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Julia M. Stephen
The Mind Research Network
Developmental psychologyPsychologyNeuroscienceCognitionMagnetoencephalography
109Publications
22H-index
1,359Citations
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Publications 123
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#1Julia M. Stephen (The Mind Research Network)H-Index: 22
#2Shikhar Shrestha (UNM: University of New Mexico)H-Index: 5
Last. Ludmila N. Bakhireva (UNM: University of New Mexico)H-Index: 17
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#1Li Xiao (Tulane University)H-Index: 1
#2Junqi Wang (Tulane University)H-Index: 1
Last. Yu-Ping Wang (Tulane University)H-Index: 22
view all 9 authors...
Recently, a hypergraph constructed from functional magnetic resonance imaging (fMRI) was utilized to explore brain functional connectivity networks (FCNs) for the classification of neurodegenerative diseases. Each edge of a hypergraph (called hyperedge) can connect any number of brain regions-of-interest (ROIs) instead of only two ROIs, and thus characterizes highorder relations among multiple ROIs that cannot be uncovered by a simple graph in the traditional graph based FCN construction methods...
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Human brain development is a complex and dynamic process caused by several factors such as genetics, sex hormones, and environmental changes. A number of recent studies on brain development have examined functional connectivity (FC) defined by the temporal correlation between time series of different brain regions. We propose to add the directional flow of information during brain maturation. To do so, we extract effective connectivity (EC) through Granger causality (GC) for two different groups...
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#1Brittany Taylor (UNMC: University of Nebraska Medical Center)
Last. Tony W. WilsonH-Index: 22
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Abstract Fluid intelligence, the ability to problem-solve in novel situations, is linked to higher-order cognitive abilities, and to academic achievement in youth. Previous research has demonstrated that fluid intelligence and the underlying neural circuitry continues to develop throughout adolescence. Neuroimaging studies have predominantly focused on identifying the spatial distribution of brain regions associated with fluid intelligence, with only a few studies examining the temporally-sensit...
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#1Biao CaiH-Index: 1
#2Julia M. StephenH-Index: 22
Last. Yu-Ping WangH-Index: 22
view all 5 authors...
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#1Junqi Wang (Tulane University)H-Index: 1
#2Li Xiao (Tulane University)H-Index: 1
Last. Yu-Ping Wang (Tulane University)H-Index: 22
view all 6 authors...
Abstract Background: Longitudinal neuroimaging studies have demonstrated that adolescence is a crucial developmental period of continued brain growth and change. Motivated by both achievements in graph signal processing and recent evidence that some brain areas act as hubs connecting functionally specialized systems, we propose an approach to detect these regions from a spectral analysis perspective. In particular, as the human brain undergoes substantial development throughout adolescence, we e...
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#1Li Xiao (Tulane University)H-Index: 1
#2Julia M. Stephen (The Mind Research Network)H-Index: 22
Last. Yu-Ping Wang (Tulane University)H-Index: 22
view all 5 authors...
Objective: Multi-modal brain functional connectivity (FC) data have shown great potential for providing insights into individual variations in behavioral and cognitive traits. The joint learning of multi-modal data can utilize the intrinsic association, and thus can boost the learning performance. Although several multi-task based learning models have already been proposed by viewing the feature learning on each modality as one task, most of them ignore the structural information inherent across...
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Background: Childhood trauma is reliably associated with smaller hippocampal volume in adults; however, this finding has not been shown in children, and even less is known about how sex and trauma interact to affect limbic structural development in children. Methods: Typically developing children aged 9 to 15 years who completed a trauma history questionnaire and structural T1-weighted MRI were included in this study (n = 172; 85 female, 87 male). All children who reported 4 or more traumas (n =...
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#1Biao Cai (Tulane University)H-Index: 1
#2Gemeng Zhang (Tulane University)
Last. Yu-Ping Wang (Tulane University)H-Index: 22
view all 8 authors...
Abstract Background: Functional magnetic resonance imaging (fMRI) has been implemented widely to study brain connectivity. In particular, time-varying connectivity analysis has emerged as an important measure to uncover essential knowledge within the network. On the other hand, independent component analysis (ICA) has served as a powerful tool to preprocess fMRI data before performing network analysis. Together, they may lead to novel findings. Methods: We propose a new framework (GICA-TVGL) tha...
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