The dataset used for this study was collected from HCP1 (WU-Minn Consortium). Our sample includes 812 subjects (ages 22–35 years-old, 450 females) scanned on a 3T Siemens connectome-Skyra scanner. For each subject, a three-dimensional T1 structural image was acquired at 0.7 mm isotropic resolution with 3D MPRAGE acquisition. The four blood-oxygen-level dependent (BOLD) resting state fMRI (R-fMRI) runs were acquired in separate sessions on two different days, each for approximately 15 min (2 mm× 2 mm× 2 mm spatial resolution, TR = 0.72 s, 1200 timepoints, multiband acceleration factor of 8, with eyes open and relaxed fixation on a projected bright cross-hair on a dark background). The WU-Minn HCP Consortium obtained full informed consent from all participants, and research procedures and ethical guidelines were followed in accordance with the Institutional Review Boards (IRB) of Washington University in St. Louis, MO, United States (IRB #20120436). To identify WFC, the whole brain was parcellated into 120 regions according to the automated anatomical labeling (AAL2) atlas (Rolls et al., 2015 (link)), with names and abbreviations listed in Table 1 .
Connectome skyra scanner
Manufactured by Siemens
The Connectome-Skyra scanner is a magnetic resonance imaging (MRI) system designed for advanced neuroimaging applications. It is a high-performance, wide-bore MRI scanner that provides exceptional image quality and powerful gradient performance. The Connectome-Skyra scanner is optimized for the comprehensive assessment of brain structure and function, enabling researchers to investigate the complex connections and pathways within the human brain.
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16 protocols using connectome skyra scanner
1
Resting-State fMRI Analysis of Whole-Brain Functional Connectivity
2
Resting-State Functional Connectivity in HCP
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The neuroimaging dataset was selected from the Mar 2017 public data release from the Human Connectome Project (HCP, N = 1,200), WU‐Minn Consortium. Our sample includes 1,017 participants (ages 22–35 years, 546 females) scanned on a 3‐T Siemens connectome‐Skyra scanner, each with four resting state scans with each scan 1,200 time points long with a TR of 0.72 s. Participants without the full 1,200 time points in four resting‐state runs were removed from the analysis in line with a previous investigation (Cheng, Rolls, Ruan, & Feng, 2018 ), leaving 1,017 participants. Further details of the subjects, and the collection and preprocessing of the data are provided in the Supplementary Material , at the HCP website (http://www.humanconnectome.org/ ), and in previous studies (Cheng et al., 2018 ; Rolls et al., 2021 ).
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Neonatal and Adult Brain Imaging Protocols
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All scans from the dHCP were conducted on a 3.0 T Philips Achieva MRI scanner equipped with a dedicated neonatal brain imaging system, which has specially designed immobilization devices that conform to the shape of the infants’ head and assists in keeping the infants asleep and minimizing gross head motion (Hughes et al. 2017 (link)). Diffusion MRI data were acquired with a monopolar spin echo echo-planar imaging (SE-EPI) Stejskal-Tanner sequence (TR/TE, 3800/90 ms; field of view (FOV), 150 × 150 × 96 mm3; matrix, 128 × 128 × 64). The acquisition time was shorter than 20 min. There were 4 different b-value shells (0, 400, 1000 and 2600 s/mm2) and 300 diffusion encoding orientations (20, 64, 88 and 128 per b-value shell) for each subject (Hutter et al. 2018 (link)). T2-weighted scans were acquired using a turbo spin echo (TSE) sequence (TR/TE, 12 s/156 ms; resolution (mm) 0.8 × 0.8 × 1.6).
All the HCP subjects were scanned on a 3.0 T Siemens connectome—Skyra scanner with a customized protocol. For each subject, the multi-shell dMRI data have an isotropic spatial resolution of 1.25 mm and over 270 gradient directions distributed over three b values (1000, 2000, 3000 s/mm2). T1-weighted images were acquired using the 3D MPRAGE sequence with 0.7 mm isotropic resolution (Sotiropoulos et al. 2013 (link)).
All the HCP subjects were scanned on a 3.0 T Siemens connectome—Skyra scanner with a customized protocol. For each subject, the multi-shell dMRI data have an isotropic spatial resolution of 1.25 mm and over 270 gradient directions distributed over three b values (1000, 2000, 3000 s/mm2). T1-weighted images were acquired using the 3D MPRAGE sequence with 0.7 mm isotropic resolution (Sotiropoulos et al. 2013 (link)).
4
Resting-state fMRI protocol for brain activity
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Every participant was scanned with two sessions, and each session included two runs. One run was phase encoded from left to right and the other was phase encoded from right to left. The left-to-right encoding dataset of the first session was used for the main analysis and the right-to-left encoding dataset of the first session was used for the validation analysis.
All participants were scanned in a 32-channel Siemens 3T ‘Connectome Skyra’ scanner. Functional images were collected using a multiband gradient-echo-planar imaging sequence. The image parameters were as follows: time repetition = 720 ms; time echo = 33.1 ms; flip angle = 52°; field of view = 208 × 180 mm2; matrix = 104 × 90; slices number = 72; slice thickness = 2 mm; voxel size = 2 × 2 × 2 mm3; multiband factor = 8; and 1200 volumes. Participants were asked to keep their eyes open, fixate on a bright cross-hair presented on a black background and relax.
