A collaborative resource platform for non-human primate neuroimaging

[1]  Afonso C. Silva,et al.  Marmoset Brain Mapping V3: Population multi-modal standard volumetric and surface-based templates , 2020, NeuroImage.

[2]  Krzysztof J. Gorgolewski,et al.  Sharing voxelwise neuroimaging results from rhesus monkeys and other species with Neurovault , 2020, NeuroImage.

[3]  Paul A. Taylor,et al.  A comprehensive macaque fMRI pipeline and hierarchical atlas , 2020, NeuroImage.

[4]  Alan C. Evans,et al.  CIVET-Macaque: An automated pipeline for MRI-based cortical surface generation and cortical thickness in macaques , 2020, NeuroImage.

[5]  Stamatios N. Sotiropoulos,et al.  XTRACT - Standardised protocols for automated tractography in the human and macaque brain , 2020, NeuroImage.

[6]  Mark Jenkinson,et al.  Cross-species cortical alignment identifies different types of anatomical reorganization in the primate temporal lobe , 2020, eLife.

[7]  Partha P. Mitra,et al.  Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey , 2020, Nature Communications.

[8]  Nikoloz Sirmpilatze,et al.  RheMAP: Non-linear warps between common rhesus macaque brain templates , 2020 .

[9]  Ravi S. Menon,et al.  Accelerating the Evolution of Nonhuman Primate Neuroimaging , 2020, Neuron.

[10]  Rogier B. Mars,et al.  A comprehensive atlas of white matter tracts in the chimpanzee , 2020, bioRxiv.

[11]  David A. Leopold,et al.  A resource for detailed 3D mapping of white matter pathways in the marmoset brain , 2019, Nature Neuroscience.

[12]  Antoine Grigis,et al.  Pypreclin: An automatic pipeline for macaque functional MRI preprocessing , 2019, NeuroImage.

[13]  Bradley C. Love,et al.  Variability in the analysis of a single neuroimaging dataset by many teams , 2019, Nature.

[14]  Hideyuki Okano,et al.  atlasBREX: Automated template-derived brain extraction in animal MRI , 2019, Scientific Reports.

[15]  Ninon Burgos,et al.  New advances in the Clinica software platform for clinical neuroimaging studies , 2019 .

[16]  Carlo Pierpaoli,et al.  Evaluating corrections for Eddy‐currents and other EPI distortions in diffusion MRI: methodology and a dataset for benchmarking , 2018, Magnetic resonance in medicine.

[17]  Saad Jbabdi,et al.  Connectivity Fingerprints: From Areal Descriptions to Abstract Spaces , 2018, Trends in Cognitive Sciences.

[18]  Daniel S. Margulies,et al.  An Open Resource for Non-human Primate Imaging , 2018, Neuron.

[19]  Carlo Pierpaoli,et al.  Detection and Distinction of Mild Brain Injury Effects in a Ferret Model Using Diffusion Tensor MRI (DTI) and DTI-Driven Tensor-Based Morphometry (D-TBM) , 2018, Front. Neurosci..

[20]  Piotr Majka,et al.  Neuronal distribution across the cerebral cortex of the marmoset monkey (Callithrix jacchus) , 2018, bioRxiv.

[21]  Roberto Toro,et al.  Evolution of neocortical folding: A phylogenetic comparative analysis of MRI from 34 primate species , 2018, Cortex.

[22]  Satrajit S. Ghosh,et al.  FMRIPrep: a robust preprocessing pipeline for functional MRI , 2018, Nature Methods.

[23]  David A. Leopold,et al.  A digital 3D atlas of the marmoset brain based on multi-modal MRI , 2018, NeuroImage.

[24]  R. Passingham,et al.  Whole brain comparative anatomy using connectivity blueprints , 2018, bioRxiv.

[25]  Jean-Francois Mangin,et al.  Primatologist: A modular segmentation pipeline for macaque brain morphometry , 2017, NeuroImage.

[26]  Tomas Knapen,et al.  Porcupine: A visual pipeline tool for neuroimaging analysis , 2017, bioRxiv.

[27]  Ludovica Griffanti,et al.  Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank , 2017, NeuroImage.

