332553.6458333252.63156879412.63156879411.56827635371.568276353758.854166662554.16666666252.2523992692.2523992692.4397501842.43975018451.562500006245.31252.60208249912.60208249912.18501843912.1850184391

ExperimentalControlTest Set% correct classification

exp 1SetExemplarFragmentAbstractGrammaticalUngrammaticalGrammaticalUngrammaticalGrammaticalUngrammaticalGroupMSDMSDMSDMSDMSDMSDExperimental5.280.834.960.655.441.094.940.985.400.705.090.86Control5.200.815.130.794.960.815.100.865.390.765.630.580.21327473150.16886855691.40530124890.28084075161.2762018040.25285026431.39319817590.18164203031.31385580880.222564840.20963942450.20442632771.28158094760.20875420451.31789016640.22284634581.39050860410.19529575551.45371354070.1494782593ExemplarFragmentAbstractGUGUGUExperimental5.284.965.444.945.405.09Control5.205.134.965.105.395.630.21327473150.16886855690.28084075160.25285026430.18164203030.222564840.20963942450.20442632770.20875420450.22284634580.19529575550.1494782593

exp 15.28124999995.20312500010.20963942450.20963942450.21327473150.21327473154.96354166685.1250.20442632770.20442632770.16886855690.16886855695.44270833344.96354166680.20875420450.20875420450.28084075160.28084075164.94270833335.10416666660.22284634580.22284634580.25285026430.25285026435.39583333345.38541666660.19529575550.19529575550.18164203030.18164203035.08854166685.63020833320.14947825930.14947825930.222564840.22256484

G = GrammaticalU = UngrammaticalExperimentalControlTest Setmean liking ratings

exp 3 likingGroupGUExperimental5.064.88Control5.115.18SE0.140.14SE0.110.10

exp 3 liking5.06365740755.11226851840.10946737250.10946737250.14306171980.14306171984.87847222225.18287037040.10384219670.10384219670.13521192920.1352119292

G = GrammaticalU = UngrammaticalExperimentalControlMean liking Ratings

zero correlationExemplar5051 - 6061 - 7071 - 8081 - 9091 - 10010.56832354150.64644540640.58222222220.57083333330.58181818180.583076923120.04591988270.04539815910.0606344950.10449328960.10234621380.188547860934Fragment5051 - 6061 - 7071 - 8081 - 9091 - 10050.54013806710.43175747860.60945938980.66666666670.59206349210.911564625960.08787867390.04805392850.08935009470.07553921390.14327753130.061913482778Abstract5051 - 6061 - 7071 - 8081 - 9091 - 10090.70952380950.38386454680.48614203260.60361111110.480.6133333333100.05771148930.06465184680.05608945580.06941089720.11632224290.17944745441112131234567891011121312345678910111213

zero correlation0.04591988270.04591988270.04539815910.04539815910.0606344950.0606344950.10449328960.10449328960.10234621380.10234621380.18854786090.1885478609

Confidence ratingClassification performance

0.08787867390.08787867390.04805392850.04805392850.08935009470.08935009470.07553921390.07553921390.14327753130.14327753130.06191348270.0619134827

Confidence ratingClassification performance

0.05771148930.05771148930.06465184680.06465184680.05608945580.05608945580.06941089720.06941089720.11632224290.11632224290.17944745440.1794474544

ConfidenceratingClassification performance

Chart650.81018518331.12784851491.127848514951.90972222710.91784887090.9178488709

classification perfomrmanceClassification performance

exp 2GroupExemplarFragmentAbstractGroupExemplarFragmentAbstractExperimental0.56770833320.58854166660.5156250001Experimental56.77083332558.854166662551.5625000062Control0.53645833320.54166666660.453125Control53.64583332554.166666662545.31250.02631568790.02252399270.0260208252.63156879412.2523992692.60208249910.01568276350.02439750180.02185018441.56827635372.4397501842.1850184391

exp 256.77083332553.6458333252.63156879412.63156879411.56827635371.568276353758.854166662554.16666666252.2523992692.2523992692.4397501842.43975018451.562500006245.31252.60208249912.60208249912.18501843912.1850184391

ExperimentalControlTest Set% correct classification

exp 1SetExemplarFragmentAbstractGrammaticalUngrammaticalGrammaticalUngrammaticalGrammaticalUngrammaticalGroupMSDMSDMSDMSDMSDMSDExperimental5.280.834.960.655.441.094.940.985.400.705.090.86Control5.200.815.130.794.960.815.100.865.390.765.630.580.21327473150.16886855691.40530124890.28084075161.2762018040.25285026431.39319817590.18164203031.31385580880.222564840.20963942450.20442632771.28158094760.20875420451.31789016640.22284634581.39050860410.19529575551.45371354070.1494782593ExemplarFragmentAbstractGUGUGUExperimental5.284.965.444.945.405.09Control5.205.134.965.105.395.630.21327473150.16886855690.28084075160.25285026430.18164203030.222564840.20963942450.20442632770.20875420450.22284634580.19529575550.1494782593

exp 15.28124999995.20312500010.20963942450.20963942450.21327473150.21327473154.96354166685.1250.20442632770.20442632770.16886855690.16886855695.44270833344.96354166680.20875420450.20875420450.28084075160.28084075164.94270833335.10416666660.22284634580.22284634580.25285026430.25285026435.39583333345.38541666660.19529575550.19529575550.18164203030.18164203035.08854166685.63020833320.14947825930.14947825930.222564840.22256484

G = GrammaticalU = UngrammaticalExperimentalControlTest Setmean liking ratings

Sheet5Groupclassification perfomrmanceExperimental50.8101851833Control51.9097222271SE1.1278485149SE0.9178488709

Sheet550.81018518331.12784851491.127848514951.90972222710.91784887090.9178488709

classification perfomrmanceClassification performance

exp 3 likingGroupGUExperimental5.064.88Control5.115.18SE0.140.14SE0.110.10

exp 3 liking5.06365740755.11226851840.10946737250.10946737250.14306171980.14306171984.87847222225.18287037040.10384219670.10384219670.13521192920.1352119292

G = GrammaticalU = UngrammaticalExperimentalControlMean liking Ratings

zero correlationExemplar5051 - 6061 - 7071 - 8081 - 9091 - 10010.56832354150.64644540640.58222222220.57083333330.58181818180.583076923120.04591988270.04539815910.0606344950.10449328960.10234621380.188547860934Fragment5051 - 6061 - 7071 - 8081 - 9091 - 10050.54013806710.43175747860.60945938980.66666666670.59206349210.911564625960.08787867390.04805392850.08935009470.07553921390.14327753130.061913482778Abstract5051 - 6061 - 7071 - 8081 - 9091 - 10090.70952380950.38386454680.48614203260.60361111110.480.6133333333100.05771148930.06465184680.05608945580.06941089720.11632224290.17944745441112131234567891011121312345678910111213

zero correlation0.04591988270.04591988270.04539815910.04539815910.0606344950.0606344950.10449328960.10449328960.10234621380.10234621380.18854786090.1885478609

Confidence ratingClassification performance

0.08787867390.08787867390.04805392850.04805392850.08935009470.08935009470.07553921390.07553921390.14327753130.14327753130.06191348270.0619134827

Confidence ratingClassification performance

0.05771148930.05771148930.06465184680.06465184680.05608945580.05608945580.06941089720.06941089720.11632224290.11632224290.17944745440.1794474544

ConfidenceratingClassification performance

Other46656.0Other46872.0