Neuroimaging of the Philadelphia Neurodevelopmental Cohort

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(1970) · Cited by 24,983

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FSL

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Federation of Brain Age Estimation in Structural Neuroimaging Data

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Transcriptome-wide association analysis of 211 neuroimaging traits identifies new genes for brain structures and yields insights into the gene-level pleiotropy with other complex traitsPreprint

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ImageNomer: developing an fMRI and omics visualization tool to detect racial bias in functional connectivityPreprint

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Unraveling the Link between CNVs, General Cognition, and Individual Neuroimaging Deviation Scores from a Reference CohortPreprint

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Fused estimation of sparse connectivity patterns from rest fMRI

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A protocol for working with open-source neuroimaging datasets

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LOCUS: A regularized blind source separation method with low-rank structure for investigating brain connectivity

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Transmit Radiant Individuality to Offspring (TRIO) study: investigating intergenerational transmission effects on brain development

Matsudaira, I. Y., Yamaguchi, R., & Taki, Y. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1150973 · Cited by 4

ImageNomer: Description of a functional connectivity and omics analysis tool and case study identifying a race confound

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Region Specific Automatic Quality Assurance For MRI-Derived Cortical Segmentations

Gadewar, S. P., Zhu, A. H., Thomopoulos, S. I., Li, Z., Gari, I. B., Maiti, P., Thompson, P. M., & Jahanshad, N. (2021) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi48211.2021.9433755 · Cited by 5

Use of Medical Imaging to Advance Mental Health Care: Contributions from Neuroimaging Informatics

Gollub, R. L., & Benson, N. M. (2021) · Health informatics · doi:10.1007/978-3-030-70558-9_8 · Cited by 4

Sex‐specific associations between traumatic experiences and resting‐state functional connectivity in the Philadelphia Neurodevelopmental Cohort

Wang, S., Malins, J. G., Zhang, H., & Gruen, J. R. (2021) · JCPP Advances · doi:10.1002/jcv2.12049 · Cited by 3

Phenotype guided interpretable graph convolutional network analysis of fMRI data reveals changing brain connectivity during adolescence

Orlichenko, A., Qu, G., & Wang, Y. (2022) · SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging · doi:10.1117/12.2613172 · Cited by 4

Functional connectivity strength and topology differences in social phobia adolescents with and without ADHD comorbidity

Kim, B., Niu, X., & Zhang, F. (2022) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2022.108418 · Cited by 6

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Working Memory

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The Impact of In-Scanner Head Motion on Structural Connectivity Derived from Diffusion Tensor ImagingPreprint

Baum, G. L., Roalf, D., Cook, P. A., Ciric, R., Rosen, A. F. G., Xia, C., Elliot, M., Ruparel, K., Verma, R., Tunç, B., et al. (2017) · bioRxiv · doi:10.1101/185397 · Cited by 6

A Hitchhiker’s Guide to Working with Large, Open-Source Neuroimaging DatasetsPreprint

Horien, C. L., Noble, S., Greene, A. S., Lee, K., Barron, D. S., Gao, S., O'Connor, D., Salehi, M., Dadashkarimi, J., Shen, X., et al. (2020) · Preprints.org · doi:10.20944/preprints202007.0153.v1 · Cited by 5

Accurate sex prediction of cisgender and transgender individuals without brain size biasPreprint

Wiersch, L., Hamdan, S., Hoffstaedter, F., Votinov, M., Habel, U., Clemens, B., Derntl, B., Eickhoff, S. B., Patil, K. R., & Weis, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.07.26.499576 · Cited by 4

WITHDRAWN: A systematic protocol to identify “clinical controls” for pediatric neuroimaging research from clinically acquired brain MRIsPreprint

Zimmerman, D., Mandal, A. S., Jung, B., Buczek, M. J., Schabdach, J., Karandikar, S., Kafadar, E., Mercedes, L., Kohler, S., Abdel-Qader, L., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.25.661530 · Cited by 4

Adolescent maturation of cortical excitation-inhibition balance based on individualized biophysical network modelingPreprint

Saberi, A., Wischnewski, K. J., Jung, K., Lotter, L. D., Schaare, H. L., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Desrivières, S., Flor, H., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.18.599509 · Cited by 4

Systematic protocol to identify ‘clinical controls’ for paediatric neuroimaging research from clinically acquired brain MRIs

Zimmerman, D., Mandal, A. S., Jung, B., Buczek, M. J., Schabdach, J., Karandikar, S., Kafadar, E., Gardner, M., Daniali, M., Mercedes, L., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2025-106428 · Cited by 8

White matter functional gradients and their formation in adolescence

Zhu, J., Margulies, D. S., & Qiu, A. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad319 · Cited by 4

Diverging Effects of Violence Exposure and Psychiatric Symptoms on Amygdala-Prefrontal Maturation During Childhood and Adolescence

Keding, T. J., Russell, J. D., Zhu, X., He, Q., Li, J. J., & Herringa, R. J. (2024) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2024.08.003 · Cited by 5

Activation of Internal Correctness Monitoring Circuitry in Youths With Psychosis Spectrum Symptoms

Levinson, T. G., Prettyman, G. E., Savage, C., White, L. K., Moore, T. M., Calkins, M. E., Ruparel, K., Gur, R. E., Gur, R. C., Satterthwaite, T. D., et al. (2023) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2023.01.010 · Cited by 4

Dorsal visual stream and LIMK1: hemideletion, haplotype, and enduring effects in children with Williams syndrome

Kippenhan, J. S., Gregory, M. D., Nash, T. A., Kohn, P. D., Mervis, C. Β., Eisenberg, D. P., Garvey, M. H., Roe, K. V., Morris, C. A., Kolachana, B. S., et al. (2023) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-023-09493-x · Cited by 3

