About a quarter of human cerebral cortex is tiled with maps of the visual field. These maps can be 3 measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated 4 visual stimuli, also known as 'retinotopic mapping'. One of the datasets collected by the Human 5Connectome Project (HCP) involved ultra-high-field (7 Tesla) fMRI retinotopic mapping in 181 healthy 6 adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we 7 describe the experimental paradigm and the results of model-based analysis of the fMRI data. These 8 results provide estimates of population receptive field position and size. Our analyses include both results 9 from individual subjects as well as results obtained by averaging fMRI time-series across subjects at each 10 cortical and subcortical location and then fitting models. Both the group-average and individual-subject 11 results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal 12 cortex as well as subcortical areas. The group-average results agree well with previously published 13 parcellations of visual areas. In addition, split-half analyses demonstrate strong within-subject reliability, 14 further evidencing the high quality of the data. We make publicly available the analysis results for 15 individual subjects and the group average, as well as associated stimuli and analysis code. These 16 resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical 17 organization and the properties of high-resolution fMRI. In addition, they provide a measure that can be 18 combined with other HCP measures acquired in these same participants. This enables comparisons 19 across groups, health, and age, and comparison of organization derived from a retinotopic task against 20 that derived from other measurements such as diffusion imaging and resting-state functional connectivity. 21 22. CC-BY 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/308247 doi: bioRxiv preprint first posted online Apr. 25, 2018; 3 Introduction 1 2The central nervous system maps sensory inputs onto topographically organized representations. In the 3 field of vision, researchers have successfully exploited functional magnetic resonance imaging (fMRI) to 4 noninvasively measure visual field representations ('retinotopy') in the living human brain (Engel et al., 5 1994;Sereno et al., 1995; DeYoe et al., 1996; Engel et al., 1997). These efforts enable parcellation of 6 visual cortex into distinct maps of the visual field, thereby laying the foundation for detailed investigations 7 of the properties of visual cortex (parcellation references: Abdollahi et al., 2014;Benson et al., 2014; 8 Wang et al., 2015; review references: Tootell et al., 1996;Wandell et...

Motor recovery following ischemic stroke is contingent on the ability of surviving brain networks to compensate for damaged tissue. In rodent models, sensory and motor cortical representations have been shown to remap onto intact tissue around the lesion site, but remapping to more distal sites (e.g. in the contralesional hemisphere) has also been observed. Resting state functional connectivity (FC) analysis has been employed to study compensatory network adaptations in humans, but mechanisms and time course of motor recovery are not well understood. Here, we examine longitudinal FC in 23 first-episode ischemic pontine stroke patients (34-74 years old; 8 female, 15 male) and utilize a graph matching approach to identify patterns of regional functional connectivity reorganization during recovery. We quantified functional reorganization between several intervals ranging from 1 week to 6 months following stroke, and demonstrated that the areas that undergo functional reorganization most frequently are in cerebellar/subcortical networks. Brain regions with more structural connectome disruption due to the stroke also had more functional remapping over time. Finally, we show that the amount of functional reorganization between time points is correlated with the extent of motor recovery observed between those time points in the early to late subacute phases, and, furthermore, individuals with greater baseline motor impairment demonstrate more extensive early subacute functional reorganization (from one to two weeks post-stroke) and this reorganization correlates with better motor recovery at 6 months. Taken together, these results suggest that our graph matching approach can quantify recovery-relevant, whole-brain functional connectivity network reorganization after stroke.