Frequency-specific coactivation patterns in resting-state and their alterations in schizophrenia: An fMRI study

被引:16
作者
Yang, Hang [1 ]
Zhang, Hong [1 ]
Meng, Chun [1 ]
Wohlschlaeger, Afra [2 ]
Brandl, Felix [3 ]
Di, Xin [1 ,4 ]
Wang, Shuai [5 ]
Tian, Lin [5 ]
Biswal, Bharat [1 ,4 ]
机构
[1] Univ Elect Sci & Technol China, Clin Hosp Chengdu Brain Sci Inst, Ctr Informat Med, MOE Key Lab Neuroinformat,Sch Life Sci & Technol, 2006 Xiyuan Ave, Chengdu 611731, Peoples R China
[2] Tech Univ Munich TUM, TUM Neuroimaging Ctr, Dept Neuroradiol, Munich, Germany
[3] Tech Univ Munich TUM, TUM Neuroimaging Ctr, Dept Psychiat, Munich, Germany
[4] New Jersey Inst Technol, Dept Biomed Engn, 607 Fenster Hall, Newark, NJ 07102 USA
[5] Nanjing Med Univ, Affiliated Wuxi Mental Hlth Ctr, Dept Psychiat, 156 Qianhu Rd, Wuxi 214151, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
coactivation patterns; dynamics; frequency-specific; schizophrenia; DYNAMIC FUNCTIONAL CONNECTIVITY; TIME-VARYING CONNECTIVITY; CEREBRAL-CORTEX; BRAIN; NETWORKS; OSCILLATIONS; INTEGRATION; DISORDER; MODELS; GRAPHS;
D O I
10.1002/hbm.25884
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The resting-state human brain is a dynamic system that shows frequency-dependent characteristics. Recent studies demonstrate that coactivation pattern (CAP) analysis can identify recurring brain states with similar coactivation configurations. However, it is unclear whether and how CAPs depend on the frequency bands. The current study investigated the spatial and temporal characteristics of CAPs in the four frequency sub-bands from slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz), to slow-2 (0.198-0.25 Hz), in addition to the typical low-frequency range (0.01-0.08 Hz). In the healthy subjects, six CAP states were obtained at each frequency band in line with our prior study. Similar spatial patterns with the typical range were observed in slow-5, 4, and 3, but not in slow-2. While the frequency increased, all CAP states displayed shorter persistence, which caused more between-state transitions. Specifically, from slow-5 to slow-4, the coactivation not only changed significantly in distributed cortical networks, but also increased in the basal ganglia as well as the amygdala. Schizophrenia patients showed significant alteration in the persistence of CAPs of slow-5. Using leave-one-pair-out, hold-out and resampling validations, the highest classification accuracy (84%) was achieved by slow-4 among different frequency bands. In conclusion, our findings provide novel information about spatial and temporal characteristics of CAP states at different frequency bands, which contributes to a better understanding of the frequency aspect of biomarkers for schizophrenia and other disorders.
引用
收藏
页码:3792 / 3808
页数:17
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