PMC:4620161 / 12085-16200
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{"target":"http://pubannotation.org/docs/sourcedb/PMC/sourceid/4620161","sourcedb":"PMC","sourceid":"4620161","source_url":"https://www.ncbi.nlm.nih.gov/pmc/4620161","text":"A motivational example\nTo demonstrate and compare various modeling approaches at the group level, we adopt the same experimental data used in our previous paper (Chen et al., 2014), with a typical group design that accounts for a confounding effect: varying age across subjects. Briefly, the experiment involved one between-subjects factor, group (two levels: 21 children and 29 adults) and one within-subject factor (two levels: congruent and incongruent conditions). Stimuli were large letters (either “H” or “S”) composed of smaller letters (“H” or “S”). For half of the stimuli, the large letter and the component letters were congruent (e.g., “H” composed of “H”s) and for half they were incongruent (e.g., “H” composed of “S”s). Parameters for the whole brain BOLD data on a 3.0 T scanner were: voxel size of 3.75 × 3.75 × 5.0 mm3, 24 contiguously interleaved axial slices, and TR of 1250 ms (TE = 25 ms, FOV = 240 mm, flip angle = 35°). Six runs of EPI data were acquired from each subject, and each run lasted for 380 s with 304 data points. The task followed an event-related design with 96 trials in each run, with three runs of congruent stimuli interleaved with three runs of incongruent stimuli (order counterbalanced across subjects). Subjects used a two button box to identify the large letter during global runs and the component letter during local runs. Each trial lasted 2500 ms: the stimulus was presented for 200 ms, followed by a fixation point for 2300 ms. Inter-trial intervals were jittered with a varying number of TRs, allowing for a trial-by-trial analysis of how the subject's BOLD response varied with changes in reaction time (RT). The experiment protocol was approved by the Combined Neuroscience Institutional Review Board at the NIMH, and the National Clinical Trials Identifier is NCT00006177.\nThe EPI time series went through the following preprocessing steps: slice timing and head motion corrections, spatial alignment to a Talairach template (TT_N27) at a voxel size of 3.5 × 3.5 × 3.5 mm3, smoothing with an isotropic FWHM of 6 mm, and scaling each voxel time series by its mean value. The scaling step during preprocessing enables one to interpret each regression coefficient of interest as an approximate estimate of percent signal change relative to the temporal mean. The six runs of data were concatenated for the individual regression analysis with the discontinuities across runs properly handled (Chen et al., 2012). To capture the subtle HDR shape under a condition, two modeling approaches were adopted, ESM and ASM, for model comparison. With ESM, each trial was modeled with 10 tent basis functions, each of which spanned one TR (or 1.25 s). The subject's RT at each trial was incorporated as a per-trial modulation variable. In other words, two effects per condition were estimated in the time series regression at the individual level: one revealed the response curve associated with the average RT while the other showed the marginal effect of RT (response amplitude change when RT increases by 1 s) at each time point subsequent to the stimulus. In addition, the following confounding effects were included in the model for each subject, for each run: third-order Legendre polynomials accounting for slow drifts, incorrect trials (misses), censored time points with extreme head motion, and the six head motion parameters. The modeling strategy remained the same with ASM except that the three SPM basis functions (canonical IRF plus time and dispersion derivatives) were employed to model the BOLD responses instead of the 10 tents.\nAt the group level, it is the BOLD effects associated with the average RT that are of interest here. In addition to the estimated HDR profiles, three other explanatory variables considered are: a) between-subjects factor, Group (two levels: children and adults), b) within-subject factors, Condition (two levels: congruent and incongruent), and c) quantitative covariate, age. The focus is on the interaction of HDR between Group and Condition: Do the two groups differ in the HDR profile contrast between the two conditions?","divisions":[{"label":"title","span":{"begin":0,"end":22}},{"label":"p","span":{"begin":23,"end":1828}},{"label":"p","span":{"begin":1829,"end":3589}}],"tracks":[{"project":"0_colil","denotations":[{"id":"26578853-24954281-358031","span":{"begin":175,"end":179},"obj":"24954281"},{"id":"26578853-22245637-358032","span":{"begin":2458,"end":2462},"obj":"22245637"}],"attributes":[{"subj":"26578853-24954281-358031","pred":"source","obj":"0_colil"},{"subj":"26578853-22245637-358032","pred":"source","obj":"0_colil"}]},{"project":"TEST0","denotations":[{"id":"26578853-152-160-358031","span":{"begin":175,"end":179},"obj":"[\"24954281\"]"},{"id":"26578853-146-154-358032","span":{"begin":2458,"end":2462},"obj":"[\"22245637\"]"}],"attributes":[{"subj":"26578853-152-160-358031","pred":"source","obj":"TEST0"},{"subj":"26578853-146-154-358032","pred":"source","obj":"TEST0"}]},{"project":"2_test","denotations":[{"id":"26578853-24954281-38285020","span":{"begin":175,"end":179},"obj":"24954281"},{"id":"26578853-22245637-38285021","span":{"begin":2458,"end":2462},"obj":"22245637"}],"attributes":[{"subj":"26578853-24954281-38285020","pred":"source","obj":"2_test"},{"subj":"26578853-22245637-38285021","pred":"source","obj":"2_test"}]}],"config":{"attribute types":[{"pred":"source","value type":"selection","values":[{"id":"0_colil","color":"#d7ec93","default":true},{"id":"TEST0","color":"#e793ec"},{"id":"2_test","color":"#93eccc"}]}]}}