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Background and Objectives: After a concussion diagnosis, the most important issue for patients and loved ones is how long it will take them to recover. The main objective of this study is to develop a prognostic model of concussion recovery. This model would benefit many patients worldwide, allowing for early treatment intervention., Methods: The Concussion Assessment, Research and Education (CARE) consortium study enrolled collegiate athletes from 30 sites (NCAA athletic departments and US Department of Defense service academies), 4 of which participated in the Advanced Research Core, which included diffusion-weighted MRI (dMRI) data collection. We analyzed the dMRI data of 51 injuries of concussed athletes scanned within 48 h of injury. All athletes were cleared to return-to-play by the local medical staff following a standardized, graduated protocol. The primary outcome measure is days to clearance of unrestricted return-to-play. Injuries were divided into early (return-to-play < 28 days) and late (return-to-play >= 28 days) recovery based on the return-to-play clinical records. The late recovery group meets the standard definition of Persisting Post-Concussion Symptoms (PPCS). Data were processed using automated, state-of-the-art, rigorous methods for reproducible data processing using brainlife.io. All processed data derivatives are made available at https://brainlife.io/project/63b2ecb0daffe2c2407ee3c5/dataset. The microstructural properties of 47 major white matter tracts, 5 callosal, 15 subcortical, and 148 cortical structures were mapped. Fractional Anisotropy (FA) and Mean Diffusivity (MD) were estimated for each tract and structure. Correlation analysis and Receiver Operator Characteristic (ROC) analysis were then performed to assess the association between the microstructural properties and return-to-play. Finally, a Logistic Regression binary classifier (LR-BC) was used to classify the injuries between the two recovery groups., Results: The mean FA across all white matter volume was negatively correlated with return-to-play (r = -0.38, p = 0.00001). No significant association between mean MD and return-to-play was found, neither for FA nor MD for any other structure. The mean FA of 47 white matter tracts was negatively correlated with return-to-play (rμ = -0.27; rσ = 0.08; r min  = -0.1; r max  = -0.43). Across all tracts, a large mean ROC Area Under the Curve (AUC FA ) of 0.71 ± 0.09 SD was found. The top classification performance of the LR-BC was AUC = 0.90 obtained using the 16 statistically significant white matter tracts., Discussion: Utilizing a free, open-source, and automated cloud-based neuroimaging pipeline and app (https://brainlife.io/docs/tutorial/using-clairvoy/), a prognostic model has been developed, which predicts athletes at risk for slow recovery (PPCS) with an AUC=0.90, balanced accuracy = 0.89, sensitivity = 1.0, and specificity = 0.79. The small number of participants in this study (51 injuries) is a significant limitation and supports the need for future large concussion dMRI studies and focused on recovery., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr Broglio has current or past research funding from the National Institutes of Health; Centers for Disease Control and Prevention; Department of Defense – USA Medical Research Acquisition Activity, National Collegiate Athletic Association; National Athletic Trainers’ Association Foundation; National Football League/Under Armour/GE; Simbex; and ElmindA. He has consulted for US Soccer (paid), US Cycling (unpaid), University of Calgary SHRed Concussions external advisory board (unpaid), medico-legal litigation, and received speaker honorarium and travel reimbursements for talks given. He is co-author of “Biomechanics of Injury (3rd edition)” and has a patent on “Brain Metabolism Monitoring Through CCO Measurements Using All-Fiber-Integrated Super-Continuum Source” (U.S. 11,529,091 B2). He is on the and is/was on the editorial boards (all unpaid) for Journal of Athletic Training (2015 to present), Concussion (2014 to present), Athletic Training & Sports Health Care (2008 to present), British Journal of Sports Medicine (2008 to 2019). Thomas McAllister has Concussion Research Grants from NIH; US Dept. of Defense; US Dept. of Energy; and the NCAA. He also has Royalties from American Psychiatric Assoc. Publishing for Textbook of TBI. He is part of the Concussion Scientific Advisory Committee; Australian Football League – uncompensated. Michael McCrea has Research funding to Medical College of Wisconsin from US Dept. of Defense (DoD) and NCAA; Research funding to Medical College of Wisconsin from NIH, VA, DoD, CDC, NFL, NCAA, Abbott Laboratories; Book royalties from Oxford University Press. He is Consultant, Neurotrauma Sciences, Inc.; Consultant, Green Bay Packers; Medical legal consulting. He receives Honoraria and travel support for professional speaking engagements and for professional meetings., (Copyright © 2024. Published by Elsevier Inc.)

