Spatiotemporal Dependency of Age-Related Changes in Brain Signal Variability

被引:147
作者
McIntosh, A. R. [1 ]
Vakorin, V. [1 ]
Kovacevic, N. [1 ]
Wang, H. [1 ]
Diaconescu, A. [2 ]
Protzner, A. B. [3 ]
机构
[1] Rotman Res Inst Baycrest, Toronto, ON, Canada
[2] Univ Zurich, Inst Empir Res Econ, CH-8006 Zurich, Switzerland
[3] Univ Calgary, Dept Psychol, Calgary, AB T2N 1N4, Canada
关键词
electroencephalograpy; functional connectivity; magnetoencephalography; multiscale entropy; nonlinear dynamics; INTERHEMISPHERIC EEG COHERENCE; WHITE-MATTER; FUNCTIONAL CONNECTIVITY; COMPLEXITY; NETWORK; ORGANIZATION; NEUROANATOMY; DYNAMICS; SYSTEMS; MEMORY;
D O I
10.1093/cercor/bht030
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Recent theoretical and empirical work has focused on the variability of network dynamics in maturation. Such variability seems to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into healthy aging. Two different data sets, one EEG (total n = 48, ages 18-72) and one magnetoencephalography (n = 31, ages 20-75) were analyzed for such spatiotemporal dependency using multiscale entropy (MSE) from regional brain sources. In both data sets, the changes in MSE were timescale dependent, with higher entropy at fine scales and lower at more coarse scales with greater age. The signals were parsed further into local entropy, related to information processed within a regional source, and distributed entropy (information shared between two sources, i.e., functional connectivity). Local entropy increased for most regions, whereas the dominant change in distributed entropy was age-related reductions across hemispheres. These data further the understanding of changes in brain signal variability across the lifespan, suggesting an inverted U-shaped curve, but with an important qualifier. Unlike earlier in maturation, where the changes are more widespread, changes in adulthood show strong spatiotemporal dependence.
引用
收藏
页码:1806 / 1817
页数:12
相关论文
共 69 条
[51]   Age differences in dynamic measures of EEG [J].
Pierce, TW ;
Kelly, SP ;
Watson, TD ;
Replogle, D ;
King, JS ;
Pribram, KH .
BRAIN TOPOGRAPHY, 2000, 13 (02) :127-134
[52]   GENERALIZED REDUNDANCIES FOR TIME-SERIES ANALYSIS [J].
PRICHARD, D ;
THEILER, J .
PHYSICA D-NONLINEAR PHENOMENA, 1995, 84 (3-4) :476-493
[53]  
Protzner AB, 2010, ARCH ITAL BIOL, V148, P289
[54]   The interplay of stimulus modality and response latency in neural network organization for simple working memory tasks [J].
Protzner, Andrea B. ;
McIntosh, Anthony R. .
JOURNAL OF NEUROSCIENCE, 2007, 27 (12) :3187-3197
[55]   Differential aging of the brain: Patterns, cognitive correlates and modifiers [J].
Raz, Naftali ;
Rodrigue, Karen M. .
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 2006, 30 (06) :730-748
[56]   Motor control and aging: Links to age-related brain structural, functional, and biochemical effects [J].
Seidler, Rachael D. ;
Bernard, Jessica A. ;
Burutolu, Taritonye B. ;
Fling, Brett W. ;
Gordon, Mark T. ;
Gwin, Joseph T. ;
Kwak, Youngbin ;
Lipps, David B. .
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 2010, 34 (05) :721-733
[57]  
Shannon CE., 1949, MATH THEORY COMMUNIC, DOI DOI 10.1145/584091.584093
[58]  
Silverman B.W., 1986, DENSITY ESTIMATION S, DOI [10.1201/9781315140919, DOI 10.1201/9781315140919]
[59]   Increased microglial activation and protein nitration in white matter of the aging monkey [J].
Sloane, JA ;
Hollander, W ;
Moss, MB ;
Rosene, DL ;
Abraham, CR .
NEUROBIOLOGY OF AGING, 1999, 20 (04) :395-405
[60]   STANDARDIZED SET OF 260 PICTURES - NORMS FOR NAME AGREEMENT, IMAGE AGREEMENT, FAMILIARITY, AND VISUAL COMPLEXITY [J].
SNODGRASS, JG ;
VANDERWART, M .
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-HUMAN LEARNING AND MEMORY, 1980, 6 (02) :174-215