The association between motor coordination, behavior, cognition and brain structure in children: an ABCD study.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches

[1] § Methods › Neuroimaging › Harmonization and processing of the dMRI data ↔ ukf/unscented_kalman_filter.h, lines 16–87 · score 0.58 · unscented Kalman Filter, reconstruction, UKF, covariates
[2] § Methods › Neuroimaging › Harmonization and processing of the dMRI data ↔ ukf/unscented_kalman_filter.cc, lines 123–236 · score 0.55 · unscented Kalman Filter, UKF, covariates

Paper

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The authors' code

C/C++ header · 89 lines · 2.9 KB · other · 1 match

/**
* \file unscented_kalman_filter.h
* \brief The implementation of the unscented Kalman Filter
* The C++ implementation of the unscented Kalman Filter (UKF) with the option to run
* with constraints
*/
#ifndef UNSCENTED_KALMAN_FILTER_H_
#define UNSCENTED_KALMAN_FILTER_H_
#include <vector>
#include "ukf_types.h"
class FilterModel;
/**
* \class UnscentedKalmanFilter
* \brief The C++ implementation of the unscented Kalman Filter
*/
class UnscentedKalmanFilter
{
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
/**
* \brief Constructor
* \param filter_model The UKF is initialized with a filter model that defines the observation
* and transition functions. Also required are the noise parameters.
*/
UnscentedKalmanFilter(FilterModel *filter_model);
/**
* \brief Does the one filter step.
* \param[in] x Current state vector
* \param[in] p Current convariance matrix of the stateal and it
* \param[in] z The signal interpolated at the current position
* \param[out] x_new Updated state
* \param[out] p_new Updated covariance
* \param[out] The normalized mean squared reconstruction error
*/
void Filter(const State& x, const ukfMatrixType& p, const ukfVectorType& z, // This is the signal
State& x_new, ukfMatrixType& p_new, ukfPrecisionType& dNormMSE);
private:
/** Spreads the points around the current state using the covariance. */
void SigmaPoints(const State& x, const ukfMatrixType& p, ukfMatrixType& x_spread);
/**
* \brief Contrains the state matrix
* \param X The state matrix which is the result of spreading out the original state through SigmaPoints.
* Will be constrained in this function.
* \param W The covariance necesseray for contraining. See the malcolm MICCAI paper.
*/
void Constrain(ukfMatrixType& X, const ukfMatrixType& W);
/**
* \brief Contrains the state vector
* \param X The state vector which will be constrained.
* \param W The covariance necesseray for contraining. See the malcolm MICCAI paper.
*/
void Constrain(ukfVectorType& x, const ukfMatrixType& W);
/** A helper function to check if the constrain operation is necessary */
bool violatesContraints(ukfVectorType& x);
/** Pointer to the filter model */
const FilterModel * const m_FilterModel;
/** state vector dimension */
// HACK REMOVE int _state_dim;
/** for the distribution of the sigma ponts (:= sqrt(dim + m_SigmaPointSpread) ) */
ukfPrecisionType m_Scale;
/** The weights for spreading the sigma points */
ukfVectorType m_Weights;
/** Matrix of weights for spreading of sigma points consisting of the repeted entries of m_Weights */
ukfMatrixType m_WeightsRepeated;
/** A fixed parameters used for spreading of the sigma points */
ukfPrecisionType m_SigmaPointSpread;
//DUMMY VARIABLES TAHT ARE ALWAYS ZERO and not used.
ukfMatrixType m_DummyZeroCE;
ukfVectorType m_DummyZeroce0;
};
#endif // UNSCENTED_KALMAN_FILTER_H_

unscented_kalman_filter.h at commit 2d2b661, under other · at the source

Overview

Authors: Elena M Bonke^1,2,3,4, Suheyla Cetin-Karayumak^4,5, Fan Zhang⁵, Yorghos Tripodis^6,7, Caroline Seer^8,9, Michael Frey^10,11, Anja K Betz^1,2,3,4, Philine Rojczyk^1,2,3,4, Leo R Zekelman^12,13, Johanna Seitz-Holland^4,14, Steve Pieper¹⁵, Gerd Schulte-Koerne¹¹, Martha E Shenton^4,5,16, Lauren J O’Donnell⁵, Yogesh Rathi^4,5, Inga K Koerte^1,2,3,4,14

