Literature DB >> 32428883

Connectomic consistency: a systematic stability analysis of structural and functional connectivity.

Yusuf Osmanlıoğlu1, Jacob A Alappatt, Drew Parker, Ragini Verma.   

Abstract

OBJECTIVE: Connectomics, the study of brain connectivity, has become an indispensable tool in neuroscientific research as it provides insights into brain organization. Connectomes are generated using different modalities such as diffusion MRI to capture structural organization of the brain or functional MRI to elaborate brain's 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 comparative understanding on how much variation should be expected in the two modalities, both between people and within a single person across scans. APPROACH: In this study, we systematically analyzed the consistency of connectomes, that is the similarity between connectomes in terms of individual connections between brain regions and in terms of overall network topology. We present a comprehensive study of consistency in connectomes for a single subject examined longitudinally and across a large cohort of subjects cross-sectionally, in structure and function separately. Within structural connectomes, we compared connectomes generated by different tracking algorithms, parcellations, edge weighting schemes, and edge pruning techniques. In functional connectomes, we compared full, positive, and negative connectivity separately along with thresholding of weak edges. We evaluated consistency using correlation (incorporating information at the level of individual edges) and graph matching accuracy (evaluating connectivity at the level of network topology). We also examined the consistency of connectomes that are generated using different communication schemes. MAIN
RESULTS: 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. SIGNIFICANCE: 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.

Entities:  

Mesh:

Year:  2020        PMID: 32428883      PMCID: PMC7584380          DOI: 10.1088/1741-2552/ab947b

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  68 in total

1.  Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information.

Authors:  Robert E Smith; Jacques-Donald Tournier; Fernando Calamante; Alan Connelly
Journal:  Neuroimage       Date:  2012-06-13       Impact factor: 6.556

2.  Correlations and anticorrelations in resting-state functional connectivity MRI: a quantitative comparison of preprocessing strategies.

Authors:  Andreas Weissenbacher; Christian Kasess; Florian Gerstl; Rupert Lanzenberger; Ewald Moser; Christian Windischberger
Journal:  Neuroimage       Date:  2009-05-13       Impact factor: 6.556

3.  Predicting human resting-state functional connectivity from structural connectivity.

Authors:  C J Honey; O Sporns; L Cammoun; X Gigandet; J P Thiran; R Meuli; P Hagmann
Journal:  Proc Natl Acad Sci U S A       Date:  2009-02-02       Impact factor: 11.205

4.  Is removal of weak connections necessary for graph-theoretical analysis of dense weighted structural connectomes from diffusion MRI?

Authors:  Oren Civier; Robert Elton Smith; Chun-Hung Yeh; Alan Connelly; Fernando Calamante
Journal:  Neuroimage       Date:  2019-03-04       Impact factor: 6.556

5.  Estimating false positives and negatives in brain networks.

Authors:  Marcel A de Reus; Martijn P van den Heuvel
Journal:  Neuroimage       Date:  2013-01-05       Impact factor: 6.556

6.  There is no single functional atlas even for a single individual: Functional parcel definitions change with task.

Authors:  Mehraveh Salehi; Abigail S Greene; Amin Karbasi; Xilin Shen; Dustin Scheinost; R Todd Constable
Journal:  Neuroimage       Date:  2019-11-15       Impact factor: 6.556

Review 7.  Neuroimaging of the Philadelphia neurodevelopmental cohort.

Authors:  Theodore D Satterthwaite; Mark A Elliott; Kosha Ruparel; James Loughead; Karthik Prabhakaran; Monica E Calkins; Ryan Hopson; Chad Jackson; Jack Keefe; Marisa Riley; Frank D Mentch; Patrick Sleiman; Ragini Verma; Christos Davatzikos; Hakon Hakonarson; Ruben C Gur; Raquel E Gur
Journal:  Neuroimage       Date:  2013-08-03       Impact factor: 6.556

8.  The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

Authors:  Kevin Murphy; Rasmus M Birn; Daniel A Handwerker; Tyler B Jones; Peter A Bandettini
Journal:  Neuroimage       Date:  2008-10-11       Impact factor: 6.556

9.  An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging.

Authors:  Jesper L R Andersson; Stamatios N Sotiropoulos
Journal:  Neuroimage       Date:  2015-10-20       Impact factor: 6.556

10.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

View more
  5 in total

1.  Graph Matching Based Connectomic Biomarker with Learning for Brain Disorders.

Authors:  Rui Sherry Shen; Jacob A Alappatt; Drew Parker; Junghoon Kim; Ragini Verma; Yusuf Osmanlıoğlu
Journal:  Uncertain Safe Util Mach Learn Med Imaging Graph Biomed Image Anal (2020)       Date:  2020-10-05

Review 2.  Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.

Authors:  Fan Zhang; Alessandro Daducci; Yong He; Simona Schiavi; Caio Seguin; Robert E Smith; Chun-Hung Yeh; Tengda Zhao; Lauren J O'Donnell
Journal:  Neuroimage       Date:  2022-01-01       Impact factor: 7.400

3.  Functional connectome reorganization relates to post-stroke motor recovery and structural and functional disconnection.

Authors:  Emily R Olafson; Keith W Jamison; Elizabeth M Sweeney; Hesheng Liu; Danhong Wang; Joel E Bruss; Aaron D Boes; Amy Kuceyeski
Journal:  Neuroimage       Date:  2021-10-09       Impact factor: 7.400

4.  Connectomic assessment of injury burden and longitudinal structural network alterations in moderate-to-severe traumatic brain injury.

Authors:  Yusuf Osmanlıoğlu; Drew Parker; Jacob A Alappatt; James J Gugger; Ramon R Diaz-Arrastia; John Whyte; Junghoon J Kim; Ragini Verma
Journal:  Hum Brain Mapp       Date:  2022-04-29       Impact factor: 5.399

5.  Associations between early-life stress exposure and internalizing symptomatology during the COVID-19 pandemic: Assessing the role of neurobehavioral mediators.

Authors:  Jordan C Foster; Emily M Cohodes; Alexis E Brieant; Sarah McCauley; Paola Odriozola; Sadie J Zacharek; Jasmyne C Pierre; H R Hodges; Sahana Kribakaran; Jason T Haberman; Bailey Holt-Gosselin; Dylan G Gee
Journal:  Biol Psychiatry Glob Open Sci       Date:  2022-08-06
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.