Biology subjects

Verma, R.

Publications and source records attributed to Verma, R..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Tractography-based targeting of ventral intermediate nucleus: A comparison between conventional stereotactic targeting and diffusion tensor imaging-based targeting

BackgroundThe ventral intermediate (VIM) nucleus of the thalamus is the main target for lesioning using magnetic resonance imaging (MRI) guided focused ultrasound (MRgFUS) or deep brain stimulation (DBS). Targeting of VIM still depends on standard stereotactic coordinates, which do not account for inter-individual variability. Several approaches have been proposed including visualization of dentato-rubro-thalamic tract (DRTT) using diffusion tensor imaging tractography. ObjectiveTo compare probabilistic tracking of DRTT with deterministic tracking of DRTT and stereotactic coordinates to identify the most appropriate approach to target VIM. MethodsIn this retrospective study, we assessed the VIM targeted using stereotactic coordinates, deterministic and probabilistic tracking of DRTT in 19 patients with essential tremor who underwent DBS with VIM targeted using microelectrode recordings. We subsequently determined the positions of VIM derived from these three approaches and compared with that of DBS lead position using paired sample t-tests. ResultsThe probabilistic tracking of DRTT was significantly anterior to the lead (1.45 {+/-} 1.61 mm (P< 0.0001)), but not in the medial/lateral position (-0.29{+/-}2.42 mm (P=0.50)). Deterministic tracking of DRTT was significantly lateral (2.16 {+/-} 1.94 mm (P< 0.0001)) and anterior to the lead (1.66 {+/-} 2.1 mm (P< 0.0001)). The stereotactic coordinates were significantly lateral (2.41 {+/-} 1.41 mm (P< 0.0001)) and anterior (1.23 {+/-} 0.89 mm (P< 0.0001)) to the lead. ConclusionProbabilistic tracking of DRTT was found to be superior in targeting VIM compared to deterministic tracking and stereotactic coordinates.

neuroscience↗

bioRxiv2021

Connectomic Assessment of Injury Burden and Longitudinal Structural Network Alterations in Moderate-to-severe Traumatic Brain Injury

Traumatic brain injury (TBI) is a major public health problem. Caused by external mechanical forces, a major characteristic of TBI is the shearing of axons across the white matter, which causes structural connectivity disruptions between brain regions. This diffuse injury leads to cognitive deficits, frequently requiring rehabilitation. Heterogeneity is another characteristic of TBI as severity and cognitive sequelae of the disease have a wide variation across patients, posing a big challenge for treatment. Thus, measures assessing network-wide structural connectivity disruptions in TBI are necessary to quantify injury burden of individuals, which would help in achieving personalized treatment, patient monitoring, and rehabilitation planning. Despite TBI being a disconnectivity syndrome, connectomic assessment of structural disconnectivity has been very scarce. In this study, we propose a novel connectomic measure that we call network anomaly score (NAS) to capture the integrity of structural connectivity in TBI patients by leveraging two major characteristics of the disease: diffuseness of axonal injury and heterogeneity of the disease. Over a longitudinal cohort of moderate-to-severe TBI patients, we demonstrate that structural network topology of patients are more heterogeneous and are significantly different than that of healthy controls at 3 months post-injury, where dissimilarity further increases up to 12 months. We also show that NAS captures injury burden as quantified by post-traumatic amnesia and that alterations in the structural brain network is not related to cognitive recovery. Finally we compare NAS to major graph theory measures used in TBI literature and demonstrate the superiority of NAS in characterizing the disease.

neuroscience↗

bioRxiv2021

Computational modeling of C-terminal tails to predict the calcium-dependent secretion of ER resident proteins

