Article
Neurosciences
Xuehu Wei, Helyne Adamson, Matthias Schwendemann, Tomas Goucha, Angela D. Friederici, Alfred Anwander
Summary: The current study investigated the differences in brain white matter connections between native speakers of German and Arabic. German speakers showed stronger connectivity in a language network associated with complex syntax processing, while Arabic speakers exhibited stronger connectivity between semantic language regions and inter-hemispheric connections. These findings suggest that the structural language connectome is influenced by the linguistic characteristics of the native language.
Article
Neurosciences
Philipp J. Koch, Gabriel Girard, Julia Bruegger, Andeol G. Cadic-Melchior, Elena Beanato, Chang-Hyun Park, Takuya Morishita, Maximilian J. Wessel, Marco Pizzolato, Erick J. Canales-Rodriguez, Elda Fischi-Gomez, Simona Schiavi, Alessandro Daducci, Gian Franco Piredda, Tom Hilbert, Tobias Kober, Jean-Philippe Thiran, Friedhelm C. Hummel
Summary: This study compares the performance of two microstructure-informed Tractography methods and finds that although raw tractograms are vulnerable to false-positive connections, they have high reproducibility. Using these techniques can increase the biological meaning of estimated fascicles, and connectivity pre-processing techniques are important for improving subject specificity.
Review
Radiology, Nuclear Medicine & Medical Imaging
Chun-Hung Yeh, Derek K. Jones, Xiaoyun Liang, Maxime Descoteaux, Alan Connelly
Summary: Diffusion MRI-based tractography is commonly used for inferring the structural brain connectome, and applying graph theory to analyze these connectomes provides important opportunities to explore connectivity patterns. However, challenges exist in this framework, particularly regarding methodological and biological plausibility.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2021)
Article
Neurosciences
Zhuopin Sun, Steven Meikle, Fernando Calamante
Summary: The CONNectome-based Non-Local Means (CONN-NLM) filter exploits synergies between dMRI-derived structural connectivity and PET intensity information to denoise PET images. The method improves PET image quality by reducing noise while preserving lesion contrasts, outperforming filters that do not use dMRI information. CONN-NLM represents a new avenue to exploit synergies between MRI and PET for more informative and accurate PET smoothing.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Neurosciences
Michiel Cottaar, Matteo Bastiani, Nikhil Boddu, Matthew F. Glasser, Suzanne Haber, David C. van Essen, Stamatios N. Sotiropoulos, Saad Jbabdi
Summary: Many brain imaging studies measure structural connectivity with diffusion tractography, but biases in the data can limit accuracy. A new algorithm reduces these biases by modeling fiber density and orientation.
Article
Neurosciences
Lidia Konopleva, Kamil A. Il'yasov, Shi Jia Teo, Volker A. Coenen, Christoph P. Kaller, Marco Reisert
Summary: This study introduces a novel method to improve the intra-subject reproducibility of quantitative estimates of structural connectivity strength by reducing the dimensionality of the connectome using Principal Component Analysis. The proposed method was found to be robust to structural variability in the data.
Article
Psychology, Developmental
Judit Ciarrusta, Daan Christiaens, Sean P. Fitzgibbon, Ralica Dimitrova, Jana Hutter, Emer Hughes, Eugene Duff, Anthony N. Price, Lucilio Cordero-Grande, J. -Donald Tournier, Daniel Rueckert, Joseph V. Hajnal, Tomoki Arichi, Grainne McAlonan, David Edwards, Dafnis Batalle
Summary: The study found that structural connectivity in early life is more stable and can represent a potential connectome fingerprint of an individual. In contrast, the similarity between functional connectomes of the same subject at different time points is low.
DEVELOPMENTAL COGNITIVE NEUROSCIENCE
(2022)
Article
Critical Care Medicine
Timo Roine, Mehrbod Mohammadian, Jussi Hirvonen, Timo Kurki, Jussi P. Posti, Riikka S. K. Takala, Virginia F. Newcombe, Jussi Tallus, Ari J. Katila, Henna-Riikka Maanpaeae, Janek Frantzen, David Menon, Olli Tenovuo
Summary: We investigated the topology of structural brain connectivity networks and found that both global and local network properties are associated with outcome after mild traumatic brain injury. Higher normalized global efficiency, degree, and strength as well as lower small-worldness are correlated with better outcome. The local network properties of the left putamen and the left postcentral gyrus show the most prominent correlations with outcome.