[28]  David A. Leopold,et al.  A population MRI brain template and analysis tools for the macaque , 2017, NeuroImage.

[29]  Russell A. Poldrack,et al.  OpenfMRI: Open sharing of task fMRI data , 2017, NeuroImage.

[30]  S. Turner,et al.  RNA sequencing analysis of the developing chicken retina , 2016, Scientific Data.

[31]  Jan Sijbers,et al.  Denoising of diffusion MRI using random matrix theory , 2016, NeuroImage.

[32]  A. Gruslys,et al.  Three-Dimensional Digital Template Atlas of the Macaque Brain , 2016, Cerebral cortex.

[33]  Muhammad G. Saleh,et al.  Assessing the performance of different DTI motion correction strategies in the presence of EPI distortion correction , 2016, Human brain mapping.

[34]  Chad J. Donahue,et al.  Using Diffusion Tractography to Predict Cortical Connection Strength and Distance: A Quantitative Comparison with Tracers in the Monkey , 2016, The Journal of Neuroscience.

[35]  Satrajit S. Ghosh,et al.  The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments , 2016, Scientific Data.

[36]  Piotr Majka,et al.  Towards a comprehensive atlas of cortical connections in a primate brain: Mapping tracer injection studies of the common marmoset into a reference digital template , 2016, The Journal of comparative neurology.

[37]  C. Pierpaoli,et al.  DR-TAMAS: Diffeomorphic Registration for Tensor Accurate Alignment of Anatomical Structures , 2016, NeuroImage.

[38]  Krzysztof J. Gorgolewski,et al.  MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites , 2016, bioRxiv.

[39]  Sean L. Hill,et al.  Brainhack: a collaborative workshop for the open neuroscience community , 2016, GigaScience.

[40]  Shoaib Sufi,et al.  Toward standard practices for sharing computer code and programs in neuroscience , 2016, Nature Neuroscience.

[41]  Erik Schultes,et al.  The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.

[42]  Paul A. Taylor,et al.  Open Environment for Multimodal Interactive Connectivity Visualization and Analysis , 2016, Brain Connect..

[43]  Matthew F.S. Rushworth,et al.  Comparing brains by matching connectivity profiles , 2016, Neuroscience & Biobehavioral Reviews.

[44]  Stamatios N. Sotiropoulos,et al.  An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging , 2016, NeuroImage.

[45]  David N. Kennedy,et al.  The NITRC image repository , 2016, NeuroImage.

[46]  Jack L. Gallant,et al.  Pycortex: an interactive surface visualizer for fMRI , 2015, Front. Neuroinform..

[47]  David N. Kennedy,et al.  The Resource Identification Initiative: A cultural shift in publishing , 2015, Neuroinformatics.

[48]  Carlo Pierpaoli,et al.  DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions , 2015, NeuroImage.

[49]  Jean-Philippe Thiran,et al.  Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data , 2015, NeuroImage.

[50]  Jan Sijbers,et al.  Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data , 2014, NeuroImage.

[51]  Daniel S. Margulies,et al.  NeuroVault.org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain , 2014, bioRxiv.

[52]  Maxime Descoteaux,et al.  Dipy, a library for the analysis of diffusion MRI data , 2014, Front. Neuroinform..

[53]  Paul A. Taylor,et al.  FATCAT: (An Efficient) Functional And Tractographic Connectivity Analysis Toolbox , 2013, Brain Connect..

[54]  Mark Jenkinson,et al.  The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.

[55]  Daniel P. Kennedy,et al.  The Autism Brain Imaging Data Exchange: Towards Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism , 2013, Molecular Psychiatry.

[56]  Oluwasanmi Koyejo,et al.  Toward open sharing of task-based fMRI data: the OpenfMRI project , 2013, Front. Neuroinform..

[57]  Keith Heberlein,et al.  Imaging human connectomes at the macroscale , 2013, Nature Methods.

[58]  Torsten Rohlfing,et al.  The INIA19 Template and NeuroMaps Atlas for Primate Brain Image Parcellation and Spatial Normalization , 2012, Front. Neuroinform..

