Literature DB >> 34050791

White matter variability in auditory callosal pathways contributes to variation in the cultural transmission of auditory symbolic systems.

Massimo Lumaca1, Giosuè Baggio2, Peter Vuust3.   

Abstract

The cultural transmission of spoken language and music relies on human capacities for encoding and recalling auditory patterns. In this experiment, we show that interindividual differences in this ability are associated with variation in the organization of cross-callosal white matter pathways. First, high-angular resolution diffusion MRI (dMRI) data were analyzed in a large participant sample (N = 51). Subsequently, these participants underwent a behavioral test that models in the laboratory the cultural transmission of auditory symbolic systems: the signaling game. Cross-callosal and intrahemispheric (arcuate fasciculus) pathways were reconstructed and analyzed using conventional diffusion tensor imaging (DTI) as well as a more advanced dMRI technique: fixel-based analysis (FBA). The DTI metric of fractional anisotropy (FA) in auditory callosal pathways predicted-weeks after scanning-the fidelity of transmission of an artificial tone system. The ability to coherently transmit auditory signals in one signaling game, irrespective of the signals learned during the previous game, was predicted by morphological properties of the fiber bundles in the most anterior portions of the corpus callosum. The current study is the first application of dMRI in the field of cultural transmission, and the first to connect individual characteristics of callosal pathways to core behaviors in the transmission of auditory symbolic systems.

Entities:  

Keywords:  Auditory symbolic systems; Corpus callosum; Cultural transmission; DTI tractography; Fixel-based analysis; Voxel-based analysis

Mesh:

Year:  2021        PMID: 34050791     DOI: 10.1007/s00429-021-02302-y

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


  96 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.  Fiber composition of the human corpus callosum.

Authors:  F Aboitiz; A B Scheibel; R S Fisher; E Zaidel
Journal:  Brain Res       Date:  1992-12-11       Impact factor: 3.252

3.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. 1996.

Authors:  Peter J Basser; Carlo Pierpaoli
Journal:  J Magn Reson       Date:  2011-12       Impact factor: 2.229

4.  Scaling of neural responses to visual and auditory motion in the human cerebellum.

Authors:  Oliver Baumann; Jason B Mattingley
Journal:  J Neurosci       Date:  2010-03-24       Impact factor: 6.167

5.  Plasticity of the superior and middle cerebellar peduncles in musicians revealed by quantitative analysis of volume and number of streamlines based on diffusion tensor tractography.

Authors:  Ihssan A Abdul-Kareem; Andrej Stancak; Laura M Parkes; May Al-Ameen; Jamaan Alghamdi; Faten M Aldhafeeri; Karl Embleton; David Morris; Vanessa Sluming
Journal:  Cerebellum       Date:  2011-09       Impact factor: 3.847

6.  Neuroprediction of future rearrest.

Authors:  Eyal Aharoni; Gina M Vincent; Carla L Harenski; Vince D Calhoun; Walter Sinnott-Armstrong; Michael S Gazzaniga; Kent A Kiehl
Journal:  Proc Natl Acad Sci U S A       Date:  2013-03-27       Impact factor: 11.205

7.  Predictive accuracy in the neuroprediction of rearrest.

Authors:  Eyal Aharoni; Joshua Mallett; Gina M Vincent; Carla L Harenski; Vince D Calhoun; Walter Sinnott-Armstrong; Michael S Gazzaniga; Kent A Kiehl
Journal:  Soc Neurosci       Date:  2014-04-10       Impact factor: 2.083

8.  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

9.  The Insight ToolKit image registration framework.

Authors:  Brian B Avants; Nicholas J Tustison; Michael Stauffer; Gang Song; Baohua Wu; James C Gee
Journal:  Front Neuroinform       Date:  2014-04-28       Impact factor: 4.081

10.  Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction.

Authors:  Matteo Bastiani; Michiel Cottaar; Sean P Fitzgibbon; Sana Suri; Fidel Alfaro-Almagro; Stamatios N Sotiropoulos; Saad Jbabdi; Jesper L R Andersson
Journal:  Neuroimage       Date:  2018-09-26       Impact factor: 6.556

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.