北大心理學(xué)系.心理物理學(xué)方法與Matlab實(shí)現(xiàn)

心理物理學(xué)方法和matlab實(shí)現(xiàn)

2015-6-21

ReferencesWatsonandPelli(1983)QUEST:ABayesianadaptivepsychometricmethod.Leek(2001)Adaptiveproceduresinpsychophysicalresearch.Strasburger(2001)Convertingbetweenmeasuresofslopeofthepsychometricfunction.Strasburger(2001)Invarianceofthepsychometricfunctionforcharacterrecognitionacrossthevisualfield.GrassiandSoranzo(2009)MLP:aMATLABtoolboxforrapidandreliableauditorythresholdestimation.-psychoacoustics/內(nèi)省法早期心理學(xué)家采用的方法(Wundt)對(duì)有意識(shí)思考和感知的自我觀察DoIperceivethislightbrighterthanthat?Why?因其主觀性而被科學(xué)的方法所拒絕

但提供“先見之明”，有利于設(shè)計(jì)實(shí)驗(yàn)和形成假說。

Irealizedthatitishardformetohearveryhighandverylowtones.Thusthefrequencyofatonemaybeafactorinitsperceivedloudness/audibility.Let’stestthisinanexperiment!Psychophysicalfunctions費(fèi)希納的三個(gè)問題第一、覺察給定刺激所必需的最小物理刺激是什么？這個(gè)問題同絕對(duì)閾限(AL)有關(guān)。第二、覺察兩個(gè)不同刺激量所需的最小物理差別是什么？這涉及差別閾限(DL)。第三、判別兩個(gè)刺激在心理感覺上相等的條件是什么？這是主觀相等點(diǎn)(PSE)的問題。GustavTheodorFechner1801–1887心理物理實(shí)驗(yàn)法古典心理物理學(xué)的基本問題在精心控制的實(shí)驗(yàn)條件下，刺激的變化直接對(duì)應(yīng)于感覺的變化心理物理學(xué)研究的目的在于決定外部世界的一致性規(guī)律-韋伯定律閾限(Thresholds)Ifalinearrelationshipisassumed,twovaluesdeterminethefunction:X-intercept:minimumstimulusvaluethatevokedanysensation;

absolutethresholdSlope:therateatwhichsensationgrowsasweincreaseintensity;

differencethreshold

(inverselyproportionaltoslope)StimulusintensitySensationmagnitudeLinearpsychophysicalequationX-interceptslopeThresholdsGeneraldefinitions(notassuminglinearity):絕對(duì)閾限（Absolutethreshold）:

intensitythattheobservercanjustbarelydetectIntensitiesbelowabsolutethreshold:undetectableIntensitiesaboveabsolutethreshold:detectable差別閾限（Differencethreshold）(justnoticeabledifference/JND/

anddifferencelimen):

minimumintensitydifferencethatisnoticeabletotheobserverAchangeinintensitythatissmallerthanthedifferencethreshold:undetectableAchangeinintensitythatislargerthanthedifferencethreshold:detectableDifferencethresholdsLinearfunction

differencethreshold(slope)isconstantAnobserverabletodetectthedifferencebetweenintensities100and110shouldalsobeabletodetectthedifferencebetween1000and1010.Thisisnotthecase:theobserverisabletodetectthedifferenceonlybetween1000and1100500&550Hztones5000&5050Hztones5000&5500HztonesDifferencethresholdisnotconstant!StimulusintensitySensationmagnitudeLinearpsychophysicalequationconstantslopeDifferencethresholdsDifferencethresholdisnotconstant(changeswithintensity)

functionisnonlinearWeber’slaw:differencethresholdisaconstantproportionoftheinitialstimulusvalueΔI/I=cPrevious

examples:

