Parcellation‐based anatomic model of the semantic network

Milton, Camille K; Dhanaraj, Vukshitha; Young, Isabella M.; Taylor, Hugh M; Nicholas, Peter J.; Briggs, Robert G.; Bai, Michael Y.; Fonseka, R. Dineth; Hormovas, Jorge; Lin, Yueh‐Hsin; Tanglay, Onur; Conner, Andrew K.; Glenn, Chad A.; Teo, Charles; Doyen, Stéphane; Sughrue, Michael E.

doi:10.1002/brb3.2065

Cited by 22 publications

(25 citation statements)

References 32 publications

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“…Therefore, affective functions may constitute an important factor of DMN reorganization during task execution. We also note that PC2 and IC2 (but PC1 as well) resemble the SemN (Noonan et al 2013;Chiou et al 2020;Evans et al 2020;Milton et al 2021). Furthermore, they remind the transitional module serving an integrative function with FPN observed by Fornito et al (2012), as well as with the Overlapping Community six found by Najafi et al (2016).…”

Section: Discussionsupporting

confidence: 60%

Tasks activating the default mode network map multiple functional systems

Mancuso

Liloia

et al. 2022

Brain Struct Funct

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Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic–extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.

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Section: Discussionsupporting

confidence: 60%

Tasks activating the default mode network map multiple functional systems

Mancuso

Liloia

et al. 2022

Brain Struct Funct

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“…By including reported stereotactic coordinates from previous studies, more anatomically precise results can be obtained. In this context, we have been attempting to characterize all of our current findings within the HCP nomenclature given its more precise parcellation scheme (Kuiper et al., 2020 ; Milton et al., 2021 ; Sandhu et al., 2021 ; Sheets, Briggs, Dadario, et al., 2021 ). For instance, the anterior cingulate cortex and insula are known to be functionally divided within numerous subdivisions (Glasser et al., 2016 ), yet previous studies on the SN network continue to generally reference these regions as just general nodes in the SN.…”

Section: Discussionmentioning

confidence: 99%

“…By utilizing coordinate‐based methodology, one can overcome the heterogeneous topographical nomenclature often described in the literature for homologous brain regions. This methodology has allowed us to precisely characterize many other brain networks in great detail, such as the default mode network (DMN); however, it has not been applied in a similar context for the SN to date and therefore remains a potentially advantageous avenue worth exploring (Milton et al., 2021 ; Poologaindran et al., 2020 ; Sandhu et al., 2021 ; Sheets, Briggs, Dadario, et al., 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Parcellation‐based tractographic modeling of the salience network through meta‐analysis

et al. 2022

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Background:The salience network (SN) is a transitory mediator between active and passive states of mind. Multiple cortical areas, including the opercular, insular, and cingulate cortices have been linked in this processing, though knowledge of network connectivity has been devoid of structural specificity. Objective:The current study sought to create an anatomically specific connectivity model of the neural substrates involved in the salience network.Methods: A literature search of PubMed and BrainMap Sleuth was conducted for resting-state and task-based fMRI studies relevant to the salience network according to PRISMA guidelines. Publicly available meta-analytic software was utilized to extract relevant fMRI data for the creation of an activation likelihood estimation (ALE) map and relevant parcellations from the human connectome project overlapping with the ALE data were identified for inclusion in our SN model. DSI-based fiber tractography was then performed on publicaly available data from healthy subjects to determine the structural connections between cortical parcellations comprising the network.Results: Nine cortical regions were found to comprise the salience network: areas AVI (anterior ventral insula), MI (middle insula), FOP4 (frontal operculum 4), FOP5 (frontal operculum 5), a24pr (anterior 24 prime), a32pr (anterior 32 prime), p32pr (posterior 32 prime), and SCEF (supplementary and cingulate eye field), and 46. The frontal aslant tract was found to connect the opercular-insular cluster to the middle cingulate clusters of the network, while mostly short U-fibers connected adjacent nodes of the network. Conclusion:Here we provide an anatomically specific connectivity model of the neural substrates involved in the salience network. These results may serve as an empiric basis for clinical translation in this region and for future study which seeks to expand ourThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Notably, pars triangularis was the most robustly-identified hub and was the only node to appear as part of the ISN in every participant, suggesting a common functional role across individuals. Parts of left IFG, particularly pars triangularis, have been previously described as both a functional and structural hub possibly involved in cognitive control due to its density of connections to medial prefrontal cortex (Milton et al, 2021; Vandenberghe et al, 2013; Xu et al, 2016). Further, rTMS experiments have shown that disruption of anterior IFG is associated with increased latency on semantic but not phonological tasks (Gough et al, 2005; Klaus & Hartwigsen, 2019; Whitney et al, 2010), supporting its role as a critical node in the semantic network.…”

Section: Discussionmentioning

confidence: 99%

The organization of individually mapped structural and functional semantic networks in aging adults

Ketchabaw

Paul

et al. 2021

Preprint

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Language function in the brain, once thought to be highly localized, is now appreciated as relying on a connected but distributed network. The semantic system is of particular interest in the language domain because of its hypothesized integration of information across multiple cortical regions. Previous work in healthy individuals has focused on group-level functional connectivity (FC) analyses of the semantic system, which may obscure interindividual differences driving variance in performance. These studies also overlook the contributions of white matter networks to semantic function. Here, we identified semantic network nodes with a semantic decision fMRI task in 53 typically-aging adults, characterized network organization using structural connectivity (SC), and quantified the segregation and integration of the network using FC. Hub regions were identified in left inferior frontal gyrus. The individualized semantic network was composed of three interacting modules: 1) default-mode module characterized by bilateral medial prefrontal and posterior cingulate regions and also including right-hemisphere homotopes of language regions; 2) left frontal module extending dorsally from inferior frontal gyrus to pre-motor area; and 3) left temporoparietal module extending from temporal pole to inferior parietal lobule. FC within Module3 and integration of the entire network related to a semantic verbal fluency task, but not a matched phonological task. These results support and extend the tri-network semantic model (Xu et al., 2017) and the controlled semantic cognition model (Chiou et al., 2018) of semantic function.

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Parcellation‐based anatomic model of the semantic network

Cited by 22 publications

References 32 publications

Tasks activating the default mode network map multiple functional systems

Tasks activating the default mode network map multiple functional systems

Parcellation‐based tractographic modeling of the salience network through meta‐analysis

The organization of individually mapped structural and functional semantic networks in aging adults

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