Connectome skyra 3t scanner

Manufactured by Siemens

The Connectome-Skyra 3T scanner is a magnetic resonance imaging (MRI) system designed for brain imaging research. It is a 3 Tesla (3T) superconducting magnet that provides high-resolution images of the brain's neural connections and structures. The scanner is capable of performing various neuroimaging techniques, including functional MRI (fMRI), diffusion tensor imaging (DTI), and anatomical imaging, to support investigations of the human connectome.

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Lab products found in correlation

32 channel head coil, by Siemens (1 mentions)

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3T Connectome Skyra Connectome-Skyra scanner 3T Connectome Scanner Skyra 3T scanner Connectome Skyra Connectome scanner Skyra 3T Skyra scanner 3T scanner Connectome

5 protocols using connectome skyra 3t scanner

Resting-State fMRI Preprocessing for Dynamic Connectivity

Cited 3 times

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As part of the HCP protocol, each participant completed four 14 minute, 33 second resting-state fMRI (rs-fMRI) runs on two separate days. The resting-state runs were eyes-open and participants were instructed to keep their eyes on the fixation cross. Scans were acquired on a Siemens connectome-Skyra 3T scanner with 32-channel head coil (multiband sequence, acceleration factor of 8, TR = 0.72 sec, 2 mm isotropic spatial resolution) (33 (link)).
Dynamic connectivity measures were computed on the time-courses from the “Parcellation-Timeseries-Netmats (PTN) extensively processed resting-state fMRI dataset” that were included in the HCP900 Data Release. This publically-released dataset had undergone the following preprocessing by the HCP (34 (link), 35 (link)): artifact removal using ICA+FIX (36 (link), 37 (link)), temporal demeaning and variance normalization (38 (link)), and data reduction using MELODIC for Incremental Group-PCA (39 (link)) and then spatial Group-ICA at several dimensionalities (34 (link), 38 (link)). For the current study, the time-courses from the 300-dimensional ICA, that were extracted using the dual-regression approach, were used to examine dynamic connectivity.

Barber A.D., Lindquist M.A., DeRosse P, & Karlsgodt K.H. (2017). Dynamic Functional Connectivity States Reflecting Psychotic-Like Experiences. Biological psychiatry. Cognitive neuroscience and neuroimaging, 3(5), 443-453.

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Healthy Adult Neuroimaging Data from the Human Connectome Project

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The 2014 Human Connectome Project 500 Parcellation + Timeseries + Netmats (HCP500-PTN) release (Van Essen et al., 2013 (link)) is a collection of neuroimaging data from 523 healthy adults acquired on a customized 3T Siemens connectome-Skyra 3T scanner. Participants completed two scanning sessions on separate days. A T1w MPRAGE structural scan was acquired during each session (acquisition time = 7.6 min, TR/TE/TI = 2400/2.14/1000 ms, resolution = 0.7 × 0.7 × 0.7 mm³, SENSE factor = 2, flip angle = 8°). A simultaneous multi-slice pulse sequence with acceleration factor eight (Uğurbil et al., 2013 (link)) was used to acquire two rs-fMRI runs during each session, each consisting of 1200 volumes sampled with TR 0.72 s, at 2 mm isotropic spatial resolution (TE = 33.1 ms, flip angle = 52°, 72 axial slices). Participants were instructed to keep their eyes open and fixated on a cross hair, while remaining as still as possible. Within sessions, phase encoding directions for the two runs were alternated between right-to-left (RL) and left-to-right (LR) directions. In addition, respiratory signals associated with each scan where acquired using a respiratory belt placed on the participant’s abdomen.

Honari H, & Lindquist M.A. (2022). Mode decomposition-based time-varying phase synchronization for fMRI. NeuroImage, 261, 119519.

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Healthy Subject MRI Dataset from Human Connectome Project

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A sample of 100 unrelated healthy subjects (54% female; mean age = 29.1 ± 3.7 years; age range = 22–36 years) was drawn from the HCP dataset, as publicly provided by the HCP1200 subjects data release^{85 (link)}. Subjects within this sample were scanned on a customized Siemens “Connectome” Skyra 3 T scanner (32-channel Siemens head coil) and underwent high-resolution 3 T MRI, including T1-weighted (3D Multi-echo Magnetization–Prepared Rapid Gradient Echo [MEMPRAGE] sequence; voxel size: 0.7 mm isotropic; repetition time [TR]: 2400 ms; echo time [TE]: 2.14 ms), T2-weighted (3D sampling perfection with application-optimized contrasts by using flip angle evolution [SPACE] sequence; voxel size: 0.7 mm isotropic; TR: 3200 ms; TE: 565 ms), resting-state fMRI (gradient-echo echo-planar imaging [EPI] sequence; four runs; 1200 volumes/run, 14:33 min:sec each; voxel size: 2 mm isotropic; TR: 720 ms; TE: 33.1 ms), and high angular resolution diffusion imaging (spin-echo planar imaging sequence; voxel size: 1.25 mm isotropic; TR: 5520 ms; TE: 89.5 ms; max b-value: 3000 s/mm²; 270 non-colinear directions; 18 b0 acquisitions) sequences^{86 (link),87 (link)}. Informed consent was obtained from all subjects, and the procedures were approved by the Washington University Institutional Review Board.

Fotiadis P., Cieslak M., He X., Caciagli L., Ouellet M., Satterthwaite T.D., Shinohara R.T, & Bassett D.S. (2023). Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex. Nature Communications, 14, 6115.

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Healthy Adult Neuroimaging Data from the Human Connectome Project

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Honari H, & Lindquist M.A. (2022). Mode decomposition-based time-varying phase synchronization for fMRI. NeuroImage, 261, 119519.

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High-Resolution Multimodal Brain Imaging

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MRIs were acquired using a Siemens Connectome Skyra 3 T scanner housed at Washington University in St. Louis. The diffusion-weighted images (DWI) were collected using an HCPspecific variant of the multiband diffusion sequence. For the diffusion images, 3 different gradient tables were used. Each table was acquired once with right-to-left and left-to-right phase-encoding polarities and included 90 diffusion-weighting directions plus 6 b = 0 images interspersed throughout each run. The DWI consisted of 3 shells of b = 1000, 2000 and 3000 s/mm 2 interspersed with an equal number of acquisitions on each shell within each run. The detailed parameters were as follows: time repetition (TR) = 5520 ms, time echo (TE) = 89.5 ms, flip angle = 78 • , refocusing flip angle = 160 • , field of view (FOV) = 210 × 180 mm 2 , matrix = 168 × 144, slice thickness = 1.25 mm (111 slices), and multiband factor = 3. For T 1 -weighted images, 256 slices per slab were acquired with a 3D magnetizationprepared rapid gradient echo sequence as follows: TR = 2400 ms, TE = 2.14 ms, time to inversion = 1000 ms, flip angle = 8 • , FOV = 224 × 224 mm 2 , and resolution = 0.7 × 0.7 × 0.7 mm 3 . DWI and T 1 -weighted images were preprocessed using the HCP minimal-preprocessing pipelines (Glasser et al. 2013) .

Zhong S., Wei L., Zhao C., Yang L., Di Z., Francks C, & Gong G. (2021). Interhemispheric Relationship of Genetic Influence on Human Brain Connectivity. Cerebral cortex (New York, N.Y. : 1991), 31(1).

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