Literature DB >> 30305712

Imaging-based parcellations of the human brain.

Simon B Eickhoff1,2, B T Thomas Yeo3,4,5,6, Sarah Genon7,8.   

Abstract

A defining aspect of brain organization is its spatial heterogeneity, which gives rise to multiple topographies at different scales. Brain parcellation - defining distinct partitions in the brain, be they areas or networks that comprise multiple discontinuous but closely interacting regions - is thus fundamental for understanding brain organization and function. The past decade has seen an explosion of in vivo MRI-based approaches to identify and parcellate the brain on the basis of a wealth of different features, ranging from local properties of brain tissue to long-range connectivity patterns, in addition to structural and functional markers. Given the high diversity of these various approaches, assessing the convergence and divergence among these ensuing maps is a challenge. Inter-individual variability adds to this challenge but also provides new opportunities when coupled with cross-species and developmental parcellation studies.

Entities:  

Mesh:

Year:  2018        PMID: 30305712     DOI: 10.1038/s41583-018-0071-7

Source DB:  PubMed          Journal:  Nat Rev Neurosci        ISSN: 1471-003X            Impact factor:   34.870


  77 in total

1.  Beyond consensus: Embracing heterogeneity in curated neuroimaging meta-analysis.

Authors:  Gia H Ngo; Simon B Eickhoff; Minh Nguyen; Gunes Sevinc; Peter T Fox; R Nathan Spreng; B T Thomas Yeo
Journal:  Neuroimage       Date:  2019-06-20       Impact factor: 6.556

Review 2.  Machine learning in resting-state fMRI analysis.

Authors:  Meenakshi Khosla; Keith Jamison; Gia H Ngo; Amy Kuceyeski; Mert R Sabuncu
Journal:  Magn Reson Imaging       Date:  2019-06-05       Impact factor: 2.546

3.  Neural activity during working memory encoding, maintenance, and retrieval: A network-based model and meta-analysis.

Authors:  Hongkeun Kim
Journal:  Hum Brain Mapp       Date:  2019-08-02       Impact factor: 5.038

4.  Multimodal Parcellations and Extensive Behavioral Profiling Tackling the Hippocampus Gradient.

Authors:  Anna Plachti; Simon B Eickhoff; Felix Hoffstaedter; Kaustubh R Patil; Angela R Laird; Peter T Fox; Katrin Amunts; Sarah Genon
Journal:  Cereb Cortex       Date:  2019-12-17       Impact factor: 5.357

5.  Evaluation of the 3D fractal dimension as a marker of structural brain complexity in multiple-acquisition MRI.

Authors:  Stephan Krohn; Martijn Froeling; Alexander Leemans; Dirk Ostwald; Pablo Villoslada; Carsten Finke; Francisco J Esteban
Journal:  Hum Brain Mapp       Date:  2019-05-15       Impact factor: 5.038

Review 6.  Towards a Universal Taxonomy of Macro-scale Functional Human Brain Networks.

Authors:  Lucina Q Uddin; B T Thomas Yeo; R Nathan Spreng
Journal:  Brain Topogr       Date:  2019-11-09       Impact factor: 3.020

7.  BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Authors:  Reinder Vos de Wael; Oualid Benkarim; Jonathan Smallwood; Boris C Bernhardt; Casey Paquola; Sara Lariviere; Jessica Royer; Shahin Tavakol; Ting Xu; Seok-Jun Hong; Georg Langs; Sofie Valk; Bratislav Misic; Michael Milham; Daniel Margulies
Journal:  Commun Biol       Date:  2020-03-05

Review 8.  Macroscopic gradients of synaptic excitation and inhibition in the neocortex.

Authors:  Xiao-Jing Wang
Journal:  Nat Rev Neurosci       Date:  2020-02-06       Impact factor: 34.870

Review 9.  Challenges and future directions for representations of functional brain organization.

Authors:  Janine Bijsterbosch; Samuel J Harrison; Saad Jbabdi; Mark Woolrich; Christian Beckmann; Stephen Smith; Eugene P Duff
Journal:  Nat Neurosci       Date:  2020-10-26       Impact factor: 24.884

10.  Space-independent community and hub structure of functional brain networks.

Authors:  Farnaz Zamani Esfahlani; Maxwell A Bertolero; Danielle S Bassett; Richard F Betzel
Journal:  Neuroimage       Date:  2020-02-17       Impact factor: 6.556

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