Biomedical subjects

Yufeng Zang

Publications and source records attributed to Yufeng Zang.

13 recordsLinked to original sources

PubMed2006

Abnormal neural activity in children with attention deficit hyperactivity disorder: a resting-state functional magnetic resonance imaging study.

In this study, a newly reported regional homogeneity approach was used to analyze blood oxygen level-dependent functional magnetic resonance imaging data on resting state in boys with attention deficit hyperactivity disorder. Boys with attention deficit hyperactivity disorder showed decreased regional homogeneity in the frontal-striatal-cerebellar circuits, but increased regional homogeneity mainly in the occipital cortex. Our findings are consistent with the hypothesis of abnormal frontal-striatal-cerebellar circuits in attention deficit hyperactivity disorder. The regional homogeneity approach may be a potentially useful method in exploring the pathophysiology of attention deficit hyperactivity disorder.

Adolescent↗

PubMed2006

Altered resting-state functional connectivity patterns of anterior cingulate cortex in adolescents with attention deficit hyperactivity disorder.

Dorsal anterior cingulate cortex (dACC) has been found to function abnormally in attention deficit hyperactivity disorder (ADHD) patients in several former functional MRI (fMRI) studies. Resting-state low-frequency fluctuations (LFFs) of blood oxygen level-dependent (BOLD) fMRI signals have been proved to be quite informative. This study used resting-state LFFs to investigate the resting-state functional connectivity pattern differences of dACC in adolescents with and without ADHD. As compared to the controls, the ADHD patients exhibited more significant resting-state functional connectivities with the dACC in bilateral dACC, bilateral thalamus, bilateral cerebellum, bilateral insula and bilateral brainstem (pons). No brain region in the controls was found to exhibit more significant resting-state functional connectivity with the dACC. We suggest these abnormally more significant functional connectivities in the ADHD patients may indicate the abnormality of autonomic control functions in them.

Adolescent↗

PubMed2006

Changes in hippocampal connectivity in the early stages of Alzheimer's disease: evidence from resting state fMRI.

A selective distribution of Alzheimer's disease (AD) pathological lesions in specific cortical layers isolates the hippocampus from the rest of the brain. However, functional connectivity between the hippocampus and other brain regions remains unclear in AD. Here, we employ a resting state functional MRI (fMRI) to examine changes in hippocampal connectivity comparing 13 patients with mild AD versus 13 healthy age-matched controls. Hippocampal connectivity was investigated by examination of the correlation between low frequency fMRI signal fluctuations in the hippocampus and those in all other brain regions. We found that functional connectivity between the right hippocampus and a set of regions was disrupted in AD; these regions are: medial prefrontal cortex (MPFC), ventral anterior cingulate cortex (vACC), right inferotemporal cortex, right cuneus extending into precuneus, left cuneus, right superior and middle temporal gyrus and posterior cingulate cortex (PCC). We also found increased functional connectivity between the left hippocampus and the right lateral prefrontal cortex in AD. In addition, rightward asymmetry of hippocampal connectivity observed in elderly controls was diminished in AD patients. The disrupted hippocampal connectivity to the MPFC, vACC and PCC provides further support for decreased activity in "default mode network" previously shown in AD. The decreased connectivity between the hippocampus and the visual cortices might indicate reduced integrity of hippocampus-related cortical networks in AD. Moreover, these findings suggest that resting-state fMRI might be an appropriate approach for studying pathophysiological changes in early AD.

Aged↗

PubMed2006

Handedness-related functional connectivity using low-frequency blood oxygenation level-dependent fluctuations.

Functional neuroimaging studies of handedness have traditionally focused on exploring regionally activated discrepancies, yet little is known regarding the effect of handedness on functional connections of brain regions. Here, we reported the relationship between cerebellar functional connectivity patterns and handedness by low-frequency blood oxygenation level-dependent fluctuations. Compared with the right-handers, the left-handers show higher cerebellar-prefrontal, cerebellar-parietal, and cerebellar-temporal functional connectivity, and lower cerebellar-limbic connectivity. Previous non-human primate studies have shown that these regions with known contributions to higher cognitive functions have afferent or efferent connections with the cerebellum. Our findings suggest that these observed low-frequency fluctuation correlations may reflect actually anatomic connections between the cerebellum and cerebral cortex, and the cerebellar involvement in higher function may be associated with handedness.