16 affiliations

cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Ludwig-Maximilians-Universität, Munich, Germany
University Hospital, Ludwig-Maximilians-Universität, NeuroImaging Core Unit Munich (NICUM), Munich, Germany
German Center for Child and Adolescent Health (DZKJ), partner site Munich, Munich, Germany
Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
Alzheimer’s Disease and CTE Centers, Boston University School of Medicine, Boston, MA USA
Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven, Belgium
KU Leuven Brain Institute (LBI), KU Leuven, Flanders, Belgium
Faculty of Applied Healthcare Sciences, Deggendorf Institute of Technology, Deggendorf, Germany
Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Ludwig-Maximilians-Universität, Munich, Germany
Graduate Program in Speech and Hearing Bioscience and Technology, Harvard Medical School, Boston, MA USA
Department of Neurosurgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
Isomics, Inc., Cambridge, MA USA
VA Boston Healthcare System, Brockton Division, Brockton, MA USA

Institutions: Brigham and Women's Hospital (United States); Harvard University (United States); LMU Klinikum (Germany); Ludwig-Maximilians-Universität München (Germany); Boston University (United States); KU Leuven (Belgium); Deggendorf Institute of Technology (Germany); Massachusetts General Hospital (United States); VA Boston Healthcare System (United States)

Journal: European child & adolescent psychiatry, volume 35, issue 6, pages 1983-1995

Dates: received 16 July 2025; accepted 14 November 2025; published online 6 April 2026; in print 2026

Type: Research article · Language: English

License: CC BY

Identifiers: DOI 10.1007/s00787-025-02931-2 · PMID 41940926 · PMCID PMC13337589 · OpenAlex W7150809085

Open access: hybrid, a free copy (OpenAlex)

Status: code verified

Categories: structural MRI / diffusion (modality), human (organism), cognitive (subfield)

Methods: Statistics, Machine learning, fMRI & imaging, Smoothing, state filtering, decompositions

Keywords: Motor coordination, Behavior, Cognition, White matter microstructure

Topic: Children's Physical and Motor Development (Developmental and Educational Psychology, Psychology), according to OpenAlex

Funding: Klinikum der Universität München

Citations: not cited yet (Europe PMC); 56 references in the paper

Abstract

The prevalence of behavioral and cognitive difficulties in children is high and often remains undetected. Evidence suggests that poor motor coordination may be an early indicator of these difficulties. However, the underlying mechanisms are unknown. This study investigates whether motor coordination is associated with behavioral and cognitive outcomes, and whether white matter microstructure characteristics mediate these relationships. Data from 9342 children participating in the Adolescent Brain Cognitive Development (ABCD) study was analyzed. Children were categorized in two groups: normal (n = 8239; mean age = 9.93; 48.5% female) and poor motor coordination (n = 1103; mean age = 9.88; 42.3% female) based on parent-report. Behavior was assessed using the Child Behavior Checklist, cognitive functioning using the Youth National Institute of Health toolbox, and white matter microstructure using diffusion magnetic resonance imaging. Children with poor motor coordination had significantly more behavioral difficulties, lower cognitive functioning and altered white matter microstructure. White matter microstructure partly mediated the associations between motor coordination and behavioral and cognitive outcomes.These findings underline the importance of early identification of poor motor coordination to support children at risk of broader developmental concerns, including behavioral and cognitive difficulties.

