6. Built-in Pipeline steps and data#
6.1. Data Grabbers#
6.1.1. Available#
Class |
Description |
Access |
Type/Config |
State |
Version Added |
|---|---|---|---|---|---|
Open with registration |
Built-in |
Done |
0.0.1 |
||
UKB VBM dataset preprocessed with CAT. Available for Juseless only. |
Restricted |
|
Done |
0.0.1 |
|
CamCAN VBM dataset preprocessed with CAT. Available for Juseless only. |
Restricted |
|
Done |
0.0.1 |
|
Open without registration |
Built-in |
Done |
0.0.1 |
||
Open without registration |
Built-in |
Done |
0.0.1 |
||
Open without registration |
Built-in |
Done |
0.0.1 |
||
AOMIC ID1000 VBM dataset. Available for Juseless only. |
Restricted |
|
Done |
0.0.1 |
|
IXI VBM dataset. Available for Juseless only. |
Restricted |
|
Done |
0.0.1 |
|
UCLA fMRIPrep dataset. Available for Juseless only. |
Restricted |
|
Done |
0.0.1 |
6.1.2. Planned#
Name |
Description |
Access |
Type/Config |
Reference |
|---|---|---|---|---|
ENKI |
ENKI dataset for Juseless |
Restricted |
|
6.2. Markers#
6.2.1. Available#
Class |
Description |
State |
Version Added |
|---|---|---|---|
Apply parcellation and perform aggregation function |
Done |
0.0.1 |
|
Compute functional connectivity over parcellation |
Done |
0.0.1 |
|
Compute functional connectivity across two parcellations |
Done |
0.0.1 |
|
Spherical aggregation using mean |
Done |
0.0.1 |
|
Compute functional connectivity over spheres placed on coordinates |
Done |
0.0.1 |
|
Compute root sum of squares of edgewise timeseries |
Done |
0.0.1 |
|
Calculate regional homogeneity over parcellation |
Done |
0.0.1 |
|
Calculate regional homogeneity over spheres placed on coordinates |
Done |
0.0.1 |
|
Calculate (f)ALFF and aggregate using parcellations |
Done |
0.0.1 |
|
Calculate (f)ALFF and aggregate using spheres placed on coordinates |
Done |
0.0.1 |
|
Calculate edge-centric functional connectivity over parcellation, as found in Jo et al. (2021) |
Done |
0.0.2 |
|
Calculate edge-centric functional connectivity over spheres placed on coordinates, as found in Jo et al. (2021) |
Done |
0.0.2 |
|
Calculate temporal signal-to-noise ratio using parcellations |
Done |
0.0.2 |
|
Calculate temporal signal-to-noise ratio using spheres placed on coordinates |
Done |
0.0.2 |
6.2.2. Planned#
6.3. Parcellations#
6.3.1. Available#
Name |
Options |
Keys |
Version added |
Publication |
|---|---|---|---|---|
Schaefer |
|
Schaefer900x7, Schaefer1000x7, Schaefer100x17,Schaefer200x17, Schaefer300x17, Schaefer400x17,Schaefer500x17, Schaefer600x17, Schaefer700x17,Schaefer800x17, Schaefer900x17, Schaefer1000x17 |
0.0.1 |
Schaefer, A., Kong, R., Gordon, E.M. et al.
Local-Global Parcellation of the Human Cerebral Cortex from
Intrinsic Functional Connectivity MRI
Cerebral Cortex, Volume 28(9), Pages 3095–3114 (2018).
|
SUIT |
|
|
0.0.1 |
Diedrichsen, J.
A spatially unbiased atlas template of the human cerebellum.
NeuroImage, Volume 33(1), Pages 127–138 (2006).
|
TIAN |
|
TianxS1x3TxMNI6thgeneration, TianxS1x7TxMNI6thgeneration,TianxS2x3TxMNI6thgeneration, TianxS2x7TxMNI6thgeneration,TianxS3x3TxMNI6thgeneration, TianxS3x7TxMNI6thgeneration,TianxS4x3TxMNI6thgeneration, TianxS4x7TxMNI6thgeneration,TianxS1x3TxMNInonlinear2009cAsym, TianxS2x3TxMNInonlinear2009cAsym,TianxS3x3TxMNInonlinear2009cAsym, TianxS4x3TxMNInonlinear2009cAsym |
0.0.1 |
Tian, Y., Margulies, D.S., Breakspear, M. et al.
Topographic organization of the human subcortex
unveiled with functional connectivity gradients.
Nature Neuroscience, Volume 23, Pages 1421–1432 (2020).
|
6.3.2. Planned#
Name |
Publication |
|---|---|
Desikan-Killiany |
Desikan, R.S., Ségonne, F., Fischl, B. et al.
