HighlightsDiffusion MRI is capable of detecting structural abnormalities of the optic chiasm.Quantification of crossing strength in optic chiasm is of promise for albinism diagnostics.Optic chiasm is a powerful test model for neuroimaging methods resolving crossing fibers.

We describe a collection of T1-, diffusion- and functional T2*-weighted magnetic resonance imaging data from human individuals with albinism and achiasma. This repository can be used as a test-bed to develop and validate tractography methods like diffusion-signal modeling and fiber tracking as well as to investigate the properties of the human visual system in individuals with congenital abnormalities. The MRI data is provided together with tools and files allowing for its preprocessing and analysis, along with the data derivatives such as manually curated masks and regions of interest for performing tractography.

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28In humans, each hemisphere comprises an overlay of two visuotopic maps of the contralateral 29 visual field, one from each eye. Is the capacity of the visual cortex limited to these two maps or 30 are plastic mechanisms available to host more maps? Using an integrative approach of 31 submillimeter fMRI, diffusion-weighted imaging and population receptive field mapping, we 32 found three hemiretinal inputs to converge onto the left hemisphere in a rare individual with 33 chiasma hypoplasia. This generates extremely atypical responses in striate and extrastriate 34 cortices, specifically an overlay of three hemifield representations. Unexpectedly, the effects of 35 this large abnormality on visual function in daily life are not easily detected. We conclude that 36 developmental plasticity including the re-wiring of local intra-and cortico-cortical connections is 37 pivotal to support the coexistence and functioning of three hemifield maps within one 38 hemisphere.39 40 41 65 dominance domains to hemifield dominance domains is a simple mechanism to accommodate 66 two hemifield maps, either two representations of one visual hemifield via binocular input in 67 normal vision or two representations of opposing hemifields via monocular input in congenital 68 chiasma malformations (Hoffmann and Dumoulin, 2015). 69These observations prompt the important question, whether V1 is limited to hosting two 70 hemifield maps, or whether the scope of plasticity in human V1 allows for the accommodation of 71 even more maps. We identified an individual with an extremely rare type of chiasma hypoplasia 72 that allowed us to address this question. Three types of investigations were performed using 3 73 4 and 7 Tesla MRI: (i) diffusion-weighted imaging (DWI) to specify the projection error of the 74 optic nerves at the optic chiasm, (ii) population receptive field (pRF) mapping (Ahmadi et al., 75 2018;Dumoulin and Wandell, 2008) to determine the cortical visual field maps, and (iii) 76 submillimeter fMRI to examine the cortical fine-grain structure. Our results demonstrate that 77 three hemifield maps can be accommodated within a single V1. We propose that mechanisms of 78 developmental plasticity that are exceeding the simple reassignment of ocular dominance 79 domains to hemifield dominance domains enable these three maps to be hosted in V1. 80 Results 81 Case description 82 A 26-year-old female with chiasma hypoplasia ('CHP') participated in the study. Her best-83 corrected decimal visual acuity (Snellen acuity) was 0.63 (20/32) for the dominant right eye and 84 0.25 (20/80) for the left eye. She had moderate vertical nystagmus, strabismus [alternating 85 strabismus, esotropia (5°), and vertical deviation (7°) with alternating suppression of each eye] 86 and no stereoscopic vision. Humphrey-like visual field testing (see Methods) revealed normal 87 visual fields in both eyes. Decussation anomalies were confirmed with visual evoked potentials 88 (VEPs) and T1-weighted MRI at the age of 22. She reported an otherwise normal ...

Convolutional neural network (CNN) models are of great promise to aid the segmentation and analysis of brain structures. Here, we tested whether CNN trained to segment normal optic chiasms from the T1w magnetic resonance imaging (MRI) image can be also applied to abnormal chiasms, specifically with optic nerve misrouting as typical for human albinism. We performed supervised training of the CNN on the T1w images of control participants (n = 1049) from the Human Connectome Project (HCP) repository and automatically generated algorithm-based optic chiasm masks. The trained CNN was subsequently tested on data of persons with albinism (PWA; n = 9) and controls (n = 8) from the CHIASM repository. The quality of outcome segmentation was assessed via the comparison to manually defined optic chiasm masks using the Dice similarity coefficient (DSC). The results revealed contrasting quality of masks obtained for control (mean DSC ± SEM = 0.75 ± 0.03) and PWA data (0.43 ± 0.8, few-corrected p = 0.04). The fact that the CNN recognition of the optic chiasm fails for chiasm abnormalities in PWA underlines the fundamental differences in their spatial features. This finding provides proof of concept for a novel deep-learning-based diagnostics approach of chiasmal misrouting from T1w images, as well as further analyses on chiasmal misrouting and their impact on the structure and function of the visual system.