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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041_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-041/func/sub-001_ses-041_task-bht_dir-AP_echo-1_part-mag_bold.nii.gz
VersionsMRIQC24.1.0.dev0+g3fe90466.d20240417
VersionsNiPype1.8.6
VersionsTemplateFlow24.2.0
md5sumd1329511c1c5cdc3990832970073dcd8

AcquisitionDuration361.475
AcquisitionMatrixPE96
AcquisitionTime09:42:32.410000
B0FieldSource['041pepolarbold', '041phasediff']
BandwidthPerPixelPhaseEncode37.879
BaseResolution96
DerivedVendorReportedEchoSpacing0.000549997
DwellTime2.3e-06
EchoNumber1
EchoTime0.0126
EchoTrainLength35
EffectiveEchoSpacing0.000274998
ImageOrientationPatientDICOM[0.99933, 0.0313952, 0.0187988, -0.0252957, 0.963897, -0.26507]
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
ReconMatrixPE96
RefLinesPE22
RepetitionTime1.6
SequenceVariantSK\SS
SeriesDescriptionfunc-bold_task-bht_dir-AP__cmrr_me4_sms4
SeriesNumber35
ShimSetting[8230, -5638, -6024, 695, -47, -216, 39, 33]
SliceThickness2.2
SliceTiming[0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.4225, 1.265, 0.5275, 1.37, 0.6325, 1.475, 0.7375, 0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.4225, 1.265, 0.5275, 1.37, 0.6325, 1.475, 0.7375, 0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.4225, 1.265, 0.5275, 1.37, 0.6325, 1.475, 0.7375, 0, 0.8425, 0.105, 0.9475, 0.21, 1.0525, 0.315, 1.1575, 0.4225, 1.265, 0.5275, 1.37, 0.6325, 1.475, 0.7375]
SpacingBetweenSlices2.2
TotalReadoutTime0.0261249
TxRefAmp248.429
WipMemBlock22b1e94b-2817-4b3e-986a-c1f5f24663d3||Sequence: R017 nxva30a/master r/d34922cc2+; Jun 27 2022 13:20:16 by eja

aor[0.0004746116504854369, 0.00045907766990291256, 0.0005284466019417477, 0.0007154368932038835]
aqi[0.0035539524271844657, 0.005092886650485436, 0.008875006019417476, 0.016072991262135922]
dummy_trs1
dvarsnstd28.65351125219511
dvarsstd1.0555528962439034
dvarsvstd1.0096903689756098
efc0.5862
fber667.3597
fdmean0.1257708151066248
fdnum37
fdperc17.961165048543688
fwhmavg3.357526220835677
fwhmx2.98933070762235
fwhmy3.4932525781502797
fwhmz3.5899953767344
gcor[0.0235559, 0.026125, 0.0244639, 0.0189871]
gsrx0.0026357003953307867
gsry0.1073232889175415
sizet206
sizex96
sizey96
sizez60
snr2.734094944250666
spacingtr1.600000023841858
spacingx2.197920083999634
spacingy2.197920083999634
spacingz2.200000047683716
summarybgk8.9526
summarybgmad19.6913
summarybgmean126.282
summarybgmedian30.0
summarybgn418349.0
summarybgp050.0
summarybgp95644.0
summarybgstdv223.9144
summaryfgk0.3238
summaryfgmad268.6893
summaryfgmean800.8754
summaryfgmedian774.0
summaryfgn134611.0
summaryfgp05385.0
summaryfgp951305.0
summaryfgstdv283.0908
tsnr50.00967029109597
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