Supplementary Information: The online version contains supplementary material available at 10.1007/s00787-025-02931-2.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.

pnlbwh/ukftractography

License: other

State: the link answers, verified on 29 September 2026

Evidence: files inventoried

Commit: 2d2b661539700aa825c1949823119601e11e1823, 2 June 2025

Languages: C/C++ (59), C++ (31), Python (2), Shell (2), MATLAB (1)

Size: 207 files, 95 scripts

Software Heritage: archived

Found in: the text, “Harmonization and processing of the dMRI data”

Holds: README, license file, environment (Dockerfile), continuous integration

Not found: CITATION.cff, tests, documentation

Availability: 1 check, the latest on 29 September 2026: the link answers

29 September 2026: the link answers

97 files

CompressedSensing/BPDN_homotopy.h, C/C++, 5 lines
CompressedSensing/BalancedDWIReplications.h, C/C++, 163 lines
CompressedSensing/BuildRidges.h, C/C++, 8 lines
CompressedSensing/BuildSensor.h, C/C++, 6 lines
CompressedSensing/CompressedSensing.h, C/C++, 12 lines
CompressedSensing/DefaultGradients.h, C/C++, 5 lines
CompressedSensing/DoCSEstimate.h, C/C++, 78 lines
CompressedSensing/MultiSample.h, C/C++, 10 lines
CompressedSensing/NrrdFile.h, C/C++, 40 lines
CompressedSensing/SphHarm.h, C/C++, 51 lines
CompressedSensing/SphericalHarmonics.h, C/C++, 7 lines
CompressedSensing/SphericalHarmonicsConst.h, C/C++, 22 lines
CompressedSensing/icosahedron3.h, C/C++, 6 lines
InteractiveUKF/Logic/vtkSlicerInteractiveUKFLogic.h, C/C++, 92 lines
InteractiveUKF/UI/InteractiveUKF.py, Python, 539 lines
InteractiveUKF/Widgets/qSlicerInteractiveUKFQWidget.h, C/C++, 52 lines
UKFTractography/Data/GenerateSynDataForTractography.m, MATLAB, 54 lines
UKFTractography/Testing/CompareFibers.cc, C++, 159 lines
UKFTractography/Testing/generate_ground_truth.sh, Shell, 41 lines
UKFTractography/Testing/slicer_cli_test.py, Python, 73 lines
common/BRAINSThreadControl.h, C/C++, 49 lines
common/fiber.h, C/C++, 42 lines
common/linalg.h, C/C++, 90 lines
common/ukf_exports.h, C/C++, 41 lines
common/ukf_types.h, C/C++, 55 lines
common/vtkPolyDataIO.h, C/C++, 93 lines
common/vtkReader.h, C/C++, 291 lines
examples/sample_run.sh, Shell, 36 lines
fibertractdispersion/computedispersion.h, C/C++, 14 lines
fibertractdispersion/fiberbundle.h, C/C++, 69 lines
ukf/ISignalData.h, C/C++, 124 lines
ukf/NrrdData.cc, C++, 947 lines
ukf/NrrdData.h, C/C++, 167 lines
