Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction

Zhu, Zhenan; Yang, Fengjun; Li, Dongning; Zhou, Lianjun; Liu, Ying; Zhang, Ying; Chen, Xuezhi

doi:10.1371/journal.pone.0189462

Cited by 12 publications

(12 citation statements)

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“…It seems, that areas naturally attributed to aging are also needing the least amount of EV energy to yield a significant result. Most interestingly areas responsible for motion control and motor processes, cognitive processing and decision making, memory encoding and retrieval, decision-making, emotions, language processing, inhibitory control and regulation of sleep as well as alertness (namely putamen, orbifrontal cortex, parahippocampal gyrus, amygdala, caudate nucleus and thalamus) are displaying the strongest correlations and are in line with other publications reporting aging effects in the brain (e.g., Brodoehl et al, 2013 ; Zhuang et al, 2017 ; Zhu et al, 2017 ). On the contrary, areas for processing visual information like calcarine, cuneus, angular gyrus among other occipital regions need almost all EV energy if they reach significance at all, hinting at an age independence, see Supplementary Table 3 .…”

Section: Discussionsupporting

confidence: 88%

“…Changes in brain organization due to healthy aging have been reported in several studies (e.g., Brodoehl et al, 2013 ; Beason-Held et al, 2016 ; Goldstone et al, 2016 ; La Corte et al, 2016 ; He et al, 2017 ; Peterson et al, 2017 ; Siman-Tov et al, 2017 ; Tremblay et al, 2017 ; Zhuang et al, 2017 ; Zhu et al, 2017 ). In accordance to Liu et al ( 2013 ), Toussaint et al ( 2014 ), and Sokunbi et al ( 2015 ) non-linear brain complexity measures, derived from information theory, find changes in brain complexity as a result of healthy aging as well.…”

Section: Introductionmentioning

confidence: 88%

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Dimensional Complexity of the Resting Brain in Healthy Aging, Using a Normalized MPSE

Scheel

Franke

Münte

et al. 2018

Front. Hum. Neurosci.

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Spontaneous fluctuations of resting-state functional connectivity have been studied in many ways, but grasping the complexity of brain activity has been difficult. Dimensional complexity measures, which are based on Eigenvalue (EV) spectrum analyses (e.g., Ω entropy) have been successfully applied to EEG data, but have not been fully evaluated on functional MRI recordings, because only through the recent introduction of fast multiband fMRI sequences, feasable temporal resolutions are reached. Combining the Eigenspectrum normalization of Ω entropy and the scalable architecture of the so called Multivariate Principal Subspace Entropy (MPSE) leads to a new complexity measure, namely normalized MPSE (nMPSE). It allows functional brain complexity analyses at varying levels of EV energy, independent from global shifts in data variance. Especially the restriction of the EV spectrum to the first dimensions, carrying the most prominent data variance, can act as a filter to reveal the most discriminant factors of dependent variables. Here we look at the effects of healthy aging on the dimensional complexity of brain activity. We employ a large open access dataset, providing a great number of high quality fast multiband recordings. Using nMPSE on whole brain, regional, network and searchlight approaches, we were able to find many age related changes, i.e., in sensorimotoric and right inferior frontal brain regions. Our results implicate that research on dimensional complexity of functional MRI recordings promises to be a unique resource for understanding brain function and for the extraction of biomarkers.

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Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 88%

Dimensional Complexity of the Resting Brain in Healthy Aging, Using a Normalized MPSE

Scheel

Franke

Münte

et al. 2018

Front. Hum. Neurosci.

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“…Consistent with the amplitude change pattern, the N400 is sensitive to semantic congruency, and this sensitivity was declined in the older adults. Such a reduced semantic integration effect could be explained by reduced brain functional response or brain shrinkage as observed in previous studies (Diaz et al, 2016;Grossman et al, 2002;Peelle et al, 2010;Tremblay, Dick, & Small, 2013;Zhu et al, 2017), or inefficient information transmission across the language network (Diaz et al, 2016;Fedorenko & Thompson-Schill, 2014).…”

Section: Discussionmentioning

confidence: 65%

Semantic integration declines independently of working memory in aging

Zhu

Wang²,

et al. 2019

Applied Psycholinguistics

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Semantic integration and working memory both decline with age. However, it remains unclear whether the semantic integration decline is independent of working memory decline or whether it can be solely explained by the latter factor. In this event-related potentials experiment, 43 younger adults and 43 cognitively healthy older adults read semantically congruent and incongruent sentences. After controlling for working memory, behavioral accuracy was significantly lower in the older adults than in the younger adults. In addition, the semantic integration related N400 effect (incongruent vs. congruent) for correct trials was apparent in the whole brain in the younger adults but restricted to the posterior region in the older adults. The results clarify the relationship between working memory and semantic integration, and clearly demonstrate that semantic integration decline is independent of working memory decline during aging.

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“…The reduced N400 effect in older adults has been linked to less efficiency in pre-activating semantic features of coming words ( Federmeier and Kutas, 2005 ; Federmeier et al, 2010 ; DeLong et al, 2012 ) and integrating the words into context ( Hagoort et al, 2004 ; Zhu et al, 2012 ). Similarly, fMRI studies of older adults have revealed under-recruitment in the left frontal-temporal regions in poorer readers compared to better readers ( Grossman et al, 2002b ) or in older adults compared to younger adults ( Zhu et al, 2017 ). The reduction of the N400 effect, however, was not correlated with accuracy differences between conditions in either group.…”

Section: Discussionmentioning

confidence: 98%

Reduced Syntactic Processing Efficiency in Older Adults During Sentence Comprehension

2018

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Researchers have frequently reported an age-related decline in semantic processing during sentence comprehension. However, it remains unclear whether syntactic processing also declines or whether it remains constant as people age. In the present study, 26 younger adults and 20 older adults were recruited and matched in terms of working memory, general intelligence, verbal intelligence and fluency. They were then asked to make semantic acceptability judgments while completing a Chinese sentence reading task. The behavioral results revealed that the older adults had significantly lower accuracy on measures of semantic and syntactic processing compared to younger adults. Event-related potential (ERP) results showed that during semantic processing, older adults had a significantly reduced amplitude and delayed peak latency of the N400 compared to the younger adults. During syntactic processing, older adults also showed delayed peak latency of the P600 relative to younger adults. Moreover, while P600 amplitude was comparable between the two age groups, larger P600 amplitude was associated with worse performance only in the older adults. Together, the behavioral and ERP data suggest that there is an age-related decline in both semantic and syntactic processing, with a trend toward lower efficiency in syntactic ability.

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Age-related reduction of adaptive brain response during semantic integration is associated with gray matter reduction

Cited by 12 publications

References 50 publications

Dimensional Complexity of the Resting Brain in Healthy Aging, Using a Normalized MPSE

Dimensional Complexity of the Resting Brain in Healthy Aging, Using a Normalized MPSE

Semantic integration declines independently of working memory in aging

Reduced Syntactic Processing Efficiency in Older Adults During Sentence Comprehension

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