The Human Connectome Project 7 Tesla retinotopy dataset: Description and population receptive field analysis

About a quarter of human cerebral cortex is dedicated mainly to visual processing. The large-scale spatial organization of visual cortex can be measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated visual stimuli, also known as “retinotopic mapping.” One of the datasets collected by the Human Connectome Project involved ultrahigh-field (7 Tesla) fMRI retinotopic mapping in 181 healthy young adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we describe the experimental paradigm and the results of model-based analysis of the fMRI data. These results provide estimates of population receptive field position and size. Our analyses include both results from individual subjects as well as results obtained by averaging fMRI time series across subjects at each cortical and subcortical location and then fitting models. Both the group-average and individual-subject results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal cortex as well as subcortical areas. The group-average results agree well with previously published parcellations of visual areas. In addition, split-half analyses show strong within-subject reliability, further demonstrating the high quality of the data. We make publicly available the analysis results for individual subjects and the group average, as well as associated stimuli and analysis code. These resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical organization and the properties of high-resolution fMRI. In addition, they provide a set of observations that can be compared with other Human Connectome Project measures acquired in these same participants.

[1]  Nick F. Ramsey,et al.  Patterns of resting state connectivity in human primary visual cortical areas: A 7T fMRI study , 2014, NeuroImage.

[2]  Ludovica Griffanti,et al.  Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers , 2014, NeuroImage.

[3]  Marlene C. Richter,et al.  Retinotopic Organization and Functional Subdivisions of the Human Lateral Geniculate Nucleus: A High-Resolution Functional Magnetic Resonance Imaging Study , 2004, The Journal of Neuroscience.

[4]  E. DeYoe,et al.  Mapping striate and extrastriate visual areas in human cerebral cortex. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Nikos K. Logothetis,et al.  A new method for estimating population receptive field topography in visual cortex , 2013, NeuroImage.

[6]  A. Dale,et al.  Functional Analysis of V3A and Related Areas in Human Visual Cortex , 1997, The Journal of Neuroscience.

[7]  Sabine Kastner,et al.  Visual responses of the human superior colliculus: a high-resolution functional magnetic resonance imaging study. , 2005, Journal of neurophysiology.

[8]  David H. Brainard,et al.  Correction of Distortion in Flattened Representations of the Cortical Surface Allows Prediction of V1-V3 Functional Organization from Anatomy , 2014, PLoS Comput. Biol..

[9]  Jonathan Winawer,et al.  Imaging retinotopic maps in the human brain , 2011, Vision Research.

[10]  A. Dale,et al.  New images from human visual cortex , 1996, Trends in Neurosciences.

[11]  B. Spehar,et al.  The Foveal Confluence in Human Visual Cortex , 2009, The Journal of Neuroscience.

[12]  Steen Moeller,et al.  The Human Connectome Project: A data acquisition perspective , 2012, NeuroImage.

[13]  D G Pelli,et al.  The VideoToolbox software for visual psychophysics: transforming numbers into movies. , 1997, Spatial vision.

[14]  Liang Wang,et al.  Probabilistic Maps of Visual Topography in Human Cortex. , 2015, Cerebral cortex.

[15]  Jonathan Winawer,et al.  Computational neuroimaging and population receptive fields , 2015, Trends in Cognitive Sciences.

[16]  R. S. J. Frackowiak,et al.  Activity in human areas V1/V2, V3 and V5 during the perception of coherent and incoherent motion , 1996, NeuroImage.

[17]  Pascal Fries,et al.  Human visual cortical gamma reflects natural image structure , 2019, NeuroImage.

[18]  Steen Moeller,et al.  Tradeoffs in pushing the spatial resolution of fMRI for the 7T Human Connectome Project , 2017, NeuroImage.

[19]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[20]  John H. R. Maunsell,et al.  The connections of the middle temporal visual area (MT) and their relationship to a cortical hierarchy in the macaque monkey , 1983, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[21]  Mircea Ariel Schoenfeld,et al.  Spatial elongation of population receptive field profiles revealed by model‐free fMRI back‐projection , 2018, Human brain mapping.