ukf/QuadProg++_Eigen.cc, C++, 882 lines
ukf/QuadProg++_Eigen.h, C/C++, 128 lines
ukf/cli.cc, C++, 324 lines
ukf/cli.h, C/C++, 4 lines
ukf/dwi_normalize.cc, C++, 348 lines
ukf/dwi_normalize.h, C/C++, 27 lines
ukf/filter_Full1T.cc, C++, 61 lines
ukf/filter_Full1T.h, C/C++, 37 lines
ukf/filter_Full1T_FW.cc, C++, 78 lines
ukf/filter_Full1T_FW.h, C/C++, 66 lines
ukf/filter_Full2T.cc, C++, 94 lines
ukf/filter_Full2T.h, C/C++, 37 lines
ukf/filter_Full2T_FW.cc, C++, 121 lines
ukf/filter_Full2T_FW.h, C/C++, 71 lines
ukf/filter_Full3T.cc, C++, 115 lines
ukf/filter_Full3T.h, C/C++, 43 lines
ukf/filter_NODDI1F.cc, C++, 64 lines
ukf/filter_NODDI1F.h, C/C++, 53 lines
ukf/filter_NODDI2F.cc, C++, 96 lines
ukf/filter_NODDI2F.h, C/C++, 62 lines
ukf/filter_Simple1T.cc, C++, 82 lines
ukf/filter_Simple1T.h, C/C++, 34 lines
ukf/filter_Simple1T_FW.cc, C++, 122 lines
ukf/filter_Simple1T_FW.h, C/C++, 64 lines
ukf/filter_Simple2T.cc, C++, 123 lines
ukf/filter_Simple2T.h, C/C++, 36 lines
ukf/filter_Simple2T_FW.cc, C++, 151 lines
ukf/filter_Simple2T_FW.h, C/C++, 66 lines
ukf/filter_Simple3T.cc, C++, 159 lines
ukf/filter_Simple3T.h, C/C++, 40 lines
ukf/filter_model.cc, C++, 100 lines
ukf/filter_model.h, C/C++, 200 lines
ukf/git_version.h, C/C++, 5 lines
ukf/math_utilities.h, C/C++, 35 lines
ukf/seed.cc, C++, 27 lines
ukf/seed.h, C/C++, 45 lines
ukf/thread.cc, C++, 114 lines
ukf/thread.h, C/C++, 55 lines
ukf/tractography.cc, C++, 2,079 lines
ukf/tractography.h, C/C++, 346 lines
ukf/ukffiber.cc, C++, 393 lines
ukf/ukffiber.h, C/C++, 76 lines
ukf/unscented_kalman_filter.cc, C++, 236 lines, 1 match
ukf/unscented_kalman_filter.h, C/C++, 89 lines, 1 match
ukf/utilities.cc, C++, 885 lines
ukf/utilities.h, C/C++, 48 lines
ukf/vtk_writer.cc, C++, 780 lines
ukf/vtk_writer.h, C/C++, 156 lines
vtk2mask/Array3D.h, C/C++, 77 lines
vtk2mask/Converter.cc, C++, 345 lines
vtk2mask/Converter.h, C/C++, 181 lines
vtkFilter/ExpressionEvaluator.cc, C++, 195 lines
vtkFilter/ExpressionEvaluator.h, C/C++, 124 lines
vtkFilter/ExpressionParser.cc, C++, 231 lines
vtkFilter/ExpressionParser.h, C/C++, 79 lines
vtkFilter/FiberFilter.cc, C++, 159 lines
vtkFilter/FiberFilter.h, C/C++, 121 lines
vtkFilter/FiberLogic.h, C/C++, 103 lines
vtkFilter/Region.cc, C++, 68 lines
vtkFilter/Region.h, C/C++, 96 lines
vtkFilter/vtkWriter.cc, C++, 155 lines
vtkFilter/vtkWriter.h, C/C++, 77 lines
LICENSE.txt, License, 195 lines
README.md, Text, 154 lines

