期刊
JOURNAL OF NEUROSCIENCE
卷 36, 期 11, 页码 3115-3126出版社
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.2733-15.2016
关键词
aging; between-/within-network; cross-spectral dynamic causal modelling; fMRI; resting-state networks; salience network
资金
- Biotechnology and Biological Sciences Research Council [BB/H008217/1]
- Wellcome Trust [103838]
- UK Medical Research Council [MC_US_A060_0046]
- Netherlands Organization for Scientific Research
- Biotechnology and Biological Sciences Research Council [BB/H008217/1] Funding Source: researchfish
- Medical Research Council [MC_U105579226, MC_U105579215, MC_U105597119] Funding Source: researchfish
- Wellcome Trust [103838/Z/14/Z] Funding Source: researchfish
- BBSRC [BB/H008217/1] Funding Source: UKRI
- MRC [MC_U105579226, MC_U105579215, MC_U105597119] Funding Source: UKRI
The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. Wepropose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors.
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