c=10%Weber’slaw

holdsonly

approximately!StimulusintensitySensationmagnitudeNonlinearpsychophysicalequationslopechangeswithintensityAbsolutethresholdsEvenintheabsenceofstimulation,thereissomerandomfiringonsensorynervesThisinnernoisecanevenvaryfrommomenttomomentObserverscannotdistinguishinnernoisefromtheeffectofaweakstimulusEvenwhenthereisnolight(perfectdarkness),observersmayexperienceadimlight(darklight,intrinsiclight)ObserversinananechoicchamberoftenreporthearingawhistlingsoundMeasuringtruly?absolute”thresholdsisproblematic:observersmayconfuseinnernoisewiththerealthingPsychophysicalmethodsThresholdmeasurements:absolutethr/differencethr.–Isitintenseenoughtosee?Howsmalladifferencecanyousee?-Fechner’s3methodsMethodofconstantstimuliMethodoflimitsMethodofadjustment-ModificationofFechner’smethodsStaircasemethodModificationofthemethodofconstantstimuli(adaptive,nostandard)Forcedchoice,objectivemethodsSensorydecisiontheory(SDT)PsychologicalfunctionsfrompsychometricdataDirectscaling:growthofsensationwithintensity,Howbrightdoyouseealight?-MagnitudeestimationandthepowerlawMultidimensionalscaling:degreetowhichstimuliarecomparablealongsomedimensions

Alongwhichdimensionsdoyoujudgethesimilarityoftwostimuli?古典心理物理實(shí)驗(yàn)的基本方法（1）極限法或最小變化法；（2）恒定刺激法；（3）調(diào)整法或平均誤差法。確定絕對(duì)閾限的方法：（1）極限法；(2）階梯法（3）恒定刺激法；（4）調(diào)整法。確定差別閾限方法：（1）極限法（最小變化法）；（2）恒定刺激法。極限法:

非常有效，只需少數(shù)刺激就可以確定閾限值。然而被試表現(xiàn)出特定的慣性偏差。恒定刺激法：

刺激以隨機(jī)序列的方式呈現(xiàn)，非?？煽坎⑶覠o偏。

調(diào)整法：比如顏色心理物理學(xué)。

心理物理學(xué)實(shí)驗(yàn)非常精細(xì)，通常在人們感覺器官的極限水平上操作，因此，很少讓人感覺到愉悅。請(qǐng)將你的大腦皮層的焦點(diǎn)活力集中在當(dāng)前當(dāng)然的任務(wù)。心理物理學(xué)的過程為產(chǎn)生并分析錯(cuò)誤。如果你不犯錯(cuò)誤，就沒有變異；沒有變異，那么大多數(shù)的心理物理學(xué)方法都失效，更別提大量的試次測(cè)試。需要達(dá)到一種平衡：練習(xí)效應(yīng)提高判斷的績(jī)效；然而“疲勞”效應(yīng)抵消了判斷的績(jī)效。

極限法（Methodoflimits）descendingseriesascendingseriesStimulusintensityStimulusnolongerdetectedStimulusdetectedThreshold:averagestimulusintensity恒定刺激法又叫正誤法，通常由5-7個(gè)刺激組成，這幾個(gè)刺激在實(shí)驗(yàn)過程中保持不變此法的特點(diǎn)是根據(jù)出現(xiàn)的次數(shù)來確定閾限，即以次數(shù)的整個(gè)分布求閾限，所以又叫次數(shù)法

具體作法如下

a、主試從預(yù)備實(shí)驗(yàn)中選出少數(shù)刺激，一般是5到7個(gè)，這幾個(gè)刺激值在整個(gè)測(cè)定過程中是固定不變的；

b、選定的每種刺激要向被試呈現(xiàn)多次，一般每種刺激呈現(xiàn)50到200次；

c、呈現(xiàn)刺激的次序事先經(jīng)隨機(jī)安排，不讓被試知道。用以測(cè)量絕對(duì)閾限，即無需標(biāo)準(zhǔn)值，如用以確定差別閾限或等值，則需包括一個(gè)標(biāo)準(zhǔn)值；

d、此法在統(tǒng)計(jì)結(jié)果時(shí)必須求出各個(gè)刺激變量引起某種反應(yīng)（有、無或大、?。┑拇螖?shù)。恒定刺激法

(Methodofconstantstimuli)StimulusintensityStimulusdetectedStimulusnotdetectedFechner’sthreemethodsPresentingonestimulusatatimeThestimulusisveryweakPossibleresponses:

“Yes,Iseeit.”/

“No,Idon’tseeit.”AbsolutethresholdDifferencethresholdMethodofconstantstimuliMethodoflimitsMethodofadjustmentnotusedPresentingtwostimuliatatime:Standard:fixed,easilydetectableComparison:eithermoreorlessintensethanthestandardPossibleresponses:

“Comparisonisstronger.”/

“Comparisonisweaker.”MethodofconstantstimuliformeasuringabsolutethresholdsSelectarangeoflightintensitiesfromcertainlyinvisibletocertainlyvisiblePickafew(4-7)pointsuniformlyinthisintensityrange;thiswillbetheconstantstimulussetWeakStrongLightintensityMethodofconstantstimuliformeasuringabsolutethresholdsTesteachstimulusmanytimes(20-25)inrandomorder…MethodofconstantstimuliformeasuringabsolutethresholdsPresentthestimulioneatatimeandasktheobserverifitwasvisibleornotVisible?

YES NOClicktostartCouldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?Couldyouseethespotoflight?MethodofconstantstimuliformeasuringabsolutethresholdsCalculatetheproportionof“yes”and“no”responsesateachlightlevel + - + + + - - - + + + - - - - + 0% 5% 20% 50% 80% 95% 100%MethodofconstantstimuliformeasuringabsolutethresholdsPlotthepercentagesagainststimulusintensity

psychometricfunctionStimulusintensityPercentage“seen”0%100%50%75%25%Psychometricfunction

forabsolutethresholdsIdealFIG(Sekuler)FixedabsolutethresholdStepfunctionActualFIG(Sekuler)Absolutethresholdvariessomewhatfromtrialtotrial(duetoconstantfluctuationsinsensitivity)Conventionally,theintensitycorrespondingto50%isconsideredtobethethresholdsigmoidfunctionMethodofconstantstimuliformeasuringdifferencethresholdsStandardstimulushasafixedintensityTheintensitiesofcomparisonstimulibracketthestandardLightintensityStandardstimulus:Comparisonstimuli:MethodofconstantstimuliformeasuringdifferencethresholdsAllpairsofstandardandcomparisonstimuliaretestedmanytimesMethodofconstantstimuliformeasuringdifferencethresholdsForeachpair,theobserverjudgesifthecomparisonstimuluswasstrongerorweakerthanthestandard

STRONGER

WEAKERMethodofconstantstimuliformeasuringdifferencethresholdsForeachcomparisonlevel,thepercentageof“stronger”responsesiscalculatedandresultsareplottedasapsychometricfunctionLightintensityofcomparisonstimuliPercentage“stronger”0%100%50%75%25%PsychometricfunctionfordifferencethresholdsWhentheobservercannotseeadifference,he/shechoosesrandomlybetween“stronger”and“weaker”;thiscorrespondsto50%onthepsychometricfunction

pointofsubjectiveequivalence(PSE)LightintensityofcomparisonstimuliPercentage“stronger”0%100%50%75%25%PSEPsychometricfunctionfordifferencethresholdsByconvention,theintensityat75%isconsideredtobejustnoticeablystrongerthanthestandard