At the source: github.com/pnlbwh/ukftractography

SlicerDMRI/whitematteranalysis

License: other

State: the link answers, verified on 29 September 2026

Evidence: files inventoried

Commit: 4532b911386d2d1bc7ebba63fdd13e65b1660623, 13 June 2025

Languages: Python (125), Shell (2)

Size: 165 files, 127 scripts

Software Heritage: not archived

Found in: the text, “Harmonization and processing of the dMRI data”

Holds: README, license file, environment (requirements.txt, requirements_dev.txt, setup.py), tests, continuous integration, documentation

Not found: CITATION.cff

Tools: NumPy (46 files), SciPy (7 files), pandas (6 files), Matplotlib (2 files), NiBabel (2 files), scikit-learn (1 file), statsmodels (1 file)

Availability: 1 check, the latest on 29 September 2026: the link answers

29 September 2026: the link answers

129 files

bin/__init__.py, Python, 1 line
bin/harden_transform_with_slicer.py, Python, 91 lines
bin/tests/__init__.py, Python, 1 line
bin/tests/test_harden_transform_with_slicer.py, Python, 6 lines
bin/tests/test_wm_append_clusters.py, Python, 6 lines
bin/tests/test_wm_append_clusters_to_anatomical_tracts.py, Python, 7 lines
bin/tests/test_wm_append_diffusion_measures_across_subjects.py, Python, 7 lines
bin/tests/test_wm_assess_cluster_location_by_hemisphere.py, Python, 7 lines
bin/tests/test_wm_average_tract_measures.py, Python, 6 lines
bin/tests/test_wm_change_nrrd_dir.py, Python, 6 lines
bin/tests/test_wm_cluster_from_atlas.py, Python, 24 lines
bin/tests/test_wm_cluster_remove_outliers.py, Python, 19 lines
bin/tests/test_wm_cluster_volumetric_measurements.py, Python, 6 lines
bin/tests/test_wm_compare_vtks.py, Python, 6 lines
bin/tests/test_wm_create_mrml_file.py, Python, 6 lines
bin/tests/test_wm_diffusion_measurements.py, Python, 6 lines
bin/tests/test_wm_download_anatomically_curated_atlas.py, Python, 7 lines
bin/tests/test_wm_harden_transform.py, Python, 6 lines
bin/tests/test_wm_preprocess_all.py, Python, 6 lines
bin/tests/test_wm_quality_control_after_clustering.py, Python, 6 lines
bin/tests/test_wm_quality_control_cluster_measurements.py, Python, 7 lines
bin/tests/test_wm_quality_control_tract_overlap.py, Python, 6 lines
bin/tests/test_wm_quality_control_tractography.py, Python, 16 lines
bin/tests/test_wm_register_multisubject_faster.py, Python, 6 lines
bin/tests/test_wm_register_to_atlas_new.py, Python, 25 lines
bin/tests/test_wm_remove_data_along_tracts.py, Python, 6 lines
bin/tests/test_wm_separate_clusters_by_hemisphere.py, Python, 17 lines
bin/tests/test_wm_tract_to_volume.py, Python, 6 lines
bin/tests/test_wm_vtp2vtk.py, Python, 6 lines
bin/wm_append_clusters.py, Python, 130 lines
bin/wm_append_clusters_to_anatomical_tracts.py, Python, 224 lines
bin/wm_append_diffusion_measures_across_subjects.py, Python, 187 lines
bin/wm_apply_ORG_atlas_to_subject.sh, Shell, 537 lines
bin/wm_assess_cluster_location_by_hemisphere.py, Python, 323 lines
bin/wm_average_tract_measures.py, Python, 134 lines
bin/wm_change_nrrd_dir.py, Python, 84 lines
bin/wm_cluster_atlas.py, Python, 680 lines
bin/wm_cluster_from_atlas.py, Python, 308 lines
bin/wm_cluster_remove_outliers.py, Python, 272 lines
bin/wm_cluster_volumetric_measurements.py, Python, 193 lines
bin/wm_compare_vtks.py, Python, 87 lines
bin/wm_create_mrml_file.py, Python, 69 lines
bin/wm_diffusion_measurements.py, Python, 68 lines
bin/wm_download_anatomically_curated_atlas.py, Python, 229 lines
bin/wm_harden_transform.py, Python, 148 lines
bin/wm_preprocess_all.py, Python, 194 lines
bin/wm_quality_control_after_clustering.py, Python, 127 lines
bin/wm_quality_control_cluster_measurements.py, Python, 159 lines
bin/wm_quality_control_tract_overlap.py, Python, 113 lines
bin/wm_quality_control_tractography.py, Python, 369 lines
bin/wm_register_multisubject_faster.py, Python, 512 lines
bin/wm_register_to_atlas_new.py, Python, 375 lines
bin/wm_remove_data_along_tracts.py, Python, 117 lines
bin/wm_separate_clusters_by_hemisphere.py, Python, 211 lines
bin/wm_tract_to_volume.py, Python, 161 lines
bin/wm_vtp2vtk.py, Python, 111 lines
docs/source/conf.py, Python, 102 lines
setup.py, Python, 59 lines
