References
Leon D. Lotter and Jürgen Dukart. NiSpace: neuroimaging spatial colocalization environment. 2024. doi:10.5281/zenodo.12514622.
Jürgen Dukart and others. JuSpace: a tool for spatial correlation analyses of magnetic resonance imaging data with nuclear imaging derived neurotransmitter maps. Human Brain Mapping, 2021. doi:10.1002/hbm.25244.
Ross D. Markello and others. Neuromaps: structural and functional interpretation of brain maps. Nature Methods, 2022. doi:10.1038/s41592-022-01625-w.
Leon D. Lotter and others. Revealing the neurobiology underlying interpersonal neural synchronization with multimodal data fusion. Neuroscience & Biobehavioral Reviews, 2023. doi:10.1016/j.neubiorev.2023.105042.
Leon D. Lotter and others. Regional patterns of human cortex development correlate with underlying neurobiology. Nature Communications, 2024. doi:10.1038/s41467-024-52366-7.
Leon D. Lotter and others. Temporal dissociation between local and global functional adaptations of the maternal brain to childbirth: a longitudinal assessment. Neuropsychopharmacology, 2024. doi:10.1038/s41386-024-01880-9.
Leon D. Lotter and others. Linking human brain functional connectivity to underlying neurotransmission. bioRxiv, 2026. doi:10.64898/2026.04.28.721294.
H. H. Wagner and S. Dray. Generating spatially constrained null models for irregularly spaced data using Moran spectral randomization methods. Methods in Ecology and Evolution, 2015. doi:10.1111/2041-210X.12407.
R. Vos de Wael and others. BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets. Communications Biology, 2020. doi:10.1038/s42003-020-0794-7.
Joshua B. Burt and others. Generative modeling of brain maps with spatial autocorrelation. NeuroImage, 2020. doi:10.1016/j.neuroimage.2020.117038.
Joshua B. Burt and others. Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography. Nature Neuroscience, 2018. doi:10.1038/s41593-018-0195-0.
Eli J. Cornblath and others. Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands. Communications Biology, 2020. doi:10.1038/s42003-020-0961-x.
Graham L. Baum and others. Development of structure–function coupling in human brain networks during youth. Proceedings of the National Academy of Sciences, 2020. doi:10.1073/pnas.1912034117.
Aaron F. Alexander-Bloch and others. On testing for spatial correspondence between maps of human brain structure and function. NeuroImage, 2018. doi:10.1016/j.neuroimage.2018.05.070.
František Váša and others. Adolescent tuning of association cortex in human structural brain networks. Cerebral Cortex, 2018. doi:10.1093/cercor/bhx249.
Harold W. Kuhn. The Hungarian method for the assignment problem. Naval Research Logistics Quarterly, 1955. doi:10.1002/nav.3800020109.
Juan Eugenio Iglesias. A ready-to-use machine learning tool for symmetric multi-modality registration of brain MRI. Scientific Reports, 2023. doi:10.1038/s41598-023-33781-0.
Malte Hoffmann and others. SynthMorph: learning contrast-invariant registration without acquired images. IEEE Transactions on Medical Imaging, 2022. doi:10.1109/TMI.2021.3116879.
Benjamin Billot and others. SynthSeg: segmentation of brain MRI scans of any contrast and resolution without retraining. Medical Image Analysis, 2023. doi:10.1016/j.media.2023.102789.
Jean-Philippe Fortin and others. Harmonization of cortical thickness measurements across scanners and sites. NeuroImage, 2017. doi:10.1016/j.neuroimage.2017.11.024.
Raymond Pomponio and others. Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. NeuroImage, 2019. doi:10.1016/j.neuroimage.2019.116450.
Yezhou Feng and others. Longitudinal development of the human white matter structural connectome and its association with brain transcriptomic and epigenomic landscapes. Communications Biology, 2023. doi:10.1038/s42003-023-05647-8.