The lumen of the endoplasmic reticulum (ER) has resident proteins that are critical to perform the various tasks of the ER such as protein maturation and lipid metabolism. These ER resident proteins typically have a carboxy-terminal ER retention sequence (ERS). The canonical ERS is Lys-Asp-Glu-Leu (KDEL) and when an ER resident protein moves from the ER to the Golgi, KDEL receptors (KDELRs) in the Golgi recognize the ERS and return the protein to the ER lumen. Depletion of ER calcium leads to the mass departure of ER resident proteins in a process termed exodosis, which is also regulated by KDELRs. Here, by combining computational prediction with machine learning-based models and experimental validation, we identify carboxy tail sequences of ER resident proteins divergent from the canonical "KDEL" ERS. Using molecular modeling and simulations, we demonstrated that two representative non-canonical ERS can stably bind to the KDELR. Collectively, we developed a method to predict whether a carboxy-terminal sequence acts as a putative ERS that would undergo secretion in response to ER calcium depletion and interact with the KDELRs. Identification of proteins that undergo exodosis will further our understanding of changes in ER proteostasis under physiological and pathological conditions where ER calcium is depleted.

cell biology↗

bioRxiv2021

Transcriptional regulation of HSFA7 and post-transcriptional modulation of HSFB4a by miRNA4200 govern general and varietal thermotolerance in tomato

Heat shock factors (HSFs) are at the core of heat stress (HS) response in plants. However, the contribution of HSFs governing the inherent thermotolerance mechanism in tomato from sub-tropical hot climates is poorly understood. With the above aim, comparative expression profiles of the HSF family in a HS tolerant (CLN1621L) and a sensitive cultivar (CA4) of tomato under HS revealed cultivar-biased regulation of an activator (HSFA7a) and repressor (HSFB4a) class HSF. Functional characterization of HSFA7a that was strongly up-regulated in the tolerant cultivar by VIGS-based silencing and overexpression established it as a positive regulator of HS-tolerance. While knock-down and overexpression analyses of HSFB4a that was down-regulated in CLN1621L in HS, showed it as a negative regulator of thermotolerance. Promoter:GUS reporter assays and promoter sequence analyses suggest heat-mediated transcriptional control of both the HSF genes in the contrasting cultivars. Moreover, we show HSFB4a is also regulated post-transcriptionally by microRNA Sly-miR4200 using degradome, short-tandem-target-mimic of Sly-miR4200 and transient in-planta Sly-miR4200-effector:HSFB4a-reporter assays. This miRNA is induced several folds upon HS in the tolerant variety thereby reducing HSFB4a levels. We thus propose that the alleviation of HSFB4a repressor governs thermotolerance in the tolerant cultivar by regulating downstream heat stress responsive genes.

molecular biology↗

bioRxiv2021

Non cell-autonomous effect of astrocytes on cerebral cavernous malformations

Cerebral cavernous malformations (CCMs) are common neurovascular lesions caused by loss-of-function mutations in one of three genes, including KRIT1 (CCM1), CCM2, and PDCD10 (CCM3), and generally regarded as an endothelial cell-autonomous disease. Here we report that proliferative astrocytes play a critical role in CCM pathogenesis by serving as a major source of VEGF during CCM lesion formation. An increase in astrocyte VEGF synthesis is driven by endothelial nitric oxide (NO) generated as a consequence of KLF2 and KLF4-dependent elevation of eNOS in CCM endothelium. The increased brain endothelial production of NO stabilizes HIF-1 in astrocytes, resulting in increased VEGF production and expression of a "hypoxic" program under normoxic conditions. We show that the upregulation of cyclooxygenase-2 (COX-2), a direct HIF-1 target gene and a known component of the hypoxic program, contributes to the development of CCM lesions because the administration of a COX-2 inhibitor significantly prevents progression of CCM lesions. Thus, non-cell-autonomous crosstalk between CCM endothelium and astrocytes propels vascular lesion development, and components of the hypoxic program represent potential therapeutic targets for CCMs.

neuroscience↗

bioRxiv2021

Fine-tuning the transcriptional regulatory model of adaptation response to phosphate stress in maize (Zea mays L.)

