scholarly journals Identification of human brain regions underlying responses to resistive inspiratory loading with functional magnetic resonance imaging.

1995 ◽  
Vol 92 (14) ◽  
pp. 6607-6611 ◽  
Author(s):  
D. Gozal ◽  
O. Omidvar ◽  
K. A. Kirlew ◽  
G. M. Hathout ◽  
R. Hamilton ◽  
...  
2021 ◽  
Author(s):  
Yu Wang ◽  
Hongfei Jia ◽  
Yifan Duan ◽  
Hongbing Xiao

Abstract Alzheimer's disease (AD) is a progressive neurodegenerative disease, which changes the structure of brain regions by some hidden causes. In this paper for assisting doctors to make correct judgments, an improved 3DPCANet method is proposed to classify AD by combining the mean (mALFF) of the whole brain. The main idea includes that firstly, the functional magnetic resonance imaging (fMRI) data is pre-processed, and mALFF is calculated to get the corresponding matrix. Then the features of mALFF images are extracted via the improved 3DPCANet network. Finally, AD patients with different stages are classified using support vector machine (SVM). Experiments results based on public data from the Alzheimer’s disease neuroimaging initiative (ADNI) show that the proposed approach has better performance compared with state-of-the-art methods. The accuracies of AD vs. significant memory concern (SMC), SMC vs. late mild cognitive impairment (LMCI), and normal control (NC) vs. SMC reach respectively 92.42%, 91.80%, and 89.50%, which testifies the feasibility and effectiveness of the proposed method.


2020 ◽  
Vol 63 (9) ◽  
pp. 3051-3067
Author(s):  
Amy E. Ramage ◽  
Semra Aytur ◽  
Kirrie J. Ballard

Purpose Brain imaging has provided puzzle pieces in the understanding of language. In neurologically healthy populations, the structure of certain brain regions is associated with particular language functions (e.g., semantics, phonology). In studies on focal brain damage, certain brain regions or connections are considered sufficient or necessary for a given language function. However, few of these account for the effects of lesioned tissue on the “functional” dynamics of the brain for language processing. Here, functional connectivity (FC) among semantic–phonological regions of interest (ROIs) is assessed to fill a gap in our understanding about the neural substrates of impaired language and whether connectivity strength can predict language performance on a clinical tool in individuals with aphasia. Method Clinical assessment of language, using the Western Aphasia Battery–Revised, and resting-state functional magnetic resonance imaging data were obtained for 30 individuals with chronic aphasia secondary to left-hemisphere stroke and 18 age-matched healthy controls. FC between bilateral ROIs was contrasted by group and used to predict Western Aphasia Battery–Revised scores. Results Network coherence was observed in healthy controls and participants with stroke. The left–right premotor cortex connection was stronger in healthy controls, as reported by New et al. (2015) in the same data set. FC of (a) connections between temporal regions, in the left hemisphere and bilaterally, predicted lexical–semantic processing for auditory comprehension and (b) ipsilateral connections between temporal and frontal regions in both hemispheres predicted access to semantic–phonological representations and processing for verbal production. Conclusions Network connectivity of brain regions associated with semantic–phonological processing is predictive of language performance in poststroke aphasia. The most predictive connections involved right-hemisphere ROIs—particularly those for which structural adaptions are known to associate with recovered word retrieval performance. Predictions may be made, based on these findings, about which connections have potential as targets for neuroplastic functional changes with intervention in aphasia. Supplemental Material https://doi.org/10.23641/asha.12735785


Nutrients ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 3010
Author(s):  
Andy Wai Kan Yeung ◽  
Natalie Sui Miu Wong

This systematic review aimed to reveal the differential brain processing of sugars and sweeteners in humans. Functional magnetic resonance imaging studies published up to 2019 were retrieved from two databases and were included into the review if they evaluated the effects of both sugars and sweeteners on the subjects’ brain responses, during tasting and right after ingestion. Twenty studies fulfilled the inclusion criteria. The number of participants per study ranged from 5 to 42, with a total number of study participants at 396. Seven studies recruited both males and females, 7 were all-female and 6 were all-male. There was no consistent pattern showing that sugar or sweeteners elicited larger brain responses. Commonly involved brain regions were insula/operculum, cingulate and striatum, brainstem, hypothalamus and the ventral tegmental area. Future studies, therefore, should recruit a larger sample size, adopt a standardized fasting duration (preferably 12 h overnight, which is the most common practice and brain responses are larger in the state of hunger), and reported results with familywise-error rate (FWE)-corrected statistics. Every study should report the differential brain activation between sugar and non-nutritive sweetener conditions regardless of the complexity of their experiment design. These measures would enable a meta-analysis, pooling data across studies in a meaningful manner.


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