Amblyopia is a common yet hard-to-cure disease in children and results in poor or blurred vision. Some efforts such as voxel-based analysis, cortical thickness analysis have been tried to reveal the pathogenesis of amblyopia. However, few studies focused on alterations of the functional connectivity (FC) in amblyopia. In this study, we analyzed the abnormalities of amblyopia patients by both the seed-based FC with the left/right primary visual cortex and the network constructed throughout the whole brain. Experiments showed the following results: (1)As for the seed-based FC analysis, FC between superior occipital gyrus and the primary visual cortex was found to significantly decrease in both sides. The abnormalities were also found in lingual gyrus. The results may reflect functional deficits both in dorsal stream and ventral stream. (2)Two increased functional connectivities and 64 decreased functional connectivities were found in the whole brain network analysis. The decreased functional connectivities most concentrate in the temporal cortex. The results suggest that amblyopia may be caused by the deficits in the visual information transmission.
Shape regression analysis is a powerful tool to study local shape changes as a function of an independent regressor
variable. In this paper, we introduce spherical harmonic(SPHARM) representation to surface manifold learning and shape regression. Here, we use root mean square distance(RMSD) to measure the deformation degree of the surface, and find out that the hippocampus’ deformation degree is increased over age. We also investigate the particular changing area, and discover that the hippocampus have significant changes in the frontal area and tail area, especially in CA1 subfield.
Hippocampal sclerosis (HS) is the most common damage seen in the patients with temporal lobe epilepsy (TLE). In the
present study, the hippocampal-cortical connectivity was defined as the correlation between the hippocampal volume and
cortical thickness at each vertex throughout the whole brain. We aimed to investigate the differences of ipsilateral
hippocampal-cortical connectivity between the unilateral TLE-HS patients and the normal controls. In our study, the
bilateral hippocampal volumes were first measured in each subject, and we found that the ipsilateral hippocampal
volume significantly decreased in the left TLE-HS patients. Then, group analysis showed significant thinner average
cortical thickness of the whole brain in the left TLE-HS patients compared with the normal controls. We found
significantly increased ipsilateral hippocampal-cortical connectivity in the bilateral superior temporal gyrus, the right
cingulate gyrus and the left parahippocampal gyrus of the left TLE-HS patients, which indicated structural vulnerability
related to the hippocampus atrophy in the patient group. However, for the right TLE-HS patients, no significant
differences were found between the patients and the normal controls, regardless of the ipsilateral hippocampal volume,
the average cortical thickness or the patterns of hippocampal-cortical connectivity, which might be related to less
atrophies observed in the MRI scans. Our study provided more evidence for the structural abnormalities in the unilateral
TLE-HS patients.
Temporal lobe epilepsy (TLE) is one of the most common epilepsy syndromes with focal seizures generated in the left or
right temporal lobes. With the magnetic resonance imaging (MRI), many evidences have demonstrated that the
abnormalities in hippocampal volume and the distributed atrophies in cortical cortex. However, few studies have
investigated if TLE patients have the alternation in the structural networks. In the present study, we used the cortical
thickness to establish the morphological connectivity networks, and investigated the network properties using the graph
theoretical methods. We found that all the morphological networks exhibited the small-world efficiency in left TLE,
right TLE and normal groups. And the betweenness centrality analysis revealed that there were statistical inter-group
differences in the right uncus region. Since the right uncus located at the right temporal lobe, these preliminary evidences
may suggest that there are topological alternations of the cortical anatomical networks in TLE, especially for the right
TLE.
Resting-state functional magnetic resonance imaging (fMRI) is a technique that measures the intrinsic function of brain
and has some advantages over task-induced fMRI. Regional homogeneity (ReHo) assesses the similarity of the time
series of a given voxel with its nearest neighbors on a voxel-by-voxel basis, which reflects the temporal homogeneity of
the regional BOLD signal. In the present study, we used the resting state fMRI data to investigate the ReHo changes of
the whole brain in the prelingually deafened patients relative to normal controls. 18 deaf patients and 22 healthy subjects
were scanned. Kendall's coefficient of concordance (KCC) was calculated to measure the degree of regional coherence
of fMRI time courses. We found that regional coherence significantly decreased in the left frontal lobe, bilateral
temporal lobes and right thalamus, and increased in the postcentral gyrus, cingulate gyrus, left temporal lobe, left
thalamus and cerebellum in deaf patients compared with controls. These results show that the prelingually deafened
patients have higher degree of regional coherence in the paleocortex, and lower degree in neocortex. Since neocortex
plays an important role in the development of auditory, these evidences may suggest that the deaf persons reorganize the
paleocortex to offset the loss of auditory.
Multi-elemental cooperative analysis can not only brings a large number of relevant information but fuzz up key
elements, so valid data excavating tools are needed to find element information which influences entities the most. Based
on the sample of bus site setting in a city, this paper employs Rough Sets method to analyze multi-elemental cooperation
which influence bus site grade and calculate importance of each element. Thus, multi-elemental cooperative analysis can
be realized. Compared with conventional multi-parameter analysis, this method based on data self-adapting is intelligent,
high-efficiency and have no use for manual intervention.
Object selection is an important technical problem in the process of map generalization. Considering creative-thinking
characteristic of map generalization process, the paper bring the Rough Set theory from spatial data mine field to map
generalization field, put forward a new thought for map generalization based on classification idea of Rough Set. The
method of Rough Set which has the benefit on enormous data with the imperfection and non-precision character has
become a new tool to make research on spatial data mining. The paper analyzes the imperfection characters of
geo-spatial data processing based on Rough Set and the selection problem in the processing of map generalization with
classification thought; presents the thought that map generalization is a kind of classification for map objects. The
method mentioned in this paper use different spatial and attribute information as different point of view to observe the
map objects. The result of the classification is ordered by the weightiness of all kinds of factors. In the end, a river
objects selection test validates the rough set map generalization method mentioned in this paper.
KEYWORDS: Virtual reality, 3D modeling, Data modeling, Network architectures, Prototyping, Computing systems, Databases, 3D image processing, Receivers, Geographic information systems
Networked Virtual Reality (NVR) is a system based on net connected and spatial information shared, whose demands cannot be fully meet by the existing architectures and application patterns of VR to some extent. In this paper, we propose a new architecture of NVR based on Multi-Agent framework. which includes the detailed definition of various agents and their functions and full description of the collaboration mechanism, Through the prototype system test with DEM Data and 3D Models Data, the advantages of Multi-Agent based Networked Virtual Reality System in terms of the data loading time, user response time and scene construction time etc. are verified. First, we introduce the characters of Networked Virtual Realty and the characters of Multi-Agent technique in Section 1. Then we give the architecture design of Networked Virtual Realty based on Multi-Agent in Section 2.The Section 2 content includes the rule of task division, the multi-agent architecture design to implement Networked Virtual Realty and the function of agents. Section 3 shows the prototype implementation according to the design. Finally, Section 4 discusses the benefits of using Multi-Agent to implement geovisualization of Networked Virtual Realty.
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