fMRI,experimental,design:,A,basic,plan, Experimental ... · • Reading&or&repeaBng&words&vs&...
Transcript of fMRI,experimental,design:,A,basic,plan, Experimental ... · • Reading&or&repeaBng&words&vs&...
Experimental,Design,for,
Brain,Imaging,I,
Susan&Bookheimer&
fMRI,experimental,design:,A,basic,plan,
Define&mental&process&
to&examine&
Define&tasks&to&manipulate&
that&process&
Measure&fMRI&data&
during&tasks&
Compare&fMRI&data&
between&tasks&
Replace&�fMRI&data�&with&�RT�&
and&you&have&cogniBve&
psychology!&
Conceptual,and,methodological,
aspects,of,experimental,design,
• There&are&two&aspects&of&fMRI&design&that&are&important&to&disBnguish&
• Conceptual&design&• How&do&we&design&tasks&to&properly&measure&the&processes&of&interest?&
• The&issues&here&are&very&similar&to&those&in&cogniBve&psychology&
• Methodological&design&• How&can&we&construct&a&task¶digm&to&opBmize&our&ability&to&measure&the&effects&of&interest,&within&the&specific&constraints&of&the&fMRI&scanning&environment?&
IV’s,and,contrasts:,basics,• There&are&(almost&always)&two&or&more&condiBons&in&acBvaBon&imaging&
• We&make&a&series&of&assumpBons&about&the&cogni&ve&and&the&neural&processes&involved,&and&their&relaBon&to&each&other,&in&every&experiment&
• The&logic&involved&and&choosing&tasks&and&contrasBng&them,&and&the&problems&of&assumpBons&in&these&choices,&spans&all&experimental&designs&
• In&this&context,&makes&no&difference&whether&we&use&event&related&or&blocked&designs,&eg.&&�Null�&events&in&ER&designs&oOen&=&�rest�&in&block&designs&
• Challenge:&Know&your&assumpBons;&choose&the&design&that&best&answers&your&quesBon,&minimizes&your&assumpBons,&and&allows&you&to&test&your&assumpBons&
General,Design,approaches,
• SubtracBonUbased&designs&• Factorial&Designs&• Parametric&Designs&
• SelecBve&AYenBon&Designs&• AdaptaBon&Designs&• ConjuncBon&approaches&• Weird&stuff&
General,Design,approaches,
• SubtracBonUbased&designs&• MulBUlevel&hierarchical&subtracBon&
• Simple&subtracBon&and&direcBonality&
• Common&baselines&and¶llel&comparisons&
• Tailored&baselines&
Experimental,Example:,
semantic,processing,,
Experimental Question: Language&sBmuli&can&enter&the&brain&through&various&modaliBes:&auditory,&printed&word,&meaningful&pictures.& What areas of the brain are essential for language (semantic) processing, independent of input modality, and unrelated to other factors such as motor output? What specific processes take place during language performance? -
&“HOUSE”&HOUSE
The,subtraction,method,
• Acquire&data&under&two&condiBons&
• These-condi&ons-puta&vely-differ-only-in-the-cogni&ve-process-of-interest-
• Compare&brain&images&
acquired&during&those&
condiBons&
• Regions-of-difference-reflect-ac&va&on-due-to-the-�subtracted�-process-of-interest- Petersen et al., 1988
Hierarchical,subtraction,
example'from'Petersen,'1991,
• Rest Control&
• Auditory&words&or&Visual&Word&(passive&presentaBon)&
• Reading&or&repeaBng&words&vs&passive&words:&motor&areas&&
• GeneraBng&words&vs.&repeaBng:&semanBc&(language)&areas&
- }
Semantic
Motor
Sensory
Design: Subtract out sensory and motor aspects of language from higher order semantic tasks using hierarchically based subtractions