The functional and computational properties of brain areas are determined, in large part, by their connectivity profiles. Advances in neuroimaging and network neuroscience allow us to characterize the human brain noninvasively, but a comprehensive understanding of the human brain demands an account of the anatomy of brain connections. Long-range anatomical connections are instantiated by white matter, which itself is organized into tracts. These tracts are often disrupted by central nervous system disorders, and they can be targeted by neuromodulatory interventions, such as deep brain stimulation. Here, we characterized the connections, morphology, traversal, and functions of the major white matter tracts in the brain. There are major discrepancies across different accounts of white matter tract anatomy, hindering our attempts to accurately map the connectivity of the human brain. However, we are often able to clarify the source(s) of these discrepancies through careful consideration of both histological tract-tracing and diffusion-weighted tractography studies. In combination, the advantages and disadvantages of each method permit novel insights into brain connectivity. Ultimately, our synthesis provides an essential reference for neuroscientists and clinicians interested in brain connectivity and anatomy, allowing for the study of the association of white matter's properties with behavior, development, and disorders., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process., (Copyright © 2021. Published by Elsevier Inc.)

The degree to which glaucoma has effects in the brain beyond the eye and the visual pathways is unclear. To clarify this, we investigated white matter microstructure (WMM) in 37 tracts of patients with glaucoma, monocular blindness, and controls. We used brainlife.io for reproducibility. White matter tracts were subdivided into seven categories ranging from those primarily involved in vision (the visual white matter) to those primarily involved in cognition and motor control. In the vision tracts, WMM was decreased as measured by fractional anisotropy in both glaucoma and monocular blind subjects compared to controls, suggesting neurodegeneration due to reduced sensory inputs. A test-retest approach was used to validate these results. The pattern of results was different in monocular blind subjects, where WMM properties increased outside the visual white matter as compared to controls. This pattern of results suggests that whereas in the monocular blind loss of visual input might promote white matter reorganization outside of the early visual system, such reorganization might be reduced or absent in glaucoma. The results provide indirect evidence that in glaucoma unknown factors might limit the reorganization as seen in other patient groups following visual loss.

We describe a dataset of processed data with associated reproducible preprocessing pipeline collected from two collegiate athlete groups and one non-athlete group. The dataset shares minimally processed diffusion-weighted magnetic resonance imaging (dMRI) data, three models of the diffusion signal in the voxel, full-brain tractograms, segmentation of the major white matter tracts as well as structural connectivity matrices. There is currently a paucity of similar datasets openly shared. Furthermore, major challenges are associated with collecting this type of data. The data and derivatives shared here can be used as a reference to study the effects of long-term exposure to collegiate athletics, such as the effects of repetitive head impacts. We use advanced anatomical and dMRI data processing methods publicly available as reproducible web services at brainlife.io.

Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bundles from diffusion Magnetic Resonance Imaging (dMRI) data indirectly, by exploiting either the idea of connectivity between regions or the geometry of fiber paths obtained with tractography techniques, or, directly, through the information in volumetric data. Despite the remarkable improvement in automatic segmentation methods over the years, their segmentation quality is not yet satisfactory, especially when dealing with datasets with very diverse characteristics, such as different tracking methods, bundle sizes or data quality. In this work, we propose a novel, supervised streamline-based segmentation method, called Classifyber, which combines information from atlases, connectivity patterns, and the geometry of fiber paths into a simple linear model. With a wide range of experiments on multiple datasets that span from research to clinical domains, we show that Classifyber substantially improves the quality of segmentation as compared to other state-of-the-art methods and, more importantly, that it is robust across very diverse settings. We provide an implementation of the proposed method as open source code, as well as web service., (Copyright © 2020. Published by Elsevier Inc.)

