scholarly journals The trajectory of the medial longitudinal fasciculus in the human brain: A diffusion imaging‐based tractography study

2021 ◽  
Author(s):  
Mengjun Li ◽  
Fang‐Cheng Yeh ◽  
Qingrun Zeng ◽  
Xiaolong Wu ◽  
Xu Wang ◽  
...  
2012 ◽  
Vol 1 (1) ◽  
pp. 78-91 ◽  
Author(s):  
S Kollias

Diffusion tensor imaging (DTI) is a neuroimaging MR technique, which allows in vivo and non-destructive visualization of myeloarchitectonics in the neural tissue and provides quantitative estimates of WM integrity by measuring molecular diffusion. It is based on the phenomenon of diffusion anisotropy in the nerve tissue, in that water molecules diffuse faster along the neural fibre direction and slower in the fibre-transverse direction. On the basis of their topographic location, trajectory, and areas that interconnect the various fibre systems of the mammalian brain are divided into commissural, projectional and association fibre systems. DTI has opened an entirely new window on the white matter anatomy with both clinical and scientific applications. Its utility is found in both the localization and the quantitative assessment of specific neuronal pathways. The potential of this technique to address connectivity in the human brain is not without a few methodological limitations. A wide spectrum of diffusion imaging paradigms and computational tractography algorithms has been explored in recent years, which established DTI as promising new avenue, for the non-invasive in vivo mapping of structural connectivity at the macroscale level. Further improvements in the spatial resolution of DTI may allow this technique to be applied in the near future for mapping connectivity also at the mesoscale level. DOI: http://dx.doi.org/10.3126/njr.v1i1.6330 Nepalese Journal of Radiology Vol.1(1): 78-91


2021 ◽  
Vol 15 ◽  
Author(s):  
Sahin Hanalioglu ◽  
Siyar Bahadir ◽  
Ilkay Isikay ◽  
Pinar Celtikci ◽  
Emrah Celtikci ◽  
...  

Objective: Graph theory applications are commonly used in connectomics research to better understand connectivity architecture and characterize its role in cognition, behavior and disease conditions. One of the numerous open questions in the field is how to represent inter-individual differences with graph theoretical methods to make inferences for the population. Here, we proposed and tested a simple intuitive method that is based on finding the correlation between the rank-ordering of nodes within each connectome with respect to a given metric to quantify the differences/similarities between different connectomes.Methods: We used the diffusion imaging data of the entire HCP-1065 dataset of the Human Connectome Project (HCP) (n = 1,065 subjects). A customized cortical subparcellation of HCP-MMP atlas (360 parcels) (yielding a total of 1,598 ROIs) was used to generate connectivity matrices. Six graph measures including degree, strength, coreness, betweenness, closeness, and an overall “hubness” measure combining all five were studied. Group-level ranking-based aggregation method (“measure-then-aggregate”) was used to investigate network properties on population level.Results: Measure-then-aggregate technique was shown to represent population better than commonly used aggregate-then-measure technique (overall rs: 0.7 vs 0.5). Hubness measure was shown to highly correlate with all five graph measures (rs: 0.88–0.99). Minimum sample size required for optimal representation of population was found to be 50 to 100 subjects. Network analysis revealed a widely distributed set of cortical hubs on both hemispheres. Although highly-connected hub clusters had similar distribution between two hemispheres, average ranking values of homologous parcels of two hemispheres were significantly different in 71% of all cortical parcels on group-level.Conclusion: In this study, we provided experimental evidence for the robustness, limits and applicability of a novel group-level ranking-based hubness analysis technique. Graph-based analysis of large HCP dataset using this new technique revealed striking hemispheric asymmetry and intraparcel heterogeneities in the structural connectivity of the human brain.


2017 ◽  
Author(s):  
Kesshi Marin Jordan ◽  
Anisha Keshavan ◽  
Eduardo Caverzasi ◽  
Joseph Osorio ◽  
Nico Papinutto ◽  
...  

Neurosurgical resection is one of the few opportunities researchers have to image the human brain both prior to and following focal damage. One of the challenges associated with studying brains undergoing surgical resection is that they often do not fit the brain templates most image-processing methodologies are based on, so manual intervention is required to reconcile the pathology and the most extreme cases must be excluded. Manual intervention requires significant time investment and introduces reproducibility concerns. We propose an automatic longitudinal pipeline based on High Angular Resolution Diffusion Imaging acquisitions to facilitate a Pathway Lesion Symptom Mapping analysis relating focal white matter injury to functional deficits. This two-part approach includes (i) automatic segmentation of focal white matter injury from anisotropic power differences, and (ii) modeling disconnection using tractography on the single-subject level, which specifically identifies the disconnections associated with focal white matter damage. The advantages of this approach stem from (1) objective and automatic lesion segmentation and tractogram generation, (2) objective and precise segmentation of affected tissue likely to be associated with damage to long-range white matter pathways (defined by anisotropic power), (3) good performance even in the cases of anatomical distortions by use of nonlinear tensor-based registration in the patient space, which aligns images using white matter contrast. Mapping a system as variable and complex as the human brain requires sample sizes much larger than the current technology can support. This pipeline can be used to execute large-scale, sufficiently powered analyses by meeting the need for an automatic approach to objectively quantify white matter disconnection.


