The AS-NoSOD group (N = 27) presented normal speech onset, whereas the AS-SOD group (N = 28) was characterized by a SOD.
groups
The AS-NoSOD group (N = 27) presented normal speech onset, whereas the AS-SOD group (N = 28) was characterized by a SOD.
groups
AS individuals (N = 55)
number of subjects
SPSS
stat tool
Brain Connectivity Toolbox
software tool
Automated Anatomical Labeling Atlas (AAL)
software tool
The FA threshold of 0.15
analysis parameter
Each line was propagated by 0.25 mm to the next point in space, at which point the process was repeated. Each of these streamlines was terminated when FA < 0.15 or when the angular deviation from paths was >55° to prevent streamlines from looping back
analysis parameters
Deterministic tractography was performed using the Diffusion Toolkit in PANDA, a MATLAB
software tool
FSL's “dtifit” tool
software tool
“auto_warp” command in AFNI
software tool
“fsl_prepare_fieldmap” tool in FSL
software tool
skull-stripped using the Brain Extraction Tool
software tool
“eddy” tool from FSL
software tool
Diffusion tensor imaging data was acquired using a single-shot spin echo echo-planar imaging (EPI) sequence with 30 gradient directions and the following acquisition parameters: repetition time (TR) = 7700 ms; echo time (TE) = 90 ms; b = 1000 s/mm2; acquisition matrix = 204 × 204; voxel size = 2.0 × 2.0 × 2.0 mm, 60 contiguous axial slices and scan time = 8 min 22 s. High-resolution T1-weighted structural images were also acquired by collecting 176 contiguous sagittal slices using a three-dimensional magnetization prepared rapid gradient echo imaging (3D MPRAGE) sequence with the following parameters: repetition time (TR) = 2250 ms; inversion time (TI) = 850 ms; echo time (TE) = 3.98 ms; field of view (FOV) = 256 mm; acquisition matrix = 256 × 256; voxel size = 1.0 × 1.0 × 1.0 mm; slice thickness = 1.0 mm; flip angle = 9°. A field map was also recorded with a gradient echo sequence with the parameters of repetition time (TR) = 488 ms; echo time 1 (TE 1) = 4.92 ms; echo time 2 (TE 2) = 7.38 ms; voxel size = 3.0 × 3.0 × 3.0 mm; field of view (FOV) = 204 mm; slice thickness = 3.0 mm; 40 slices; flip angle = 60° to measure field inhomogeneities and compensate for geometrical distortions that result from standard EPI sequences.
Acquisition details
3 T Siemens Trio MRI scanner using a 12-channel head coil
Scanner
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Data availability statement
GWCi = β0 + β1Gj + β2 agej + β3 agej2 + β4 agej3 + β5 (agej × groupj) + β6 (agej2 × groupj) + β7 (agej3 × groupj) + β8 IQj + εi, where ε denotes the residual error.
stat model
Corrections for multiple comparisons across the whole brain were performed using random-field theory (RFT)-based cluster-corrected analysis for non-isotropic images using a p < 0.05 (two-tailed) cluster-significance threshold
stat detail: multiple compariuson
F-test for nested model comparisons was performed at each vertex
stat test
linear, quadratic, and cubic effects of age, in addition to the main effect of group in a vertex-wise fashion
stat detail
SurfStat toolbox (http://www.math.mcgill.ca/keith/surfstat/) for Matlab (R2016a; www.mathworks.com)
Statistical analysis
smoothed using a 10-mm full-width at half-maximum (FWHM) surface-based Gaussian kernel prior to statistical analyses
analysis detail
final sample size of 153 participants (n = 77 individuals with ASD and n = 76 TD controls)
final sample size
FreeSurfer v5.3.0
Analysis tool
3-Tesla GE Signa System (General-Electric, Milwaukee, WI) with full-head coverage, 196 contiguous slices (1.1-millimetre (mm) thickness, with 1.09 × 1.09 mm in-plane resolution), a 256 × 256 × 196 matrix, and a repetition time/echo time (TR/TE) of 7/2.8 milliseconds (ms) (flip angle = 20°, FOV = 28 cm). A (birdcage) head coil was used for radiofrequency transmission and reception.