Tractography has created new horizons for researchers to study brain connectivity in vivo. However, tractography is an advanced and challenging method that has not been used so far for medical data analysis at a large scale in comparison to other traditional brain imaging methods. This work allows tractography to be used for large scale and high-quality medical analytics. BUndle ANalytics (BUAN) is a fast, robust, and flexible computational framework for real-world tractometric studies. BUAN combines tractography and anatomical information to analyze the challenging datasets and identifies significant group differences in specific locations of the white matter bundles. Additionally, BUAN takes the shape of the bundles into consideration for the analysis. BUAN compares the shapes of the bundles using a metric called bundle adjacency which calculates shape similarity between two given bundles. BUAN builds networks of bundle shape similarities that can be paramount for automating quality control. BUAN is freely available in DIPY. Results are presented using publicly available Parkinson's Progression Markers Initiative data.

The human visual system is capable of processing visual information from fovea to the far peripheral visual field. Recent fMRI studies have shown a full and detailed retinotopic map in area prostriata, located ventro-dorsally and anterior to the calcarine sulcus along the parieto-occipital sulcus with strong preference for peripheral and wide-field stimulation. Here, we report the anatomical pattern of white matter connections between area prostriata and the thalamus encompassing the lateral geniculate nucleus (LGN). To this end, we developed and utilized an automated pipeline comprising a series of Apps that run openly on the cloud computing platform brainlife.io to analyse 139 subjects of the Human Connectome Project (HCP). We observe a continuous and extended bundle of white matter fibers from which two subcomponents can be extracted: one passing ventrally parallel to the optic radiations (OR) and another passing dorsally circumventing the lateral ventricle. Interestingly, the loop travelling dorsally connects the thalamus with the central visual field representation of prostriata located anteriorly, while the other loop travelling more ventrally connects the LGN with the more peripheral visual field representation located posteriorly. We then analyse an additional cohort of 10 HCP subjects using a manual plane extraction method outside brainlife.io to study the relationship between the two extracted white matter subcomponents and eccentricity, myelin and cortical thickness gradients within prostriata. Our results are consistent with a retinotopic segregation recently demonstrated in the OR, connecting the LGN and V1 in humans and reveal for the first time a retinotopic segregation regarding the trajectory of a fiber bundle between the thalamus and an associative visual area.

The primate brain contains a large number of interconnected visual areas, whose spatial organization and intracortical projections show a high level of conservation across species. One fiber pathway of recent interest is the vertical occipital fasciculus (VOF), which is thought to support communication between dorsal and ventral visual areas in the occipital lobe. A recent comparative diffusion MRI (dMRI) study reported that the VOF in the macaque brain bears a similar topology to that of the human, running superficial and roughly perpendicular to the optic radiation. The present study reports a comparative investigation of the VOF in the common marmoset, a small New World monkey whose lissencephalic brain is approximately tenfold smaller than the macaque and 150-fold smaller than the human. High-resolution ex vivo dMRI of two marmoset brains revealed an occipital white matter structure that closely resembles that of the larger primate species, with one notable difference. Namely, unlike in the macaque and the human, the VOF in the marmoset is spatially fused with other, more anterior vertical tracts, extending anteriorly between the parietal and temporal cortices. We compare several aspects of this continuous structure, which we term the VOF complex (VOF +), and neighboring fasciculi to those of macaques and humans. We hypothesize that the essential topology of the VOF+ is a conserved feature of the posterior cortex in anthropoid primates, with a clearer fragmentation into multiple named fasciculi in larger, more gyrified brains.

