scholarly journals Investigating Age-related changes in fine motor control across different effectors and the impact of white matter integrity

NeuroImage ◽  
2014 ◽  
Vol 96 ◽  
pp. 81-87 ◽  
Author(s):  
Joseph L. Holtrop ◽  
Torrey M. Loucks ◽  
Jacob J. Sosnoff ◽  
Bradley P. Sutton
Keyword(s):  
Motor Control ◽  
White Matter ◽  
White Matter Integrity ◽  
Fine Motor ◽  
Fine Motor Control ◽  
Age Related ◽  
The Impact ◽  
Age Related Changes

Age-related changes in white matter integrity: A diffusion tensor imaging study

NeuroImage ◽  
2009 ◽  
Vol 47 ◽  
pp. S128
Author(s):  
H Lemaitre ◽  
S Marenco ◽  
M Emery ◽  
T Alam ◽  
M Geramita ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
White Matter Integrity ◽  
Age Related ◽  
Diffusion Tensor Imaging Study ◽  
Age Related Changes

The Influence of Age and Work-Related Expertise on Fine Motor Control

GeroPsych ◽  
2012 ◽  
Vol 25 (4) ◽  
pp. 199-206 ◽  
Author(s):  
Solveig Vieluf ◽  
Jasmin Mahmoodi ◽  
Ben Godde ◽  
Eva-Maria Reuter ◽  
Claudia Voelcker-Rehage
Keyword(s):  
Motor Control ◽  
Precision Grip ◽  
Middle Finger ◽  
Fine Motor ◽  
Force Variability ◽  
Fine Motor Control ◽  
Left Hand ◽  
Work Related ◽  
Age Related ◽  
The Right

Age-related decline of fine motor control commences even in middle adulthood. Less is known, however, whether age-related changes can be postponed through continuous practice. In this study we tested how age and professional expertise influence fine motor control in middle-aged adults. Forty-eight right-handed novices and experts (35 to 65 years) performed submaximal precision grip force modulation tasks with index or middle finger opposing the thumb, either with the right hand or the left hand. Novices revealed expected age-related differences in all performance measures (force initialization, mean applied force, variability), whereas experts outperformed novices in all outcome measures. Expertise seems to contribute to maintaining manual skills into older age, as indicated by the age and expertise interaction for the force initialization.

scholarly journals Age-related changes in parahippocampal white matter integrity: A diffusion tensor imaging study

2012 ◽  
Vol 50 (8) ◽  
pp. 1759-1765 ◽  
Author(s):  
E. Rogalski ◽  
G.T. Stebbins ◽  
C.A. Barnes ◽  
C.M. Murphy ◽  
T.R. Stoub ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
White Matter Integrity ◽  
Age Related ◽  
Diffusion Tensor Imaging Study ◽  
Age Related Changes

scholarly journals Circle drawing and tracing dataset for evaluation of fine motor control

Data in Brief ◽  
2021 ◽  
Vol 35 ◽  
pp. 106763
Author(s):  
Eros Quarta ◽  
Riccardo Bravi ◽  
Diego Minciacchi ◽  
Erez James Cohen
Keyword(s):  
Motor Control ◽  
Fine Motor ◽  
Fine Motor Control ◽  
Circle Drawing

Hand fine motor control in classic galactosemia

2021 ◽  
Author(s):  
Jessica MacWilliams ◽  
Sneh Patel ◽  
Grace Carlock ◽  
Sarah Vest ◽  
Nancy L. Potter ◽  
...  
Keyword(s):  
Motor Control ◽  
Fine Motor ◽  
Fine Motor Control ◽  
Classic Galactosemia

Developmental Trends in Letter-Printing Skill

1972 ◽  
Vol 34 (1) ◽  
pp. 183-186 ◽  
Author(s):  
R. G. Stennett ◽  
P. C. Smythe ◽  
Madeline Hardy ◽  
H. R. Wilson
Keyword(s):  
Motor Control ◽  
Fine Motor ◽  
Factor Analyses ◽  
Fine Motor Control ◽  
Developmental Trends ◽  
Factor Pattern ◽  
Lower Case ◽  
Grade 3

Tests of kindergarten to Grade 3 students' ability to copy upper- and lower-case primary print letters showed that lower-case letters are more difficult to print. Within upper- and lower-case formats, the letters vary considerably in difficulty as a function of their composition and/or the degree of fine motor control required. Factor analyses, based upon separate intercorrelations for upper- and lower-case letters, produced 7 factors for each type of letter. Although some of the factors tended to contain letters with similar characteristics, no obvious rationale explaining the factor pattern could be developed.

The relationship between executive function and fine motor control in young and older adults

2017 ◽  
Vol 51 ◽  
pp. 41-50 ◽  
Author(s):  
Emily J. Corti ◽  
Andrew R. Johnson ◽  
Hayley Riddle ◽  
Natalie Gasson ◽  
Robert Kane ◽  
...  
Keyword(s):  
Older Adults ◽  
Motor Control ◽  
Executive Function ◽  
Fine Motor ◽  
Fine Motor Control ◽  
The Relationship

scholarly journals Age-related differences in multiple measures of white matter integrity: A diffusion tensor imaging study of healthy aging

2009 ◽  
pp. NA-NA ◽  
Author(s):  
Ilana J. Bennett ◽  
David J. Madden ◽  
Chandan J. Vaidya ◽  
Darlene V. Howard ◽  
James H. Howard
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Healthy Aging ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
White Matter Integrity ◽  
Multiple Measures ◽  
Age Related ◽  
Diffusion Tensor Imaging Study

Abstract T P136: Potential Contributors to the Declining Impact of Stroke Risk Factors with Age: Implications for Stroke Epidemiology in the Elderly

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
George Howard ◽  
Mary Cushman ◽  
Maciej Banach ◽  
Brett M Kissela ◽  
David C Goff ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Stroke Risk ◽  
Multivariable Analysis ◽  
The Elderly ◽  
Stroke Risk Factors ◽  
Age Related ◽  
Increased Risk ◽  
The Impact ◽  
Age Related Changes

Purpose: The importance of stroke research in the elderly is increasing as America is “graying.” For most risk factors for most diseases (including stroke), the magnitude of association with incident events decreases at older ages. Potential changes in the impact of risk factors could be a “true” effect, or could be due to methodological issues such as age-related changes in residual confounding. Methods: REGARDS followed 27,748 stroke-free participants age 45 and over for an average of 5.3 years, during which 715 incident strokes occurred. The association of the “Framingham” risk factors (hypertension [HTN], diabetes, smoking, AFib, LVH and heart disease) with incident stroke risk was assessed in age strata of 45-64 (Young), 65-74 (Middle), and 75+ (Old). For those with and without an “index” risk factor (e.g., HTN), the average number of “other” risk factors was calculated. Results: With the exception of AFib, there was a monotonic decrease in the magnitude of the impact across the age strata, with HTN, diabetes, smoking and LVH even becoming non-significant in the elderly (Figure 1). However, for most factors, the increasing prevalence of other risk factors with age impacts primarily those with the index risk factor absent (Figure 2, example HTN as the “index” risk factor). Discussion: The impact of stroke risk factors substantially declined at older ages. However, this decrease is partially attributable to increases in the prevalence of other risk factors among those without the index risk factor, as there was little change in the prevalence of other risk factors in those with the index risk factor. Hence, the impact of the index risk factor is attenuated by increased risk in the comparison group. If this phenomenon is active with latent risk factors, estimates from multivariable analysis will also decrease with age. A deeper understanding of age-related changes in the impact of risk factors is needed.

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