Acquisition details
aged 7 to 25
age range
Eighty-two (82) right-handed males with ASD and eighty-two (82)
N Subjects
2019 FSL Course; 17-21 June 2019; Split, Crotia
Mini FSL Course; 18 - 22 February 2019; Dunedin, New Zealand
FORCE11 Scholarly Communications Institute; Aug 5-9, 2019; UCLA, Los Angeles, CA, USA
support the connections among research networks, rather than supportingfundamental research as the primary activity
key concept
NSF Big Ideas
where are these?
These data are obtained from the Human Connectome Project and thus we must adhere to their data use terms (https://www.humanconnectome.org/study/hcp-young-adult/data-use-terms). They provide data access at the following link: https://db.humanconnectome.org/.
Data source
independent samples t-tests and analyses of covariance (ANCOVAs; controlling for age and ICV) to test for gender differences in FFM traits and amygdala/hippocampal volumes, respectively
Stat method
Hippocampal subfield segmentation was derived using the automated algorithm available in FreeSurfer version 6.0
software tool
a modified version of the FreeSurfer automated “recon-all” pipeline
software tool
Chris Rorden’s DICOM to NIFTI
Software tool
8 participants did not complete the NEO-FFI
subjects group modifier
1,113 participants
Data subset
Data were drawn from the publicly available repository of the WU-Minn HCP
Data Source
Human Connectome Project sample (N = 1105)
Data Source
FreeSurfer amygdala and hippocampus segmentation pipelines
Method
The raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.
Sharing Statement: raw data
covariates
stat
Inferential statistics on the clinical variables were performed with SPSS v24
stat tool and version
All the statistics were performed with SPM12 using a threshold p < 0.05 corrected for the False Discovery Rate (FDR) at voxel level.
Statistical method
The ARtifact Detection Tool (ART) was employed to create regressors and detect outliers
Processing tool
FWHM equal to 6 mm
processing: smoothing
final voxel size of 2 × 2 × 2 mm3
processing: resample
pre-processed using SPM12 (49) and ANTs
Analysis tools
FA, MD, AD, and RD with a GLM comparing HCs and FRDA patients while accounting for age and sex as covariates
statistical details
JHU DTI-based WM atlas
Analysis tools
Voxel-wise statistics were performed for each DTI derived map with a general linear model (GLM) using age and sex as covariates, with the same approach previously described for VBM
Statistical approach
DTI-TK
Analysis tool
Tortoise
Processing tool
Voxel-wise statistics were computed with a general linear model (GLM) using FSL (41), with age, sex, and intracranial volume (ICV) in native space as covariates.
Statistics approach
FSL anatomical pipeline
Analysis tools
pre-processed with the N4 tool of ANTs
Analysis Tools
Voxel-Based Morphometry (VBM) pipeline
Analysis Method 'Concept'
Instructors: J. Bates, S. Ghosh, J. Grethe, Y. Halchenko, M. Hanke, C. Haselgrove, S. Hodge, D. Jarecka, D. Keator, D. Kennedy, M. Martone, N. Nichols, S. A. Abraham, J.-B. Poline, N. Preuss, M. Travers, and others
Reproducible NeuroImaging Training at SFN; November 2-3, 2018; La Jolla, CA USA
IBM SPSS Statistics,
stat tool
FSL (version 5.0.7)
Tool
FSL and Freesurfer software
tools
(VBM) protocol, using the default pipeline as implemented in FSL
'Default pipeline' for VBM in FSL is ambiguous, I think.
INCF 2018 Workshop on Advanced Data Discovery for Neuroscience; August 11, 2018; Montreal, Quebec
INCF Neuroinformatics Hackathon 2018; Montreal; August 7-8, 2018
METHODS IN NEUROSCIENCE AT DARTMOUTH COMPUTATIONAL SUMMER SCHOOL; 7/30 - 8/7/2018; Dartmouth, NH, USA
EEGLAB 2018; Sept 4-5, 2018; Pittsburgh, USA
94 AD
GroupDescription: AD; GroupN: 94
217 MCI
GroupDescription: MCI; GroupN: 217
145 CTRL
GroupDescription: CTRL; GroupN: 145
Controls and patients aged 60 years or older and from both genders, were included prospectively during 2015–2016 (n = 44). AD patients
GroupDescription: AD Patients; GroupN:44
cognitively normal individuals paired by age (n = 16)
GroupDescription: cognitively normal individuals; GroupN: 16
3T whole-body MRI systems (Magnetom TIM Trio; VB17 software version; Siemens Healthcare):
MRI Scanner description
MPM sequence
Imgaging sequence
We used a backtracking algorithm (55) to parcellate 66 regions defined by sulcogyral criteria in the Desikan–Killiany atlas (56) into 308 contiguous parcels of approximately equal area (500 mm2) across both hemispheres in standard space (SI Appendix, Fig. S2A).