Somatomotor-visual resting state functional connectivity increases after 2 years in the UK Biobank longitudinal cohort

Orlichenko, A., Su, K., Tian, Q., Shen, H., Deng, H.-W., & Wang, Y. (2024) · Journal of medical imaging · doi:10.1117/1.jmi.11.2.024010 · Cited by 3

Regression and alignment for functional data and network topology

Tu, D., Wrobel, J., Satterthwaite, T. D., Goldsmith, J., Gur, R. C., Gur, R. E., Gertheiss, J., Bassett, D. S., & Shinohara, R. T. (2024) · Biostatistics · doi:10.1093/biostatistics/kxae026 · Cited by 2

Presence, Severity, and Functional Associations of Incomplete Hippocampal Inversion in 22q11.2 Deletion Syndrome

Roalf, D. R., Atkins, A., Czernuszenko, A., Pecsok, M. K., McDonald‐McGinn, D. M., Schmitt, J. E., Roeske, M. J., Hopkins, S. E., Freedman, P., Alexander‐Bloch, A. F., et al. (2025) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2025.04.009 · Cited by 3

Discovering Synchronized Subsets of Sequences: A Large Scale Solution

Sarıyanidi, E., Zampella, C., Bartley, K. G., Herrington, J. D., Satterthwaite, T. D., Schultz, R. T., & Tunç, B. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00951 · Cited by 3

Understanding How Learning Takes Place with Neuroscience and Applying the Results to Education

Ioannides, A. A. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67615-9_2 · Cited by 4

What the Journal of the American Academy of Child and Adolescent Psychiatry Is Looking for in Neuroimaging Submissions

White, T. J. H., Frazier, J. A., Althoff, R. R., & Novins, D. K. (2020) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2020.12.001 · Cited by 3

Large-scale neuroimaging and genetic study reveals genetic architecture of brain white matter microstructurePreprint

Zhao, B., Zhang, J., Ibrahim, J. G., Santelli, R., Li, Y., Li, T., Shan, Y., Zhu, Z., Zhou, F., Liao, H., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/288555 · Cited by 3

Genetic variation in CSMD1 affects amygdala connectivity and prosocial behaviorPreprint

Bickart, K. C., Napolioni, V., Khan, R. R., Kim, Y., Altmann, A., Richiardi, J., Newsom, M. R., Sadaghiani, S., Banaschewski, T., Bokde, A. L. W., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.27.315622 · Cited by 3

Mapping Complex Brain Torque Components and Their Genetic and Phenomic Architecture in 24,112 healthy individualsPreprint

Zhao, L., Matloff, W., Shi, Y.-G., Cabeen, R. P., & Toga, A. (2021) · bioRxiv · doi:10.1101/2021.03.09.434625 · Cited by 5

Compression supports low-dimensional representations of behavior across neural circuitsPreprint

Zhou, D., Kim, J. Z., Pines, A. R., Sydnor, V. J., Roalf, D. R., Detre, J. A., Gur, R. C., Gur, R. E., Satterthwaite, T. D., & Bassett, D. S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.29.518415 · Cited by 5

In-vivo whole-cortex estimation of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youthPreprint

Zhang, S., Larsen, B., Sydnor, V. J., Zeng, T., An, L., Yan, X., Kong, R., Kong, X., Gur, R. C., Gur, R. E., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.22.546023 · Cited by 3

Identifiability in Functional Connectivity May Unintentionally Inflate Prediction ResultsPreprint

Orlichenko, A., Qu, G., Su, K., Liu, A., Shen, H., Deng, H., & Wang, Y. (2023) · medRxiv · doi:10.1101/2023.08.02.23293565 · Cited by 3

Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain

Lan, Y., Qiao, C., Kanamori, T., Calhoun, V. D., Stephen, J. M., Wilson, T. W., & Wang, Y. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.106974 · Cited by 2

Big Data, Small Bias: Harmonizing Diffusion MRI ‐Based Structural Connectomes to Mitigate Site‐Related Bias in Data Integration

Shen, R. S., Parker, D., Chen, A. A., Yerys, B. E., Tunç, B., Roberts, T. P. L., Shinohara, R. T., & Verma, R. (2025) · Human Brain Mapping · doi:10.1002/hbm.70256 · Cited by 2

The Philadelphia Neurodevelopmental Cohort: A publicly available resource for the study of normal and abnormal brain development in youth

Satterthwaite, T. D., Connolly, J. J., Ruparel, K., Calkins, M. E., Jackson, C., Elliott, M. A., Roalf, D. R., Hopson, R., Prabhakaran, K., Behr, M., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.056 · Cited by 335

Sex differences in brain and behavior in adolescence: Findings from the Philadelphia Neurodevelopmental Cohort

Gur, R. E., & Gur, R. C. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.07.035 · Cited by 211

A longitudinal data resource to study brain development and transdiagnostic variation in executive function

Sevchik, B. L., Shafiei, G., Murtha, K., Linguiti, S., Brodrick, L., Brook, J. B. H., Cieslak, M., Flook, E. A., Mehta, K. P., Meisler, S. L., et al. (2026) · Scientific Data · doi:10.1038/s41597-026-08095-1 · Cited by 2

DLPFC: The Decade circLe CCNP Family Cohort

Zhang, Z., & Yang, N. (2025) · Neuropsychopharmacology · doi:10.1038/s41386-025-02131-1 · Cited by 1

The pediatric template of brain perfusion

Avants, B., Duda, J., Kilroy, E., Krasileva, K. E., Jann, K., Kandel, B. M., Tustison, N. J., Yan, L., Jog, M., Smith, R. X., et al. (2015) · Scientific Data · doi:10.1038/sdata.2015.3 · Cited by 60