An automated labeling system for subdividing the human cerebral cortex
on MRI scans into gyral based regions of interest.
NeuroImage, Volume 31(3), Pages 968-980 (2006).
|
Glasser |
Glasser, M.F., Coalson, T.S., Robinson, E.C. et al.
A multi-modal parcellation of human cerebral cortex.
Nature (2016).
|
AAL |
Rolls, E.T., Huang, C.C., Lin, C.P., et al.
Automated anatomical labelling atlas 3.
Neuroimage, Volume 206 (2020).
|
Shen |
Shen, X., Tokoglu, F., Papademetris, X., Constable, R.T.
Groupwise whole-brain parcellation from resting-state fMRI data
for network node identification.
Neuroimage, Volume 82 (2013).
|
Mindboggle 101 |
Klein, A., & Tourville, J.
101 labeled brain images and a consistent human cortical labeling protocol.
Frontiers in Neuroscience (2012).
|
Destrieux |
Destrieux, C., Fischl, B., Dale, A., & Halgren, E.
Automatic parcellation of human cortical gyri and sulci using standard
anatomical nomenclature.
NeuroImage, Volume 53(1), Pages 1–15 (2010).
|
Fan |
Fan, L., Li, H., Zhuo, J. et al.
The human brainnetome atlas: a new brain atlas based on connectional
architecture.
Cerebral cortex, Volume 26(8), Pages 3508-3526 (2016).
|
Buckner |
Buckner, R.L., Krienen, F.M., Castellanos, A., Diaz, J.C., Yeo, B.T.T.
The organization of the human cerebellum estimated by intrinsic functional
connectivity.
Journal of Neurophysiology, Volume 106(5), Pages 2322–2345 (2011).
Yeo, B.T.T., Krienen, F.M., Sepulcre, J. et al.
The organization of the human cerebral cortex estimated by intrinsic functional
connectivity.
Journal of Neurophysiology, Volume 106(3), Pages 1125–1165 (2011).
|
6.4. Coordinates#
6.4.1. Available#
Name |
Keys |
Version added |
Publication |
|---|---|---|---|
Cognitive action control |
|
0.0.1 |
Cieslik, E.C., Mueller, V.I., Eickhoff, C.R., Langner, R., Eickhoff, S.B.
Three key regions for supervisory attentional control: Evidence from neuroimaging
meta-analyses.
Neuroscience & Biobehavioral Reviews, Volume 48, Pages 22-34 (2015).
|
Cognitive action regulation |
|
0.0.1 |
Langner, R., Leiberg, S., Hoffstaedter, F., Eickhoff, S.B.
Towards a human self-regulation system: Common and distinct neural signatures
of emotional and behavioural control.
Neuroscience & Biobehavioral Reviews, Volume 90, Pages 400-410 (2018).
|
Default mode network |
|
0.0.1 |
Van Dijk, K.R., Hedden, T., Venkataraman, A. et al.
Intrinsic functional connectivity as a tool for human connectomics:
theory, properties, and optimization.
Journal of neurophysiology, Volume 103(1), Pages 297-321 (2010).
Buckner, R.L., Andrews‐Hanna, J.R., & Schacter, D.L.
The brain’s default network: anatomy, function, and relevance to disease.
Annals of the New York Academy of Sciences, Volume 1124(1), Pages 1-38 (2008).
|
Missing formal name |
|
0.0.1 |
Missing publication details |
Empathic processing |
|
0.0.1 |
Bzdok, D., Schilbach, L., Vogeley, K. et al.
Parsing the neural correlates of moral cognition: ALE meta-analysis on morality,
theory of mind, and empathy.
Brain Structure and Function, Volume 217(4), Pages 783-796 (2012).
|
Extended social-affective default |
|
0.0.1 |
Amft, M., Bzdok, D., Laird, A.R. et al.
Definition and characterization of an extended social-affective default network.
Brain structure & function, Volume 220, Pages 1031–1049 (2015).
|
Extended multiple-demand network |
|
0.0.1 |
Camilleri, J.A., Müller, V.I., Fox, P. et al.
Definition and characterization of an extended multiple-demand network.
NeuroImage, Volume 165, Pages 138-147 (2018).
|
Motor execution |
|
0.0.1 |
Witt, S.T., Laird, A.R., Meyerand, M.E.
Functional neuroimaging correlates of finger-tapping task variations:
An ALE meta-analysis,
NeuroImage, Volume 42(1), Pages 343-356 (2008).
|
Multitasking |
|
0.0.1 |
Worringer, B., Langner, R., Koch, I. et al.
