Literature DB >> 35657419

Modelling the laminar connectome of the human brain.

Ittai Shamir1, Omri Tomer2, Ronnie Krupnik2, Yaniv Assaf3,2.   

Abstract

The human connectome is the complete structural description of the network of connections and elements that form the 'wiring diagram' of the brain. Due to the current scarcity of information regarding laminar end points of white matter tracts inside cortical grey matter, tractography remains focused on cortical partitioning into regions, while ignoring radial partitioning into laminar components. To overcome this biased representation of the cortex as a single homogenous unit, we use a recent data-derived model of cortical laminar connectivity, which has been further explored and corroborated in the macaque brain by comparison to published studies. The model integrates multimodal MRI imaging datasets of both white matter connectivity and grey matter laminar composition into a laminar-level connectome. In this study, we model the laminar connectome of healthy human brains (N = 30) and explore them via a set of complex network measures. Our analysis demonstrates a subdivision of network hubs that appear in the standard connectome into each individual component of the laminar connectome, giving a fresh look into the role of laminar components in cortical connectivity and offering new prospects in the fields of both structural and functional connectivity.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Anatomical mapping; Brain network analysis; Computational models; Connectomics; Cortical layers; Neuronal structures

Mesh:

Year:  2022        PMID: 35657419     DOI: 10.1007/s00429-022-02513-x

Source DB:  PubMed          Journal:  Brain Struct Funct        ISSN: 1863-2653            Impact factor:   3.270


  34 in total

1.  How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging.

Authors:  Jesper L R Andersson; Stefan Skare; John Ashburner
Journal:  Neuroimage       Date:  2003-10       Impact factor: 6.556

2.  Imaging cortical anatomy by high-resolution MR at 3.0T: detection of the stripe of Gennari in visual area 17.

Authors:  Emmanuel L Barbier; Sean Marrett; Adrian Danek; Alexander Vortmeyer; Peter van Gelderen; Jeff Duyn; Peter Bandettini; Jordan Grafman; Alan P Koretsky
Journal:  Magn Reson Med       Date:  2002-10       Impact factor: 4.668

3.  In vivo myeloarchitectonic analysis of human striate and extrastriate cortex using magnetic resonance imaging.

Authors:  V P Clark; E Courchesne; M Grafe
Journal:  Cereb Cortex       Date:  1992 Sep-Oct       Impact factor: 5.357

Review 4.  Neuronal circuits of the neocortex.

Authors:  Rodney J Douglas; Kevan A C Martin
Journal:  Annu Rev Neurosci       Date:  2004       Impact factor: 12.449

Review 5.  The economy of brain network organization.

Authors:  Ed Bullmore; Olaf Sporns
Journal:  Nat Rev Neurosci       Date:  2012-04-13       Impact factor: 34.870

6.  Visualization of cortical lamination patterns with magnetic resonance imaging.

Authors:  Daniel Barazany; Yaniv Assaf
Journal:  Cereb Cortex       Date:  2011-10-08       Impact factor: 5.357

Review 7.  The role of diffusion MRI in neuroscience.

Authors:  Yaniv Assaf; Heidi Johansen-Berg; Michel Thiebaut de Schotten
Journal:  NMR Biomed       Date:  2017-07-11       Impact factor: 4.044

8.  Conservation of brain connectivity and wiring across the mammalian class.

Authors:  Yaniv Assaf; Arieli Bouznach; Omri Zomet; Assaf Marom; Yossi Yovel
Journal:  Nat Neurosci       Date:  2020-06-08       Impact factor: 24.884

9.  Julich-Brain: A 3D probabilistic atlas of the human brain's cytoarchitecture.

Authors:  Katrin Amunts; Hartmut Mohlberg; Sebastian Bludau; Karl Zilles
Journal:  Science       Date:  2020-07-30       Impact factor: 47.728

10.  Why diffusion tensor MRI does well only some of the time: variance and covariance of white matter tissue microstructure attributes in the living human brain.

Authors:  Silvia De Santis; Mark Drakesmith; Sonya Bells; Yaniv Assaf; Derek K Jones
Journal:  Neuroimage       Date:  2013-12-14       Impact factor: 6.556

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