[59]  Bharat B. Biswal,et al.  Improving DTI Tractography by including Diagonal Tract Propagation , 2012, PloS one.

[60]  Bruce Fischl,et al.  FreeSurfer , 2012, NeuroImage.

[61]  Daniel C. Alexander,et al.  NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain , 2012, NeuroImage.

[62]  Russell Greiner,et al.  ADHD-200 Global Competition: diagnosing ADHD using personal characteristic data can outperform resting state fMRI measurements , 2012, Front. Syst. Neurosci..

[63]  Alan Connelly,et al.  MRtrix: Diffusion tractography in crossing fiber regions , 2012, Int. J. Imaging Syst. Technol..

[64]  M. Corbetta,et al.  Inter-species activity correlations reveal functional correspondences between monkey and human brain areas , 2012, Nature Methods.

[65]  J. Rilling,et al.  Continuity, Divergence, and the Evolution of Brain Language Pathways , 2011, Front. Evol. Neurosci..

[66]  Satrajit S. Ghosh,et al.  Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python , 2011, Front. Neuroinform..

[67]  M. Mallar Chakravarty,et al.  An MRI based average macaque monkey stereotaxic atlas and space (MNI monkey space) , 2011, NeuroImage.

[68]  M. Perrot,et al.  Diffeomorphic Brain Registration Under Exhaustive Sulcal Constraints , 2011, IEEE Transactions on Medical Imaging.

[69]  D. Louis Collins,et al.  Unbiased average age-appropriate atlases for pediatric studies , 2011, NeuroImage.

[70]  Brian B. Avants,et al.  N4ITK: Improved N3 Bias Correction , 2010, IEEE Transactions on Medical Imaging.

[71]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[72]  David N. Kennedy,et al.  Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) Resource Announcement , 2009, Neuroinformatics.

[73]  Brian B. Avants,et al.  Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain , 2008, Medical Image Anal..

[74]  Mark W. Woolrich,et al.  Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? , 2007, NeuroImage.

[75]  J. Helpern,et al.  Diffusional kurtosis imaging: The quantification of non‐gaussian water diffusion by means of magnetic resonance imaging , 2005, Magnetic resonance in medicine.

[76]  Mark W. Woolrich,et al.  Constrained linear basis sets for HRF modelling using Variational Bayes , 2004, NeuroImage.

[77]  Nikos K Logothetis,et al.  Interpreting the BOLD signal. , 2004, Annual review of physiology.

[78]  Stefan Skare,et al.  How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging , 2003, NeuroImage.

[79]  N. Logothetis.  The Underpinnings of the BOLD Functional Magnetic Resonance Imaging Signal , 2003, The Journal of Neuroscience.

[80]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[81]  Stephen M. Smith,et al.  Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data , 2001, NeuroImage.

[82]  N. Logothetis,et al.  Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.

[83]  A. Toga,et al.  The Rhesus Monkey Brain in Stereotaxic Coordinates , 1999 .

[84]  N. Logothetis,et al.  Functional imaging of the monkey brain , 1999, Nature Neuroscience.

[85]  M. Hallett.  Human Brain Function , 1998, Trends in Neurosciences.

[86]  Karl J. Friston,et al.  Human Brain Function , 1997 .

[87]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[88]  R. H. Clarke,et al.  THE STRUCTURE AND FUNCTIONS OF THE CEREBELLUM EXAMINED BY A NEW METHOD. , 1908 .

[89]  Wim Vanduffel,et al.  Functional MRI of Awake Behaving Macaques Using Standard Equipment , 2014 .

[90]  Li Qingyang,et al.  Towards Automated Analysis of Connectomes: The Configurable Pipeline for the Analysis of Connectomes (C-PAC) , 2013 .

[91]  John C Gore,et al.  Functional magnetic resonance imaging of awake monkeys: some approaches for improving imaging quality. , 2012, Magnetic resonance imaging.

[92]  Michael Petrides,et al.  The marmoset brain in stereotaxic coordinates , 2012 .

[93]  P. Coupé,et al.  Adaptive non‐local means denoising of MR images with spatially varying noise levels , 2010, Journal of magnetic resonance imaging : JMRI.

[94]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.