http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : R Southgate (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
-
-
-
Childhood Features which Correlated with the Evolving Course of Anorexia Nervosa
YoulRi Kim,Laura Southgate 대한신경정신의학회 2007 PSYCHIATRY INVESTIGATION Vol.4 No.1
Objective-The aim of this study was to determine the extent to which the childhood features correlate with the evolving course of anorexia nervosa (AN). Methods-All participants with a lifetime diagnosis of AN (restricting or binge purging subtype) were from our volunteer database maintained by the eating disorders research register at Institute of Psychiatry in London. By 3 years after entry to the register, 65 participants continued to fulfill the criteria for AN, 40 participants had moved to develop a bulimic spectrum disorder, and 37 participants had remitted. We performed comprehensive assessements of the developmental factors based on an adapted form of the McKnight Risk Factor Scale to identify which features correlate with the course of AN. Results-Those subjects with restricting AN were more likely to continue their disease. Those with binge purging AN were more likely to undergo a later transition to a bulimic spectrum disorder. Those with continued AN were less likely to report emotional overeating in childhood. Those whose disease transformed into a bulimic spectrum disorder were more likely to have parents or adults concerned with thinness and to experience high parental expectations. Conclusions-There were only a few differences in the important childhood factors between the groups, viz. emotional eating, adults concerned with thinness, and parental expectations. The new instrument which we used to measure the childhood factors is a valuable one to assess a broad range of developmental feasures for AN.
-
Bulgarelli, Chiara,Blasi, Anna,Arridge, Simon,Powell, Samuel,de Klerk, Carina C.J.M.,Southgate, Victoria,Brigadoi, Sabrina,Penny, William,Tak, Sungho,Hamilton, Antonia Elsevier 2018 NeuroImage Vol.175 No.-
<P><B>Abstract</B></P> <P>Tracking the connectivity of the developing brain from infancy through childhood is an area of increasing research interest, and fNIRS provides an ideal method for studying the infant brain as it is compact, safe and robust to motion. However, data analysis methods for fNIRS are still underdeveloped compared to those available for fMRI. Dynamic causal modelling (DCM) is an advanced connectivity technique developed for fMRI data, that aims to estimate the coupling between brain regions and how this might be modulated by changes in experimental conditions. DCM has recently been applied to adult fNIRS, but not to infants. The present paper provides a proof-of-principle for the application of this method to infant fNIRS data and a demonstration of the robustness of this method using a simultaneously recorded fMRI-fNIRS single case study, thereby allowing the use of this technique in future infant studies.</P> <P>fMRI and fNIRS were simultaneously recorded from a 6-month-old sleeping infant, who was presented with auditory stimuli in a block design. Both fMRI and fNIRS data were preprocessed using SPM, and analysed using a general linear model approach. The main challenges that adapting DCM for fNIRS infant data posed included: (i) the import of the structural image of the participant for spatial pre-processing, (ii) the spatial registration of the optodes on the structural image of the infant, (iii) calculation of an accurate 3-layer segmentation of the structural image, (iv) creation of a high-density mesh as well as (v) the estimation of the NIRS optical sensitivity functions. To assess our results, we compared the values obtained for variational Free Energy (F), Bayesian Model Selection (BMS) and Bayesian Model Average (BMA) with the same set of possible models applied to both the fMRI and fNIRS datasets. We found high correspondence in F, BMS, and BMA between fMRI and fNIRS data, therefore showing for the first time high reliability of DCM applied to infant fNIRS data. This work opens new avenues for future research on effective connectivity in infancy by contributing a data analysis pipeline and guidance for applying DCM to infant fNIRS data.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Connectivity studies give important insights into infant brain development. </LI> <LI> fNIRS is a valuable method for infancy studies, but can we analyse connectivity? </LI> <LI> On fMRI-fNIRS acquired simultaneously, we estimate effective connectivity with DCM. </LI> <LI> We showed high correspondence of DCM values between fMRI and fNIRS data. </LI> <LI> We validated DCM on fNIRS infant data, providing guidance for future projects. </LI> </UL> </P>
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
