Neuroscience & Biobehavioral ReviewsNeurosciencePeer-reviewed journal article
How do brain regions specialised for concrete and abstract concepts align with functional brain networks? A neuroimaging meta-analysis
Abstract
Identifying the brain regions that process concrete and abstract concepts is key to understanding the neural architecture of thought, memory and language. We review current theories of concreteness effects and test their neural predictions in a meta-analysis of 72 neuroimaging studies (1400 participants). Our analysis includes more than twice as many studies as previous meta-analyses, allowing for a more sensitive mapping of these effects across the brain. We also conducted a quantitative assessment of the degree to which concreteness effects aligned with a range of large-scale functional brain networks. Our results suggest that concrete and abstract concepts vary both in the information-processing modalities they engage and in the demands they place on cognitive control processes. Abstract concepts preferentially activated networks for social cognition (particularly for sentences), language and semantic control (particularly when presented as single words). Concrete concepts preferentially activated action processing regions when presented in sentences, though we found no evidence that they activated visual networks. Specialisation for both concept types was present in different parts of the default mode network (DMN), with effects dissociating along a social-spatial axis. Concrete concepts generated greater activation in a medial temporal DMN component, implicated in constructing mental models of spatial contexts and scenes. In contrast, abstract concepts showed greater activation in frontotemporal DMN regions involved in social and language processing. These results align with prior claims that generating models of situations and events is a core DMN function and indicate specialisation within DMN for different aspects of these models.
- organism: human
- assay: imaging
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: statistical model
- Citations
- 14
- FWCI
- 2.33
- Field percentile
- top 10%
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