scholarly journals Functional Network Connectivity Underlying Food Processing: Disturbed Salience and Visual Processing in Overweight and Obese Adults

2012 ◽  
Vol 23 (5) ◽  
pp. 1247-1256 ◽  
Author(s):  
Stephanie Kullmann ◽  
Anna-Antonia Pape ◽  
Martin Heni ◽  
Caroline Ketterer ◽  
Fritz Schick ◽  
...  
2021 ◽  
pp. 1-14
Author(s):  
Jie Huang ◽  
Paul Beach ◽  
Andrea Bozoki ◽  
David C. Zhu

Background: Postmortem studies of brains with Alzheimer’s disease (AD) not only find amyloid-beta (Aβ) and neurofibrillary tangles (NFT) in the visual cortex, but also reveal temporally sequential changes in AD pathology from higher-order association areas to lower-order areas and then primary visual area (V1) with disease progression. Objective: This study investigated the effect of AD severity on visual functional network. Methods: Eight severe AD (SAD) patients, 11 mild/moderate AD (MAD), and 26 healthy senior (HS) controls undertook a resting-state fMRI (rs-fMRI) and a task fMRI of viewing face photos. A resting-state visual functional connectivity (FC) network and a face-evoked visual-processing network were identified for each group. Results: For the HS, the identified group-mean face-evoked visual-processing network in the ventral pathway started from V1 and ended within the fusiform gyrus. In contrast, the resting-state visual FC network was mainly confined within the visual cortex. AD disrupted these two functional networks in a similar severity dependent manner: the more severe the cognitive impairment, the greater reduction in network connectivity. For the face-evoked visual-processing network, MAD disrupted and reduced activation mainly in the higher-order visual association areas, with SAD further disrupting and reducing activation in the lower-order areas. Conclusion: These findings provide a functional corollary to the canonical view of the temporally sequential advancement of AD pathology through visual cortical areas. The association of the disruption of functional networks, especially the face-evoked visual-processing network, with AD severity suggests a potential predictor or biomarker of AD progression.


2017 ◽  
Vol 265 ◽  
pp. 45-53 ◽  
Author(s):  
Claire E. Wilcox ◽  
Vince D. Calhoun ◽  
Srinivas Rachakonda ◽  
Eric D. Claus ◽  
Rae A. Littlewood ◽  
...  

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