Literature DB >> 30014279

Towards Differential Connectomics with NeuroVIISAS.

Sebastian Schwanke1, Jörg Jenssen1, Peter Eipert1, Oliver Schmitt2.   

Abstract

The comparison of connectomes is an essential step to identify changes in structural and functional neuronal networks. However, the connectomes themselves as well as the comparisons of connectomes could be manifold. In most applications, comparisons of connectomes are applied to specific sets of data. In many studies collections of scripts are applied optimized for certain species (non-generic approaches) or diseases (control versus disease group connectomes). These collections of scripts have a limited functionality which do not support functional and topographic mappings of connectomes (hemispherical asymmetries, peripheral nervous system). The platform-independent and generic neuroVIISAS framework is built to circumvent limitations that come with variants of nomenclatures, connectivity lists and connectional hierarchies as well as restrictions to structural connectome analyses. A new analytical module is introduced into the framework to compare different types of connectomes and different representations of the same connectome within a unique software environment. As an example a differential analysis of the partial connectome of the laboratory rat that is based on virus tract tracing with the same regions of non-virus tract tracing has been performed. A relatively large connectional coherence between the two different techniques was found. However, some detected connections are described by virus tract-tracing only.

Entities:  

Keywords:  Connectome; Differential connectomics; Graph analysis; Multidimensional connectomes; Nervous system; Neuronal networks; Rat; Visualization

Mesh:

Year:  2019        PMID: 30014279     DOI: 10.1007/s12021-018-9389-6

Source DB:  PubMed          Journal:  Neuroinformatics        ISSN: 1539-2791


  96 in total

1.  neuroVIISAS: approaching multiscale simulation of the rat connectome.

Authors:  Oliver Schmitt; Peter Eipert
Journal:  Neuroinformatics       Date:  2012-07

2.  Principal components of functional connectivity: a new approach to study dynamic brain connectivity during rest.

Authors:  Nora Leonardi; Jonas Richiardi; Markus Gschwind; Samanta Simioni; Jean-Marie Annoni; Myriam Schluep; Patrik Vuilleumier; Dimitri Van De Ville
Journal:  Neuroimage       Date:  2013-07-18       Impact factor: 6.556

3.  Connectomic reconstruction of the inner plexiform layer in the mouse retina.

Authors:  Moritz Helmstaedter; Kevin L Briggman; Srinivas C Turaga; Viren Jain; H Sebastian Seung; Winfried Denk
Journal:  Nature       Date:  2013-08-08       Impact factor: 49.962

Review 4.  The ontogeny of the human connectome: development and dynamic changes of brain connectivity across the life span.

Authors:  Guusje Collin; Martijn P van den Heuvel
Journal:  Neuroscientist       Date:  2013-09-18       Impact factor: 7.519

5.  Controllability of complex networks.

Authors:  Yang-Yu Liu; Jean-Jacques Slotine; Albert-László Barabási
Journal:  Nature       Date:  2011-05-12       Impact factor: 49.962

6.  Developmental Changes in Brain Network Hub Connectivity in Late Adolescence.

Authors:  Simon T E Baker; Dan I Lubman; Murat Yücel; Nicholas B Allen; Sarah Whittle; Ben D Fulcher; Andrew Zalesky; Alex Fornito
Journal:  J Neurosci       Date:  2015-06-17       Impact factor: 6.167

Review 7.  A fourth generation of neuroanatomical tracing techniques: exploiting the offspring of genetic engineering.

Authors:  Floris G Wouterlood; Bernard Bloem; Huibert D Mansvelder; Antonio Luchicchi; Karl Deisseroth
Journal:  J Neurosci Methods       Date:  2014-08-11       Impact factor: 2.390

8.  A DTI tractography analysis of infralimbic and prelimbic connectivity in the mouse using high-throughput MRI.

Authors:  David A Gutman; Orion P Keifer; Matthew E Magnuson; Dennis C Choi; Waqas Majeed; Shella Keilholz; Kerry J Ressler
Journal:  Neuroimage       Date:  2012-07-14       Impact factor: 6.556

9.  Paintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data.

Authors:  Fernando García-Alcalde; Federico García-López; Joaquín Dopazo; Ana Conesa
Journal:  Bioinformatics       Date:  2010-11-23       Impact factor: 6.937

10.  A predictive model of the cat cortical connectome based on cytoarchitecture and distance.

Authors:  Sarah F Beul; Simon Grant; Claus C Hilgetag
Journal:  Brain Struct Funct       Date:  2014-07-26       Impact factor: 3.270

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  2 in total

1.  The brainstem connectome database.

Authors:  Oliver Schmitt; Peter Eipert; Frauke Ruß; Julia Beier; Kanar Kadir; Anja Horn
Journal:  Sci Data       Date:  2022-04-12       Impact factor: 6.444

2.  Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI.

Authors:  Maged Goubran; Christoph Leuze; Brian Hsueh; Markus Aswendt; Li Ye; Qiyuan Tian; Michelle Y Cheng; Ailey Crow; Gary K Steinberg; Jennifer A McNab; Karl Deisseroth; Michael Zeineh
Journal:  Nat Commun       Date:  2019-12-03       Impact factor: 14.919

  2 in total

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