DSAcomparisonintensityat25%isjustnoticeablyweakerthanthestandard

DWDifferencethreshold=theaverageofDSandDWLightintensityofcomparisonstimuliPercentage“stronger”0%100%50%75%25%DWDSPsychometricfunctionfordifferencethresholdsMethodoflimitsformeasuringabsolutethresholdsOneachtrial,theobserverreportsifshe/hecouldseethelightornot.Startwithpresentingalightintensitywellabovetheexpectedthreshold(theobservercancertainlyseeit)DecreasetheintensityuntiltheobservercannotseeitThresholdestimate:theintensityatwhichtheresponsechanges+-+++++----LightintensityTrialsDescendingseries:startfromabovetheexpectedthresholdanddecreaseintensityAscendingseries:startfrombelowtheexpectedthresholdandincreaseintensitythresholdestimateClicktostartMethodoflimitsformeasuringabsolutethresholdsAscendinganddescendingseriesmayyielddifferentresults

usebothEveninthesamedirection,thereisvariabilityinthethreshold(innernoise,etc)

averagemanymeasurementsMeasuredthresholdcorrespondsto50%pointinapsychometricfunction(methodofconstantstimuli)+-+++++-----+++++----LightintensityTrialsthresholdestimateMethodoflimitsformeasuringdifferencethresholdsIntensityofthecomparisonstimulusisdecreased(descending)orincreased(ascending)untiltheresponsechangesThresholdestimate:intensitydifferencebetweenthestandardandcomparisonstimuliwheretheresponsechangesAverageresultsfrommultipleseriesinbothdirections+-++++LightintensityofcomparisonstimulusTrials+ comparisonbrighter- comparisonweaker+----+-++++-----+

例子1-確定視覺的相對(duì)閾限

(Hecht,Shlaer,andPirenne,1942-energy,quantaandvision)

中央注視點(diǎn)clearall;%Emptyingworkspacecloseall;%closingallfigurestemp=uint8(zeros(400,400,3));%Createadarkstimulusmatrixtemp1=cell(10,1);%Createacellthatcanhold10matricesfori=1:10%Fillingtemp1temp(200,200,:)=255;%Insertingafixationpointtemp(200,240,:)=(i-1)*10;%Insertingatestpoint40pixelsrightofit.%Brightnessrange0to90temp1{i}=temp;%Puttingtherespectivemodifiedmatrixincellend%Donedoingthat

h=figure%Creatingafigurewithahandlehstimulusorder=randperm(200);%Creatingarandomorderfrom1to200.%Forthe200trials.Allowstohavea%preciselyequalnumberperconditionstimulusorder=mod(stimulusorder,10);%Usingthemodulusfunctionto%createarangefrom0to9.20eachstimulusorder=stimulusorder+1;%Now,therangeisfrom1to10,asdesired.score=zeros(10,1);%Keepingscore.Howmanystimuliwerereportedseen.fori=1:200%200trials,20perconditionimage(temp1{stimulusorder(1,i)})%Imagetherespectivematrix.As%designatedbystimulusorderi%Givesubjectfeedbackaboutwhichtrialwearein.Nootherfeedbackpause;%Getthekeypresstemp2=get(h,'CurrentCharacter');%Getthekeypress,"."forpresent,%","forabsenttemp3=strcmp('.',temp2);%Comparestrings.If.(present),temp3=1,%otherwise0score(stimulusorder(1,i))=score(stimulusorder(1,i))+temp3;%Addup%Intherespectivescoresheetend%Endthepresentationoftrials,after200havelapsed.Whichisbrighter?心理物理學(xué)曲線（Thepsychometriccurve）典型的心理物理學(xué)曲線Example:Fitaprobitregressionmodelforyonx.glmfit心理物理學(xué)階梯法

如果所有給定的事情對(duì)于行為分析很重要，那么利用恒定刺激法否則，考慮使用階梯法(staircasemethod)Leek(2001)Transformedup-downmethodImprovementofthesimpleup-down(staircase)methodXn+1dependson2ormoreprecedingresponsesE.g.1-up/2-downor2-steprule:IncreasestimuluslevelaftereachincorrectresponseDecreaseonlyafter2correctresponsesφ=70.7%Threshold:

mid-runestimate8rulesfor8differentφvalues

(15.9%,29.3%,50%,70.7%,79.4%,84.1%)reversalpointstwo-down,one-upprocedure,whichtargetsthe70.7%levelonthepsychometricfunctionSimpleup–downprocedure,boththepositiveandthenegativesequencesconsistofonetrial,andthetracklevelmovesaftereachresponse,targetingthe50%performancelevel.例子2-聽覺時(shí)距判斷/觸覺強(qiáng)度(staircase)StaircaseDoublestaircaseTFLEDurstaircase.mBertelson,1998使用PEST（ParameterEstimationbySequential

