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This 20 page Class Notes was uploaded by Henderson Schneider on Friday September 4, 2015. The Class Notes belongs to MED 0160B at University of California - Los Angeles taught by Staff in Fall. Since its upload, it has received 80 views. For similar materials see /class/177931/med-0160b-university-of-california-los-angeles in Medicine at University of California - Los Angeles.
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Date Created: 09/04/15
Percent Change and Power Calculation NITP 2009 Outline Calculating change How to do it What featquery does Power analysis Why you should use power calculations How to carry out power calculations Why Change As it is parameter estimates do not reflect a specific unit Tstats are okay they are unitless What if we want to tell other people how large our activation was Convert to change change How big is the signal magnitude relative to baseline sig magnitude mean change X 100 iggg39me m A n F J W WW La2 nu Block Design How to get the signal magnitude from parameter estimates 45 Design 4 39 Signal 39 35 3 25 39339 El5 num f f v 5 Hill 150 EDI 1 El 100 150 EDI pe4 EV height1 pe2 EV height2 1x4signal magnitude 2x2signal magnitude Block Design To make life easier set minmax range of EV s1 In FSL the Grand Mean Scaling sets mean1002 in all voxels PE100change roughly To be completely accurate you should divide by the true mean Event Related Design Tricky Proximity and length of events changes height v v v v t tz mu ts Event Related Design How about using minmax range Is it interpretable tell you I found a 2 change calculated using the minmax range Can you interpret this with your own design ER design Isoloated 2 second events I I l Design 2 Signal est 15 U Stimulua 1 05 I L AIfffffff U5 II II III II II II III III II I 2 4 BI SD 100 12D 14B 150 180 200 Variable ISI 2 second evenm 5 Ans 9 m M I III I III II III 5 39 ch2 nggl ePEXMiMMQXiJ hg 2PE AO 1A 1A 1A A El 0 51 III II II 39 U I 40 EU BU 1EJ 12D 141 160 180 Design Signal est Stimulue ER design Isoloated 2 second events 2 I I I 15 1 3 AAAAAAAAAA II III III III III III III II 0 5 II II I I 2 4 BI SD 100 12D 14D Variable ISI 2 second evenm 2 1 l I 15 I15 A A I I A 39 u H39 i r 39 III I III I 1 3 5 1 F I 39 I 4 5 SCI WEI 120 140 lscIoated variable length eve mg I l I III III III I I II III 2 40 EU BU 1EJ 12D 14D 393 ifkn J u AHA 50 J 150 180 201 ER design Isoloated 2 second events I I l Design 2 39 39 39 Signal est 15 U Stimulus 1 05 I L AIfffffff U5 II II III II II II III III II 1 2 4 131 SD 1110 12D 141 1131 181 21311 239 Variable ISI 2 second events All designs 15 have an a isolated 2 second event BUT the estimated signal is very E different 3905 I I F 39 I 4 5 SCI 1110 121 140 1 prAvAw may I 21 05 soloated variable length eve mg I l l 2 5 1 5 1 III I I II III 39 2 40 EU BU 1EJ 12D 140 V Ekn J u AHA p ER Design Minmax range doesn t work as well for event related design Doesn t translate well to other designs warning Featquery uses minmax range Instead of minmax range choose something specific isolated 2 second event and make sure to report what you used 1 change based on height of isolated 2s event ER Design isoloated 2 second eve nts l l l V ED 100 120 Variable ISI 2 second eventa 1quot I 1 quot El 1GB 120 Isoloated variable length evehm l l l 1 change based on height of isolated 2s event Now we can compare across designs Design 1 BIA FR AA VHfAfAf it it it 1 1 isoloated 2 second eve nts l l l I 2 Y Y 4 5 El 100 120 141 IEIJ ISIJ Variable ISI 2 second eventa l ZEN r I 1 quot I 4 8 El 100 120 141 Isoloated variable Iength evehm I l l w fx irr f x A A 9 139 ED 100 121 141 180 180 A note about contrasts What does the contrast 1 1 1 1 mean 3961 32 3 34 beta s are mean activations for 4 levels of subjects performing some task beginners some training medium training experts Test beginnerssome training medexperts 81 2182 2533 5364 52 1 2 45 and 3 4102 Difference is twice the mean difference A note about contrasts Although 1 1 1 1 implies a difference that is twice the original scale our test statistic is okay Since we re interested in preserving scale use contrast that give us means Positive parts sum to 1 Negative parts sum to 1 Rules to get almost change in FSL Baseline is already 1OO2 EV is constructed appropriately Boxcar height 1 ER design Specified event has height1 I like to ignore the post stimulus undershoot Construct contrast that follow the rules Positive parts sum to 1 Negative parts sum to 1 PE100change What if you didn t follow the rules Calculate the height of regressor as it was Height of block Height of specified typed of event Calculate contrast fix Number you d have to divide contrast by to fix it PEEV height 1 contrast x baseline x 00 change Example Study with subjects that were beginners some training medium training experts Level 1 isolated 2 second event using the gamma HRF has height02917 Level 2 used the contrast 1 1 1 1 COPE500 from contrast estimate 50002917 change 20002 x 100 0729
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