Historically, the primary focus of studies of human white matter tracts has been on large tracts that connect anterior-to-posterior cortical regions. These include the superior longitudinal fasciculus (SLF), the inferior longitudinal fasciculus (ILF), and the inferior fronto-occipital fasciculus (IFOF). Recently, more refined and well-understood tractography methods have facilitated the characterization of several tracts in the posterior of the human brain that connect dorsal-to-ventral cortical regions. These include the vertical occipital fasciculus (VOF), the posterior arcuate fasciculus (pArc), the temporo-parietal connection (TP-SPL), and the middle longitudinal fasciculus (MdLF). The addition of these dorso-ventral connective tracts to our standard picture of white matter architecture results in a more complicated pattern of white matter connectivity than previously considered. Dorso-ventral connective tracts may play a role in transferring information from superior horizontal tracts, such as the SLF, to inferior horizontal tracts, such as the IFOF and ILF. We present a full anatomical delineation of these major dorso-ventral connective white matter tracts (the VOF, pArc, TP-SPL, and MdLF). We show their spatial layout and cortical termination mappings in relation to the more established horizontal tracts (SLF, IFOF, ILF, and Arc) and consider standard values for quantitative features associated with the aforementioned tracts. We hope to facilitate further study on these tracts and their relations. To this end, we also share links to automated code that segments these tracts, thereby providing a standard approach to obtaining these tracts for subsequent analysis. We developed open source software to allow reproducible segmentation of the tracts: https://github.com/brainlife/Vertical&#95;Tracts . Finally, we make the segmentation method available as an open cloud service on the data and analyses sharing platform brainlife.io. Investigators will be able to access these services and upload their data to segment these tracts.

Classical studies of attention have identified areas of parietal and frontal cortex as sources of attentional control. Recently, a ventral region in the macaque temporal cortex, the posterior infero-temporal dorsal area PITd, has been suggested as a third attentional control area. This raises the question of whether and how spatially distant areas coordinate a joint focus of attention. Here we tested the hypothesis that parieto-frontal attention areas and PITd are directly interconnected. By combining functional MRI with ex-vivo high-resolution diffusion MRI, we found that PITd and dorsal attention areas are all directly connected through three specific fascicles. These results ascribe a new function, the communication of attention signals, to two known fiber-bundles, highlight the importance of vertical interactions across the two visual streams, and imply that the control of endogenous attention, hitherto thought to reside in macaque dorsal cortical areas, is exerted by a dorso-ventral network., Competing Interests: IS, BM, HS, FP, WF No competing interests declared, (© 2019, Sani et al.)

We investigated the impact of age-related macular degeneration (AMD) on visual acuity and the visual white matter. We combined an adaptive cortical atlas and diffusion-weighted magnetic resonance imaging (dMRI) and tractography to separate optic radiation (OR) projections to different retinal eccentricities in human primary visual cortex. We exploited the known anatomical organization of the OR and clinically relevant data to segment the OR into three primary components projecting to fovea, mid- and far-periphery. We measured white matter tissue properties-fractional anisotropy, linearity, planarity, sphericity-along the aforementioned three components of the optic radiation to compare AMD patients and controls. We found differences in white matter properties specific to OR white matter fascicles projecting to primary visual cortex locations corresponding to the location of retinal damage (fovea). Additionally, we show that the magnitude of white matter properties in AMD patients' correlates with visual acuity. In sum, we demonstrate a specific relation between visual loss, anatomical location of retinal damage and white matter damage in AMD patients. Importantly, we demonstrate that these changes are so profound that can be detected using magnetic resonance imaging data with clinical resolution. The conserved mapping between retinal and white matter damage suggests that retinal neurodegeneration might be a primary cause of white matter degeneration in AMD patients. The results highlight the impact of eye disease on brain tissue, a process that may become an important target to monitor during the course of treatment.