The post green revolution agriculture is based on generous application of fertilizers and high-yielding genotypes that are suited for such high input regimes. Cereals, like maize (Zea mays L.) are capable of utilizing less than 20% of the applied inorganic phosphate (Pi) - a non-renewable fertilizer resource. A greater understanding of the molecular mechanisms underlying the acquisition, transportation and utilization of Pi may lead to strategies to enhance phosphorus use efficiency (PUE) in field crops. In this study, we selected 12 Pi responsive genes in maize and carried out their comparative transcriptional expression in root and leaf tissues of a hydroponically grown Pi stress tolerant maize inbred line HKI-163, under sufficient and deficient Pi conditions. Pi starvation led to significant increase in root length; marked proliferation of root hairs and lesser number of crown roots. Eleven genes were significantly up or down regulated in Pi deficient condition. The putative acid phosphatase, ZmACP5, expression was up regulated by 162.81 and 74.40 fold in root and leaf tissues, respectively. The RNase, ZmRNS1 showed 115 fold up regulation in roots under Pi deprivation. Among the two putative high affinity Pi transporters ZmPht1;4 was found specific to root, whereas ZmPht2 was found to be up regulated in both root and leaf tissues. The genes involved in Pi homeostasis pathway (ZmSIZ1, SPX1 and Pho2) were up regulated in root and leaf. In light of the expression profiling of selected regulatory genes, an updated model of transcriptional regulation under Pi starvation in maize has been proposed.

plant biology↗

bioRxiv2021

RNA-protein interaction analysis of SARS-CoV-2 5'- and 3'-untranslated regions identifies an antiviral role of lysosome-associated membrane protein-2

Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is a positive-strand RNA virus. Viral genome is capped at the 5-end, followed by an untranslated region (UTR). There is poly-A tail at 3-end, preceded by an UTR. Self-interaction between the RNA regulatory elements present within 5- and 3-UTRs as well as their interaction with host/virus-encoded proteins mediate the function of 5- and 3-UTRs. Using RNA-protein interaction detection (RaPID) assay coupled to liquid chromatography with tandem mass-spectrometry, we identified host interaction partners of SARS-CoV-2 5- and 3-UTRs and generated an RNA-protein interaction network. By combining these data with the previously known protein-protein interaction data proposed to be involved in virus replication, we generated the RNA-protein-protein interaction (RPPI) network, likely to be essential for controlling SARS-CoV-2 replication. Notably, bioinformatics analysis of the RPPI network revealed the enrichment of factors involved in translation initiation and RNA metabolism. Lysosome-associated membrane protein-2a (Lamp2a) was one of the host proteins that interact with the 5-UTR. Further studies showed that Lamp2 level is upregulated in SARS-CoV-2 infected cells and overexpression of Lamp2a and Lamp2b variants reduced viral RNA level in infected cells and vice versa. In summary, our study provides an useful resource of SARS-CoV-2 5- and 3-UTR binding proteins and reveal the antiviral function of host Lamp2 protein. ImportanceReplication of a positive-strand RNA virus involves an RNA-protein complex consisting of viral genomic RNA, host RNA(s), virus-encoded proteins and host proteins. Dissecting out individual components of the replication complex will help decode the mechanism of viral replication. 5- and 3-UTRs in positive-strand RNA viruses play essential regulatory roles in virus replication. Here, we identified the host proteins that associate with the UTRs of SARS-CoV-2, combined those data with the previously known protein-protein interaction data (expected to be involved in virus replication) and generated the RNA-protein-protein interaction (RPPI) network. Analysis of the RPPI network revealed the enrichment of factors involved in translation initiation and RNA metabolism, which are important for virus replication. Analysis of one of the interaction partners of the 5-UTR (Lamp2a) demonstrated its antiviral role in SARS-CoV-2 infected cells. Collectively, our study provides a resource of SARS-CoV-2 UTR-binding proteins and identifies an antiviral role of host Lamp2a protein.

microbiology↗

bioRxiv2020

Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?