- } - }
The,pure,insertion,assumption,
• SubtracBon&requires&a&strong&assumpBon&of&
�pure&inserBon�&
• Inser&on(of(a(single(cogni&ve(process(does(not(affect(any(of(the(other(processes((no(interac&ons)(
• �Controlled�&variables&do¬&change&as&you&add&processes&(move&“up”&the&hierarchy)&• Eg,&Neural&processes&involved&in&reading&words&out&loud&are&idenBcal&to&those&in&reading&silently,&plus&motor&
• &PI&must&hold&at&both&neural&and&cogniBve&levels&
Pure,insertion,in,a,hierarchical,model,
S& M&
“rest”& Sensory:&View&
words&
Motor:&Read&
words&
SemanBc:&generate&
words&
L&
In&hierarchical&subtracBon&models,&you&pile&up&the&pure&inserBon&assumpBons&with&each&addiBonal&
hierarchical&level!&&
Failure,of,pure,insertion,in,a,hierarchical,
model,
S&V1&
M&M1&
“rest”&Sensory:&View&
words&
Motor:&Read&
words&
SemanBc:&generate&
words&
L&
=&M&
M&
MotorUsensory&
U1& 1&
Motor:&Read&
words&
=&U1& 1&L&
M&SemanBcU&Motor&
• One&level&of&hierarchy&&&• Test&for&violaBon&of&addiBvity&assumpBon&
• Allows&you&to&see&common&areas&acBve&for&A&and&B&
• Assumes&A&and&B&have&similar&psychometric&properBes&
(ie,&level&of&difficulty,&variaBon,&and&distribuBon&in&the&
populaBon)&
• Need&addiBonal&approach&to&see&unique&areas&
Ex B Ex A
Control
Common Baseline Is(there(evidence(for(pure(inser&on:((Does(reading(words(aloud(add(motor(areas(without(changing(silent(reading(areas?((
Oral Reading
Silent reading
Rest
&&&&&Read&&
�HOUSE�&
Name&
Simple,subtraction,assumptions,
• Make&assumpBons&about&&• What&your&tasks&are&doingU&do&they&tap&into&the&processes&of&interest&
• How&they&differ&(what&variables&are&shared,&what&are&unique)&
• OOen&assume&(mistakenly)&that&differences&
are&due&to&increases&in&one&condiBonU&that&
which&is&the&�higher&order�&task&or&the&
experiment&(vs.&control)&task&From Morcom and Fletcher, NeuroImage, 2006
• EG:&Seeing&words&vs.&hearing&words&• Alone,&see&no&common&areas&
• Good&adjunct&to&common&baseline&
• Use&common&baseline&as&mask&to&reduce&errors&and&
increase&power&in&likely&areas&
• Assumes-similar-psychometric-proper&es-of-A-and-B-
Ex B Ex A
Ex A Ex B >
>
Assuming,no,hierarchy:,Parallel,Comparisons,,
,
See Words
Speak Words
Speak Words
See Words
>
>
Word-order-change-
Word-change-
DapreYo&et&al:&SemanBc&vs.&SyntacBc&Processing&
The&city&is&west&of&the&school&
&West&of&the&school&
is&the&city&
The&city&is&west&of&the&school&
&The&town&is&west&of&
the&school&
Common&Baseline&comparison&
DapreYo&and&Bookheimer,&Neuron,&1999&
47&45&
DapreYo&et&al:&SemanBc&vs.&SyntacBc&Processing&
Parallel&comparison&
Common,baseline,and,
Parallel,comparisons,
Sem& Syn&Other&
lang,&task&
“rest”& SemanBc&decision&
SyntacBc&decision&
Direct&comparisons&
Sem&
Other&lang,&task&
Syn&
But,one,task,could,be,harder…..,
Sem&Syn&
Other&lang,&task&
“rest”& SemanBc&decision&
vs.&rest&
SyntacBc&decision&vs.&
rest&
Direct&comparisons&
Sem&Other&lang,&task&
Syn&
UUUAssumes&similar&psychometric&properBes&of&tasks&
Other&lang,&task&
• Example&study&(ThomsponUSchill,&PNAS&1997):&Do&frontal&areas&implicated&in&semanBc&processing&really&involve&semanBcs,&or&are&they&instead&important&for&response&selecBon&(independent&of&task)&