Charles R. Harris and others. Array programming with NumPy. Nature, 2020. doi:10.1038/s41586-020-2649-2.
Wes McKinney. Data structures for statistical computing in Python. In Proceedings of the 9th Python in Science Conference. 2010. doi:10.25080/Majora-92bf1922-00a.
Pauli Virtanen and others. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 2020. doi:10.1038/s41592-019-0686-2.
Skipper Seabold and Josef Perktold. Statsmodels: econometric and statistical modeling with Python. In Proceedings of the 9th Python in Science Conference. 2010. doi:10.25080/majora-92bf1922-011.
Matthew Brett and others. NiBabel: access a cacophony of neuro-imaging file formats. 2020. doi:10.5281/zenodo.591597.
Alexandre Abraham and others. Machine learning for neuroimaging with scikit-learn. Frontiers in Neuroinformatics, 2014. doi:10.3389/fninf.2014.00014.
John D. Hunter. Matplotlib: a 2D graphics environment. Computing in Science & Engineering, 2007. doi:10.1109/MCSE.2007.55.
Michael L. Waskom. Seaborn: statistical data visualization. Journal of Open Source Software, 2021. doi:10.21105/joss.03021.
Peter H. Westfall and S. Stanley Young. Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment. Wiley, 1993.
N. W. Galwey. A new measure of the effective number of tests, a practical tool for comparing families of non-independent significance tests. Genetic Epidemiology, 2009. doi:10.1002/gepi.20408.
Jun Li and Libo Ji. Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix. Heredity, 2005. doi:10.1038/sj.hdy.6800717.
Yoav Benjamini and Yosef Hochberg. Controlling the False Discovery Rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 1995. doi:10.1111/j.2517-6161.1995.tb02031.x.
Steven M. Weinstein and others. A simple permutation-based test of intermodal correspondence. Human Brain Mapping, 2021. doi:10.1002/hbm.25577.
Joshua Faskowitz and others. Spatial maps of similarity across the cortex. 2026. OHBM 2026 Annual Meeting, Abstract #0342. doi:10.5281/zenodo.20817055.
Razia Azen and David V. Budescu. The dominance analysis approach for comparing predictors in multiple regression. Psychological Methods, 2003. doi:10.1037/1082-989X.8.2.129.
Sijmen de Jong. SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 1993. doi:10.1016/0169-7439(93)85002-X.
Jacob Cohen. Statistical Power Analysis for the Behavioral Sciences. Routledge, 2nd edition, 1988.
Larry V. Hedges and Ingram Olkin. Statistical Methods for Meta-Analysis. Academic Press, 1985.
Ben D. Fulcher and others. Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data. Nature Communications, 2021. doi:10.1038/s41467-021-22862-1.
R. Dennis Cook and Sanford Weisberg. Residuals and Influence in Regression. Chapman and Hall, 1982.
David A. Belsley, Edwin Kuh, and Roy E. Welsch. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. Wiley, 1980.
Ross D. Markello and others. Standardizing workflows in imaging transcriptomics with the abagen toolbox. eLife, 2021. doi:10.7554/eLife.72129.
Michael J. Hawrylycz and others. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature, 2012. doi:10.1038/nature11405.
Konrad Wagstyl and others. Transcriptional cartography integrates multiscale biology of the human cortex. eLife, 2024. doi:10.7554/eLife.86933.2.
Malte Hoffmann and others. Anatomy-aware and acquisition-agnostic joint registration with SynthMorph. Imaging Neuroscience, 2024. doi:10.1162/imag_a_00197.
Justine Y. Hansen and others. Mapping neurotransmitter systems to the structural and functional organization of the human neocortex. Nature Neuroscience, 2022. doi:10.1038/s41593-022-01186-3.
Yongbin Wei and others. Statistical testing in transcriptomic-neuroimaging studies: a how-to and evaluation of methods assessing spatial and gene specificity. Human Brain Mapping, 2022. doi:10.1002/hbm.25711.