Computational protocol: Neural correlates of cerebellar-mediated timing during finger tapping in children with fetal alcohol spectrum disorders

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Protocol publication

[…] High-resolution T1-weighted structural MR images were acquired using a 3D echo planar imaging (EPI) navigated () multi-echo MPRAGE () sequence that had been optimized for morphometric analyses using FreeSurfer software. Imaging parameters were: FOV 256 × 256 mm2; 128 sagittal slices, TR 2530 ms; TE 1.53/3.21/4.89/6.57 ms; TI 1100 ms; flip angle 7°; voxel size 1.3 × 1.0 × 1.3 mm3. The 3D EPI navigator provided real-time motion tracking and correction, which served to substantially reduce the presence of any motion artifacts in structural imaging data, despite significant subject motion.A T2*-weighted gradient echo, EPI sequence was used to acquire 114 functional volumes that are sensitive to BOLD contrast (TR 2000 ms, TE 30 ms, 34 interleaved slices, 3 mm slice thickness, gap 1.5 mm, FOV 200 × 200 mm2, in-plane resolution 3.125 × 3.125 mm2) while the children performed the task. Despite the low resolution of the fMRI data, this analysis succeeded in resolving the complex geometry of the cerebellum and its respective lobules.All procedures were performed according to protocols that had been approved by the Institutional Review Board of Wayne State University and the Faculty of Health Sciences Human Research Ethics Committee at the University of Cape Town. All parents/guardians provided informed written consent, and all children provided oral assent. [...] To ensure that only data from blocks in which the child was fully engaged in the task were included in the fMRI data analysis, we applied performance criteria based on inspection of the distribution of the SDs of the ITIs in the rhythmic and non-rhythmic blocks. SDs displayed a bimodal distribution and the local minimum was used to select thresholds for each condition. In the rhythmic tapping condition, only blocks with SDs less than 150 ms, mean ITIs between 500 and 1000 ms, and 6 or fewer missed taps were included in the analyses. ITIs during the rhythmic blocks that exceeded 1200 ms were assumed to occur due to one or more missed taps, which occasionally occurred when a child did not press the button firmly enough. In such instances, for the purposes of computing SD, additional taps were inserted with an ITI as close to 736 ms as possible to ensure that missed taps were interpolated with the appropriate rhythm. Inserted taps were counted as “missed” in determining whether to include the block in the analysis. Non-rhythmic tapping blocks were included in the analysis only if their SDs were greater than 170 ms and if the difference between the number of tones presented and the number of button presses did not exceed 9. Blocks that did not meet inclusion criteria were labeled as bad blocks and treated as separate predictors in the general linear model (GLM). Only children who met behavioral performance criteria for two or more blocks in each condition were included in the analysis as only these children were considered to be fully engaged in the task.fMRI data analyses were performed in Brain Voyager QX (Brain Innovation, Maastricht, The Netherlands). The first four dummy scans were excluded from all analyses. Pre-processing included motion correction relative to the first volume that was acquired during the functional scan, linear scan time correction, temporal filtering with a high pass filter of 3 cycles/point, and linear trend removal. Scans with motion exceeding 3 mm translation or 3° rotation within a functional run were excluded from all further analyses. Whole-brain group analyses were performed with a random effects analysis of variance using the general linear model with predictor time courses for the successful rhythmic and non-rhythmic tapping blocks convolved by the standard hemodynamic response function. The six motion correction parameters were z-transformed and added as predictors of no interest together with the predictors for the excluded (bad) rhythmic and non-rhythmic tapping blocks.Beta maps were created for each subject for the contrast comparing BOLD activation during rhythmic and non-rhythmic finger tapping. The beta maps were exported into Analyze format for second level analyses using the spatially unbiased atlas template (SUIT) toolbox () in SPM5 (Statistical Parametric Mapping) to obtain more detailed information on activation patterns in the cerebellum. This atlas, which is based on the structural data of 20 healthy individuals, has been shown to significantly improve the alignment of individual fissures in the cerebellum when compared to normalization to the MNI whole-brain template ().Each subject's cerebellum was initially isolated in the structural images by calculating the probability of each voxel belonging to the cerebellum or brain-stem. The isolation maps were then used to transform each subject's cerebellum to the SUIT template in the subsequent step, which normalized the data. Manual correction was applied using MRICRON () for each subject to eliminate contamination from the visual cortex. The functional data for the cerebella were then resliced according to the isolated and normalized structural data for each subject to render the data in the SUIT atlas space. [...] A one-sample t-test was used to identify clusters where percent signal change values comparing rhythmic and non-rhythmic tapping were significantly different from zero in the control children. Cluster size correction with a cluster defining threshold of 0.05 on the normalized group images was applied to reduce the risk of multiple comparisons and a minimum cluster size of 193 mm3 was found to be statistically significant.To determine whether normalizing the children's cerebella to an adult template would lead to excessively small effective regions of interest (ROIs), cerebellar volumes generated by FreeSurfer (version 5.1.0, were compared to values reported in adult studies (; ). calculated cerebellar volumes ranging from 122.73 to 142.37 ml in eight adults (age 21–35 years) and found a range of 99.86–170.6 ml in 48 adults (age 19.8–73.1 years). The children included in our functional study had an average cerebellar volume of 130.85 ± 13.03 ml (range 107.18–170.11 ml), which is within the limits of the aforementioned studies. The children from all diagnostic groups were included in this analysis, as previous studies have shown that children prenatally exposed to alcohol have reduced cerebellar volumes (; ). It was, therefore, necessary to establish whether the volumes in these children were also comparable to the cerebellar volumes of adults. The overall effect of normalization to an adult template was, therefore, deemed negligible.ROIs were defined with radius 3 mm, centered on the peak coordinates, in these regions. Due to the large cluster sizes in the vermal lobules, percent signal changes were extracted around the center of mass instead of the peak voxels in these two clusters. Mean percent signal change values were extracted in these ROIs for each child and exported to SPSS (version 20; IBM, New York, USA) to examine differences in activation in these regions as a function of diagnosis as well as associations with the extent of prenatal alcohol exposure.Differences between diagnostic groups in each ROI were examined using analysis of variance. Eight control variables were considered as potential confounders: child's sex, age at assessment, postnatal lead exposure, IQ and cerebellar volume; maternal education, smoking (cigarettes/day) during pregnancy and age at delivery. Pearson correlations were used to examine the relations of the mean percent signal change values in the ROIs to each of the potential confounders. All control variables related to a given outcome at p < 0.10 were considered possible confounders. These variables were entered into an analysis of covariance (ANCOVA) to determine whether group differences in the ROIs remained significant after controlling for these measures.Correlations between extent of prenatal alcohol exposure and activation were also examined in SPSS. Although the continuous measures of the control group were essentially all zero, the data for these children were included in the correlation analyses to avoid artificially truncating the range of exposure. Hierarchical multiple regression analyses were used to control for confounding. The alcohol measure was entered in the first step of each analysis for each outcome. All control variables related to the outcome at p < 0.10 were entered in the second step to determine if the effect of the continuous alcohol measure on activation patterns continued to be significant after statistical adjustment for potential confounders. Pearson correlations were used to examine the relation between BOLD activations in the ROIs and EBC performance. […]

Pipeline specifications

Software tools FreeSurfer, SUIT, MRIcron, SPSS
Applications Miscellaneous, Magnetic resonance imaging, Functional magnetic resonance imaging
Organisms Homo sapiens
Diseases Fetal Alcohol Spectrum Disorders
Chemicals Oxygen