Healthy Aging by Staying Selectively Connected: A Mini-Review

Cognitive neuroscience of the healthy aging human brain has thus far addressed age-related changes of local functional and structural properties of gray and white matter and their association with declining or preserved cognitive functions. In addition to these localized changes, recent neuroimaging research has attributed an important role to neural networks with a stronger focus on interacting rather than isolated brain regions. The analysis of functional connectivity encompasses task-dependent and -independent synchronous activity in the brain, and thus reflects the organization of the brain in distinct performance-relevant networks. Structural connectivity in white matter pathways, representing the integrity of anatomical connections, underlies the communication between the nodes of these functional networks. Both functional and structural connectivity within these networks have been demonstrated to change with aging, and to have different predictive values for cognitive abilities in older compared to young adults. Structural degeneration has been found in the entire cerebral white matter with greatest deterioration in frontal areas, affecting whole brain structural network efficiency. With regard to functional connectivity, both higher and lower functional coupling has been observed in the aging compared to the young brain. Here, high connectivity within the nodes of specific functional networks on the one hand, and low connectivity to regions outside this network on the other hand, were associated with preserved cognitive functions in aging in most cases. For example, in the language domain, connections between left-hemisphere language-related prefrontal, posterior temporal and parietal areas were described as beneficial, whereas connections between the left and right hemisphere were detrimental for language task performance. Of note, interactions between structural and functional network properties may change in the course of aging and differentially impact behavioral performance in older versus young adults. Finally, studies using noninvasive brain stimulation techniques like transcranial direct current stimulation (tDCS) to simultaneously modulate behavior and functional connectivity support the importance of ‘selective connectivity' of aging brain networks for preserved cognitive functions. These studies demonstrate that enhancing task performance by tDCS is paralleled by increased connectivity within functional networks. In this review, we outline the network perspective on healthy brain aging and discuss recent developments in this field.

[1]  L. Nyberg,et al.  Opposing Effects of Aging on Large-Scale Brain Systems for Memory Encoding and Cognitive Control , 2012, The Journal of Neuroscience.

[2]  G. Busatto,et al.  Resting-state functional connectivity in normal brain aging , 2013, Neuroscience & Biobehavioral Reviews.

[3]  Daniel L. Kimmel,et al.  Neuroimaging insights into network-based neurodegeneration. , 2012, Current opinion in neurology.

[4]  P. Baltes,et al.  Emergence of a powerful connection between sensory and cognitive functions across the adult life span: a new window to the study of cognitive aging? , 1997, Psychology and aging.

[5]  T. Flaisch,et al.  Anodal Transcranial Direct Current Stimulation Temporarily Reverses Age-Associated Cognitive Decline and Functional Brain Activity Changes , 2013, The Journal of Neuroscience.

[6]  A. Friederici The brain basis of language processing: from structure to function. , 2011, Physiological reviews.

[7]  Timothy Edward John Behrens,et al.  Diffusion MRI : from quantitative measurement to in vivo neuroanatomy , 2014 .

[8]  Alvaro Pascual-Leone,et al.  Assessing brain plasticity across the lifespan with transcranial magnetic stimulation: why, how, and what is the ultimate goal? , 2013, Front. Neurosci..

[9]  Walter Paulus,et al.  Functional Neuroimaging and Transcranial Electrical Stimulation , 2012, Clinical EEG and neuroscience.

[10]  L. Phillips,et al.  Importance Effects on Age Differences in Performance in Event-Based Prospective Memory , 2013, Gerontology.

[11]  Roberto Cabeza,et al.  The architecture of cross-hemispheric communication in the aging brain: linking behavior to functional and structural connectivity. , 2012, Cerebral cortex.

[12]  R. N. Spreng,et al.  Default network modulation and large-scale network interactivity in healthy young and old adults. , 2012, Cerebral cortex.

[13]  Ulman Lindenberger,et al.  Does variability in cognitive performance correlate with frontal brain volume? , 2013, NeuroImage.

[14]  C. D’Arcy,et al.  Successful Aging in Canada: Prevalence and Predictors from a Population-Based Sample of Older Adults , 2013, Gerontology.

[15]  Denise C. Park,et al.  The adaptive brain: aging and neurocognitive scaffolding. , 2009, Annual review of psychology.

[16]  Robert Lindenberg,et al.  Grammar learning in older adults is linked to white matter microstructure and functional connectivity , 2012, NeuroImage.

[17]  T. Flaisch,et al.  Electrical Brain Stimulation Improves Cognitive Performance by Modulating Functional Connectivity and Task-Specific Activation , 2012, The Journal of Neuroscience.

[18]  Rachael D. Seidler,et al.  Age Differences in Interhemispheric Interactions: Callosal Structure, Physiological Function, and Behavior , 2011, Front. Neurosci..

[19]  J. A. Almendral,et al.  Reorganization of Functional Networks in Mild Cognitive Impairment , 2011, PloS one.

[20]  Linda Geerligs,et al.  Reduced specificity of functional connectivity in the aging brain during task performance , 2014, Human brain mapping.

[21]  R. Cabeza,et al.  Que PASA? The posterior-anterior shift in aging. , 2008, Cerebral cortex.

[22]  Michelle Hampson,et al.  Functional connectivity between task-positive and task-negative brain areas and its relation to working memory performance. , 2010, Magnetic resonance imaging.

[23]  Allen W. Song,et al.  Measurement of spontaneous signal fluctuations in fMRI: adult age differences in intrinsic functional connectivity , 2009, Brain Structure and Function.

[24]  C. Grady The cognitive neuroscience of ageing , 2012, Nature Reviews Neuroscience.

[25]  Scott A. Huettel,et al.  Diffusion tensor imaging of adult age differences in cerebral white matter: relation to response time , 2004, NeuroImage.

[26]  D. Lombard,et al.  SIRT3: As Simple As It Seems? , 2013, Gerontology.

[27]  Justin L. Vincent,et al.  Disruption of Large-Scale Brain Systems in Advanced Aging , 2007, Neuron.

[28]  Yong He,et al.  Discrete Neuroanatomical Networks Are Associated with Specific Cognitive Abilities in Old Age , 2011, The Journal of Neuroscience.

[29]  P. Basser Diffusion MRI: From Quantitative Measurement to In vivo Neuroanatomy , 2009 .

[30]  Edward T. Bullmore,et al.  Age-related changes in modular organization of human brain functional networks , 2009, NeuroImage.

[31]  David H. Salat,et al.  The Declining Infrastructure of the Aging Brain , 2011, Brain Connect..

[32]  M. Fox,et al.  Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.

[33]  Angela D. Friederici,et al.  Functional and structural syntax networks in aging , 2013, NeuroImage.

[34]  Rachael D. Seidler,et al.  Frontiers in Systems Neuroscience Systems Neuroscience , 2022 .