Zhang B.,Otto Von Guericke University of Magdeburg |
Zhang B.,Shanghai JiaoTong University |
Li S.,Otto Von Guericke University of Magdeburg |
Li S.,East China Normal University |
And 13 more authors.
Journal of Affective Disorders | Year: 2017
Background Major depressive disorder (MDD) is a highly prevalent psychiatric condition in which patients often have difficulties regulating their emotions. Prior studies have shown that attention bias towards negative emotion is linked to activation in regions of the default mode network (DMN) in MDD individuals. Furthermore, MDD patients showed increased resting-state functional connectivity (FC) between the medial prefrontal cortex and other DMN structures. Methods Twenty-one MDD patients that currently experiencing depressive episodes and twenty-five healthy control participants performed the current emotional expectancy paradigm in a gradient-echo SENSE-SPIRAL fMRI. Whole brain and psycho-physiological interaction (PPI) analysis were applied to explore the task-related brain activity and FCs. Results Relative to healthy participants, we found MDD patients had greater activity in dorsal medial prefrontal cortex as a function of positive vs. neutral expectancy conditions. PPI results revealed a significant group difference of MDD patients having relatively decreased task-dependent decoupling from dorsal medial prefrontal cortex (DMPFC) towards posterior cingulate cortex (PCC) and parieto-occipital cortex during positive vs. neutral expectancy conditions, and patients exhibited a positive correlation between PPI (DMPFC and PCC) and anhedonia as measured via SHAPS during the same conditions. Limitations Modest sample size and lack of concurrent depressive episodes limit the generalizability of our findings. Conclusions In MDD patients, insufficient DMN decoupling might occur in response to positive expectancy conditions. Our findings are consistent with the hypothesis that high intrinsic DMN connectivity in MDD patients interfere with the down-regulation of intrinsic focus in order to incorporate information derived from external positive events. © 2016
Zhou Z.,Columbia University |
Zhou Z.,New York State Psychiatric Institute |
Liu W.,Columbia University |
Liu W.,New York State Psychiatric Institute |
And 20 more authors.
Magnetic Resonance Imaging | Year: 2011
Signal variation in diffusion-weighted images (DWIs) is influenced both by thermal noise and by spatially and temporally varying artifacts, such as rigid-body motion and cardiac pulsation. Motion artifacts are particularly prevalent when scanning difficult patient populations, such as human infants. Although some motion during data acquisition can be corrected using image coregistration procedures, frequently individual DWIs are corrupted beyond repair by sudden, large amplitude motion either within or outside of the imaging plane. We propose a novel approach to identify and reject outlier images automatically using local binary patterns (LBP) and 2D partial least square (2D-PLS) to estimate diffusion tensors robustly. This method uses an enhanced LBP algorithm to extract texture features from a local texture feature of the image matrix from the DWI data. Because the images have been transformed to local texture matrices, we are able to extract discriminating information that identifies outliers in the data set by extending a traditional one-dimensional PLS algorithm to a two-dimension operator. The class-membership matrix in this 2D-PLS algorithm is adapted to process samples that are image matrix, and the membership matrix thus represents varying degrees of importance of local information within the images. We also derive the analytic form of the generalized inverse of the class-membership matrix. We show that this method can effectively extract local features from brain images obtained from a large sample of human infants to identify images that are outliers in their textural features, permitting their exclusion from further processing when estimating tensors using the DWIs. This technique is shown to be superior in performance when compared with visual inspection and other common methods to address motion-related artifacts in DWI data. This technique is applicable to correct motion artifact in other magnetic resonance imaging (MRI) techniques (e.g., the bootstrapping estimation) that use univariate or multivariate regression methods to fit MRI data to a pre-specified model. © 2011 Elsevier Inc.
Demenescu L.R.,Clinical Affective Neuroimaging Laboratory |
Demenescu L.R.,Otto Von Guericke University of Magdeburg |
Colic L.,Clinical Affective Neuroimaging Laboratory |
Colic L.,Leibniz Institute for Neurobiology |
And 18 more authors.
European Archives of Psychiatry and Clinical Neuroscience | Year: 2016
Abnormal anterior insula (AI) response and functional connectivity (FC) is associated with depression. In addition to clinical features, such as severity, AI FC and its metabolism further predicted therapeutic response. Abnormal FC between anterior cingulate and AI covaried with reduced glutamate level within cingulate cortex. Recently, deficient glial glutamate conversion was found in AI in major depression disorder (MDD). We therefore postulate a local glutamatergic mechanism in insula cortex of depressive patients, which is correlated with symptoms severity and itself influences AI’s network connectivity in MDD. Twenty-five MDD patients and 25 healthy controls (HC) matched on age and sex underwent resting state functional magnetic resonance imaging and magnetic resonance spectroscopy scans. To determine the role of local glutamate–glutamine complex (Glx) ratio on whole brain AI FC, we conducted regression analysis with Glx relative to creatine (Cr) ratio as factor of interest and age, sex, and voxel tissue composition as nuisance factors. We found that in MDD, but not in HC, AI Glx/Cr ratio correlated positively with AI FC to right supramarginal gyrus and negatively with AI FC toward left occipital cortex (p < 0.05 family wise error). AI Glx/Cr level was negatively correlated with HAMD score (p < 0.05) in MDD patients. We showed that the local AI ratio of glutamatergic–creatine metabolism is an underlying candidate subserving functional network disintegration of insula toward low level and supramodal integration areas, in MDD. While causality cannot directly be inferred from such correlation, our finding helps to define a multilevel network of response-predicting regions based on local metabolism and connectivity strength. © 2016 Springer-Verlag Berlin Heidelberg
Hu C.,Key Laboratory of Brain Functional Genomics |
Ma M.-L.,Key Laboratory of Brain Functional Genomics |
Li X.-Y.,Key Laboratory of Brain Functional Genomics |
Hu W.-J.,Key Laboratory of Brain Functional Genomics |
And 3 more authors.