Understanding how knowledge is represented in the human brain is a fundamental challenge in neuroscience. To date, most of the work on this topic has focused on knowledge representation in cortical areas and debated whether knowledge is represented in a distributed or localized fashion. Fang and colleagues provide evidence that brain connections and the white matter supporting such connections might play a significant role. The work opens new avenues of investigation, breaking through disciplinary boundaries across network neuroscience, computational neuroscience, cognitive science, and classical lesion studies.

Diffusion imaging coupled with tractography algorithms allows researchers to image human white matter fiber bundles in-vivo. These bundles are three-dimensional structures with shapes that change over time during the course of development as well as in pathologic states. While most studies on white matter variability focus on analysis of tissue properties estimated from the diffusion data, e.g. fractional anisotropy, the shape variability of white matter fiber bundle is much less explored. In this paper, we present a set of tools for shape analysis of white matter fiber bundles, namely: (1) a concise geometric model of bundle shapes; (2) a method for bundle registration between subjects; (3) a method for deformation estimation. Our framework is useful for analysis of shape variability in white matter fiber bundles. We demonstrate our framework by applying our methods on two datasets: one consisting of data for 6 normal adults and another consisting of data for 38 normal children of age 11 days to 8.5 years. We suggest a robust and reproducible method to measure changes in the shape of white matter fiber bundles. We demonstrate how this method can be used to create a model to assess age-dependent changes in the shape of specific fiber bundles. We derive such models for an ensemble of white matter fiber bundles on our pediatric dataset and show that our results agree with normative human head and brain growth data. Creating these models for a large pediatric longitudinal dataset may improve understanding of both normal development and pathologic states and propose novel parameters for the examination of the pediatric brain., (Copyright © 2017 Elsevier Inc. All rights reserved.)

We compare several major white-matter tracts in human and macaque occipital lobe using diffusion magnetic resonance imaging. The comparison suggests similarities but also significant differences in the tracts. There are several apparently homologous tracts in the 2 species, including the vertical occipital fasciculus (VOF), optic radiation, forceps major, and inferior longitudinal fasciculus (ILF). There is one large human tract, the inferior fronto-occipital fasciculus, with no corresponding fasciculus in macaque. We could identify the macaque VOF (mVOF), which has been little studied. Its position is consistent with classical invasive anatomical studies by Wernicke. VOF homology is supported by similarity of the endpoints in V3A and ventral V4 across species. The mVOF fibers intertwine with the dorsal segment of the ILF, but the human VOF appears to be lateral to the ILF. These similarities and differences between the occipital lobe tracts will be useful in establishing which circuitry in the macaque can serve as an accurate model for human visual cortex., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Visual neuroscience has traditionally focused much of its attention on understanding the response properties of single neurons or neuronal ensembles. The visual white matter and the long-range neuronal connections it supports are fundamental in establishing such neuronal response properties and visual function. This review article provides an introduction to measurements and methods to study the human visual white matter using diffusion MRI. These methods allow us to measure the microstructural and macrostructural properties of the white matter in living human individuals; they allow us to trace long-range connections between neurons in different parts of the visual system and to measure the biophysical properties of these connections. We also review a range of findings from recent studies on connections between different visual field maps, the effects of visual impairment on the white matter, and the properties underlying networks that process visual information supporting visual face recognition. Finally, we discuss a few promising directions for future studies. These include new methods for analysis of MRI data, open datasets that are becoming available to study brain connectivity and white matter properties, and open source software for the analysis of these data.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder found to have widespread alterations in the function and synchrony of brain regions. These differences may underlie alterations in microstructural organization, such as in white matter pathways. To investigate the diffusion of major white matter tracts, the current study examined multiple indices of white matter diffusion in 42 children and adults with ASD and 44 typically developing (TD) age- and IQ-matched peers using diffusion tensor imaging. Diffusivity measures were compared between groups for the following tracts: bilateral cingulum bundle, corpus callosum, inferior longitudinal fasciculus, superior longitudinal fasciculus, and uncinate fasciculus. Results indicate a significant reduction in fractional anisotropy (FA) for the left superior longitudinal fasciculus (LSLF) in ASD children and adults compared with TD peers. A significant increase in radial diffusivity for ASD participants was also found in the same cluster along the LSLF. In addition, a significant positive correlation emerged for all subjects between FA for the LSLF and age, with FA increasing with age. These findings point to a significant alteration in long-distance white matter connectivity in children and adults with ASD, potentially underscoring the relationship between alterations in white matter diffusion and the ASD phenotype. These results also suggest that the white matter alterations in autism may be subtle and related to the developmental trajectory., Competing Interests: Author Disclosure Statement No competing financial interests exist.