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.

neuroscience↗

bioRxiv2020

Injectable hydrogels for sustained co-delivery of subunit vaccines enhance humoral immunity

Vaccines aim to elicit a robust, yet targeted, immune response. Failure of a vaccine to elicit such a response arises in part from inappropriate temporal control over antigen and adjuvant presentation to the immune system. In this work, we sought to exploit the immune systems natural response to extended pathogen exposure during infection by designing an easily administered slow-delivery vaccine platform. We utilized an injectable and self-healing polymer-nanoparticle (PNP) hydrogel platform to prolong the co-delivery of vaccine components to the immune system. We demonstrated that these hydrogels exhibit unique delivery characteristics whereby physicochemically distinct compounds (such as antigen and adjuvant) could be co-delivered over the course of weeks. When administered in mice, hydrogel-based sustained vaccine exposure enhanced the magnitude, duration, and quality of the humoral immune response compared to standard PBS bolus administration of the same model vaccine. We report that the creation of a local inflammatory niche within the hydrogel, coupled with sustained release of vaccine cargo, enhanced the magnitude and duration of germinal center responses in the lymph nodes. This strengthened germinal center response promoted greater antibody affinity maturation, resulting in a more than 1000-fold increase in antigen-specific antibody affinity in comparison to bolus immunization. In summary, this work introduces a simple and effective vaccine delivery platform that increases the potency and durability of subunit vaccines.

bioengineering↗

bioRxiv2019

Connectomic consistency: a systematic stability analysisof structural and functional connectivity

Connectomics, the study of brain connectivity, has become an indispensable tool in neuroscientific research as it provides insights into brain organization. Connectomes are generated for different modalities such as using diffusion MRI to capture structural organization of the brain or using functional MRI to elaborate brains functional organization. Understanding links between structural and functional organizations is crucial in explaining how observed behavior emerges from the underlying neurobiological mechanisms. Many studies have investigated how these two organizations relate to each other; however, we still lack a proper understanding on how much variation should be expected on the two modalities, both between people cross-sectionally and within a single person longitudinally. Notably, connectomes of both modalities were shown to have significant differences depending on how they are generated. In this study, for both modalities, we systematically analyzed consistency of connectomes, that is the similarity between connectomes in terms of individual connections between brain regions or in terms of overall network topology. We present a comprehensive study of consistency in structural and resting-state functional connectomes both for a single subject examined longitudinally and across a large cohort of subjects cross-sectionally. We compared connectomes generated by different tracking algorithms, parcellations, edge weighting schemes, and edge pruning techniques. We evaluated consistency both at the levels of individual edges using correlation and at the level of network topology via graph matching accuracy. We also examined consistency of connectomes that are generated using most commonly applied communication schemes. Our results demonstrate varying degrees of consistency for the two modalities, with structural connectomes showing higher consistency than functional connectomes. Moreover, we observed a wide variation in consistency depending on how connectomes are generated. Our study sets a reference point for consistency of connectome types, which is especially important for structure-function coupling studies in evaluating mismatches between modalities.

neuroscience↗

bioRxiv2019

Freewater EstimatoR using iNtErpolated iniTialization (FERNET): Toward Accurate Estimation of Free Water in Peritumoral Region Using Single-Shell Diffusion MRI Data

Characterization of healthy versus pathological tissue is a key concern when modeling tissue microstructure in the peritumoral area, confounded by the presence of free water (e.g., edema). Most methods that model tissue microstructure are either based on advanced acquisition schemes not readily available in the clinic, or are not designed to address the challenge of edema. This underscores the need for a robust free water elimination (FWE) method that estimates free water in pathological tissue but can be used with clinically prevalent single-shell diffusion tensor imaging data. FWE in single-shell data requires the fitting of a bi-compartment model, which is an ill-posed problem. Its solution requires optimization, which relies on an initialization step. We propose a novel initialization approach for FWE, FERNET, which improves the estimation of free water in edematous and infiltrated peritumoral regions, using single-shell diffusion MRI data. The method has been extensively investigated on simulated data and healthy and brain tumor datasets, demonstrating its applicability on clinically acquired data. Additionally, it has been applied to data from brain tumor patients to demonstrate the improvement in tractography in the peritumoral region.

