Literature DB >> 27939959

Age-related differences in the structural complexity of subcortical and ventricular structures.

Christopher R Madan1, Elizabeth A Kensinger2.   

Abstract

It has been well established that the volume of several subcortical structures decreases in relation to age. Different metrics of cortical structure (e.g., volume, thickness, surface area, and gyrification) have been shown to index distinct characteristics of interindividual differences; thus, it is important to consider the relation of age to multiple structural measures. Here, we compare age-related differences in subcortical and ventricular volume to those differences revealed with a measure of structural complexity, quantified as fractal dimensionality. Across 3 large data sets, totaling nearly 900 individuals across the adult lifespan (aged 18-94 years), we found greater age-related differences in complexity than volume for the subcortical structures, particularly in the caudate and thalamus. The structural complexity of ventricular structures was not more strongly related to age than volume. These results demonstrate that considering shape-related characteristics improves sensitivity to detect age-related differences in subcortical structures.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Age; Atrophy; Brain morphometry; Fractal dimensionality; Hippocampus; Putamen; Thalamus; Ventricles

Mesh:

Year:  2016        PMID: 27939959      PMCID: PMC5209263          DOI: 10.1016/j.neurobiolaging.2016.10.023

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  79 in total

1.  How long is the coast of britain? Statistical self-similarity and fractional dimension.

Authors:  B Mandelbrot
Journal:  Science       Date:  1967-05-05       Impact factor: 47.728

2.  Fractals in the Neurosciences, Part I: General Principles and Basic Neurosciences.

Authors:  Antonio Di Ieva; Fabio Grizzi; Herbert Jelinek; Andras J Pellionisz; Gabriele Angelo Losa
Journal:  Neuroscientist       Date:  2013-12-20       Impact factor: 7.519

3.  Three-dimensional fractal analysis of the white matter surface from magnetic resonance images of the human brain.

Authors:  S L Free; S M Sisodiya; M J Cook; D R Fish; S D Shorvon
Journal:  Cereb Cortex       Date:  1996 Nov-Dec       Impact factor: 5.357

4.  Effects of age and gender on neuroanatomical volumes.

Authors:  Sachiko Inano; Hidemasa Takao; Naoto Hayashi; Naoki Yoshioka; Harushi Mori; Akira Kunimatsu; Osamu Abe; Kuni Ohtomo
Journal:  J Magn Reson Imaging       Date:  2012-11-13       Impact factor: 4.813

5.  Cortical complexity as a measure of age-related brain atrophy.

Authors:  Christopher R Madan; Elizabeth A Kensinger
Journal:  Neuroimage       Date:  2016-04-19       Impact factor: 6.556

6.  Alcohol use disorders contribute to hippocampal and subcortical shape differences in schizophrenia.

Authors:  Matthew J Smith; Lei Wang; Will Cronenwett; Morris B Goldman; Daniel Mamah; Deanna M Barch; John G Csernansky
Journal:  Schizophr Res       Date:  2011-06-12       Impact factor: 4.939

7.  BrainPrint: a discriminative characterization of brain morphology.

Authors:  Christian Wachinger; Polina Golland; William Kremen; Bruce Fischl; Martin Reuter
Journal:  Neuroimage       Date:  2015-01-19       Impact factor: 6.556

8.  Brain development and aging: overlapping and unique patterns of change.

Authors:  Christian K Tamnes; Kristine B Walhovd; Anders M Dale; Ylva Østby; Håkon Grydeland; George Richardson; Lars T Westlye; J Cooper Roddey; Donald J Hagler; Paulina Due-Tønnessen; Dominic Holland; Anders M Fjell
Journal:  Neuroimage       Date:  2012-12-12       Impact factor: 6.556

9.  The significance of age-related enlargement of the cerebral ventricles in healthy men and women measured by quantitative computed X-ray tomography.

Authors:  J A Kaye; C DeCarli; J S Luxenberg; S I Rapoport
Journal:  J Am Geriatr Soc       Date:  1992-03       Impact factor: 5.562

10.  Object and spatial mnemonic interference differentially engage lateral and medial entorhinal cortex in humans.

Authors:  Zachariah M Reagh; Michael A Yassa
Journal:  Proc Natl Acad Sci U S A       Date:  2014-09-22       Impact factor: 11.205

View more
  14 in total

1.  Predicting age from cortical structure across the lifespan.

Authors:  Christopher R Madan; Elizabeth A Kensinger
Journal:  Eur J Neurosci       Date:  2018-02-12       Impact factor: 3.386

2.  Longitudinal Effects of Combination Antiretroviral Therapy on Cognition and Neuroimaging Biomarkers in Treatment-Naive People With HIV.

Authors:  Miriam T Weber; Alan Finkelstein; Md Nasir Uddin; Elizabeth Asiago Reddy; Roberto C Arduino; Lu Wang; Madalina E Tivarus; Jianhui Zhong; Xing Qiu; Giovanni Schifitto
Journal:  Neurology       Date:  2022-06-22       Impact factor: 11.800

3.  Advances in Studying Brain Morphology: The Benefits of Open-Access Data.

Authors:  Christopher R Madan
Journal:  Front Hum Neurosci       Date:  2017-08-04       Impact factor: 3.169

4.  Test-retest reliability of brain morphology estimates.

Authors:  Christopher R Madan; Elizabeth A Kensinger
Journal:  Brain Inform       Date:  2017-01-05

Review 5.  Selective vulnerabilities and biomarkers in neurocognitive aging.

Authors:  Zachariah Reagh; Michael Yassa
Journal:  F1000Res       Date:  2017-04-13

6.  The Association of Aging and Aerobic Fitness With Memory.

Authors:  Alexis M Bullock; Allison L Mizzi; Ana Kovacevic; Jennifer J Heisz
Journal:  Front Aging Neurosci       Date:  2018-03-09       Impact factor: 5.750

7.  Age differences in head motion and estimates of cortical morphology.

Authors:  Christopher R Madan
Journal:  PeerJ       Date:  2018-07-27       Impact factor: 2.984

8.  Robust estimation of sulcal morphology.

Authors:  Christopher R Madan
Journal:  Brain Inform       Date:  2019-06-11

Review 9.  Curcuma longa L. extract improves the cortical neural connectivity during the aging process.

Authors:  Gonzalo Flores
Journal:  Neural Regen Res       Date:  2017-06       Impact factor: 5.135

10.  Age is reflected in the Fractal Dimensionality of MRI Diffusion Based Tractography.

Authors:  Gernot Reishofer; Fritz Studencnik; Karl Koschutnig; Hannes Deutschmann; Helmut Ahammer; Guilherme Wood
Journal:  Sci Rep       Date:  2018-04-03       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.