• Use&3&different&tasks:&generaBon,&classificaBon,&and&comparison;&each&has&its&own&control,&each&as&different&levels&of&selecBon&demand&
Tailored,baseline,
Do(visual(language(and(auditory(language(s&muli(share(seman&c(representa&ons?(U Want(to(look(only(at(seman&c(areas,(not(sensory(areasA(
tailor(control(tasks(for(each(experimental(tasks,(each(control(task((matched(for(unwanted(variables(
ThompsonUSchill&et&al&PNAS&1997&
Tailored,baseline,
• Assumes&baseline&tasks&control&for&(sensory&input)&equally&
• &&reading&a&word&controls&for&generaBng&an&associate&to&a&word,&as&well&as&matching&a&word&controls&&for&matching&a&property&&
Tailored,baseline,
• Assumes&similar&psychometric&properBes&of&both&experimental&and&both&control&tasks&
• The&distribuBon&of&behavior&and&its&neural&responses&(magnitude,&RT,&sd,&etc)&for&high&selecBon&generaBon&compared&to&reading&:&is&the&same&as&that&for&high&selecBon&classificaBon&compared&to&the&control&
• Need&very&extensive&behavioral&tesBng&&
Factorial,design,
• A&factorial&design&involves&mulBple&concurrent&subtracBons&
• Allows&for&tesBng&of&interacBons&between&components&
• SBll&requires&pure&inserBon&assumpBon&and&task&decomposiBon&
• But&addiBvity&can&be&tested&for&the&specific&factors&that&are&manipulated&
Directed,Attention,Models,
• All&sBmuli&idenBcal&in&all&condiBons&
• Direct&aYenBon&towards&different&features&• Implicit&or&explicit&
• Assumes&process&is&modified&by&directed&aYenBon&
• Assumes&passive&processing&does¬&capture&your&variable&of&interest&&
EG,Corbetta,et,al,
Selective,attention,
• In&every&condiBon,&all&three&variables&change&• Told&to&respond&to&a&shape,&color&or&movement&
change&in&different&blocks&
• SelecBvely&acBvates&form,&color,&moBon¢ers&
• Assumes&your&process&of&interest&is&modified&by&
directed&aYenBon&(oOen&true,¬&always)&
• Can&be&done&explicitly&or&implicitly&(You&can&change&a&
factor&that&does¬&change&instrucBons)&
• Read&words;&some&may&be&high,&others&low&imagery&
Parametric,designs,
• Employs&conBnuous&variaBon&in&a&sBmulus/task¶meter&• E.g.,&working&memory&load,&sBmulus&contrast&
• Inference:&• ModulaBon&of&acBvity&reflects&sensiBvity&to&the&modulated¶meter&
Boynton,et,al.,,1996, Assumptions,of,parametric,designs,
• Pros:&you&don’t&have&to&design&a&control&conidBonU&no&subtracBon&
• AssumpBon&of&pure&modulaBon&• Each&level&of&the&task&differs&quanBtaBvely&in&the&level&of&engagement&of&the&process&of&interest,&rather&than&qualitaBvely&
• Assumes&you&can&define&the&magnitude&differences&across&levels&(usually&assumes&equality,&but¬&necessarily&
• Failures:&• Response&is&a&step&funcBon&• There&are&different&processes&engaged&at&different&levels&
Cohen,et,al.,,1996,
0&and&1Uback&do¬&require&WM;&2&does;&step&funcBon&with&a&qualitaBve&change&in&process&
Priming/adaptation,designs,
• PresentaBon&of&an&item&mulBple&Bmes&leads&to&
changes&in&acBvity&• Usually&decreased&acBvity&upon&repeBBon&
• Inference:&• Regions&showing&decreased&acBvity&are&sensiBve&to&(i.e.&represent)&whatever&sBmulus&features&were&repeated&
• Requires&version&of&pure&modulaBon&assumpBon&• Assumes&that&processing&of&specific&features&is&reduced&but&that&
