FMI Studies in Obesity

FMI Studies in ObesityObesity insights from fMRI vision studiesAbstract third gear of the US adult population is heavy. Obesity is associated with serious medical complications and cost a lot of money. In my paper, we leave study this phenomena with fMRI ( serviceal magnetic resonance imaging) when subjects were at resting state (subjects were instructed simply to keep their eyes unlikable and to not think of anything in particular). Before this, we postulate that there testament be disruption in neural term of enlistments, which subject in fleshiness. thither argon four circuits that we mainly focus on (a) reward, find in the effect accumbens (NAc) and the ventral pallidum (b) motivation/drive, located in the orbitofrontal lens cerebral cortex (OFC) and the subcallosal cortex (c) memory and encyclopedism, located in the amygdala and the hippocampus and (d) potency, located in the prefrontal cortex and the anterior cingulate gyrus (CG). We used SPM, which found on Mat lab, to analyse our data, and processed the results by GCA ( granger causality analysis). by it, we will get the connection between two ROIs(region of interesting).Key spoken langu maturate fleshiness fMRI resting state GCA(Granger causality analysis)IntroductionObesity is a global line with the improvement of our life. in that location be one-third of US adult population who is obese, whose body mass index(BMI)30 kg*m-2.1 Undoubtedly, obesity costs a lot because it is associated with serious diseases(e.g. diabetes, heart disease, fatty liver and approximately stinkpotcers)2,3. What lead to obesity ar complex and ambiguity, such as social and cultural factors, environments that promote unhealthy eating habits and physical inactivity, unmarried factors, etc 4. Obesity with long time can result in use of goods and services substitutes in human brain, but we do not know how this works. bare-ass imaging technologies such as positron emission tomography ( court) and availa ble magnetic resonance imaging (fMRI) have provided new ways to check into the relationship of human brain. Much of previous studies were based on PET images which focus on the brain dopamine system, they found that there are different between normal and obese in DA system.Methods base on previous studies, we study function changes of human brain by fMRI. On account of discover that early(a)s found before, we support some hypotheses that obesity can result in difference between normal and obese. We think on four brain circuits in our research which were discussed in drug-addiction. As well, what we found mayhap provide a method to treat obesity. There are two groups, one is normal and the other is obesity. The information of subjects are showed in Figure1. In our experiment, there were three groups, which were obesity before operating theatre and after one month, compared with the normal control. We collected data form TangDu Hospital. During scanning, subjects were asked for c limax eyes Figure1Subjects Information. StandardDeviation(STD). Body Mass Index(BMI). Yale Food Addiction scale(YFAS). Sympton Check come 90(SCL90).without thinking anything but waking. Before scanning, they filled a questionnaire, which include depression, anxiety, and so on, to see their mental state. In this address, we just analysed the data that scanned before military operation and normal control.Obesity involved multiple brain circuitsObesity can result in multiple variation, however, there are four circuits which are very important in obesity (a) reward, located in the nucleus accumbens (NAc) and the ventral pallidum (b) motivation/drive, located in the orbitofrontal cortex (OFC) and the subcallosal cortex (c) memory and learning, located in the amygdala and the hippocampus and (d) control, located in the prefrontal cortex and the anterior cingulate gyrus (CG). These circuits work together and change with experience5,6. Moreover, there are other circuits involved in obesi ty which we will study further.Four circuits in obesityWe processed data through and through SPM,7 which is based on matlab. After that, we analysed the data by GCA(Granger Casual Analysis)8. At resting state, we found that there was abnormal in motivation/drive circuit which receded in obesity than normal (figure2). Because of the exception of motivation, it could lead to disorder of other circuits. In reward circuit, the saliency value to regimen stimulation was define in obesity, which resulted in overeating to reach satisfy. Circuit of memory and learning maybe influence individual habit. When somebody who is overweight saw intellectual nourishment or some place for more time. He or she would mark the stimulation and when he or she met it again, it would arouse memory to drive individual to get it. We also found that there was reduction in control circuit. Due to this reduction, obesity can not control their eating style very well even if they were full. BasedFigure2Result of GCA 10 .on these disorder, we postulate that long-term obesity destroyed human brain functionthrough the top-down modulation9.Vulnerability to obesityA challenging problem in the neurobiology of obesity is to understand why some individuals become obese while others do not. Genetic factors are estimated to contribute between 45% and 85% of the variability in BMI 3,4. Beyond that, we hypothesize that decreased esthesia of reward circuit and the disorder of control circuit in obesity would lead a subject more or less open to regimen. At the same time, the environment that subjects could get high calorie food was significant. Because of these findings, obese could lose fat by intervening the brain circuits or controlling the environment around obesity.DiscussionIn our study, we just pore on four brain circuits. There were other circuits which involved in obesity. In further study, we would find them and research their function. In the future, our discover maybe be applied to cl inic treatment with less wounds. There are some limitation in our experiment, for example, we didnt get the result of fMRI what was gotten when subjects were at tasking state(somebody lies on bed with seeing images which are about low or high calorie food). In the further research, we will combine these result and obtain an excellent conclusion.AcknowledgmentsThis work was supported by National graphic Science Foundation of China. My tutor gave me help on many fronts. I have to appreciate upperclassmen who gave me help too. The doctors who scanned subjects, the subjects who coordinated our experiment and the authors who provided idea should be given great appreciation. Finally, thanking Dr. Karen for teaching me how to address our experiment.References1 N.D. Volkow, Gene-Jack Wang and R.D. Baler, Reward, dopamine and the control of food intake implications for obesity, Trends in Cognitive Sciences January 2011, Vol. 15, No. 1.2 Finkelstein, E.A.et al.(2009) Annual medical disbursa l attributable to obesity payer-and service-specific estimates. Health Aff.28, w822w8313 Baessler, A.et al.(2005) Genetic linkage and association of the ripening hormone secretagogue receptor (ghrelin receptor) gene in human obesity. Diabetes 54, 2592674 Silventoinen, K. and Kaprio, J. (2009) Genetics of introduce of body mass index from birth to late middle age evidence from twin and family studies. Obes. Facts 2, 1962025 N. D. Volkow, J. S. Fowler, and Gene-Jack Wang,(2003) The addicted human brain insights from imaging studies, posture SERIES, 11114441451.6 N.D. Volkow, B. Rosen, and L.Farde, 1997. Imaging the living human brain magnetic resonance imaging and positron emission tomography. Proc. Natl. Acad. Sci. U. S. A. 9427872788.7 ReHofMRI1.0 (by Dr. HE Yong, free download from http//www.bic.mni.mcgill.ca/users/yonghe)8 Mingzhou Ding, Yonghong Chen, Steven L. Bressler, Granger Causality Basic Theory and coat to Neuroscience, Preprint submitted to Elsevier Science,2008.02.07 .9 Wen X, Liu Y, Yao L, Ding M (2013) Top-down regulation of default mode activity in spatial visual attention. J Neurosci 33(15) 6444 645310 Mingzhou Ding, Yonghong Chen,(2006) Granger Causality Basic Theory and Application to Neuroscience, Preprint submitted to Elsevier Science, arXivq-bio/0608035v1Cai Weiwei