dset 1 1 1 stats.sb04.betas+tlrc

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-18- Subject sb23’s 9 newly created volume registered datasets:pb02.sb23.blk.r01.volreg+orig (.HEAD/.BRIK)...pb02.sb23.blk.r10.volreg+orig (.HEAD/.BRIK) Below is run 01 of sb23’s volume registered datasets.
-19- view the registration parameters in the text file, dfile.rall.1Dthis is the concatenation of the registration files for all 9 runs1dplot -volreg dfile.rall.1D Slight movements going on here, especially at the “Pitch” angle
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 and 14: -13- Subject sb23’s outlier files
Page 15 and 16: -15-• Next, perform temporal alig
Page 17: -17-• STEP 2: Register the volume
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

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