NeuroImage ◽  
2014 ◽  
Vol 91 ◽  
pp. 177-186 ◽  
Author(s):  
Anna Varentsova ◽  
Shengwei Zhang ◽  
Konstantinos Arfanakis

2016 ◽  
Vol 124 (5) ◽  
pp. 1396-1405 ◽  
Author(s):  
Kaan Yagmurlu ◽  
Erik H. Middlebrooks ◽  
Necmettin Tanriover ◽  
Albert L. Rhoton

OBJECT The aim of this study was to examine the arcuate (AF) and superior longitudinal fasciculi (SLF), which together form the dorsal language stream, using fiber dissection and diffusion imaging techniques in the human brain. METHODS Twenty-five formalin-fixed brains (50 hemispheres) and 3 adult cadaveric heads, prepared according to the Klingler method, were examined by the fiber dissection technique. The authors’ findings were supported with MR tractography provided by the Human Connectome Project, WU-Minn Consortium. The frequencies of gyral distributions were calculated in segments of the AF and SLF in the cadaveric specimens. RESULTS The AF has ventral and dorsal segments, and the SLF has 3 segments: SLF I (dorsal pathway), II (middle pathway), and III (ventral pathway). The AF ventral segment connects the middle (88%; all percentages represent the area of the named structure that is connected to the tract) and posterior (100%) parts of the superior temporal gyri and the middle part (92%) of the middle temporal gyrus to the posterior part of the inferior frontal gyrus (96% in pars opercularis, 40% in pars triangularis) and the ventral premotor cortex (84%) by passing deep to the lower part of the supramarginal gyrus (100%). The AF dorsal segment connects the posterior part of the middle (100%) and inferior temporal gyri (76%) to the posterior part of the inferior frontal gyrus (96% in pars opercularis), ventral premotor cortex (72%), and posterior part of the middle frontal gyrus (56%) by passing deep to the lower part of the angular gyrus (100%). CONCLUSIONS This study depicts the distinct subdivision of the AF and SLF, based on cadaveric fiber dissection and diffusion imaging techniques, to clarify the complicated language processing pathways.


2009 ◽  
Vol 27 (8) ◽  
pp. 1151-1162 ◽  
Author(s):  
Robert V. Mulkern ◽  
Steven J. Haker ◽  
Stephan E. Maier

Author(s):  
Stephanie J. Forkel ◽  
Marco Catani

The field of neuroanatomy of language is moving forward at a fast pace. This progression is partially due to the development of diffusion tractography, which has been used to describe white matter connections in the living human brain. For the field of neurolinguistics, this advancement is timely and important for two reasons. First, it allows clinical researchers to liberate themselves from neuroanatomical models of language derived from animal studies. Second, for the first time, it offers the possibility of testing network correlates of neurolinguistic models directly in the human brain. This chapter introduces the reader to general principles of diffusion imaging and tractography. Examples of its applications to normal language and its disorders will be used to explicate its potentials and limitations.


2020 ◽  
Vol 9 (5) ◽  
pp. 1340 ◽  
Author(s):  
Sang Seok Yeo ◽  
Sung Ho Jang ◽  
Jung Won Kwon ◽  
In Hee Cho

Background: The medial longitudinal fasciculus (MLF) interacts with eye movement control circuits involved in the adjustment of horizontal, vertical, and torsional eye movements. In this study, we attempted to identify and investigate the anatomical characteristics of the MLF in human brain, using probabilistic diffusion tensor imaging (DTI) tractography. Methods: We recruited 31 normal healthy adults and used a 1.5-T scanner for DTI. To reconstruct MLFs, a seed region of interest (ROI) was placed on the interstitial nucleus of Cajal at the midbrain level. A target ROI was located on the MLF of the medulla in the reticular formation of the medulla. Mean values of fractional anisotropy, mean diffusivity, and tract volumes of MLFs were measured. Results: The component of the MLF originated from the midbrain MLF, descended through the posterior side of the medial lemniscus (ML) and terminated on the MLF of medulla on the posterior side of the ML in the medulla midline. DTI parameters of right and left MLFs were not significantly different. Conclusion: The tract of the MLF in healthy brain was identified by probabilistic DTI tractography. We believe this study will provide basic data and aid future comparative research on lesion or age-induced MLF changes.


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