bioengineering↗

bioRxiv2019

Studying functional brain networks from dry electrode EEG set during music and resting states in neurodevelopment disorder

There has been an emerging interest in the study of functional brain networks in cognitive neuroscience in order to better understand brain responses to different stimuli. Such studies can help in understanding brain connectivity alterations that arise in neurodevelopmental disorders such as intellectual disability (ID). This research contributes to this body of knowledge by studying alterations in brain connectivity in ID compared to the typically developing controls (TDC). Electroencephalography (EEG) data of subjects with ID and TDC is collected through limited channel dry electrode system. Data was analyzed for the auditory and rest state processing along with the study of intra-network connectivity of the brain via clustering coefficients. Research findings indicate evidences for links between the sensory deficits and social impairment in ID individuals.

neuroscience↗

bioRxiv2019

Multimodal parameters of brain structure and function related to sex differences in cognitive performance.

The Parieto-Frontal Integration Theory (PFIT) identified a fronto-parietal network of regions where individual differences in brain parameters most strongly relate to cognitive performance. PFIT was supported and extended in adult samples, but not in youths or within single-scanner well-powered multimodal studies. We performed multimodal neuroimaging in 1601 youths age 8-22 on the same 3-Tesla scanner with contemporaneous neurocognitive assessment, measuring volume, gray matter density (GMD), mean diffusivity (MD), cerebral blood flow (CBF), resting-state functional MRI measures of amplitude of low frequency fluctuations (ALFF) and regional homogeneity (ReHo), and activation to a working memory and a social cognition task. Across age and sex groups, better performance was associated with higher volumes, greater GMD, lower MD, lower CBF, higher ALFF and ReHo and greater activation for the working memory task in PFIT regions. However, additional cortical, striatal, limbic and cerebellar regions showed comparable effects, hence PFIT needs expansion into an Extended PFIT (ExtPFIT) network incorporating nodes that support motivation and affect. Associations of brain parameters became stronger with advancing age group from childhood to adolescence to young adulthood, effects occurring earlier in females. This ExtPFIT network is developmentally fine-tuned, optimizing abundance and integrity of neural tissue while maintaining low resting energy state.

neuroscience↗

bioRxiv2019

Single-cell RNA-seq reveals spatially restricted multicellular fibrotic niches during lung fibrosis

Ontologically distinct populations of macrophages differentially contribute to organ fibrosis through unknown mechanisms. We applied lineage tracing, spatial methods and single-cell RNA-seq to a spatially-restricted model of asbestos-induced pulmonary fibrosis. We demonstrate that while tissue-resident interstitial macrophages, tissue-resident alveolar macrophages, and monocyte-derived alveolar macrophages are present in the fibrotic niche, only monocyte-derived alveolar macrophages are causally related to fibrosis. Monocyte-derived alveolar macrophages were specifically localized to fibrotic regions in the proximity of fibroblasts where they expressed molecules known to drive fibroblast proliferation, including PDGFA. Moreover, we identified autocrine M-CSF/M-CSFR signaling in monocyte-derived alveolar macrophages as a novel mechanism promoting their self-maintenance and persistence in the fibrotic niche. Pharmacological blockade of M-CSF signaling led to disappearance of the established population of monocyte-derived alveolar macrophages. Thus, our data indicate that monocyte-derived alveolar macrophages are specifically recruited to the fibrotic niche where they are maintained by autocrine signaling and drive fibrosis by stimulating fibroblast proliferation.

immunology↗

bioRxiv2018

Tractography Reproducibility Challenge with Empirical Data (TraCED): The 2017 ISMRM Diffusion Study Group Challenge