JOURNAL OF NEUROTRAUMA
(2022)
Article
Anatomy & Morphology
Sang-Han Choi, Gangwon Jeong, Young-Eun Hwang, Yong-Bo Kim, Haigun Lee, Zang-Hee Cho
Summary: This study introduced a novel cortical mapping method based on three categories of nerve fibers: projection, commissural, and association fibers. Analysis of MRI data revealed that the majority of nerve fibers in the brain are association fibers, with specific regions showing distinct distributions of projection and commissural fibers. Hemispheric asymmetries in fiber density were also observed in certain brain areas.
FRONTIERS IN NEUROANATOMY
(2021)
Article
Neurosciences
Chengyuan Wu, Francisca Ferreira, Michael Fox, Noam Harel, Jona Hattangadi-Gluth, Andreas Horn, Saad Jbabdi, Joshua Kahan, Ashwini Oswal, Sameer A. Sheth, Yanmei Tie, Vejay Vakharia, Ludvic Zrinzo, Harith Akram
Summary: Advances in computational neuroimaging techniques have expanded the arsenal of imaging tools available for clinical neuroscience, allowing for identification of therapeutic targets, preservation of eloquent brain regions, and insight into pathological processes and treatments. However, factors such as data quality, processing methodology, and statistical models can impact results. Lack of standardization in data acquisition and processing has led to issues with reproducibility.
Article
Neurosciences
Tanzil Mahmud Arefin, Choong Heon Lee, Zifei Liang, Harikrishna Rallapalli, Youssef Z. Wadghiri, Daniel H. Turnbull, Jiangyang Zhang
Summary: In this study, we aimed to optimize the imaging and computational pipeline to achieve the best possible spatial overlaps between dMRI tractography and tracer-based axonal projection maps in the mouse brain corticothalamic network. We developed a dMRI-based atlas of the mouse forebrain and reconstructed detailed corticothalamic structural connectivity matrices using different imaging and tractography parameters. Our results suggest that these parameters significantly affect tractography outcomes and our atlas can be used to investigate macroscopic structural connectivity in the mouse brain.
Article
Clinical Neurology
Xin-Yuan Chen, Zi-Qiang Huang, Wei Lin, Meng-Cheng Li, Zhi-Xian Ye, Yu-Sen Qiu, Xiao-Yue Xia, Na-Ping Chen, Jian-Ping Hu, Shi-Rui Gan, Qun-Lin Chen
Summary: This study investigates changes in the white matter structural motor network in Spinocerebellar ataxia type 3 (SCA3) and their relationship with disease severity. The results show that these changes start before ataxia onset and increase with disease progression. The findings suggest that global network topological measures of the white matter motor network could be a promising imaging biomarker for disease severity in SCA3/MJD.
ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY
(2023)
Article
Neurosciences
Ronnie Krupnik, Yossi Yovel, Yaniv Assaf
Summary: The structure of the brain's connectome has a significant impact on information transfer efficiency, with a trade-off between inner hemispheric and interhemispheric connectivity. Certain brain regions, such as the cingulate cortex and frontal areas, play a key role in this phenomenon. The connectivity conservation phenomenon observed in the study may explain the functional, behavioral, and cognitive variability among different brains.
JOURNAL OF NEUROSCIENCE
(2021)
Article
Neurosciences
Colin R. Buchanan, Susana Munoz Maniega, Maria C. Valdes Hernandez, Lucia Ballerini, Gayle Barclay, Adele M. Taylor, Tom C. Russ, Elliot M. Tucker-Drob, Joanna M. Wardlaw, Ian J. Deary, Mark E. Bastin, Simon R. Cox
Summary: The study found differences in MRI measurements between different scanners, but good consistency. Between-scanner consistency was good to excellent for global volumes and some brain regions, fair for white matter tracts and cortical surface measures, and improved for whole-brain networks. While individual network connections showed poor consistency, overall global metrics showed good to excellent consistency after adjustments.