[22]  S. Zeki,et al.  The position and topography of the human colour centre as revealed by functional magnetic resonance imaging. , 1997, Brain : a journal of neurology.

[23]  R. Tootell,et al.  Projection of rods and cones within human visual cortex , 2000, Human brain mapping.

[24]  Mark Jenkinson,et al.  MSM: A new flexible framework for Multimodal Surface Matching , 2014, NeuroImage.

[25]  Tor D. Wager,et al.  Emotion schemas are embedded in the human visual system , 2018, Science Advances.

[26]  G. Glover,et al.  Retinotopic organization in human visual cortex and the spatial precision of functional MRI. , 1997, Cerebral cortex.

[27]  B. Wandell,et al.  Visual field maps, population receptive field sizes, and visual field coverage in the human MT+ complex. , 2009, Journal of neurophysiology.

[28]  Jonathan Winawer,et al.  GLMdenoise: a fast, automated technique for denoising task-based fMRI data , 2013, Front. Neurosci..

[29]  G. Orban,et al.  The Retinotopic Organization of the Human Middle Temporal Area MT/V5 and Its Cortical Neighbors , 2010, The Journal of Neuroscience.

[30]  B. Wandell,et al.  Specializations for Chromatic and Temporal Signals in Human Visual Cortex , 2005, Journal of Neuroscience.

[31]  D. V. van Essen,et al.  Mapping Human Cortical Areas In Vivo Based on Myelin Content as Revealed by T1- and T2-Weighted MRI , 2011, The Journal of Neuroscience.

[32]  Kevin DeSimone,et al.  Population Receptive Field Estimation Reveals New Retinotopic Maps in Human Subcortex , 2015, The Journal of Neuroscience.

[33]  Sabine Kastner,et al.  Topographic maps in human frontal cortex revealed in memory-guided saccade and spatial working-memory tasks. , 2007, Journal of neurophysiology.

[34]  Lawrence L. Wald,et al.  Accurate prediction of V1 location from cortical folds in a surface coordinate system , 2008, NeuroImage.

[35]  Kathleen A. Hansen,et al.  Topographic Organization in and near Human Visual Area V4 , 2007, The Journal of Neuroscience.

[36]  Justin L. Gardner,et al.  Inverted Encoding Models Reconstruct an Arbitrary Model Response, Not the Stimulus , 2019, eNeuro.

[37]  Serge O Dumoulin,et al.  Measurement of population receptive fields in human early visual cortex using back-projection tomography. , 2014, Journal of vision.

[38]  Wayne E. Mackey,et al.  Visual field map clusters in human frontoparietal cortex , 2016, bioRxiv.

[39]  Keiji Tanaka,et al.  Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey , 2008, Neuron.

[40]  Adrian T. Lee,et al.  fMRI of human visual cortex , 1994, Nature.

[41]  B. Wandell,et al.  Compressive spatial summation in human visual cortex. , 2013, Journal of neurophysiology.

[42]  Ione Fine,et al.  Resting-State Retinotopic Organization in the Absence of Retinal Input and Visual Experience , 2015, The Journal of Neuroscience.

[43]  Jonathan Winawer,et al.  Bayesian analysis of retinotopic maps , 2018, bioRxiv.

[44]  B. Wandell,et al.  Visual Field Maps in Human Cortex , 2007, Neuron.

[45]  P. Cotton,et al.  Contralateral visual hemifield representations in the human pulvinar nucleus. , 2007, Journal of neurophysiology.

[46]  Matthew F. Glasser,et al.  The Brain Analysis Library of Spatial maps and Atlases (BALSA) database , 2017, NeuroImage.

[47]  Abraham Z. Snyder,et al.  Function in the human connectome: Task-fMRI and individual differences in behavior , 2013, NeuroImage.

[48]  Omar H. Butt,et al.  The Retinotopic Organization of Striate Cortex Is Well Predicted by Surface Topology , 2012, Current Biology.

[49]  Brian A Wandell,et al.  Visual field map clusters in human cortex , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[50]  J W Belliveau,et al.  Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. , 1995, Science.

[51]  Matthew F. Glasser,et al.  Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans , 2018, Neuron.

