Video-evoked fMRI BOLD responses are highly consistent across different data acquisition sites
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Daniel P. Kennedy | R. Adolphs | Ye He | J. Tyszka | Lisa Byrge | Hu Cheng | Dorit Kliemann | Hu Cheng | H. Cheng
[1] H. Saarimäki. Naturalistic Stimuli in Affective Neuroimaging: A Review , 2021, Frontiers in Human Neuroscience.
[2] Annchen R. Knodt,et al. Striving toward translation: strategies for reliable fMRI measurement , 2021, Trends in Cognitive Sciences.
[3] U. Hasson,et al. The default mode network: where the idiosyncratic self meets the shared social world , 2021, Nature Reviews Neuroscience.
[4] Yang Hu,et al. Individualized psychiatric imaging based on inter-subject neural synchronization in movie watching , 2020, NeuroImage.
[5] M. Milham,et al. Towards clinical applications of movie fMRI , 2020, NeuroImage.
[6] Luca Turella,et al. Variability in the analysis of a single neuroimaging dataset by many teams , 2019, Nature.
[7] Michael Breakspear,et al. Naturalistic Stimuli in Neuroscience: Critically Acclaimed , 2019, Trends in Cognitive Sciences.
[8] Fiona L. Weathersby,et al. Generalizability and reproducibility of functional connectivity in autism , 2019, Molecular Autism.
[9] Lisa Byrge,et al. Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies , 2019, bioRxiv.
[10] Jonathan D. Power,et al. Distinctions among real and apparent respiratory motions in human fMRI data , 2019, NeuroImage.
[11] Samuel A. Nastase,et al. Measuring shared responses across subjects using intersubject correlation , 2019, bioRxiv.
[12] Russell A. Poldrack,et al. Editorial: Reliability and Reproducibility in Functional Connectomics , 2019, Front. Neurosci..
[13] Monica D. Rosenberg,et al. Relationships between depressive symptoms and brain responses during emotional movie viewing emerge in adolescence , 2019, NeuroImage.
[14] Luke J. Chang,et al. Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience , 2018, Science Advances.
[15] Lisa D. Nickerson,et al. Replication of Resting State-Task Network Correspondence and Novel Findings on Brain Network Activation During Task fMRI in the Human Connectome Project Study , 2018, Scientific Reports.
[16] F. Castellanos,et al. Movies in the magnet: Naturalistic paradigms in developmental functional neuroimaging , 2018, Developmental Cognitive Neuroscience.
[17] Saori C. Tanaka,et al. Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias , 2018, bioRxiv.
[18] Danielle S Bassett,et al. Mitigating head motion artifact in functional connectivity MRI , 2018, Nature Protocols.
[19] M. Weissman,et al. Statistical harmonization corrects site effects in functional connectivity measurements from multi‐site fMRI data , 2018, Human brain mapping.
[20] P. Bandettini,et al. Trait paranoia shapes inter-subject synchrony in brain activity during an ambiguous social narrative , 2018, Nature Communications.
[21] Lisa Byrge,et al. Accurate prediction of individual subject identity and task, but not autism diagnosis, from functional connectomes , 2018, Human brain mapping.
[22] Satrajit S. Ghosh,et al. FMRIPrep: a robust preprocessing pipeline for functional MRI , 2018, Nature Methods.
[23] R. Saxe,et al. Development of the social brain from age three to twelve years , 2018, Nature Communications.
[24] A. Holmes,et al. The Myth of Optimality in Clinical Neuroscience , 2018, Trends in Cognitive Sciences.
[25] Annchen R. Knodt,et al. The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences , 2017, Behavior research methods.
[26] Vincent Frouin,et al. The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders , 2017, Molecular Autism.
[27] Evan M. Gordon,et al. Local-Global Parcellation of the Human Cerebral Cortex From Intrinsic Functional Connectivity MRI , 2017, bioRxiv.
[28] Daniel P. Kennedy,et al. Enhancing studies of the connectome in autism using the autism brain imaging data exchange II , 2017, Scientific Data.
[29] Theo G. M. van Erp,et al. Multisite reliability of MR-based functional connectivity , 2017, NeuroImage.
[30] R. Cox,et al. Untangling the relatedness among correlations, part I: Nonparametric approaches to inter-subject correlation analysis at the group level , 2016, NeuroImage.
[31] Timothy O. Laumann,et al. Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project , 2016, Brain Connect..
[32] Thomas E. Nichols,et al. Best Practices in Data Analysis and Sharing in Neuroimaging using MRI , 2016, bioRxiv.
[33] Thomas E. Nichols,et al. Scanning the horizon: towards transparent and reproducible neuroimaging research , 2016, Nature Reviews Neuroscience.
[34] Hans Knutsson,et al. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates , 2016, Proceedings of the National Academy of Sciences.
[35] R. Adolphs,et al. Building a Science of Individual Differences from fMRI , 2016, Trends in Cognitive Sciences.
[36] Peter Szolovits,et al. MIMIC-III, a freely accessible critical care database , 2016, Scientific Data.
[37] Krzysztof J. Gorgolewski,et al. MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites , 2016, bioRxiv.
[38] Tapani Ristaniemi,et al. The reliability of continuous brain responses during naturalistic listening to music , 2016, NeuroImage.
[39] Daniel P. Kennedy,et al. A specific hypoactivation of right temporo-parietal junction/posterior superior temporal sulcus in response to socially awkward situations in autism. , 2015, Social cognitive and affective neuroscience.
[40] Christine C. Guo,et al. Out-of-sync: disrupted neural activity in emotional circuitry during film viewing in melancholic depression , 2015, Scientific Reports.
[41] Ludovica Griffanti,et al. Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers , 2014, NeuroImage.
[42] M. Sams,et al. The brains of high functioning autistic individuals do not synchronize with those of others☆ , 2013, NeuroImage: Clinical.
[43] K. Amunts,et al. Individual variability is not noise , 2013, Trends in Cognitive Sciences.
[44] Matthew J. McAuliffe,et al. Sharing Heterogeneous Data: The National Database for Autism Research , 2012, Neuroinformatics.
[45] Noah D. Brenowitz,et al. Whole-brain, time-locked activation with simple tasks revealed using massive averaging and model-free analysis , 2012, Proceedings of the National Academy of Sciences.
[46] D. Heeger,et al. Reliability of cortical activity during natural stimulation , 2010, Trends in Cognitive Sciences.
[47] Uri Hasson,et al. Shared and idiosyncratic cortical activation patterns in autism revealed under continuous real‐life viewing conditions , 2009, Autism research : official journal of the International Society for Autism Research.
[48] J. Ruscio,et al. A probability-based measure of effect size: robustness to base rates and other factors. , 2008, Psychological methods.
[49] Brian B. Avants,et al. Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..
[50] Gary H. Glover,et al. Reducing interscanner variability of activation in a multicenter fMRI study: Controlling for signal-to-fluctuation-noise-ratio (SFNR) differences , 2006, NeuroImage.
[51] J. Ioannidis,et al. Why Most Published Research Findings Are False , 2005, PLoS medicine.
[52] R. Malach,et al. Intersubject Synchronization of Cortical Activity During Natural Vision , 2004, Science.
[53] A. Vargha,et al. A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong , 2000 .
[54] K. Schmidt,et al. Symmetric Gibbs measures , 1996, math/9604240.
[55] L. Varga. Bootstrap methods and their applications , 2022 .
[56] H. Richardson. Edinburgh Research Explorer Development of brain networks for social functions , 2022 .