Adult↗

PubMed2005

Side and handedness effects on the cingulum from diffusion tensor imaging.

In order to explore the microstructure of bilateral cingulum bundles associated with side and handedness, fractional anisotropy was extracted from diffusion tensor imaging. Distinguished from the conventional region of interest-based method, a fiber-based analysis method called scale-invariant parameterization method was employed to ascertain the anisotropy along the cingulum bundle in 31 normal right-handers and 14 normal left-handers. The statistical results showed a remarkable left-greater-than-right asymmetry pattern of anisotropy in most segments of cingulum bundles except the most posterior segment, for both right-handers and left-handers. Interestingly, higher anisotropy of the right-hander than the left-hander was found in the bilateral cingulum bundles. No significant handedness-by-side interaction was obtained in the present study, however.

Adult↗

PubMed2005

Asymmetry analysis of cingulum based on scale-invariant parameterization by diffusion tensor imaging.

Current analysis of diffusion tensor imaging (DTI) is based mostly on a region of interest (ROI) in an image dataset, which is specified by users. This method is not always reliable, however, because of the uncertainty of manual specification. We introduce an improved fiber-based scheme rather than an ROI-based analysis to study in DTI datasets of 31 normal subjects the asymmetry of the cingulum, which is one of the most prominent white matter fiber tracts of the limbic system. The present method can automatically extract the quantitative anisotropy properties along the cingulum bundles from tractography. Moreover, statistical analysis was carried out after anatomic correspondence specific to the cingulum across subjects was established, rather than the traditional whole-brain registration. The main merit of our method compared to existing counterparts is that to find such anatomic correspondence in cingulum, a scale-invariant parameterization method by arc-angle was proposed. It can give a continuous and exact description on any segment of cingulum. More interestingly, a significant left-greater-than-right asymmetry pattern was obtained in most segments of cingulum bundle (-50-25 degrees), except in the most posterior portion of cingulum (25-50 degrees).

Adult↗

PubMed2005

Single-trial variable model for event-related fMRI data analysis.

Most methods for fMRI data analysis assume that the hemodynamic responses (HRs) across similar experimental events are same. This assumption is not appropriate when HRs vary unpredictably from trial to trial. Here, we introduce a new method for fMRI data analysis. The main features of the proposed method are as follows: 1) The trial-to-trial variability is modeled as meaningful signal rather than assuming that the same HR is evoked in each trial; 2) Since the proposed method is a constrained optimization based general framework, it could be extended by utilizing prior knowledge of HR; 3) The traditional deconvolution method can be included into our method as a special case. A comparison of performance on simulated fMRI datasets is made using the general linear model, the deconvolution method and the proposed method with receiver operating characteristic (ROC) methodology. In addition, we examined the effectiveness and usefulness of our method on real experimental data.

Adult↗

PubMed2004

Modulation of functional connectivity during the resting state and the motor task.

Quite a few studies in functional magnetic resonance imaging (fMRI) have tested that, even in a resting state, motor cortices constitute a network. It has never been investigated how the network modulates from the resting state to the motor task state. In this report, by a newly developed approach taking into account n-to-1 connectivity using 1-to-1 connectivity measures instead of conventional pairwise connectivity, we show the existence of a large organized functional connectivity network related to motor function in the resting brain with fMRI. More importantly, we found that such a network can be modulated from a conscious resting state to planning, initiation, coordination, guidance, and termination of voluntary movement state, exhibited by significant changes of functional connectivity of some brain regions in different brain activity. Moreover, a quantitative description of such a functional modulation has also been presented.

Adult↗

PubMed2004

A split-merge-based region-growing method for fMRI activation detection.

