Topographical Functional Connectivity Pattern in the Perisylvian Language Networks

Xiang, Huadong; Fonteijn, Hubert; Norris, David G.; Hagoort, Peter

doi:10.1093/cercor/bhp119

Cited by 190 publications

(203 citation statements)

References 84 publications

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“…The other region activated in the READ task was the left inferior parietal lobe (IPL), a region that is often associated with semantic or phonological working memory (Gold et al, 2005), as well as general working memory load (Owen et al, 2005). Connectivity analysis revealed close coupling between the LIFG and IPL as well as between the IPL and the temporal cortex (Catani et al, 2005;Xiang et al, 2010). These results suggest that the posterior activation may be task-dependent.…”

Section: Discussionmentioning

confidence: 92%

The anterior left inferior frontal gyrus contributes to semantic unification

et al. 2012

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a b s t r a c t a r t i c l e i n f oSemantic unification, the process by which small blocks of semantic information are combined into a coherent utterance, has been studied with various types of tasks. However, whether the brain activations reported in these studies are attributed to semantic unification per se or to other task-induced concomitant processes still remains unclear. The neural basis for semantic unification in sentence comprehension was examined using event-related potentials (ERP) and functional Magnetic Resonance Imaging (fMRI). The semantic unification load was manipulated by varying the goodness of fit between a critical word and its preceding context (in high cloze, low cloze and violation sentences). The sentences were presented in a serial visual presentation mode. The participants were asked to perform one of three tasks: semantic congruency judgment (SEM), silent reading for comprehension (READ), or font size judgment (FONT), in separate sessions. The ERP results showed a similar N400 amplitude modulation by the semantic unification load across all of the three tasks. The brain activations associated with the semantic unification load were found in the anterior left inferior frontal gyrus (aLIFG) in the FONT task and in a widespread set of regions in the other two tasks. These results suggest that the aLIFG activation reflects a semantic unification, which is different from other brain activations that may reflect task-specific strategic processing.

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Section: Discussionmentioning

confidence: 92%

The anterior left inferior frontal gyrus contributes to semantic unification

et al. 2012

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“…This is in keeping with left hemisphere predominance of other aspects of phonological processing at the network level (Glasser and Rilling 2008; Price 2010; Xiang et al. 2010). …”

Section: Discussionmentioning

confidence: 99%

Dominant hemisphere functional networks compensate for structural connectivity loss to preserve phonological retrieval with aging

Agarwal

Stamatakis

Geva³

et al. 2016

Brain and Behavior

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IntroductionLoss of hemispheric asymmetry during cognitive tasks has been previously demonstrated in the literature. In the context of language, increased right hemisphere activation is observed with aging. Whether this relates to compensation to preserve cognitive function or dedifferentiation implying loss of hemispheric specificity without functional consequence, remains unclear.MethodsWith a multifaceted approach, integrating structural and functional imaging data during a word retrieval task, in a group of younger and older adults with equivalent cognitive performance, we aimed to establish whether interactions between hemispheres or reorganization of dominant hemisphere networks preserve function. We examined functional and structural connectivity on data from our previously published functional activation study. Functional connectivity was measured using psychophysiological interactions analysis from the left inferior frontal gyrus (LIFG) and the left insula (LINS), based on published literature, and the right inferior frontal gyrus (RIFG) based on our previous study.ResultsAlthough RIFG showed increased activation, its connectivity decreased with age. Meanwhile, LIFG and LINS connected more bilaterally in the older adults. White matter integrity, measured by fractional anisotropy (FA) from diffusion tensor imaging, decreased significantly in the older group. Importantly, LINS functional connectivity to LIFG correlated inversely with FA.ConclusionsWe demonstrate that left hemispheric language areas show higher functional connectivity in older adults with intact behavioral performance, and thus, may have a role in preserving function. The inverse correlation of functional and structural connectivity with age is in keeping with emerging literature and merits further investigation with tractography studies and in other cognitive domains.

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“…This allows in vivo analysis of the anatomical connectivity of different regions, and how they vary between species (e.g., Rilling et al, 2008). Such analyses are complemented by functional connectivity analysis (which uses cross-correlation in time across multiple brain areas) to evaluate which regions are coactivated in particular tasks (Sporns et al, 2004;Xiang et al, 2010;Hamilton et al, 2013), an approach also potentially applicable to interspecies comparisons (Rilling et al, 2007). Such approaches have led to important advances in our understanding of the neural computations that underlie language, including the still ongoing debate about whether any are specific to language or not (cf.…”

Section: Neuroscientific Datamentioning

confidence: 99%

Empirical approaches to the study of language evolution

2017

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The study of language evolution, and human cognitive evolution more generally, has often been ridiculed as unscientific, but in fact it differs little from many other disciplines that investigate past events, such as geology or cosmology. Well-crafted models of language evolution make numerous testable hypotheses, and if the principles of strong inference (simultaneous testing of multiple plausible hypotheses) are adopted, there is an increasing amount of relevant data allowing empirical evaluation of such models. The articles in this special issue provide a concise overview of current models of language evolution, emphasizing the testable predictions that they make, along with overviews of the many sources of data available to test them (emphasizing comparative, neural, and genetic data). The key challenge facing the study of language evolution is not a lack of data, but rather a weak commitment to hypothesistesting approaches and strong inference, exacerbated by the broad and highly interdisciplinary nature of the relevant data. This introduction offers an overview of the field, and a summary of what needed to evolve to provide our species with language-ready brains. It then briefly discusses different contemporary models of language evolution, followed by an overview of different sources of data to test these models. I conclude with my own multistage model of how different components of language could have evolved.

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Topographical Functional Connectivity Pattern in the Perisylvian Language Networks

Cited by 190 publications

References 84 publications

The anterior left inferior frontal gyrus contributes to semantic unification

The anterior left inferior frontal gyrus contributes to semantic unification

Dominant hemisphere functional networks compensate for structural connectivity loss to preserve phonological retrieval with aging

Empirical approaches to the study of language evolution

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