PurposeFiber tracking with diffusion weighted magnetic resonance imaging has become an essential tool for estimating in vivo brain white matter architecture. Fiber tracking results are sensitive to the choice of processing method and tracking criteria. Phantom studies provide concrete quantitative comparisons of methods relative to absolute ground truths, yet do not capture variabilities because of in vivo physiological factors.\n\nMethodsTo date, a large-scale reproducibility analysis has not been performed for the assessment of the newest generation of tractography algorithms with in vivo data. Reproducibility does not assess the validity of a brain connection however it is still of critical importance because it describes the variability for an algorithm in group studies. The ISMRM 2017 TraCED challenge was created to fulfill the gap. The TraCED dataset consists of a single healthy volunteer scanned on two different scanners of the same manufacturer. The multi-shell acquisition included b-values of 1000, 2000 and 3000 s/mm2 with 20, 45 and 64 diffusion gradient directions per shell, respectively.\n\nResultsNine international groups submitted 46 tractography algorithm entries. The top five submissions had high ICC > 0.88. Reproducibility is high within these top 5 submissions when assessed across sessions or across scanners. However, it can be directly attributed to containment of smaller volume tracts in larger volume tracts. This holds true for the top five submissions where they are contained in a specific order. While most algorithms are contained in an ordering there are some outliers.\n\nConclusionThe different methods clearly result in fundamentally different tract structures at the more conservative specificity choices (i.e., volumetrically smaller tractograms). The data and challenge infrastructure remain available for continued analysis and provide a platform for comparison.

neuroscience↗

bioRxiv2018

Non-Communicable Diseases and their determinants: A Cross-sectional State-Wide STEPS Survey, Haryana, North India

BackgroundRecent studies have documented high variation in epidemiologic transition levels among Indian states with noncommunicable disease epidemic rising swiftly. However, the estimates suffer from non-availability of reliable data for NCDs from sub populations. In order to fill the knowledge gap, the distribution and determinants of NCD risk factors were studied along with awareness, treatment and control of NCDs among the adult population in Haryana, India.\n\nMethodsNCD risk factors survey was conducted among 5078 residents, aged 18-69 years during 2016-17. Behavioural risk factors were assessed using STEPS instrument, administered through an android software (mSTEPS). This was followed by physical measurements using standard protocols. Finally, biological risk factors were determined through the analysis of serum and urine samples.\n\nResultsMales were found to be consuming tobacco and alcohol at higher rates of 38.9% (95% CI: 35.3-42.4) and 18.8% (95% CI: 15.8-21.8). One-tenth (11%) (95% CI: 8.6-13.4) of the respondents did not meet the specified WHO recommendations for physical activity for health. Around 35.2% (95%CI: 32.6-37.7) were overweight or obese. Hypertension and diabetes were prevalent at 26.2% (95% CI: 24.6-27.8) and 15.5% (95% CI: 11.0-20.0). 91.3% (95% CI: 89.3-93.3) of the population had higher salt intake than recommended 5gms per day.\n\nConclusionThe documentation of strikingly high and uniform distribution of different NCDs and their risk factors in state warrants urgent need for evidence based interventions and advocacy of policy measures.

epidemiology↗

bioRxiv2018

Structural connectivity analysis using Finsler geometry

In this work we demonstrate how Finsler geometry--and specifically the related geodesic tractography-- can be levied to analyze structural connections between different brain regions. We present new theoretical developments which support the definition of a novel Finsler metric and associated con-nectivity measures, based on closely related works on the Riemannian framework for diffusion MRI. Using data from the Human Connectome Project, as well as population data from an autism spectrum disorder study, we demonstrate that this new Finsler metric, together with the new connectivity measures, results in connectivity maps that are much closer to known tract anatomy compared to previous geodesic connectivity methods. Our implementation can be used to compute geodesic distance and connectivity maps for segmented areas, and is publicly available.

neuroscience↗

bioRxiv2018

Limits to anatomical accuracy of diffusion tractography using modern approaches

Diffusion MRI fiber tractography is widely used to probe the structural connectivity of thebrain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the ISBI 2018 3D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge. We made available three unique independent tractography validation datasets - a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractographys inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.

neuroscience↗