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Proceedings Paper

Resting fMRI measures are associated with cognitive deficits in schizophrenia assessed by the MATRICS consensus cognitive battery
Author(s): Hao He; Juan Bustillo; Yuhui Du; Qingbao Yu; Thomas R. Jones; Tianzi Jiang; Vince D. Calhoun; Jing Sui
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Paper Abstract

The cognitive deficits of schizophrenia are largely resistant to current treatment, and are thus a life-long burden to patients. The MATRICS consensus cognitive battery (MCCB) provides a reliable and valid assessment of cognition across a comprehensive set of cognitive domains for schizophrenia. In resting-state fMRI, functional connectivity associated with MCCB has not yet been examined. In this paper, the interrelationships between MCCB and the abnormalities seen in two types of functional measures from resting-state fMRI—fractional amplitude of low frequency fluctuations (fALFF) and functional network connectivity (FNC) maps were investigated in data from 47 schizophrenia patients and 50 age-matched healthy controls. First, the fALFF maps were generated and decomposed by independent component analysis (ICA), and then the component showing the highest correlation with MCCB composite scores was selected. Second, the whole brain was separated into functional networks by group ICA, and the FNC maps were calculated. The FNC strengths with most significant correlations with MCCB were displayed and spatially overlapped with the fALFF component of interest. It demonstrated increased cognitive performance associated with higher fALFF values (intensity of regional spontaneous brain activity) in prefrontal regions, inferior parietal lobe (IPL) but lower ALFF values in thalamus, striatum, and superior temporal gyrus (STG). Interestingly, the FNC showing significant correlations with MCCB were in well agreement with the activated regions with highest z-values in fALFF component. Our results support the view that functional deficits in distributed cortico-striato-thalamic circuits and inferior parietal lobe may account for several aspects of cognitive impairment in schizophrenia.

Paper Details

Date Published: 25 March 2015
PDF: 8 pages
Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 94171V (25 March 2015); doi: 10.1117/12.2083171
Show Author Affiliations
Hao He, The Mind Research Network and Lovelace Biomedical and Environmental Research Institute (United States)
The Univ. of New Mexico (United States)
Juan Bustillo, The Univ. of New Mexico (United States)
Yuhui Du, The Mind Research Network and Lovelace Biomedical and Environmental Research Institute (United States)
North Univ. of China (China)
Qingbao Yu, The Mind Research Network and Lovelace Biomedical and Environmental Research Institute (United States)
Thomas R. Jones, The Univ. of New Mexico (United States)
Tianzi Jiang, Brainnetome Ctr. and National Lab. of Pattern Recognition, Institute of Automation (China)
Vince D. Calhoun, The Mind Research Network and Lovelace Biomedical and Environmental Research Institute (United States)
The Univ. of New Mexico (United States)
Jing Sui, The Mind Research Network and Lovelace Biomedical and Environmental Research Institute (China)
Brainnetome Ctr. and National Lab. of Pattern Recognition, Institute of Automation (China)


Published in SPIE Proceedings Vol. 9417:
Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Robert C. Molthen, Editor(s)

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