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https://www.selleckchem.com/products/smoothened-agonist-sag-hcl.html Language production deficits occur early in the course of Alzheimer's disease (AD); however, only a few studies have focused on language network's functional connectivity in mild cognitive impairment (MCI) due to AD. The current study aims to uncover the extent of language alteration at the MCI stage, at a behavioral and neural level, using univariate and multivariate analyses of structural MRI and resting-state fMRI. Twenty-four MCI due to AD participants and 24 matched healthy controls underwent a comprehensive language evaluation, a structural T1-3D MRI, and resting-state fMRI. We performed seed-based analyses, using the left inferior frontal gyrus and left posterior temporal gyrus as seeds. Then, we analyzed connectivity between executive control networks and language network in each group. Finally, we used multivariate pattern analyses to test whether the two groups could be distinguished based on the pattern of atrophy within the language network; within the executive control networks, as well as the pattern of functional connectivity within the language network and within the executive control networks. MCI due to AD participants had language impairment during standardized language tasks and connected-speech production. Regarding functional connectivity, univariate analyses were not able to discriminate participants, while multivariate pattern analyses could significantly predict participants' group. Language network's functional connectivity could discriminate MCI due to AD participants better than executive control networks. Most notably, they revealed an increased connectivity at the MCI stage, positively correlated with language performance. Multivariate analyses represent a useful tool for investigating the functional and structural (re-)organization of the neural bases of language. Multivariate analyses represent a useful tool for investigating the functional and structural (re-)organi

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