scholarly journals Gray Matter Volume and Cognitive Performance During Normal Aging. A Voxel-Based Morphometry Study

2018 ◽  
Vol 10 ◽  
Author(s):  
Stephen Ramanoël ◽  
Elena Hoyau ◽  
Louise Kauffmann ◽  
Félix Renard ◽  
Cédric Pichat ◽  
...  
Keyword(s):  
Cognitive Performance ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Normal Aging ◽  
Voxel Based Morphometry ◽  
Matter Volume

CHARACTERIZATION OF COGNITIVE PERFORMANCE, GRAY MATTER VOLUME AND WHITE MATTER MICROSTRUCTURE IN COGNITIVELY UNIMPAIRED ADULTS WITH INSOMNIA SYMPTOMS

2019 ◽  
Vol 15 (7) ◽  
pp. P207-P209
Author(s):  
Oriol Grau-Rivera ◽  
Grégory Operto ◽  
Carles Falcon ◽  
Raffaele Cacciaglia ◽  
Gonzalo Sánchez-Benavides ◽  
...  
Keyword(s):  
White Matter ◽  
Cognitive Performance ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Matter Volume ◽  
White Matter Microstructure ◽  
Insomnia Symptoms

Reproducibility of Brain Volume Changes in Longitudinal Voxel-Based Morphometry Between Non-Accelerated and Accelerated Magnetic Resonance Imaging

2021 ◽  
pp. 1-10
Author(s):  
Hidemasa Takao ◽  
Shiori Amemiya ◽  
Osamu Abe ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Elderly Subjects ◽  
Voxel Based Morphometry ◽  
Volume Changes ◽  
Matter Volume ◽  
Healthy Elderly

Background: Scan acceleration techniques, such as parallel imaging, can reduce scan times, but reliability is essential to implement these techniques in neuroimaging. Objective: To evaluate the reproducibility of the longitudinal changes in brain morphology determined by longitudinal voxel-based morphometry (VBM) between non-accelerated and accelerated magnetic resonance images (MRI) in normal aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Methods: Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2 database, comprising subjects who underwent non-accelerated and accelerated structural T1-weighted MRI at screening and at a 2-year follow-up on 3.0 T Philips scanners, we examined the reproducibility of longitudinal gray matter volume changes determined by longitudinal VBM processing between non-accelerated and accelerated imaging in 50 healthy elderly subjects, 54 MCI patients, and eight AD patients. Results: The intraclass correlation coefficient (ICC) maps differed among the three groups. The mean ICC was 0.72 overall (healthy elderly, 0.63; MCI, 0.75; AD, 0.63), and the ICC was good to excellent (0.6–1.0) for 81.4%of voxels (healthy elderly, 64.8%; MCI, 85.0%; AD, 65.0%). The differences in image quality (head motion) were not significant (Kruskal–Wallis test, p = 0.18) and the within-subject standard deviations of longitudinal gray matter volume changes were similar among the groups. Conclusion: The results indicate that the reproducibility of longitudinal gray matter volume changes determined by VBM between non-accelerated and accelerated MRI is good to excellent for many regions but may vary between diseases and regions.

scholarly journals Is Gray Matter Volume an Intermediate Phenotype for Schizophrenia? A Voxel-Based Morphometry Study of Patients with Schizophrenia and Their Healthy Siblings

2008 ◽  
Vol 63 (5) ◽  
pp. 465-474 ◽  
Author(s):  
Robyn A. Honea ◽  
Andreas Meyer-Lindenberg ◽  
Katherine B. Hobbs ◽  
Lukas Pezawas ◽  
Venkata S. Mattay ◽  
...  
Keyword(s):  
Gray Matter ◽  
Gray Matter Volume ◽  
Intermediate Phenotype ◽  
Voxel Based Morphometry ◽  
Matter Volume ◽  
Healthy Siblings

Putaminal gray matter volume decrease in panic disorder: an optimized voxel-based morphometry study

