Back

Age-related changes in the neural processing of semantics, within and beyond the core semantic network

Wu, W.; Hoffman, P.

2023-05-05 neuroscience
10.1101/2023.05.05.539561 bioRxiv
Show abstract

Ageing is associated with increases in functional activation, which have been interpreted either as compensatory responses to the higher task demands older people experience, or as neural dedifferentiation. Ageing is also characterised by a shift to greater reliance on prior knowledge and less on executive function, whose underlying neural mechanism is poorly understood. This pre-registered fMRI study investigated these questions within the domain of semantic cognition. To disentangle the compensation and dedifferentiation theories, we extracted activation signal in core verbal semantic regions, for young and older participants during semantic tasks. Verbal semantic processing relies heavily on left inferior frontal gyrus (IFG) but older people frequently show additional right IFG activation. We found that right IFG exhibited a similar linear activation-demand relationship as left IFG across age groups and semantic tasks, indicating that age-related over-recruitment of this region may be compensatory in nature. To answer the second question, we examined network-level activity and connectivity changes in semantic and non-semantic tasks. Older people showed more engagement of the default mode network (DMN) and less of the executive multiple demand network (MDN) aligning with their greater reserves of prior knowledge and declined executive control. In contrast, activation was age-invariant in regions contributing specifically to executive control of semantic processing. Older adults also showed a degraded ability to modulate MDN activation as a function of demand in the non-semantic task, but not in the semantic tasks. These findings provide a new perspective on the neural basis of semantic cognition in later life, and suggest that preservation of activation in specialised semantic networks may support preserved performance in this critical domain.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.