dset 1 1 1 stats.sb04.betas+tlrc

More documents

Recommendations

Info

-14- in afni, view run 01, time points 38, 39 and 40 while it appears that something happened at time point 39 such as a swallow,sneeze, or similar movement it may not be enough to worry about if there had been a more significant problem, and if it could not be fixed by3dvolreg, then it might be good to censor this time point via the -censor optionin 3dDeconvolveinternal movement canbe seen in this area,using afniBig spike attimepoint 39
-15-• Next, perform temporal alignment using 3dTshift. Slices were acquired in an interleaved manner (slice 0, 2, 4, …, 1, 3, 5, …). Interpolate each voxel's time series onto a new time grid, as if each entirevolume had been acquired at the beginning of the TR (TR=3 seconds in thisexample) For example, slice #0 was acquired at times t = 0, 3, 6, 9, etc., in seconds.However, slice #1 was acquired at times t = 1.5, 4.5, 7.5, 10.5, etc., whichis asynchronous with the TR. After applying 3dTshift, all slices will have offset times of t = 0, 3, 6, etc.3dTshift -tzero 0 -quintic \-prefix pb01.$subj.r$run.tshift \pb00.$subj.r$run.tcat+orig-tzero 0 : the offset for each slice is set to the beginning of the TR-quintic : interpolate using a 5th degree polynomial
Page 1 and 2: -1-AFNI Soup to Nuts:How to Analyze
Page 3 and 4: -3-• The Experiment : Cognitive T
Page 5 and 6: -5-• Analysis Steps: Part I: Proc
Page 7 and 8: -7- LinebyLine Explanation of s
Page 9 and 10: -9-• PART I ⇒ Process Data for
Page 11 and 12: -11-• STEP 0 (tcat): Apply 3dTcat
Page 13: -13- Subject sb23’s outlier files
Page 17 and 18: -17-• STEP 2: Register the volume
Page 19 and 20: -19- view the registration paramete
Page 21 and 22: -21-results from 3dmerge:pb02.sb23.
Page 23 and 24: -23- next, take the union of the ru
Page 25 and 26: -25-• STEP 4: Scaling the Data
Page 27 and 28: -27- Scale the Data:foreach run ( $
Page 29 and 30: -29- compare EPI images from before
Page 31 and 32: -31-• 3dDeconvolve command Par
Page 33 and 34: -33-• 3dDeconvolve command Par
Page 35 and 36: -35-• There are a many reasons wh
Page 37 and 38: -37-• Create ideal response files
Page 39 and 40: -39-• Generate a script that the
Page 41 and 42: -41-• Now plot the all_runs datas
Page 43 and 44: -43- Result: One dataset for each o
Page 45 and 46: -45-• PART 2 ⇒ Run Group Analys
Page 47 and 48: -47-• 3dANOVA3 Command Part 2-
Page 49 and 50: -49- -adiff: Performs contrasts bet
Page 51 and 52: -51- In class -- Let s run the ANOV
Page 53 and 54: -53- Brain areas corresponding to
Page 55: -55-• Many thanks to NIMH LBC for

dset 1 1 1 stats.sb04.betas+tlrc

Create successful ePaper yourself

Delete template?

Save as template?