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Meta-Analysis
. 2021 Jan 1:224:117444.
doi: 10.1016/j.neuroimage.2020.117444. Epub 2020 Oct 12.

The neural correlates of semantic control revisited

Affiliations
Meta-Analysis

The neural correlates of semantic control revisited

Rebecca L Jackson. Neuroimage. .

Abstract

Semantic control, the ability to selectively access and manipulate meaningful information on the basis of context demands, is a critical component of semantic cognition. The precise neural correlates of semantic control are disputed, with particular debate surrounding parietal involvement, the spatial extent of the posterior temporal contribution and network lateralisation. Here semantic control is revisited, utilising improved analysis techniques and a decade of additional data to refine our understanding of the network. A meta-analysis of 925 peaks over 126 contrasts illuminated a left-focused network consisting of inferior frontal gyrus, posterior middle temporal gyrus, posterior inferior temporal gyrus and dorsomedial prefrontal cortex. This extended the temporal region implicated, and found no parietal involvement. Although left-lateralised overall, relative lateralisation varied across the implicated regions. Supporting analyses confirmed the multimodal nature of the semantic control network and situated it within the wider set of regions implicated in semantic cognition.

Keywords: ALE meta-analysis; Control; Executive processing; Semantic cognition; Semantic control.

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Conflict of interest statement

Declaration of Competing Interest As no new data were collected, there were no ethical concerns. The author has no competing interests.

Figures

Fig. 1
Fig. 1
Results of the meta-analysis contrasting high > low semantic control. Top: Activation likelihood estimate map from the new extended analysis of semantic control based on 925 peaks from 126 contrasts comparing high > low semantic control. Activation likelihood is significant at a voxel-level of 0.001 and an FWE-corrected cluster-level of 0.001. Cutouts are centred upon peak coordinates on the x-axis. Bottom: Regions identified as responsive to high > low semantic control in Noonan et al., 2013 on the basis of 395 foci from 71 contrasts.
Fig. 2
Fig. 2
The multimodal semantic control network. Top: The activation likelihood estimate map for visual semantic control, based on 713 peaks from 65 studies, shown in green. The activation likelihood estimate map for auditory semantic control, based on 177 peaks from 18 studies, shown in blue. Activation likelihood is significant at a voxel-level of 0.001 and an FWE-corrected cluster-level of 0.001. Bottom: Contrasting visual and auditory semantic control allows visualisation of the conjunction of the two thresholded maps (the activation likelihood of the intersection is shown in red). Direct contrasts of auditory and visual semantic control did not result in any significant clusters. Cutouts are focused upon the peak of the conjunction analysis.
Fig. 3
Fig. 3
Semantic control in the broader context of general semantic cognition, including both representation and control processes. Top: the regions reliably activated for semantic cognition are displayed. The semantic cognition meta-analysis contrasted semantic with non-semantic stimuli and tasks and includes 3606 peaks over 415 contrasts. Bottom: binary maps demonstrating how the semantic control regions (red) fit within the wider network for semantic cognition (green). Overlap is shown in yellow. Cutouts are focused upon peaks from both meta-analyses.
Fig. 4
Fig. 4
Semantic control in the wider context of domain-general control processing. The binarised semantic control map (red) is displayed overlaid with the multi-demand network mask generated in Federenko et al., 2013 (blue). Overlap is shown in violet. This mask is formed by contrasting the hard over easy versions of seven diverse tasks. Results were averaged over the two hemispheres resulting in a symmetrical mask. Cutouts are focused upon peaks from the semantic meta-analyses. A high degree of separation can be seen with semantic control tending to rely on domain-specific areas, although overlap may be seen within dmPFC, posterior inferior temporal gyrus and along the posterior edge of the IFG.

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