bioRxivNeurosciencePreprint
The language network ages well: Preserved topography, lateralization, selectivity, and within-network functional connectivity in older brains
Anne BillotiD, Niharika JhinganiD, Maria VarkanitsaiD, Agata WolnaiD, Cory ShainiD, Idan BlankiD, Rachel Anna RyskiniD, Swathi KiraniD, Evelina G. FedorenkoiD
Abstract
Healthy aging is associated with structural and functional brain changes. However, cognitive abilities vary in how they change with age: whereas executive functions, like working memory, show age-related decline, aspects of linguistic processing remain relatively preserved. The heterogeneity of the cognitive-behavioral landscape in aging predicts differences among brain networks in whether and how they should change with age. To evaluate this prediction, we used individual-subject fMRI analyses (precision fMRI) to examine the language-selective network and--for control purposes--the Multiple Demand (MD) network, which supports executive functions, in older adults (n=64) relative to young controls (n=483). In line with past claims, relative to young adults, the MD network of older adults shows weaker, less spatially extensive, and more topographically variable activations during an executive function task and reduced within-network functional connectivity. However, in stark contrast to the MD network, we find remarkable preservation of the language network in older adults. Their language network responds during language comprehension as strongly and selectively as in younger adults, and shows a similar degree of left-hemispheric lateralization and within-network functional connectivity. Our findings suggest that the language network remains young-like--at least on standard measures of function and connectivity--and align with behavioral preservation of language comprehension in healthy aging.
- organism: human
- assay: imaging
- research focus: cell-cell communication
- research focus: spatial domain detection
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 5
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