the&task&is&otherwise&qualitaBvely&the&same&
Can,adaptation,fMRI,characterize,
,neural,representations?,,
,
• A&voxel&containing&neurons&that&respond&to&all&poliBcians,&irrespecBve&of&party&
• A&voxel&containing&some&specifically&DemocraBc&
neurons,&and&other&specifically&Republican&
neurons.&&
Two&sBmuli:&can&neurons&tell&the&
difference?&
From&R.&Raizada&
Responses,to,individual,stimuli,
do,not,show,whether,neurons,can,tell,the,
difference,
• Different&sets&of&neurons&are&acBve&
within&the&voxel,&
but&overall&fMRI&
responses&are&
indisBnguishable&&
From&R.&Raizada&
Neural,adaptation,to,repeated,stimuli,does,show,the,difference:,
What,counts,as,repetition,for,neurons,in,a,voxel?,
It�s a politician" Same neurons, adapting:"It�s a politician again"
It�s a Republican" Different, fresh neurons: It�s a Democrat"
From&R.&Raizada&
Adaptation,in,bilingual,subjects,
,Do(different(language(share(seman&c(representa&ons(across(languages(in(bilingual(subjects?((Chee(et(al(
Chee,et,al,2003,
Main&effect&for&meaning&(adaptaBon)&in&LIFG,¬&LOcc&
Conjunction,analysis,(Price,&,Friston,,1997),
• Perform&several¶llel&subtracBons&
• Each&of&which&isolates&only&the&process&of&interest&• Find®ions&that&show&common&acBvaBon&across&all&of&these&
Ex A - Ctl Ex B - Ctl Ex C - Ctl
A AND B AND C
from&Price&&&Friston,&1997&
BTLA],all,tasks,involving,accessing,phonology,
Problems,with,conjunction,analysis,,
(Caplan,&,Moo,,2003),
• Many&assumpBons&about&what&processes&are&involved&
• Implicit&processing&• Subjects&may&engage&processes&that&are¬&necessary&for&the&taskU&does¬&measure&magnitude&differences&
• InteracBons&between&processing&stages&• ConjuncBon&only&gets&rid&of&interacBons&if&they&do¬&acBvate&the&same®ions&to&the&same°ree&across&tasks&
• We&use&this&approach&for&finding&consistent&but&lowUlevel&acBvaBons&in&clinical&mapping&&
&
Factor]determined,component,classi^ication:,
Badre,,Poldrack,et,al,2005,
IFG,dissociations,
Badre,&Poldrack&etc&2005&
2]group,designs,
• Build&on&any&of&the&prior&designs&• AddiBonal&between&group&comparisons&
• Hypothesis&sounds&something&like:&
• “&the(differences(between(experimental(and(control(task(in(my(pa&ent(group(differs(from(that(difference(in(controls”(
• Assumes&baseline&task&performance&is&equal&
• What&if&one&group&cannot&perform&the&task&well?&
• Eg:&dyslexia:&give&a&nonUword&reading&task&
Counterbalancing,
• With&more&than&2&condiBonsU&essenBal&
• EG:&Low,&medium&and&high&stress&condiBons&• HabituaBon&• Order&effects&&eg&High&carryUover&
• Complete&counterbalancing&(recruit&in&groups&of&N!&where&N&is&the&total&number&of&condiBons)&• 1&2&3&&&&132&&&&231&&&&213&&&312&&&&312&
• LaBn&Square&(recruit&in&groups&of&N&condiBons)&• 123&&231&&312&• Each&condiBon&in&each&serial&order&• &assumes-no-taskDtask-order-interac&ons-
Summary,
• No&design&is&perfect&• &Use&that&which&is&most&consistent&with&your&specific&
research&quesBon&
• MulBple&�baseline�&condiBons&help&interpretaBon&
• Behavioral&data&is&extremely&helpful&in&supporBng&
many&assumpBons&and&prevenBng&criBcal&errors&
• Beware&of&your&assumpBons!&all&designs&make&
assumpBons&that&are¬&fully&verifiable;&know&
them!&
• Freely&admit&your&design&limitaBons&