Common and distinct neural correlates of dual-tasking and task-switching:
a meta-analytic review and a neuro-cognitive processing model of human multitasking.
Brain structure & function, Volume 224(5), Pages 1845–1869 (2019).
|
Physiological stress |
|
0.0.1 |
Kogler, L., Müller, V.I., Chang, A. et al.
Psychosocial versus physiological stress — Meta-analyses on deactivations and
activations of the neural correlates of stress reactions.
NeuroImage, Volume 119, Pages 235-251 (2015).
|
Reward-related decision making |
|
0.0.1 |
Liu, X., Hairston, J., Schrier, M., Fan, J.
Common and distinct networks underlying reward valence and processing stages:
A meta-analysis of functional neuroimaging studies.
Neuroscience & Biobehavioral Reviews, Volume 35(5), Pages 1219-1236 (2011).
|
Missing formal name |
|
0.0.1 |
Missing publication details |
Theory-of-mind cognition |
|
0.0.1 |
Bzdok, D., Schilbach, L., Vogeley, K. et al.
Parsing the neural correlates of moral cognition: ALE meta-analysis on morality,
theory of mind, and empathy.
Brain Structure and Function, Volume 217(4), Pages 783-796 (2012).
|
Vigilant attention |
|
0.0.1 |
Langner, R., & Eickhoff, S.B.
Sustaining attention to simple tasks: a meta-analytic review of the neural
mechanisms of vigilant attention.
Psychological bulletin, Volume 139 4, Pages 870-900 (2013).
|
Working memory |
|
0.0.1 |
Rottschy, C., Langner, R., Dogan, I. et al.
Modelling neural correlates of working memory: A coordinate-based meta-analysis.
NeuroImage, Volume 60, Pages 830-846 (2012).
|
Areal functional network from Power et al. (2011) |
|
0.0.2 |
Power, J. D., Cohen, A. L., Nelson, S. M. et al.
Functional network organization of the human brain.
Neuron, Volume 72(4), Pages 665–678 (2011).
|
Brain maturity functional connections from Dosenbach et al. (2010) |
|
0.0.2 |
Dosenbach, N.U.F., Nardos, B., Cohen, A.L. et al.
Prediction of Individual Brain Maturity Using fMRI
Science, Volume 329(5997), Pages 1358-1361 (2010).
|
6.4.2. Planned#
Name |
Publication |
|---|---|
Emotional scene and face processing (EmoSF) |
Sabatinelli, D., Fortune, E.E., Li, Q. et al.
Emotional perception: Meta-analyses of face and natural scene processing.
NeuroImage, Volume 54(3), Pages 2524-2533 (2011).
|
Perceptuo-motor network |
Heckner, M.K., Cieslik, E.C., Eickhoff, S.B. et al.
The Aging Brain and Executive Functions Revisited: Implications from Meta-analytic
and Functional-Connectivity Evidence.
Journal of Cognitive Neuroscience, Volume 33(9), Pages 1716–1752 (2021).
|
6.5. Masks#
6.5.1. Available#
Name |
Keys |
Version added |
Description - Publication |
|---|---|---|---|
Vickery-Patil (Gray Matter) |
GM_prob0.2 |
0.0.1 |
Vickery, Sam, & Patil, Kaustubh. (2022).
Chimpanzee and Human Gray Matter Masks [Data set]. Zenodo.
|
Vickery-Patil (Cortex + Basal Ganglia) |
GM_prob0.2_cortex |
0.0.1 |
Vickery, Sam, & Patil, Kaustubh. (2022).
Chimpanzee and Human Gray Matter Masks [Data set]. Zenodo.
|
Nilearn’s MNI152 1mm-resolution mask |
compute_brain_mask |
0.0.2 |
Compute the whole-brain mask. This mask is calculated using MNI152 1mm-resolution template mask onto the
target image. See
nilearn.masking.compute_brain_mask() |
Nilearn’s mask computed from FMRI data |
compute_epi_mask |
0.0.2 |
Compute a brain mask from fMRI data. This is based on an heuristic proposed by T.Nichols: find the least
dense point of the histogram, between fractions
lower_cutoff and upper_cutoff of the total imagehistogram. See
nilearn.masking.compute_epi_mask() |
Nilearn’s background mask |
compute_background_mask |
0.0.2 |
Compute a brain mask for the images by guessing the value of the background from the border of the image.
|
Nilearn’s ICBM152 template gray-matter mask |
fetch_icbm152_brain_gm_mask |
0.0.2 |
Compute a gray-matter mask from the asymmetrical ICBM152 2009 template, release a.
|