Basic echo-wise reports

Reports for: echo 1.

Standard deviation of signal through time

The voxel-wise standard deviation of the signal (variability along time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-1_desc-stdev_bold.svg

View of the background of the voxel-wise average of the BOLD timeseries

This panel shows a mosaic enhancing the background around the head. Artifacts usually unveil themselves in the air surrounding the head, where no signal sources are present.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-1_desc-background_bold.svg

Voxel-wise average of BOLD time-series, zoomed-in covering just the brain

This panel shows a mosaic of the brain. This mosaic is the most suitable to screen head-motion intensity inhomogeneities, global/local noise, signal leakage (for example, from the eyeballs and across the phase-encoding axis), etc.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-1_desc-zoomed_bold.svg

Carpetplot and nuisance signals

The so-called «carpetplot» may assist in assessing head-motion derived artifacts and respiation effects.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-1_desc-carpet_bold.svg

Reports for: echo 2.

Standard deviation of signal through time

The voxel-wise standard deviation of the signal (variability along time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-2_desc-stdev_bold.svg

View of the background of the voxel-wise average of the BOLD timeseries

This panel shows a mosaic enhancing the background around the head. Artifacts usually unveil themselves in the air surrounding the head, where no signal sources are present.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-2_desc-background_bold.svg

Voxel-wise average of BOLD time-series, zoomed-in covering just the brain

This panel shows a mosaic of the brain. This mosaic is the most suitable to screen head-motion intensity inhomogeneities, global/local noise, signal leakage (for example, from the eyeballs and across the phase-encoding axis), etc.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-2_desc-zoomed_bold.svg

Carpetplot and nuisance signals

The so-called «carpetplot» may assist in assessing head-motion derived artifacts and respiation effects.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-2_desc-carpet_bold.svg

Reports for: echo 3.

Standard deviation of signal through time

The voxel-wise standard deviation of the signal (variability along time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-3_desc-stdev_bold.svg

View of the background of the voxel-wise average of the BOLD timeseries

This panel shows a mosaic enhancing the background around the head. Artifacts usually unveil themselves in the air surrounding the head, where no signal sources are present.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-3_desc-background_bold.svg

Voxel-wise average of BOLD time-series, zoomed-in covering just the brain

This panel shows a mosaic of the brain. This mosaic is the most suitable to screen head-motion intensity inhomogeneities, global/local noise, signal leakage (for example, from the eyeballs and across the phase-encoding axis), etc.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-3_desc-zoomed_bold.svg

Carpetplot and nuisance signals

The so-called «carpetplot» may assist in assessing head-motion derived artifacts and respiation effects.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-3_desc-carpet_bold.svg

Reports for: echo 4.

Standard deviation of signal through time

The voxel-wise standard deviation of the signal (variability along time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-4_desc-stdev_bold.svg

View of the background of the voxel-wise average of the BOLD timeseries

This panel shows a mosaic enhancing the background around the head. Artifacts usually unveil themselves in the air surrounding the head, where no signal sources are present.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-4_desc-background_bold.svg

Voxel-wise average of BOLD time-series, zoomed-in covering just the brain

This panel shows a mosaic of the brain. This mosaic is the most suitable to screen head-motion intensity inhomogeneities, global/local noise, signal leakage (for example, from the eyeballs and across the phase-encoding axis), etc.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-4_desc-zoomed_bold.svg

Carpetplot and nuisance signals

The so-called «carpetplot» may assist in assessing head-motion derived artifacts and respiation effects.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-4_desc-carpet_bold.svg

Extended echo-wise reports

Reports for: echo 1.

Voxel-wise average of BOLD time-series

The average signal calculated across the last axis (time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-1_desc-mean_bold.svg

Reports for: echo 2.

Voxel-wise average of BOLD time-series

The average signal calculated across the last axis (time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-2_desc-mean_bold.svg

Reports for: echo 3.

Voxel-wise average of BOLD time-series

The average signal calculated across the last axis (time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-3_desc-mean_bold.svg

Reports for: echo 4.

Voxel-wise average of BOLD time-series

The average signal calculated across the last axis (time).

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_echo-4_desc-mean_bold.svg

Extended reports shared across echos

Brain extraction performance

Brain mask as internally extracted by MRIQC. Defects on the brainmask could indicate problematic aspects of the image quality-wise.

Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_desc-brainmask_bold.svg

Spatial normalization of the anatomical image

This panel shows a quick-and-dirty nonlinear registration into the MNI152NLin2009cAsym template accessed with TemplateFlow.

