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Combination of Resting State fMRI, DTI, and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA

Overview of attention for article published in Frontiers in Human Neuroscience, January 2013
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Title
Combination of Resting State fMRI, DTI, and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA
Published in
Frontiers in Human Neuroscience, January 2013
DOI 10.3389/fnhum.2013.00235
Pubmed ID
Authors

Jing Sui, Hao He, Qingbao Yu, Jiayu Chen, Jack Rogers, Godfrey D. Pearlson, Andrew Mayer, Juan Bustillo, Jose Canive, Vince D. Calhoun

Abstract

Multimodal brain imaging data have shown increasing utility in answering both scientifically interesting and clinically relevant questions. Each brain imaging technique provides a different view of brain function or structure, while multimodal fusion capitalizes on the strength of each and may uncover hidden relationships that can merge findings from separate neuroimaging studies. However, most current approaches have focused on pair-wise fusion and there is still relatively little work on N-way data fusion and examination of the relationships among multiple data types. We recently developed an approach called "mCCA + jICA" as a novel multi-way fusion method which is able to investigate the disease risk factors that are either shared or distinct across multiple modalities as well as the full correspondence across modalities. In this paper, we applied this model to combine resting state fMRI (amplitude of low-frequency fluctuation, ALFF), gray matter (GM) density, and DTI (fractional anisotropy, FA) data, in order to elucidate the abnormalities underlying schizophrenia patients (SZs, n = 35) relative to healthy controls (HCs, n = 28). Both modality-common and modality-unique abnormal regions were identified in SZs, which were then used for successful classification for seven modality-combinations, showing the potential for a broad applicability of the mCCA + jICA model and its results. In addition, a pair of GM-DTI components showed significant correlation with the positive symptom subscale of Positive and Negative Syndrome Scale (PANSS), suggesting that GM density changes in default model network along with white-matter disruption in anterior thalamic radiation are associated with increased positive PANSS. Findings suggest the DTI anisotropy changes in frontal lobe may relate to the corresponding functional/structural changes in prefrontal cortex and superior temporal gyrus that are thought to play a role in the clinical expression of SZ.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Turkey 1 <1%
United States 1 <1%
Germany 1 <1%
Unknown 155 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 26%
Researcher 29 18%
Student > Master 21 13%
Professor > Associate Professor 10 6%
Student > Bachelor 9 6%
Other 26 16%
Unknown 22 14%
Readers by discipline Count As %
Neuroscience 33 21%
Psychology 26 16%
Engineering 23 14%
Medicine and Dentistry 16 10%
Agricultural and Biological Sciences 12 8%
Other 18 11%
Unknown 31 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 October 2018.
All research outputs
#14,170,039
of 22,710,079 outputs
Outputs from Frontiers in Human Neuroscience
#4,582
of 7,128 outputs
Outputs of similar age
#167,513
of 280,734 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#617
of 862 outputs
Altmetric has tracked 22,710,079 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,128 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,734 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 862 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.