scholarly journals Erratum for van Meer F et al. Developmental differences in the brain response to unhealthy food cues: an fMRI study of children and adults. Am J Clin Nutr 2016;104:1515–22

2017 ◽  
Vol 105 (3) ◽  
pp. 772.1-772
2016 ◽  
Vol 104 (6) ◽  
pp. 1515-1522 ◽  
Author(s):  
Floor van Meer ◽  
Laura N van der Laan ◽  
Lisette Charbonnier ◽  
Max A Viergever ◽  
Roger AH Adan ◽  
...  

2014 ◽  
Vol 99 (10) ◽  
pp. E2101-E2106 ◽  
Author(s):  
Agatha A. van der Klaauw ◽  
Elisabeth A. H. von dem Hagen ◽  
Julia M. Keogh ◽  
Elana Henning ◽  
Stephen O'Rahilly ◽  
...  

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 286
Author(s):  
Soheil Keshmiri

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.


2007 ◽  
Vol 104 (46) ◽  
pp. 18276-18279 ◽  
Author(s):  
K. Baicy ◽  
E. D. London ◽  
J. Monterosso ◽  
M.-L. Wong ◽  
T. Delibasi ◽  
...  
Keyword(s):  

NeuroImage ◽  
2000 ◽  
Vol 11 (5) ◽  
pp. S49
Author(s):  
D.L. Harrington ◽  
L.A. Mead ◽  
A.R. Mayer ◽  
K.Y. Haaland ◽  
S.M. Rao

2011 ◽  
Vol 33 (8) ◽  
pp. 1780-1791 ◽  
Author(s):  
Andrea Ginestroni ◽  
Stefano Diciotti ◽  
Paolo Cecchi ◽  
Ilaria Pesaresi ◽  
Carlo Tessa ◽  
...  

Author(s):  
M. S. Chafi ◽  
V. Dirisala ◽  
G. Karami ◽  
M. Ziejewski

In the central nervous system, the subarachnoid space is the interval between the arachnoid membrane and the pia mater. It is filled with a clear, watery liquid called cerebrospinal fluid (CSF). The CSF buffers the brain against mechanical shocks and creates buoyancy to protect it from the forces of gravity. The relative motion of the brain due to a simultaneous loading is caused because the skull and brain have different densities and the CSF surrounds the brain. The impact experiments are usually carried out on cadavers with no CSF included because of the autolysis. Even in the cadaveric head impact experiments by Hardy et al. [1], where the specimens are repressurized using artificial CSF, this is not known how far this can replicate the real functionality of CSF. With such motivation, a special interest lies on how to model this feature in a finite element (FE) modeling of the human head because it is questionable if one uses in vivo CSF properties (i.e. bulk modulus of 2.19 GPa) to validate a FE human head against cadaveric experimental data.


2018 ◽  
Vol 314 (5) ◽  
pp. E522-E529 ◽  
Author(s):  
Renata Belfort-DeAguiar ◽  
Dongju Seo ◽  
Cheryl Lacadie ◽  
Sarita Naik ◽  
Christian Schmidt ◽  
...  

Blood glucose levels influence brain regulation of food intake. This study assessed the effect of mild physiological hyperglycemia on brain response to food cues in individuals with obesity (OB) versus normal weight individuals (NW). Brain responses in 10 OB and 10 NW nondiabetic healthy adults [body mass index: 34 (3) vs. 23 (2) kg/m2, means (SD), P < 0.0001] were measured with functional MRI (blood oxygen level-dependent contrast) in combination with a two-step normoglycemic-hyperglycemic clamp. Participants were shown food and nonfood images during normoglycemia (~95 mg/dl) and hyperglycemia (~130 mg/dl). Plasma glucose levels were comparable in both groups during the two-step clamp ( P = not significant). Insulin and leptin levels were higher in the OB group compared with NW, whereas ghrelin levels were lower (all P < 0.05). During hyperglycemia, insula activity showed a group-by-glucose level effect. When compared with normoglycemia, hyperglycemia resulted in decreased activity in the hypothalamus and putamen in response to food images ( P < 0.001) in the NW group, whereas the OB group exhibited increased activity in insula, putamen, and anterior and dorsolateral prefrontal cortex (aPFC/dlPFC; P < 0.001). These data suggest that OB, compared with NW, appears to have disruption of brain responses to food cues during hyperglycemia, with reduced insula response in NW but increased insula response in OB, an area involved in food perception and interoception. In a post hoc analysis, brain activity in obesity appears to be associated with dysregulated motivation (striatum) and inappropriate self-control (aPFC/dlPFC) to food cues during hyperglycemia. Hyperstimulation for food and insensitivity to internal homeostatic signals may favor food consumption to possibly play a role in the pathogenesis of obesity.


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