Problem loading figure sub-001/figures/sub-001_ses-023_task-bht_dir-AP_desc-norm_bold.svg. If the link below works, please try reloading the report in your browser.
Get figure file: sub-001/figures/sub-001_ses-023_task-bht_dir-AP_desc-norm_bold.svg

About

Errors

Reproducibility and provenance information

Thanks for using MRIQC. The following information may assist in reconstructing the provenance of the corresponding derivatives.

Execution environmentsingularity
Input filename/sub-001/ses-023/func/sub-001_ses-023_task-bht_dir-AP_echo-1_part-mag_bold.nii.gz
VersionsMRIQC24.1.0.dev0+g3fe90466.d20240417
VersionsNiPype1.8.6
VersionsTemplateFlow24.2.0
md5sum8faa9b3ce80630f8426880e96149dd09

AcquisitionDuration361.475
AcquisitionMatrixPE96
AcquisitionTime20:45:56.445000
B0FieldSource['023pepolarbold', '023phasediff']
BandwidthPerPixelPhaseEncode37.879
BaseResolution96
DerivedVendorReportedEchoSpacing0.000549997
DwellTime2.3e-06
EchoNumber1
EchoTime0.0126
EchoTrainLength35
EffectiveEchoSpacing0.000274998
ImageOrientationPatientDICOM[0.998852, -0.00202939, 0.0478582, 0.0212718, 0.913976, -0.405209]
ImageType['ORIGINAL', 'PRIMARY', 'FMRI', 'NONE']
ImageTypeText['ORIGINAL', 'PRIMARY', 'M', 'MB', 'TE1', 'DIS2D']
InPlanePhaseEncodingDirectionDICOMCOL
PercentPhaseFOV100
PercentSampling100
PhaseEchoTime10.0126
PhaseEchoTime20.03304
PhaseEncodingDirectionj-
PhaseResolution1
PixelBandwidth2264
ProtocolNamefunc-bold_task-bht_dir-AP__cmrr_me4_sms4
PulseSequenceNameepfid2d4_96
ReceiveCoilActiveElementsHC1-7;NC1
ReconMatrixPE96
RefLinesPE22
RepetitionTime1.6
SequenceVariantSK\SS
SeriesDescriptionfunc-bold_task-bht_dir-AP__cmrr_me4_sms4
SeriesNumber25
ShimSetting[8239, -5621, -6013, 709, -19, -249, -27, 56]
SliceThickness2.2
SliceTiming[0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.42, 1.2625, 0.525, 1.3675, 0.63, 1.4725, 0.7375, 0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.42, 1.2625, 0.525, 1.3675, 0.63, 1.4725, 0.7375, 0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.42, 1.2625, 0.525, 1.3675, 0.63, 1.4725, 0.7375, 0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.42, 1.2625, 0.525, 1.3675, 0.63, 1.4725, 0.7375]
SpacingBetweenSlices2.2
TotalReadoutTime0.0261249
TxRefAmp247.278
WipMemBlock174b615f-d67a-40f9-a47b-9105d794d1de||Sequence: R017 nxva30a/master r/d34922cc2+; Jun 27 2022 13:20:16 by eja

aor[0.0005474757281553399, 0.0006175728155339806, 0.0007116990291262137, 0.0008635436893203885]
aqi[0.0067268544174757285, 0.006953534611650485, 0.011224444368932038, 0.019502331067961162]
dummy_trs1
dvarsnstd33.13522160219513
dvarsstd1.1176062548292678
dvarsvstd1.009506924780488
efc0.5866
fber539.3699
fdmean0.18809980368991058
fdnum86
fdperc41.74757281553398
fwhmavg3.5174652445261607
fwhmx3.2180924372504065
fwhmy3.5325624696376785
fwhmz3.801740826690396
gcor[0.0155726, 0.0218081, 0.021876, 0.0177018]
gsrx-0.0007677786634303629
gsry0.1063968762755394
sizet206
sizex96
sizey96
sizez60
snr2.549394616256939
spacingtr1.600000023841858
spacingx2.197920083999634
spacingy2.197920083999634
spacingz2.200000047683716
summarybgk9.7754
summarybgmad22.7932
summarybgmean128.4594
summarybgmedian34.0
summarybgn418395.0
summarybgp051.0
summarybgp95629.0
summarybgstdv221.6856
summaryfgk1.0824
summaryfgmad281.7736
summaryfgmean815.1749
summaryfgmedian781.0
summaryfgn134565.0
summaryfgp05375.0
summaryfgp951354.0
summaryfgstdv306.3461
tsnr48.21193146239966
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