Parcellation Region procedure description
FreeSurfer v5.3.0
Software used
sample of 297 healthy young people sampled from primary healthcare registers, stratified by age, and balanced for sex in the adolescent age range 14–24 y old, with ∼60 participants in each of five age-defined strata: 14–15 y old inclusive, 16–17 y old, 18–19 y old, 20–21 y old, and 22–24 y old
Subjects description
that adolescent consolidation of these connectome hubs was associated with a specific gene expression profile, enriched for neuronal and oligodendroglial function, and enriched for risk of schizophrenia, a neurodevelopmental disorder with its highest incidence in young adults
Hypothesis 3
(ii) that adolescent cortical shrinkage/myelination (also known as consolidation) was concentrated anatomically on association cortex and topologically on the most strongly connected regions (hubs) of the human brain anatomical network
Hypothesis 2
(i) that adolescent cortical shrinkage was coupled to intracortical myelination
Hypothesis 1
Statistics With R; June 7-8, 2018; Philadelphia, Pennsylvania
Preparing your data and code for computationally reproducible publication; April 24, 2018; Cambridge, MA
Brain Lesion (BrainLes) workshop; September 16, 2018; Granada, Spain
The age, MMSE, HAMD,and HAMA were performed with independent samples T test, and sex was performed with Chi-Square test.
Stat method
Significant difference was set at a P value of <0.05
stat threshold
PASW Statistics 18.0
stat tool
ITK-SNAP (V3.6.0)
Tool
visually inspected to confirm anatomical accuracy
Method
the new segment tool embedded in SPM 12 software
Tool
rest software
Tool
WMH volume was examined as a percentage of166ICV
Stat process
adjusted for age159and
Stat method
3dRegAna, AFNI
Software tool
sigma 2 mm
analysis parameter
Voxelwise GM density was calculated using the145standard FSL VBM package
Software
subject’s age, sex, and eTIV were considered in the matrix design in the SPM12
stat detail
extent threshold was set at 250 voxels
Stat detail
SPM12 using an uncorrected threshold of p < 0.001
Stat detail
Statistical Package for Social Sciences software ver. 16.0
Stat software
p-value of less than 0.05 was used for group comparisons, and the extent threshold was set at 50 voxels
Stat Parameters
SPM12
Stat software
adjusted for estimated total intracranial volume (eTIV) and age
Stat: Age and ICV adjustment
FreeSurfer
Tool
5.3.0
FreeSurfer version
8-mm full-width-half-maximum Gaussian smoothing kernel
Parameter
SPM12
Tool
MRICRON
Software tool
VBM technique implemented in the CAT toolbox
NIfTI
data format
Computational Psychiatry Course 2018; Sept. 10-14, 2018; Zurich
For investigating group differences, we run voxel-wise linear regression in the form:X~A + βgroupGroup + βageAge + βsexSex + βscan−chScan − ch + βintervalInterval + βICVICV + εwhere X is the Jacobian determinant value at a given position, A is the constant Jacobian determinant term, the βs are the covariate regression coefficients, and ε is an error term.
Stat model
ANTs Symmetric Normalization (SyN; (Avants et al., 2008))
Software
flirt (http://fsl.fmrib.ox.ac.uk)
Software
Brainsuite (http://brainsuite.org)
Software
(http://www.itksnap.org)
Software
SPSS version 20.0
Stat software
Student’s t-test.