We introduce a hybrid method for functional magnetic resonance imaging (fMRI) activation detection based on the well-developed split-merge and region-growing techniques. The proposed method includes conjoining both of the spatio-temporal priors inherent in split-merge and the prior information afforded by the hypothesis-led component of region selection. Compared to the fuzzy c-means clustering analysis, this method avoids making assumptions about the number of clusters and the computation complexity is reduced markedly. We evaluated the effectiveness of the proposed method in comparison with the general linear model and the fuzzy c-means clustering method conducted on simulated and in vivo datasets. Experimental results show that our method successfully detected expected activated regions and has advantages over the other two methods.

Acoustic Stimulation↗

PubMed2004

Regional homogeneity approach to fMRI data analysis.

Kendall's coefficient concordance (KCC) can measure the similarity of a number of time series. It has been used for purifying a given cluster in functional MRI (fMRI). In the present study, a new method was developed based on the regional homogeneity (ReHo), in which KCC was used to measure the similarity of the time series of a given voxel to those of its nearest neighbors in a voxel-wise way. Six healthy subjects performed left and right finger movement tasks in event-related design; five of them were additionally scanned in a rest condition. KCC was compared among the three conditions (left finger movement, right finger movement, and the rest). Results show that bilateral primary motor cortex (M1) had higher KCC in either left or right finger movement condition than in rest condition. Contrary to prediction and to activation pattern, KCC of ipsilateral M1 is significantly higher than contralateral M1 in unilateral finger movement conditions. These results support the previous electrophysiologic findings of increasing ipsilateral M1 excitation during unilateral movement. ReHo can consider as a complementary method to model-driven method, and it could help reveal the complexity of the human brain function. More work is needed to understand the neural mechanism underlying ReHo.

Adult↗

PubMed2003

Functional organization of the primary motor cortex characterized by event-related fMRI during movement preparation and execution.

Neuronal recording and neuroimaging studies have shown that the primary motor area (M1) not only participates in motor execution, but is also engaged during movement preparation. The purpose of the present study was to map the distribution of the preparation- and execution-related activity within the contralateral M1 using functional magnetic resonance imaging. Eleven subjects performed a delayed sequential finger movement task, in which a CUE signal indicated a movement sequence in advance of an imperative GO signal. The hemodynamic response related to the CUE and GO signals decreased in a linear fashion across the central sulcus, with activity greater along the lateral extent compared to the medial extent. This decrease was especially evident in the epoch following the CUE. Our data reveal a pattern of functional organization within M1 related to the preparation and execution of movement sequences.

Adult↗

PubMed2003

Region growing method for the analysis of functional MRI data.

Existing analytical techniques for functional magnetic resonance imaging (fMRI) data always need some specific assumptions on the time series. In this article, we present a new approach for fMRI activation detection, which can be implemented without any assumptions on the time series. Our method is based on a region growing method, which is very popular for image segmentation. A comparison of performance on fMRI activation detection is made between the proposed method and the deconvolution method and the fuzzy clustering method with receiver operating characteristic (ROC) methodology. In addition, we examine the effectiveness and usefulness of our method on real experimental data. Experimental results show that our method outperforms over the deconvolution method and the fuzzy clustering method on a number of aspects. These results suggest that our region growing method can serve as a reliable analysis of fMRI data.

Acoustic Stimulation↗

PubMed2003

A modified temporal self-correlation method for analysis of fMRI time series.

Temporal self-correlation has recentlybeen proposed as a measure for fMRI-activation detection. In this paper, a modified temporal self-correlation method is introduced. The modified temporal self-correlation is based on the expectation value and standard deviation of the correlation coefficients between all pairs of epochs, while the original temporal self-correlation method is only based on the expectation value. Performance of the proposed method is evaluated on both simulated and in vivo fMRI data. Compared with the original temporal self-correlation method, the proposed method shows a significant improvement. In addition, a technique for quantitative comparison of different fMRI data analysis methods is proposed.

Algorithms↗