slicer/installWMA.sh, Shell, 16 lines
utilities/__init__.py, Python, 1 line
utilities/tests/__init__.py, Python, 1 line
utilities/tests/test_wm_assess_cluster_location.py, Python, 6 lines
utilities/tests/test_wm_compute_FA_from_DWIs.py, Python, 6 lines
utilities/tests/test_wm_compute_TAP.py, Python, 6 lines
utilities/tests/test_wm_compute_bundle_feature_population_math.py, Python, 7 lines
utilities/tests/test_wm_extract_cluster.py, Python, 6 lines
utilities/tests/test_wm_extract_clusters_by_endpoints.py, Python, 6 lines
utilities/tests/test_wm_fix_UKF_trace.py, Python, 6 lines
utilities/tests/test_wm_fix_hemisphere_loc_name_in_tractogram.py, Python, 7 lines
utilities/tests/test_wm_flatten_length_distribution.py, Python, 6 lines
utilities/tests/test_wm_laterality_all.py, Python, 6 lines
utilities/tests/test_wm_measure_all_clusters.py, Python, 6 lines
utilities/tests/test_wm_measure_endpoint_overlap.py, Python, 6 lines
utilities/tests/test_wm_query_atlas_bundle_names.py, Python, 6 lines
utilities/tests/test_wm_statistics.py, Python, 6 lines
utilities/tests/test_wm_statistics_export_data.py, Python, 6 lines
utilities/tests/test_wm_transform_polydata.py, Python, 6 lines
utilities/wm_assess_cluster_location.py, Python, 160 lines
utilities/wm_compute_FA_from_DWIs.py, Python, 78 lines
utilities/wm_compute_TAP.py, Python, 116 lines
utilities/wm_compute_bundle_feature_population_math.py, Python, 228 lines
utilities/wm_extract_cluster.py, Python, 82 lines
utilities/wm_extract_clusters_by_endpoints.py, Python, 202 lines
utilities/wm_fix_UKF_trace.py, Python, 96 lines
utilities/wm_fix_hemisphere_loc_name_in_tractogram.py, Python, 91 lines
utilities/wm_flatten_length_distribution.py, Python, 154 lines
utilities/wm_laterality_all.py, Python, 199 lines
utilities/wm_measure_all_clusters.py, Python, 121 lines
utilities/wm_measure_endpoint_overlap.py, Python, 129 lines
utilities/wm_query_atlas_bundles_names.py, Python, 65 lines
utilities/wm_statistics.py, Python, 410 lines
utilities/wm_statistics_export_data.py, Python, 122 lines
utilities/wm_transform_polydata.py, Python, 141 lines
whitematteranalysis/__init__.py, Python, 6 lines
whitematteranalysis/anatomy/__init__.py, Python, 1 line
whitematteranalysis/anatomy/org_atlas_utils.py, Python, 174 lines
whitematteranalysis/anatomy/tests/__init__.py, Python, 1 line
whitematteranalysis/anatomy/tests/test_org_atlas_utils.py, Python, 150 lines
whitematteranalysis/cluster.py, Python, 1,223 lines
whitematteranalysis/congeal_multisubject.py, Python, 525 lines
whitematteranalysis/congeal_to_atlas.py, Python, 214 lines
whitematteranalysis/data/__init__.py, Python, 1 line
whitematteranalysis/data/atlas/__init__.py, Python, 1 line
whitematteranalysis/data/atlas/tests/__init__.py, Python, 1 line
whitematteranalysis/data/atlas/tests/test_utils.py, Python, 15 lines
whitematteranalysis/data/atlas/utils.py, Python, 30 lines
whitematteranalysis/fibers.py, Python, 461 lines
whitematteranalysis/fileio/__init__.py, Python, 1 line
whitematteranalysis/fileio/utils.py, Python, 33 lines
whitematteranalysis/filter.py, Python, 1,180 lines
whitematteranalysis/io.py, Python, 768 lines
whitematteranalysis/laterality.py, Python, 252 lines
whitematteranalysis/mrml.py, Python, 139 lines
whitematteranalysis/register.py, Python, 205 lines
whitematteranalysis/register_two_subjects.py, Python, 502 lines
whitematteranalysis/register_two_subjects_nonrigid.py, Python, 355 lines
whitematteranalysis/register_two_subjects_nonrigid_bsplines.py, Python, 414 lines
whitematteranalysis/relative_distance.py, Python, 82 lines
whitematteranalysis/render.py, Python, 459 lines
whitematteranalysis/similarity.py, Python, 433 lines
whitematteranalysis/tract_measurement.py, Python, 191 lines
whitematteranalysis/utils/__init__.py, Python, 1 line
whitematteranalysis/utils/opt_pckg.py, Python, 87 lines
whitematteranalysis/utils/tests/__init__.py, Python, 1 line
whitematteranalysis/utils/tests/test_tripwire.py, Python, 26 lines
whitematteranalysis/utils/tripwire.py, Python, 55 lines
whitematteranalysis/utils/utils.py, Python, 8 lines
License.txt, License, 199 lines
README.md, Text, 82 lines