[52]  Jesper Andersson,et al.  A multi-modal parcellation of human cerebral cortex , 2016, Nature.

[53]  N. Kanwisher,et al.  The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.

[54]  Lotfi B Merabet,et al.  Visual Topography of Human Intraparietal Sulcus , 2007, The Journal of Neuroscience.

[55]  Steen Moeller,et al.  Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project , 2013, NeuroImage.

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

[57]  Dwight J. Kravitz,et al.  Differential Sampling of Visual Space in Ventral and Dorsal Early Visual Cortex , 2018, The Journal of Neuroscience.

[58]  P. Cavanagh,et al.  Retinotopy and color sensitivity in human visual cortical area V8 , 1998, Nature Neuroscience.

[59]  Alex R. Wade,et al.  Visual areas and spatial summation in human visual cortex , 2001, Vision Research.

[60]  D. Heeger,et al.  Two Retinotopic Visual Areas in Human Lateral Occipital Cortex , 2006, The Journal of Neuroscience.

[61]  Alex R. Wade,et al.  Functional measurements of human ventral occipital cortex: retinotopy and colour. , 2002, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[62]  T. Knapen,et al.  Visual Organization of the Default Network , 2019, Cerebral cortex.

[63]  Stephen M. Smith,et al.  Using Temporal ICA to Selectively Remove Global Noise While Preserving Global Signal in Functional MRI Data , 2017 .

[64]  S. Kastner,et al.  Topographic maps in human frontal and parietal cortex , 2009, Trends in Cognitive Sciences.

[65]  Leslie G. Ungerleider,et al.  Modulation of sensory suppression: implications for receptive field sizes in the human visual cortex. , 2001, Journal of neurophysiology.

[66]  R. Tootell,et al.  Where is 'dorsal V4' in human visual cortex? Retinotopic, topographic and functional evidence. , 2001, Cerebral cortex.

[67]  M. Pinsk,et al.  The Anatomical and Functional Organization of the Human Visual Pulvinar , 2015, The Journal of Neuroscience.

[68]  K. Grill-Spector,et al.  The functional architecture of the ventral temporal cortex and its role in categorization , 2014, Nature Reviews Neuroscience.

[69]  J. Winawer,et al.  Human V4 and ventral occipital retinotopic maps , 2015, Visual Neuroscience.

[70]  Steen Moeller,et al.  The Human Connectome Project's neuroimaging approach , 2016, Nature Neuroscience.

[71]  Daniel Rueckert,et al.  Multimodal surface matching with higher-order smoothness constraints , 2017, NeuroImage.

[72]  Benjamin D. Singer,et al.  Retinotopic Organization of Human Ventral Visual Cortex , 2009, The Journal of Neuroscience.

[73]  Brian A. Wandell,et al.  Population receptive field estimates in human visual cortex , 2008, NeuroImage.

[74]  A. T. Smith,et al.  Estimating receptive field size from fMRI data in human striate and extrastriate visual cortex. , 2001, Cerebral cortex.

[75]  D. Heeger,et al.  Topographic maps of visual spatial attention in human parietal cortex. , 2005, Journal of neurophysiology.

[76]  Nancy Kanwisher,et al.  A cortical representation of the local visual environment , 1998, Nature.

[77]  Ben Glocker,et al.  Multimodal Surface Matching with Higher-Order Smoothness Constraints , 2017 .

[78]  S. Dumoulin,et al.  Modeling center-surround configurations in population receptive fields using fMRI. , 2012, Journal of vision.

[79]  David C Van Essen,et al.  The impact of traditional neuroimaging methods on the spatial localization of cortical areas , 2018, Proceedings of the National Academy of Sciences.

[80]  David Ress,et al.  Topography of covert visual attention in human superior colliculus. , 2010, Journal of neurophysiology.

[81]  Mark Jenkinson,et al.  Correspondences between retinotopic areas and myelin maps in human visual cortex , 2014, NeuroImage.

[82]  Steen Moeller,et al.  ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging , 2014, NeuroImage.

[83]  Essa Yacoub,et al.  The WU-Minn Human Connectome Project: An overview , 2013, NeuroImage.