Stat test
FreeSurfer 5.1.0
Software
Inbrain®, a Korea Food and Drug Administration (KFDA)-cleared software and a registered trademark of MIDAS Information Technology Co., Ltd., which performs fully-automated image analysis of brain structures
Software
Brain regions showing a significant interaction between group and Eyes Test score in the association with gray matter volume
Result
1.5 × 1.5 × 1.5 mm and smoothed using a 12-mm full-width at half-maximum (FWHM) isotropic Gaussian kernel
analysis parameters
SPM81 and the VBM8 toolbox2 implemented in MATLAB R2012b
Analysis tools
analyzed using a t-test between groups and analysis of covariance (ANCOVA) with group (TD and ASD) as an effect-of-interest factor and age, sex and full-scale IQ as effect-of-no-interest covariates. A p-value < 0.05 was considered significant.
stat method
SPSS 16.0J
Stat software
we performed PLS (McIntosh et al., 1996) using PLSGUI7
Software
probabilistic cytoarchitectonic atlas included in the SPM Anatomy toolbox
Software
Automated Anatomical Labeling atlas (Tzourio-Mazoyer et al., 2002) included in the MRIcron software
Software
significance in both of these parametric and nonparametric analyses are reported. We also explored the effects of ASD subtype (Asperger’s disorder vs. PDD-NOS) using these predefined thresholds. The clusters that showed significant group difference (TD > ASD) were used as an inclusive mask.
Stat details
Permutation Analysis of Linear Models software
Stat software
VBM using a general linear model analysis, with group as the effect-of-interest factor and sex and age as the effect-of-no-interest covariates. The association between group difference and the volume of the gray matter was tested using T-statistics and reported as a Z-score after the T-value was transformed into the standard normal distribution. Voxels were deemed to be statistically significant if they reached the extent threshold of p < 0.05, after false-discovery rate (FDR) correction for multiple comparisons based on the topological FDR procedure (Chumbley and Friston, 2009), with a cluster-forming threshold (CFT) of p < 0.01 (uncorrected)
Stat details
with default settings
parameters
visual inspection of T1 images and confirmed no macroscopic lesions or artifacts in the images
QA
VBM8 toolbox
Tool and version
MATLAB R2012b
Tool version
eLife Innovation Sprint 2018; May 10-11, 2018; Cambridge, UK
MarsBaR toolbox
Stat tool
GingerAle
tool
Statistical Non-Parametric Mapping toolbox
stat tool
age as a covariate and the results were assessed on the basis of nonparametric cluster-wise inference, with a cluster-forming threshold of 0.005 and cluster-based correction for multiple comparisons such that pFWE < 0.05. In addition, we re-ported any results passing the cluster-forming threshold of p < 0.005
stat details
GingerAle
software
Anatomic Labelling (AAL) system in the WFU pickatlas (www.nitrc.org/projects/wfu_pickatlas/).
software
controlling for age
stat detail
MarsBaR toolbox (http://marsbar.sourceforge.net/)
stat analysis
Statistical Non-Parametric Mapping toolbox (http://warwick.ac.uk/snpm), with a cluster-forming threshold of 0.005 and a family-wise error (FWE) of 0.05
stat method
included age as a covariate
stat detail
Neurosynth software (neurosynth.org) to conduct a reverse inference meta-analysis of previously published studies with the predefined search term “theory mind.”
analysis approach
smoothed with an iso-tropic 8 mm full-width at half-maximum
Analysis detail
final voxel size of 1.5 × 1.5 ×1.5 mm3; segmentation into grey matter, white matter and cerebrospinal fluid; and modulation by the nonlinear com-ponent only for volume changes during spatial normalization to identify regional differences in grey matter volume cor-rected for individual brain size
analysis detail
MATLAB 2014
Software
SPM8
Software
VBM
Software
IBM SPSS Statistics® version 22.
Stat software
z-distribution Monte Carlo simulation with 10,000 repeats was then applied to correct for multiple comparisons using a cluster-forming threshold set at p < .05.
Stat method
FreeSurfer version 6.0
Software and version
3D MP-RAGE sequence (TR/TE:2300/3.03 ms; flip angle: 90; 192 sagittal slices with 1 mm3 voxel size
Imaging details
3 T Siemens Skyra scanner with a 20-channel head coil
Acq Details
Workshop Details August 20 – September 4, 2016 Friday Harbor Laboratories
Summer Workshop on the Dynamic Brain; August 18 – September 2, 2018; Friday Harbor, WA
First International Workshop on Reproducible Open Science; Sept 9, 2016; Hannover, Germany
Big Data, Little Brains; May 6-8, 2018; UNC Chapel Hill
Credit for Data Sharing Workshop; April 9, 2018; Washington, DC
empowering users to make local changes.
Local changes are great for customizability, but, it can play some havoc with reliability and reproducibility. 'ReproNim' recommends making such custom changes under the control of a version management system (ie. GitHub) so that the user can document an exact version of analysis used.
Way to go, eLife!