Testing)

/QuestPEST:Findthreshold.m,

QUEST:WatsonandPelli,1983利用心理物理法階梯法：對(duì)于實(shí)驗(yàn)中反應(yīng)的每一個(gè)點(diǎn)，根據(jù)已經(jīng)收集的數(shù)據(jù)和對(duì)閾值的先驗(yàn)知識(shí)，計(jì)算閾值的最大似然率例3-使用PSET方法-聲音時(shí)距比較SndComparison.m使用QuestUsingQuestWatsonandPelli,1983Thequestalgorithmisaveryefficientwaytoconductexperimentsusingpsychophysicalstaircases.Ateachpointintheexperiment,itcalculatesthemaximumlikelihoodestimateofthethreshold,giventhedatacollectedsofarintheexperimentandthepriorwehadonthethresholdgoingintotheexperimentItproposestheintensityofthestaircaseparameter,forwhichatrialwouldresultinthemaximalinformationonthevalueofthethresholdOnemajordisadvantageoftheQuestalgorithmisthatitrequiresinputonalogscale.例子4:目標(biāo)檢測(cè)找紅色圓形的目標(biāo)。即在一堆的綠色圓和紅色方塊中是否出現(xiàn)紅色圓目標(biāo)使用Quest方法-目標(biāo)偵測(cè)inputonalogscaleQuestQuantileQuestUpdateQuestcanbesetuptorununtilitreachesanestimateofthethresholdwithaspecificsizeoftheconfidenceintervalaroundgivesasanoutputanestimateofthestaircaseparametergiventhedatastoredinthequeststructupdatesthequeststructwiththeresultofthistrialintializationofthehistorystructbeta=3.5;delta=0.01;gamma=0.5;history.q=QuestCreate(tGuess,tGuessSd,params.pThreshold,beta,delta,gamma);信號(hào)檢測(cè)理論觀察者對(duì)一個(gè)信號(hào)是否出現(xiàn)，存在一個(gè)標(biāo)準(zhǔn)（criterion),這個(gè)標(biāo)準(zhǔn)也適用于神經(jīng)經(jīng)濟(jì)學(xué)家慣常研究的選擇行為(choicebehavior)d-prime(d’):

標(biāo)準(zhǔn)化信號(hào)（分布）-標(biāo)準(zhǔn)化噪聲（分布）；

信號(hào)檢測(cè)理論完美偵測(cè):100%100%0%0%信號(hào)檢測(cè)理論無法偵測(cè)100%0%0%100%信號(hào)檢測(cè)理論無法偵測(cè)0%100%100%0%信號(hào)檢測(cè)理論無法偵測(cè)：擲硬幣

50%50%50%50%信號(hào)檢測(cè)理論沒有檢測(cè)，比如統(tǒng)一匯報(bào)看見的比例為30%30%70%70%30%==Rowsequal

nodetection信號(hào)檢測(cè)理論

操作特征曲線(ROC):falsealarmratehitrate100%100%

操作特征曲線(ROC):falsealarmratehitrate100%100%90%30%10%70%信號(hào)檢測(cè)理論信號(hào)檢測(cè)理論操作特征曲線