Human visual cortex comprises many visual field maps organized into clusters. A standard organization separates visual maps into 2 distinct clusters within ventral and dorsal cortex. We combined fMRI, diffusion MRI, and fiber tractography to identify a major white matter pathway, the vertical occipital fasciculus (VOF), connecting maps within the dorsal and ventral visual cortex. We use a model-based method to assess the statistical evidence supporting several aspects of the VOF wiring pattern. There is strong evidence supporting the hypothesis that dorsal and ventral visual maps communicate through the VOF. The cortical projection zones of the VOF suggest that human ventral (hV4/VO-1) and dorsal (V3A/B) maps exchange substantial information. The VOF appears to be crucial for transmitting signals between regions that encode object properties including form, identity, and color and regions that map spatial information., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Individuals sometimes show inconsistent risk preferences, including excessive attraction to gambles featuring small chances of winning large amounts (called "positively skewed" gambles). While functional neuroimaging research indicates that nucleus accumbens (NAcc) and anterior insula (AIns) activity inversely predict risky choice, structural connections between these regions have not been described in humans. By combining diffusion-weighted MRI with tractography, we identified the anatomical trajectory of white-matter tracts projecting from the AIns to the NAcc and statistically validated these tracts using Linear Fascicle Evaluation (LiFE) and virtual lesions. Coherence of the right AIns-NAcc tract correlated with reduced preferences for positively skewed gambles. Further, diminished NAcc activity during gamble presentation mediated the association between tract structure and choice. These results identify an unreported tract connecting the AIns to the NAcc in humans and support the notion that structural connections can alter behavior by influencing brain activity as individuals weigh uncertain gains against uncertain losses., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Amblyopia is a visual disorder caused by poorly coordinated binocular input during development. Little is known about the impact of amblyopia on the white matter within the visual system. We studied the properties of six major visual white-matter pathways in a group of adults with amblyopia (n=10) and matched controls (n=10) using diffusion weighted imaging (DWI) and fiber tractography. While we did not find significant differences in diffusion properties in cortico-cortical pathways, patients with amblyopia exhibited increased mean diffusivity in thalamo-cortical visual pathways. These findings suggest that amblyopia may systematically alter the white matter properties of early visual pathways., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Models of diffusion MRI within a voxel are useful for making inferences about the properties of the tissue and inferring fiber orientation distribution used by tractography algorithms. A useful model must fit the data accurately. However, evaluations of model-accuracy of commonly used models have not been published before. Here, we evaluate model-accuracy of the two main classes of diffusion MRI models. The diffusion tensor model (DTM) summarizes diffusion as a 3-dimensional Gaussian distribution. Sparse fascicle models (SFM) summarize the signal as a sum of signals originating from a collection of fascicles oriented in different directions. We use cross-validation to assess model-accuracy at different gradient amplitudes (b-values) throughout the white matter. Specifically, we fit each model to all the white matter voxels in one data set and then use the model to predict a second, independent data set. This is the first evaluation of model-accuracy of these models. In most of the white matter the DTM predicts the data more accurately than test-retest reliability; SFM model-accuracy is higher than test-retest reliability and also higher than the DTM model-accuracy, particularly for measurements with (a) a b-value above 1000 in locations containing fiber crossings, and (b) in the regions of the brain surrounding the optic radiations. The SFM also has better parameter-validity: it more accurately estimates the fiber orientation distribution function (fODF) in each voxel, which is useful for fiber tracking.