At the source: github.com/SlicerDMRI/whitematteranalysis

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
222 scripts, each with its path and the digest of its content;
2 matches between paragraphs of the paper and lines of the code (method lexical-v1);
neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data Availability Statement

A data use certificate has been signed between the authors and NIHM Data Archive. Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive Development (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children aged 9-10 and follow them over 10 years into early adulthood. The ABCD Study® is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at [https://abcdstudy.org/federal-partners.html](https:/abcdstudy.org/federal-partners.html). A listing of participating sites and a complete listing of the study investigators can be found at [https://abcdstudy.org/consortium\_members/](https:/abcdstudy.org/consortium_members). ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators.

Not applicable.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Recorded: type, language, journal, volume, issue, pages, dates, 16 authors, 4 keywords, 1 funder, 52 references.

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Bonke, E. M., Cetin-Karayumak, S., Zhang, F., Tripodis, Y., Seer, C., Frey, M., Betz, A. K., Rojczyk, P., Zekelman, L. R., Seitz-Holland, J., Pieper, S., Schulte-Koerne, G., Shenton, M. E., O’Donnell, L. J., Rathi, Y., & Koerte, I. K. (2026). The association between motor coordination, behavior, cognition and brain structure in children: an ABCD study. European child & adolescent psychiatry, 35(6), 1983-1995. https://doi.org/10.1007/s00787-025-02931-2

BibTeX

@article{bonke2026association, author = {Bonke, Elena M and Cetin-Karayumak, Suheyla and Zhang, Fan and Tripodis, Yorghos and Seer, Caroline and Frey, Michael and Betz, Anja K and Rojczyk, Philine and Zekelman, Leo R and Seitz-Holland, Johanna and Pieper, Steve and Schulte-Koerne, Gerd and Shenton, Martha E and O’Donnell, Lauren J and Rathi, Yogesh and Koerte, Inga K}, title = {{The association between motor coordination, behavior, cognition and brain structure in children: an ABCD study}}, journal = {European child \& adolescent psychiatry}, year = {2026}, month = apr, volume = {35}, number = {6}, pages = {1983--1995}, publisher = {Springer Science+Business Media}, issn = {1018-8827}, doi = {10.1007/s00787-025-02931-2}, url = {https://doi.org/10.1007/s00787-025-02931-2}, pmid = {41940926}, pmcid = {PMC13337589} }

RIS

TY - JOUR AU - Bonke, Elena M AU - Cetin-Karayumak, Suheyla AU - Zhang, Fan AU - Tripodis, Yorghos AU - Seer, Caroline AU - Frey, Michael AU - Betz, Anja K AU - Rojczyk, Philine AU - Zekelman, Leo R AU - Seitz-Holland, Johanna AU - Pieper, Steve AU - Schulte-Koerne, Gerd AU - Shenton, Martha E AU - O’Donnell, Lauren J AU - Rathi, Yogesh AU - Koerte, Inga K TI - The association between motor coordination, behavior, cognition and brain structure in children: an ABCD study T2 - European child & adolescent psychiatry J2 - Eur Child Adolesc Psychiatry PY - 2026 DA - 2026/04/06 VL - 35 IS - 6 SP - 1983 EP - 1995 SN - 1018-8827 PB - Springer Science+Business Media DO - 10.1007/s00787-025-02931-2 UR - https://doi.org/10.1007/s00787-025-02931-2 LA - en ER -

CSL-JSON

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