Gaodeng Xuexiao Huaxue Xuebao/Chemical Journal of Chinese Universities | Year: 2011
Aligning functional groups on a respective molecular platform is one of the fundamental design principle in construction of supramolecular objects. The geometrical alignment of the functional groups of the tripodal molecular scaffold, 1, 3, 5-trisubstituted-2, 4, 6-triethyllbenzene, has made it fulfill this requirement, and thus being used extensively as molecular platform in designing artificial receptors. Tripodal 1, 3, 5-tris(2-methylenemalonic acid)-2, 4, 6-triethyllbenzene derivatives(2-5), 1, 3, 5-tris(2-methylenepentane-2, 4-dione)-2, 4, 6-triethyllbenzene(6) and 1, 3, 5-tri[(3, 5-dimethyl-1H-pyrazol-4-yl)methyl]-2, 4, 6-triethylbenzene(7), adopting up-down alternate conformations with three substituted functional groups reside on one side of the central phenyl plane, and the three ethyl groups located on the opposite side of the central benzene ring, have thus been synthesized. 1H NMR spectra of these compounds were in accord with that they are all in high levels of symmetry. Single crystal X-ray structure analysis revealed that they all indeed adopt an 1, 3, 5-alternate conformation with the three functional arms reside on one side of the benzene plane, and the three ethyl groups were placed on the opposite side of the benzene plane. Intermolecular hydrogen-bond interactions were the major driving force for the solid state assembly of the compounds with malonic acid(4), malonamide(5), as well as 3, 5-dimethyl-1H-pyrazolyl(7) functions. However, no molecular capsules were formed by these compounds via intermolecular hydrogen-bond interactions in the solid state. The interaction of copper(II) ions and pyrazolyl-containing compound 7(L) resulted in the formation of a discrete cylindrical cage-like complex(Cu3L2)(8) via Cu-N coordination bonds by the connection of three Cu2+ ions and six pyrazolyl nitrogen atoms from two 7 ligands. The two ligands 7 in complex 8 were in a cis, cis, cis-conformation and a face-to-face orientation. The system could thus been used in construction of tripo-shaped molecular scaffold with high local concentration of those functional groups.
Liu X.,Key Laboratory of Brain Functional Genomics |
Liu X.,East China Normal University |
Liu X.,Columbia University |
Liu W.,Key Laboratory of Brain Functional Genomics |
And 7 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011
Region-based active contour model (ACM) has been extensively used in medical image segmentation and Chan & Vese's (C-V) model is one of the most popular ACM methods. We propose to incorporate into the C-V model a weighting function to take into consideration the fact that different locations in an image with differing distances from the active contour have differing importance in generating the segmentation result, thereby making it a weighted C-V (WC-V) model. The theoretical properties of the model and our experiments both demonstrate that the proposed WC-V model can significantly reduce the computational cost while improve the accuracy of segmentation over the results using the C-V model. © 2011 Springer-Verlag.
Liu X.,Key Laboratory of Brain Functional Genomics |
Liu X.,East China Normal University |
Liu X.,Columbia University |
Yang G.,Key Laboratory of Brain Functional Genomics |
And 5 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010
High angular resolution diffusion imaging (HARDI) has become an important tool for resolving neural architecture in regions with complex patterns of fiber crossing. A popular method for estimating the diffusion orientation distribution function (ODF) employs a least square (LS) approach by modeling the raw HARDI data on a spherical harmonic basis. We propose herein a novel approach for reconstruction of ODF fields from raw HARDI data that combines into one step the smoothing of raw HARDI data and the estimation of ODF field using correlated information in a local neighborhood. Based on the most popular method of least square for estimating ODF, we incorporated into it local weights that are determined by a special weighting function, making it a locally weighted linear least square method (LWLLS). The method thus can efficiently perform the smoothing of HARDI data and estimating the ODF field simultaneously. We evaluated the effectiveness of this method using both simulated and real-world HARDI data. © 2010 Springer-Verlag.
Lack of global precedence and global-to-local interference without local processing deficit: A robust finding in children with attention-deficit/hyperactivity disorder under different visual angles of the Navon task
Song Y.,Key Laboratory of Brain Functional Genomics |
Song Y.,East China Normal University |
Hakoda Y.,China Women's University
Neuropsychology | Year: 2015
Objective: The Navon effect (Navon, 1977) is an automatic tendency to process the global picture prior to local details when processing compound patterns. However, several recent studies have reported that this effect is lacking in attention-deficit/hyperactivity disorder (ADHD). Although previous research has shown that the Navon effect is strongly affected by visual angles, whether this phenomenon will also be observed in ADHD is yet to be understood. We examine the lack of the Navon effect in ADHD under various visual angles to ensure that this phenomenon is not an artifact of saliency. Method: By employing three different visual angles for the local stimuli, global and local processing of Navon-type hierarchical letters was examined in participants with ADHD (n = 15) and a comparison group (n = 17). Results: ADHD participants presented with a lack of the Navon effect without local processing deficit regardless of visual angle, in comparison to non-ADHD participants. Conclusion: A lack of global precedence and global-to-local interference without local processing deficit can be generalized in ADHD. This suggests that people with ADHD experience difficulties in processing the "whole picture," and it also challenges the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; American Psychiatric Association, 2013) criteria of ADHD in which the failure to pay close attention to details was emphasized. Moreover, the current results have important implications for understanding ADHD and could also have significant clinical value.