Page 114 - 《运动与健康科学》(英文)2024年第2期

TaggedAPTARAEnd236 X.R. Tan et al.
time = 2000 ms, echo time = 30 ms, field of view = 256 Where significant motion was seen in the motion parameters,
mm £ 256 mm, matrix size = 64 £ 64. During imaging, or where the non-motion corrected data were significantly
the participant performed the Stroop color-naming task. 19 affected by motion, label/non-label data pairs containing
A color word was presented on the projector screen, motion were removed and regeneration of cerebral blood flow
where the participant was instructed to select for the ink images were performed on the truncated set. GLM results
color of the word, instead of its semantic meaning, using were obtained using a 1-sample group mean GLM with vertex-
a 4-button box (Lumina LU444-RH; Cedrus, San Pedro, wise threshold p < 0.05 and cluster correction at p < 0.05,
CA, USA) with their right hand. Stimuli consisted of correcting for 2 spaces (left and right hemispheres). Extraction
words printed in 1 of 4 colors (red, blue, green, or of regions of interest averaged data was performed using in-
yellow), and the congruent or incongruent stimuli were house built Matlab scripts, and regions of interest generated
presented in random sequence. The proportion of from Freesurfer parcellation (surfaces transformed to volume
congruent or incongruent stimuli presented was approxi- space). To obtain the normalized values accounting for circa-
mately equal. The stimuli were presented centrally for dian-related changes, the % perfusion values were subtracted
1 min and repeated for 4 cycles. A solid black cross was with time-matched CT values, and comparisons were made
presented on a white background as control stimulus for between baseline and post scans. Similar analysis was applied
1 min prior to each Stroop cycle, as intervals between the for task response accuracy and reaction time. fMRI data were
cycles, and at the end of the 4 cycles (total duration = 9 analyzed using the Freesurfer Functional Analysis STream
min; Fig. 1G). Single subject level analysis was (FS-FAST, http://www.surfer.nmr.mgh.harvard.edu). The
performed using general linear model (GLM) analysis pipeline involves motion correction of fMRI data to the
with the motion regressor (on/off). The hemodynamic middle time-point of each run, registration of the anatomical
response function was modeled during the presentation of and fMRI images, intensity then spatial normalization (to Free-
stimuli, and was compared to the baseline signal when surfer “fsaverage”) using a 6-parameter affine transformation
and smoothing (5-mm full width at half maximum). Individual
the control cross was displayed.TaggedAPTARAEnd
participant/visit scans were analyzed, using a GLM,
convolving the task regressor with a canonical hemodynamic
TaggedAPTARAH22.4. MRI data analysisTaggedAPTARAEnd
response function (g function with delay d = 2.25 s and decay
25
TaggedAPTARAPRaw Digital Imaging and Communications in Medicine time constant t = 1.25 ).TaggedAPTARAEnd
(DICOM) data were converted to Neuroimaging Informatics TaggedAPTARAPFor the ergometer paradigm, an event-related design was
Technology Initiative (NIfTI) using MCverter (Lewis Centre used with 4 contrasts (20%, 40%, 60%, and 80% maximal
voluntary contraction) and rest. Positive clusters were
for Neuroimaging, University of Oregon, Eugene, OR, USA).TaggedAPTARAEnd
1
TaggedAPTARAPFor H MRS, Siemens Twix data were analyzed using in-house extracted for 60% + 80% vs. rest using vertexwise threshold
built Matlab scripts, which included 2 Hz exponential line (p < 0.001), with clusterwise threshold (p < 0.05) and
broadening and phase correction. The brain temperature (T br ) correcting for 2 spaces. Individual participant’s % signal
was estimated for each individual acquisition from the change was extracted from the activated clusters. Data were
frequency shift between the water and N-acetylaspartate normalized with time-matched CT values and compared
(NAA) peaks using an equation from Cady et al. 20 (T br = 286.9 between baseline and post scans.TaggedAPTARAEnd
94.0 DH 2 0-NAA) and then averaged across individual TaggedAPTARAPFor Stroop-task fMRI analysis, the comparison across all
spectra. The data were compared to T re as recorded during the trials was performed for (a) all stimuli vs. neutral stimuli, and
1
scan corresponding to the same timepoint at which the H (b) incongruent stimuli vs. congruent stimuli to generate the
task-induced regions with vertexwise (p < 0.001) and cluster-
MRS scan was conducted.TaggedAPTARAEnd
TaggedAPTARAPIndividual subjects’ MPRAGE images were run through the wise (p < 0.05) thresholds. For trial-to-trial comparison (PA
Freesurfer longitudinal analysis pipeline 21,22 to parcellate the S2 vs. CT S2), voxelwise paired comparisons were made
brain for coregistration and further analysis. For ASL, image between scans with the clusterwise threshold set to 0.05.TaggedAPTARAEnd
preprocessing was performed with Matlab R2014a Package
(FIL Methods Group, London, UK) and Statistical Parametric
TaggedAPTARAH22.5. Statistical analysisTaggedAPTARAEnd
Mapping version 12.0 (SPM12). ASL data were split into
label/non-label pairs before motion correction and averaging. TaggedAPTARAPStatistical Package for Social Sciences (SPSS) Version 22.0
Label and non-label images were coregistered to the (IBM Corp., Armonk, NY, USA) was used to compute all
MPRAGE images using Advanced Normalization Tools 23 data, and 2-tailed paired Student’s t tests were performed to
based on the non-label coregistration parameters, before test for statistical differences between trial conditions. For
projection to the cortical surface and application of surface time-by-trial interaction effects, 2-way repeated-measures
smoothing (10 mm). These smoothed cortical signals were analysis of variance was performed to test for significance
used to generate the difference and perfusion images for between trial conditions. Where significant interaction effects
further analysis by normalizing with relaxation-corrected were established, pairwise differences were identified using
label-off image and performing quantification correction. 24 To the Bonferroni post hoc analysis adjusted for multiple compar-
remove motion artifacts, a second set of data was generated isons. Significance level was set at p < 0.05. All values were
without motion correction, and a comparison was made. expressed as mean § SD.TaggedAPTARAEnd