research on learning & memory with neuromodulation in clmn lab€¦ · learning & memory...
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ResearchonLearning&MemorywithNeuromodulationinCLMNlab
PresentedbySungshinKimJune,30,2018http://clmnlab.com
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Taxonomyofbiologicalmemory
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3
WhymotorLearning?
OurlifeisacontinuumofmotorlearningLearningnewmotorskills
Adaptingtochanges
Regaininglostmotorskills
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Twotypesofmotorlearning2.Motorskilllearning1. Motoradaptation
(1)visuomotor adaptation(kinematics)
(2)force-fieldadaptation(dynamics)
Advantageofmotorlearningresearch:ü Easytoquantifytheamountoflearningü Possibletomeasureprogressoflearningü Theoretical&computationalapproacheswithmodelsareencouragedBut,within-subjectexperimentdesignisdifficult
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Effectsoftaskschedule onmotorlearningInterferencebetweentasks- Contextualinterferenceeffect
Timedecayofmemory- Spacingeffect
Grade:A
Grade:B
Grade:B
Grade:C
1h
Grade:A
1h1h1h1h 1h1h1h
4h 4h
8h
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Acomputationalmodelofmotorlearning&memory
f s( 1) ( 1) ( 1)y n x n x n+ = + + +f( )/
f f f( 1) ( ) ( )T nx n x n e e nt b-+ = +
xs (n+1) = xs (n)e−T (n)/τ s +βse(n) ⋅c(n)
Fastmemory
SlowMemory
Forgetting Learning
Trials
Learning
Slowmemory
Fastmemory
Motoroutput
xs
xf
y
Fast memory
Slow memory
e+
y
d-
c
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Bestschedulesforbothtwotasks?231 ≈2×109 possibleschedules!
Model-basedoptimalschedulesearchingAlgorithm(e.g.,Geneticalgorithm)
JYLee,YOh,SSKim,RScheidt,NScweighofer,NeuralComput,2016
…
Evolution(Crossover,Mutation)
Insearchofoptimallearningschedule
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Neuralsubstratesofmemorieswithmultipletimescales(modeling)
SKim,KOgawa,JLv,NScweighofer,HImamizu,PLoS Biology,2015
o 2RMSE 4.96 ,R 0.981= =
xk (n+1) = xk (n)exp(−T (n) / τ k )+βk ⋅e(n) ⋅c(n) Forgetting Learning
βk =rτ kq (k =1,..,30)
y(n) = xk (n)T
k=1
30
∑ c(n)
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Neuralsubstratesofmemorieswithmultipletimescales(fMRIresults)
SKim,KOgawa,JLv,NScweighofer,HImamizu,PLoS Biology,2015
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Fourprincipalnetworkswithdifferenttimescales
Applyingthestate-of-the-artsparsesingularvaluedecompositionmethod
SKim,KOgawa,JLv, NScweighofer,HImamizu,PLoS Biology,2015
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Multi-voxelpatternclassificationwithmachinelearningtechniques
Pattern Classifier
Task1
Task2
ClassificationofTask1vs.Task2- LinearSupportVectorMachine,averagedclassificationaccuracyreported
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Non-invasiveneuromodulation :Transcranial MagneticStimulation(TMS)
Maedaetal.,ClinicalNeurophysiol,2000
facilitation
inhibition
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TargetedTMSselectivelyactivatehippocampal-corticalmemorynetwork
Kimetal.,ScienceAdvances,2018
Stimulationlocation
Targetlocation
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Current&FutureResearch
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Multimodalapproachtolearning&memory
Behavior
Measurementoflearning,forgetting,interference
Modeling
Neuro-modulation
Computationmodelsforbehavioraldataandprediction
CausalinterventiontolearningusingTMS
fMRI
Investigationonneuralmechanisms
Learning&Memory
Clinicalstudy
Parkinson’sdisease,Stroke,Alzheimer’sdisease
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Setupofthelaboratory
ReachingtaskinfMRIscanner MR-compatibledataglove
Visuomotor experimentsetup TMSwithNeuronavigation system
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Ourteammembers
Sungshin KimPrincipalInvestigator
Kyusung LimPostdoc
Yera ChoiTo-be-hired
Yunha ShinTo-be-hired
Nayeon KwonStudentIntern
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Topic1:Neuralcorrelatesofreward-basedmotorskilllearninginhigh-dimensionalspace
ThefirstfMRIexperimentoflearninganewmotorskillfromscratch
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PreliminarybehavioralandfMRIresults
Early Late
FirstfMRIdemonstrationinhigh-dimensionalLearningmotorskillfromscratchWefoundstrongfMRIactivitiesinbilateralputamenmodulatingrewardduringmotorskilllearning
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Topic2:TMSmodulationofmotorlearning&memory
SKim,etal.,PLoS Biology,2015
Fast memory
Slow memory
e+
y
d-
c
+
Disruptingplanning
Disruptinglearning
Group1 Group2
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Thankyou
CLMN