It is unknown if the white-matter properties associated with specific visual networks selectively affect category-specific processing. In a novel protocol we combined measurements of white-matter structure, functional selectivity, and behavior in the same subjects. We find two parallel white-matter pathways along the ventral temporal lobe connecting to either face-selective or place-selective regions. Diffusion properties of portions of these tracts adjacent to face- and place-selective regions of ventral temporal cortex correlate with behavioral performance for face or place processing, respectively. Strikingly, adults with developmental prosopagnosia (face blindness) express an atypical structure-behavior relationship near face-selective cortex, suggesting that white-matter atypicalities in this region may have behavioral consequences. These data suggest that examining the interplay between cortical function, anatomical connectivity, and visual behavior is integral to understanding functional networks and their role in producing visual abilities and deficits., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Purpose: Patients with Leber hereditary optic neuropathy (LHON) and cone-rod dystrophy (CRD) have central vision loss; but CRD damages the retinal photoreceptor layer, and LHON damages the retinal ganglion cell (RGC) layer. Using diffusion MRI, we measured how these two types of retinal damage affect the optic tract (ganglion cell axons) and optic radiation (geniculo-striate axons)., Methods: Adult onset CRD (n = 5), LHON (n = 6), and healthy controls (n = 14) participated in the study. We used probabilistic fiber tractography to identify the optic tract and the optic radiation. We compared axial and radial diffusivity at many positions along the optic tract and the optic radiation., Results: In both types of patients, diffusion measures within the optic tract and the optic radiation differ from controls. The optic tract change is principally a decrease in axial diffusivity; the optic radiation change is principally an increase in radial diffusivity., Conclusions: Both photoreceptor layer (CRD) and retinal ganglion cell (LHON) retinal disease causes substantial change in the visual white matter. These changes can be measured using diffusion MRI. The diffusion changes measured in the optic tract and the optic radiation differ, suggesting that they are caused by different biological mechanisms., (Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.)

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC‐ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real‐life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra‐rater agreement (Dice score) was approximately 0.77, while inter‐rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science. [ABSTRACT FROM AUTHOR]

• Advanced neuroimaging methods are useful for comparative neuroanatomy studies. • Modern diffusion MRI replicates classic strychnine neuronography findings. • Quantitative MRI maps are similar to classic myelin stains across species. • Historical neuroanatomy guides interpretations of comparative neuroimaging studies. Comparative neuroanatomy studies improve understanding of brain structure and function and provide insight regarding brain development, evolution, and also what features of the brain are uniquely human. With modern methods such as diffusion MRI (dMRI) and quantitative MRI (qMRI), we are able to measure structural features of the brain with the same methods across human and non-human primates. In this review article, we discuss how recent dMRI measurements of vertical occipital connections in humans and macaques can be compared with previous findings from invasive anatomical studies that examined connectivity, including relatively forgotten classic strychnine neuronography studies. We then review recent progress in understanding the neuroanatomy of vertical connections within the occipitotemporal cortex by combining modern quantitative MRI and classical histological measurements in human and macaque. Finally, we a) discuss current limitations of dMRI and tractography and b) consider potential paths for future investigations using dMRI and tractography for comparative neuroanatomical studies of white matter tracts between species. While we focus on vertical association connections in visual cortex in the present paper, this same approach can be applied to other white matter tracts. Similar efforts are likely to continue to advance our understanding of the neuroanatomical features of the brain that are shared across species, as well as to distinguish the features that are uniquely human. [ABSTRACT FROM AUTHOR]