All participants were scanned in a 32-channel Siemens 3T ‘Connectome Skyra’ scanner. Functional images were collected using a multiband gradient-echo-planar imaging sequence. The image parameters were as follows: time repetition = 720 ms; time echo = 33.1 ms; flip angle = 52°; field of view = 208 × 180 mm2; matrix = 104 × 90; slices number = 72; slice thickness = 2 mm; voxel size = 2 × 2 × 2 mm3; multiband factor = 8; and 1200 volumes. Participants were asked to keep their eyes open, fixate on a bright cross-hair presented on a black background and relax.
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Resting-state fMRI data from HCP-YA
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We used data obtained from four resting-state fMRI (rs-fMRI) sessions taken from the HCP-YA S1200 release38 (link). Subjects were selected if data was available for all four resting state sessions and 25 predefined behavioural variables of interest. This resulted in a dataset consisting of 771 subjects (384 female, 387 male). Participants’ age ranged from 22 to 37 (M = 28.41, SD = 3.74). The four sessions of rs-fMRI were obtained on two separate days (each lasted ca. 15 min; ~60 minutes across all four sessions). On each day, two sessions were recorded for different phase encoding directions (left-right [LR] and right-left [RL]) providing four overall rs-fMRI datasets. Scans were acquired using a 3T Siemens connectome-Skyra scanner with a gradient-echo EPI sequence (TE = 33.1 ms, TR = 720 ms, flip angle = 52∘, 2.0 mm isotropic voxels, 72 slices, multiband factor of 8).
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High-Resolution Human Connectome Imaging
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Smoking Behavior and Nicotine Dependence in the Human Connectome Project
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Total 330 regular smokers (ages 22-37 years, mean age 29.49 y, 152 females) from the Human Connectome Project40 (link) were included in our current study. The HCP consortium is a public shared large-scale neuroimaging dataset and the details on the inclusion and exclusion criteria of HCP consortium were provided in the previous study40 (link) and the HCP website (https://www.humanconnectome.org ). High resolution 3-dimensional T1-weighted images (0.8 mm isotropic voxel size) were scanned on a 3 T Siemens connectome-Skyra scanner. The processing of VBM was the same as that in the IMAGEN project. Smoking behaviour and the level of nicotine dependence were assessed according to the Fagerström Test for Nicotine Dependence (FTND) and DSM.
8
High-Resolution Human Connectome Imaging
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We used resting-state functional magnetic resonance imaging (rfMRI) data from 461 subjects taking part in the Human Connectome Project. All subjects were healthy adults (ages 22-35 y, 271 females) scanned on a 3 T Siemens connectome-Skyra scanner (customised to achieve 100 mT/m gradient strength). For each subject there were 4 × 15-minute runs of rfMRI timeseries data with temporal resolution 0.73 s and spatial resolution 2 mm isotropic. This high spatial and temporal resolution was made possible through the use of multiband echo-planar imaging, with a simultaneous-multi-slice acceleration factor of 818 . To aid in cross-subject registration and surface mapping, T1-weighted and T2-weighted structural images of resolution 0.7 mm isotropic were also acquired, and B0 field mapping was also carried out to aid in correcting EPI distortions. The original set of subject measures was all the behavioral, demographic and other measures reported in the “open access” and “restricted” subject information spreadsheets available from the HCP database website (http://humanconnectome.org/data ).
9
Resting-state fMRI of the Human Connectome
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The dataset was selected from the Mar 2017 public data release from the Human Connectome Project (HCP, n = 1200), WU-Minn Consortium. Our sample includes 1017 subjects (ages 22–35 years, 546 females) scanned on a 3-T Siemens connectome-Skyra scanner, each with four resting state scans. Further details of the subjects, and the collection and preprocessing of the data are provided in the Supplementary Material , at the HCP website (http://www.humanconnectome.org/ ), and in a previous study10 (link).
10
Hypertension Neuroimaging Analysis in HCP
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The dataset used for cross-validation was selected from the Mar 2017 public data release from the Human Connectome Project (HCP, N = 1200), WU-Minn Consortium. Our sample included 1002 subjects (ages 22–37 years, 534 females) scanned on a 3-T Siemens connectome-Skyra scanner. The WU-Minn HCP Consortium obtained full informed consent from all participants, and research procedures and ethical guidelines were followed in accordance with the Institutional Review Boards (IRB). The demographic characteristics of participants are summarized in Table S2. The participants with systolic/diastolic blood pressure (SBP/DBP) higher than 130/85 [31] (link) were defined as the high blood pressure group. There were 144 participants with high blood pressure as the hypertension group, and 582 participants with normal blood pressure as the healthy control group. The collection and preprocessing of the data are provided at the HCP website (http://www.humanconnectome.org/) . The parameters and data preprocessing procedures are very consistent in both datasets which makes the HCP dataset useful for cross-validating the findings described here based on the UK Biobank dataset
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