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A new hypothesis called \u2018variable neuro-displacement\u2019 suggests that cognitive systems are formed with dynamic, spare processing capacity, which balances energy consumption against performance requirements and can be resilient to changes in performance demands. Here, we tested this hypothesis by investigating the neural dynamics of the semantic system by manipulating performance demand. The performance demand was manipulated with two levels of task difficulty (easy vs. hard) in two different ways (stimulus type and response timing). We found that the demanding semantic processing increased regional activity in both the domain-specific semantic representational system (anterior temporal lobe) and the parallel executive control networks (prefrontal, posterior temporal, and parietal regions). Functional connectivity between these regions was also increased during demanding semantic processing and these increases were related to better semantic task performance. Our results suggest that semantic cognition is made resilient by flexible, dynamic changes including increased regional activity and functional connectivity across both domain-specific and domain-general systems. It reveals the intrinsic resilience-related mechanisms of semantic cognition, mimicking alterations caused by perturbation or brain damage. Our findings provide a strong implication that the intrinsic mechanisms of a well-engineered semantic system might be attributed to the compensatory functional alterations in the impaired brain.<\/jats:p>","DOI":"10.1007\/s00429-021-02272-1","type":"journal-article","created":{"date-parts":[[2021,4,20]],"date-time":"2021-04-20T05:03:36Z","timestamp":1618895016000},"page":"1585-1599","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["The neural bases of resilient semantic system: evidence of variable neuro-displacement in cognitive systems"],"prefix":"10.1007","volume":"226","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3739-7331","authenticated-orcid":false,"given":"Je Young","family":"Jung","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grace E.","family":"Rice","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew A.","family":"Lambon Ralph","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,4,20]]},"reference":[{"issue":"1","key":"2272_CR1","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neuroimage.2007.07.007","volume":"38","author":"J Ashburner","year":"2007","unstructured":"Ashburner J (2007) A fast diffeomorphic image registration algorithm. 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