2005 ◽  
Vol 22 (8) ◽  
pp. 2089-2094 ◽  
Author(s):  
Hanik K. Yoo ◽  
Minue J. Kim ◽  
Seog Ju Kim ◽  
Young Hoon Sung ◽  
Minyoung E. Sim ◽  
...  
Keyword(s):  
Panic Disorder ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Voxel Based Morphometry ◽  
Matter Volume ◽  
Volume Decrease

P2-410: Total gray matter volume is preserved in normal aging: A longitudinal community-based cohort study

2010 ◽  
Vol 6 ◽  
pp. S439-S439
Author(s):  
Masashi Tamura ◽  
Kiyotaka Nemoto ◽  
Fumio Yamashita ◽  
Chiine Kodama ◽  
Hiroshi Matsuda ◽  
...  
Keyword(s):  
Cohort Study ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Normal Aging ◽  
Community Based ◽  
Matter Volume

P300 responses are associated with subcortical gray matter volume in amnestic mild cognitive impairment and normal aging

2016 ◽  
Vol 108 ◽  
pp. 100
Author(s):  
Derya Durusu Emek-Sava ◽  
Berrin Çavuşoğlu ◽  
Duygu Hünerli ◽  
Deniz Yerlikaya ◽  
Arife Gökçeoğlu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Normal Aging ◽  
Amnestic Mild Cognitive Impairment ◽  
Matter Volume

scholarly journals The Gray Matter Volume of the Amygdala Is Correlated with the Perception of Melodic Intervals: A Voxel-Based Morphometry Study

PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e99889 ◽  
Author(s):  
Xueting Li ◽  
Alain De Beuckelaer ◽  
Jiahui Guo ◽  
Feilong Ma ◽  
Miao Xu ◽  
...  
Keyword(s):  
Gray Matter ◽  
Gray Matter Volume ◽  
Voxel Based Morphometry ◽  
Matter Volume

Effects of cumulative illness severity on hippocampal gray matter volume in major depression: a voxel-based morphometry study

2018 ◽  
Vol 48 (14) ◽  
pp. 2391-2398 ◽  
Author(s):  
Dario Zaremba ◽  
Verena Enneking ◽  
Susanne Meinert ◽  
Katharina Förster ◽  
Christian Bürger ◽  
...  
Keyword(s):  
Major Depression ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
Principal Component ◽  
Hippocampal Volume ◽  
Illness Severity ◽  
Voxel Based Morphometry ◽  
Matter Volume ◽  
Duration Of Illness ◽  
Component Scores

AbstractBackgroundPatients with major depression show reduced hippocampal volume compared to healthy controls. However, the contribution of patients’ cumulative illness severity to hippocampal volume has rarely been investigated. It was the aim of our study to find a composite score of cumulative illness severity that is associated with hippocampal volume in depression.MethodsWe estimated hippocampal gray matter volume using 3-tesla brain magnetic resonance imaging in 213 inpatients with acute major depression according to DSM-IV criteria (employing the SCID interview) and 213 healthy controls. Patients’ cumulative illness severity was ascertained by six clinical variables via structured clinical interviews. A principal component analysis was conducted to identify components reflecting cumulative illness severity. Regression analyses and a voxel-based morphometry approach were used to investigate the influence of patients’ individual component scores on hippocampal volume.ResultsPrincipal component analysis yielded two main components of cumulative illness severity: Hospitalization and Duration of Illness. While the component Hospitalization incorporated information from the intensity of inpatient treatment, the component Duration of Illness was based on the duration and frequency of illness episodes. We could demonstrate a significant inverse association of patients’ Hospitalization component scores with bilateral hippocampal gray matter volume. This relationship was not found for Duration of Illness component scores.ConclusionsVariables associated with patients’ history of psychiatric hospitalization seem to be accurate predictors of hippocampal volume in major depression and reliable estimators of patients’ cumulative illness severity. Future studies should pay attention to these measures when investigating hippocampal volume changes in major depression.

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