(ROC):falsealarmratehitrate100%100%100%0%0%100%Perfectdetection信號(hào)檢測(cè)理論操作特征曲線(ROC):falsealarmratehitrate100%100%100%100%0%0%Nodetection:always“yes”信號(hào)檢測(cè)理論操作特征曲線(ROC):falsealarmratehitrate100%100%0%0%100%100%Nodetection:always“no”信號(hào)檢測(cè)理論操作特征曲線(ROC):falsealarmratehitrate100%100%50%50%50%50%Nodetection:reporting“yes”in50%ofthetrials(flippingacoin)信號(hào)檢測(cè)理論操作特征曲線(ROC):falsealarmratehitrate100%100%40%40%60%60%Nodetection:reporting“yes”in40%ofthetrials信號(hào)檢測(cè)理論操作特征曲線(ROC):falsealarmratehitrate100%100%30%30%70%70%Nodetection:reporting“yes”in30%ofthetrials信號(hào)檢測(cè)理論操作特征曲線(ROC):falsealarmratehitrate100%100%60%60%40%40%Nodetection:reporting“yes”in60%ofthetrials信號(hào)檢測(cè)理論操作特征曲線(ROC):falsealarmratehitrate100%100%Diagonal:nodetection信號(hào)檢測(cè)理論SDT模型:無法消除噪聲但通過ROC，可以分離知覺與決策。

感知覺噪聲決策信號(hào)出現(xiàn)/不出現(xiàn)感知覺水平(SL)SL≥

β標(biāo)準(zhǔn)

(β)SL<βYESNO信號(hào)檢測(cè)理論感覺水平概率如果沒有噪聲，完全偵測(cè)是有可能的。標(biāo)準(zhǔn)信號(hào)出現(xiàn)信號(hào)不出現(xiàn)感知覺噪聲決策信號(hào)出現(xiàn)/不出現(xiàn)感知覺水平(SL)SL≥

β標(biāo)準(zhǔn)

(β)SL<βYESNO感覺水平概率標(biāo)準(zhǔn)信號(hào)出現(xiàn)信號(hào)不出現(xiàn)100%0%0%100%信號(hào)檢測(cè)理論感知覺噪聲決策信號(hào)出現(xiàn)/不出現(xiàn)感知覺水平(SL)SL≥

β標(biāo)準(zhǔn)

(β)SL<βYESNO感覺水平probability噪聲:使得信號(hào)分布變得模糊無法完美偵測(cè)(特別是信號(hào)和噪聲分布重合)信號(hào)不出現(xiàn)

(只有噪聲)信號(hào)出現(xiàn)

(信號(hào)+噪聲)標(biāo)準(zhǔn)信號(hào)檢測(cè)理論感知覺噪聲決策信號(hào)出現(xiàn)/不出現(xiàn)感知覺水平(SL)SL≥

β標(biāo)準(zhǔn)

(β)SL<βYESNO信號(hào)檢測(cè)理論SensationlevelSensationlevel信號(hào)檢測(cè)理論SensationlevelSensationlevelfalsealarmratehitrate信號(hào)檢測(cè)理論falsealarmratehitrateROCcurveβ=8β=6β=10β=6β=8β=10信號(hào)檢測(cè)理論falsealarmratehitrateβsensationlevelprobability標(biāo)準(zhǔn)(β):定義在ROC曲線上的位置ROC曲線僅由感覺通道的容量（能力）所定義

(即可辨別性)信號(hào)檢測(cè)理論可辨別性:觀察者從噪聲的疊加分布中區(qū)分出信號(hào)的能力測(cè)量d’(可辨別性指標(biāo)，亦稱“敏感度”

)信號(hào)檢測(cè)理論d’:選擇

ROC曲線β:選擇ROCcurve上的一點(diǎn)對(duì)于擊中與虛報(bào)，信息采樣是一樣的，但是:擊中與虛報(bào)率:

都反映了知覺與決策的特性，但不能分離兩者;

d’:取決于感知覺β:取決于決策β這兩個(gè)過程是分離的！！信號(hào)檢測(cè)理論Fechner方法:

Isastimulusdetectable?Yesorno?Clear-cutthresholdvalue(withsomevariability)thatcanbemeasuredStimulusintensity>thresholddetectableStimulusintensity<thresholdnotdetectable兩分法、絕對(duì)模型信號(hào)檢測(cè)理論:

Howwellisitdetectable?Howsensitivetheobserveristothestimulus?Measuredbyd’Thehigherd’is,themorethestimulusisdetectabled’=0

notdetectableatall線性結(jié)果