HUMAN BRAIN MAPPING
(2021)
Article
Neurosciences
Tingting Liu, Zhiyong Zhao, Yuqing You, Fusheng Gao, Ying Lv, Mingyan Li, Chai Ji, Can Lai, Hongxi Zhang, Dan Wu
Summary: This study aimed to investigate the developmental trajectory of structural connectivity in preterm-born infants and explore the potential function correlation associated with network properties. The findings revealed a unique developmental pattern of structural networks in early infancy, with enhanced efficiency and small-worldness, and a significant correlation between local efficiency and late language comprehension.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Fan Huang, Behdad Dashtbozorg, Bart M. ter Haar Romeny
MACHINE VISION AND APPLICATIONS
(2018)
Article
Computer Science, Interdisciplinary Applications
Fan Huang, Behdad Dashtbozorg, Tao Tan, Bart M. ter Haar Romeny
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2018)
Article
Engineering, Biomedical
Jiong Zhang, Erik Bekkers, Da Chen, Tos T. J. M. Berendschot, Jan Schouten, Josien P. W. Pluim, Yonggang Shi, Behdad Dashtbozorg, Bart M. ter Haar Romeny
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2018)
Article
Computer Science, Artificial Intelligence
Samaneh Abbasi-Sureshjani, Marta Favali, Giovanna Citti, Alessandro Sarti, Bart M. ter Haar Romeny
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2018)
Article
Computer Science, Artificial Intelligence
Behdad Dashtbozorg, Jiong Zhang, Fan Huang, Bart M. ter Haar Romeny
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2018)
Article
Computer Science, Artificial Intelligence
Erik Johannes Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2018)
Article
Biochemical Research Methods
Zhang Li, Fan Huang, Jiong Zhang, Behdad Dashtbozorg, Samaneh Abbasi-Sureshjani, Yue Sun, Xi Long, Qifeng Yu, Bart ter Haar Romeny, Tao Tan
BIOMEDICAL OPTICS EXPRESS
(2018)
Article
Endocrinology & Metabolism
Wenjie Li, Miranda T. Schram, Tos T. J. M. Berendschot, Carroll A. B. Webers, Abraham A. Kroon, Carla J. H. van der Kallen, Ronald M. A. Henry, Nicolaas C. Schaper, Fan Huang, Behdad Dashtbozorg, Tao Tan, Jiong Zhang, Samaneh Abbasi-Sureshjani, Bart M. Ter Haar Romeny, Coen D. A. Stehouwer, Alfons J. H. M. Houben
Article
Biochemical Research Methods
Fan Huang, Tao Tan, Behdad Dashtbozorg, Yi Zhou, Bart M. Ter Haar Romeny
IEEE TRANSACTIONS ON NANOBIOSCIENCE
(2020)
Article
Engineering, Biomedical
Jiong Zhang, Behdad Dashtbozorg, Fan Huang, Tao Tan, B. M. ter Haar Romeny
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Bart M. ter Haar Romeny
2018 SIGNAL PROCESSING: ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, AND APPLICATIONS (SPA)
(2018)
Meeting Abstract
Endocrinology & Metabolism
W. Li, M. Schram, T. Berendschot, J. Schouten, A. Kroon, C. van der Kallen, R. Henry, A. Koster, P. Dagnelie, N. Schaper, F. Huang, B. ter Haar Romeny, C. Stehouwer, A. Houben
Proceedings Paper
Computer Science, Artificial Intelligence
Jiong Zhang, Behdad Dashtbozorg, Fan Huang, Tos T. J. M. Berendschot, Bart M. ter Haar Romeny
Proceedings Paper
Computer Science, Artificial Intelligence
Fan Huang, Behdad Dashtbozorg, Jiong Zhang, Alexander Yeung, Tos T. J. M. Berendschot, Bart M. ter Haar Romeny
Proceedings Paper
Computer Science, Artificial Intelligence
Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart M. ter Haar Romeny, Francois Fleuret