Literature DB >> 27441037

The brain science interface.

Sean Simpson, Jonathan Burdette, Paul Laurienti.   

Abstract

The human brain consists of billions of neurons clustered into many different regions, each of which work together to give rise to complex human behaviour. But understanding how these regions are networked together - and the effect trauma and disease might have on network functions - requires greater statistical input. Sean L. Simpson, Jonathan H. Burdette and Paul J. Laurienti discuss neuroscience past and present, and how statistics can help its future.

Entities:  

Year:  2015        PMID: 27441037      PMCID: PMC4948029          DOI: 10.1111/j.1740-9713.2015.00843.x

Source DB:  PubMed          Journal:  Signif (Oxf)        ISSN: 1740-9705


  5 in total

Review 1.  The brain as a complex system: using network science as a tool for understanding the brain.

Authors:  Qawi K Telesford; Sean L Simpson; Jonathan H Burdette; Satoru Hayasaka; Paul J Laurienti
Journal:  Brain Connect       Date:  2011

2.  An exponential random graph modeling approach to creating group-based representative whole-brain connectivity networks.

Authors:  Sean L Simpson; Malaak N Moussa; Paul J Laurienti
Journal:  Neuroimage       Date:  2012-01-17       Impact factor: 6.556

3.  A two-part mixed-effects modeling framework for analyzing whole-brain network data.

Authors:  Sean L Simpson; Paul J Laurienti
Journal:  Neuroimage       Date:  2015-03-19       Impact factor: 6.556

4.  Analyzing complex functional brain networks: Fusing statistics and network science to understand the brain*†

Authors:  Sean L Simpson; F DuBois Bowman; Paul J Laurienti
Journal:  Stat Surv       Date:  2013

5.  Exponential random graph modeling for complex brain networks.

Authors:  Sean L Simpson; Satoru Hayasaka; Paul J Laurienti
Journal:  PLoS One       Date:  2011-05-25       Impact factor: 3.240

  5 in total
  3 in total

1.  Mixed Modeling Frameworks for Analyzing Whole-Brain Network Data.

Authors:  Sean L Simpson
Journal:  Methods Mol Biol       Date:  2022

2.  Detecting and Testing Altered Brain Connectivity Networks with K-partite Network Topology.

Authors:  Shuo Chen; F DuBois Bowman; Yishi Xing
Journal:  Comput Stat Data Anal       Date:  2019-07-09       Impact factor: 1.681

3.  Latent and Abnormal Functional Connectivity Circuits in Autism Spectrum Disorder.

Authors:  Shuo Chen; Yishi Xing; Jian Kang
Journal:  Front Neurosci       Date:  2017-03-21       Impact factor: 4.677

  3 in total

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