Brain Networks Connectivity in Mild to Moderate Depression: Resting State fMRI Study with Implications to Nonpharmacological Treatment by Dmitry D. Bezmaternykh, Mikhail Ye. Melnikov, Andrey A. Savelov, Lyudmila I. Kozlova, Evgeniy D. Petrovskiy, Kira A. Natarova, Mark B. Shtark

“…Resting state fMRI data of 21 healthy adults and 51 patients with mild or moderate depression were analyzed with spatial independent component analysis; then, correlations between time series of the components were calculated and compared between-group (study 1). …”
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EEG-based functional and effective connectivity patterns during emotional episodes using graph theoretical analysis by Majid Roshanaei, Hamzeh Norouzi, Julie Onton, Scott Makeig, Alireza Mohammadi

“…After applying independent component analysis (ICA) to eliminate non-cortical activity, we assessed frequency-specific connectivity patterns using coherence, Granger causality, and graph theoretical measures to evaluate both functional and effective connectivity. …”
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A Synchronized Hybrid Brain-Computer Interface System for Simultaneous Detection and Classification of Fusion EEG Signals by Dalin Yang, Trung-Hau Nguyen, Wan-Young Chung

“…The fast independent component analysis algorithm is employed to hybrid signals for obtaining clear EEG signals resulting from denoising. …”
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Identification of Alzheimer’s Disease Progression Stages Using Topological Measures of Resting-State Functional Connectivity Networks: A Comparative Study by Zhanxiong Wu, Jinhui Wu, Xumin Chen, Xun Li, Jian Shen, Hui Hong

“…This study comparatively characterized topological properties of rs-FC networks constructed with Pearson correlation (PC), dynamic time warping (DTW), and group information guided independent component analysis (GIG-ICA), aimed at investigating the sensitivity and effectivity of these methods in differentiating AD stages. …”
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Smartphone Household Wireless Electroencephalogram Hat by Harold Szu, Charles Hsu, Gyu Moon, Takeshi Yamakawa, Binh Q. Tran, Tzyy Ping Jung, Joseph Landa

“…During the design phase, we took tethered laboratory EEG dataset and applied fuzzy logic to compute (a) spatiotemporal average of larger magnitude EEG data centers in 0.3 second intervals and (b) inside brainwave sources by Independent Component Analysis blind deconvolution without knowing the impulse response function. …”
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Study of Chemical Intermediates by Means of ATR-IR Spectroscopy and Hybrid Hard- and Soft-Modelling Multivariate Curve Resolution-Alternating Least Squares by Junxiu Ma, Juan Qi, Xinyu Gao, Chunhua Yan, Tianlong Zhang, Hongsheng Tang, Hua Li

“…The subspace comparison method (SCM) was used to obtain the principal components number, and then the pure IR spectra of each substance were obtained by independent component analysis (ICA) and HS-MCR. The extent of rotation ambiguity was estimated from the band boundaries of feasible solutions calculated using the MCR-BANDS procedure. …”
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Altered Spontaneous Brain Activity of Children with Unilateral Amblyopia: A Resting State fMRI Study by Peishan Dai, Jinlong Zhang, Jing Wu, Zailiang Chen, Beiji Zou, Ying Wu, Xin Wei, Manyi Xiao

“…FC analysis methods consisted of the FC between the primary visual cortex (PVC-FC) and other brain regions and the FC network between regions of interest (ROIs-FC) selected by independent component analysis. Results. The ALFF in the bilateral frontal, temporal, and occipital lobes in the amblyopia group was lower than that in the HCs. …”
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Progress in the Application of Resting-State Functional Magnetic Resonance Imaging in Chronic Nonspecific Low Back Pain by XU Ting, XUE Qin, LÜ Ying, TU Jianchun, DAI Dechun

“…Common methods for functional integration mainly include Seed-based Functional Connectivity Analysis (SCA), Independent Component Analysis (ICA), and graph theory-based complex brain network analysis. …”
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Resting-state BOLD temporal variability of the default mode network predicts spontaneous mind wandering, which is negatively associated with mindfulness skills by Sara Sorella, Cristiano Crescentini, Alessio Matiz, Alessio Matiz, Minah Chang, Alessandro Grecucci, Alessandro Grecucci

“…Therefore, resting-state MRI scans from 76 participants were analyzed with group independent component analysis to decompose brain networks into independent macro-networks and to see which of them predicted specific aspects of spontaneous and deliberate MW or mindfulness traits. …”
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Exploring the Effectiveness of Machine Learning and Deep Learning Techniques for EEG Signal Classification in Neurological Disorders by Souhaila Khalfallah, William Puech, Mehdi Tlija, Kais Bouallegue

“…We present a detailed workflow that begins with EEG data acquisition using a headset, followed by data preprocessing with Finite Impulse Response (FIR) filters and Independent Component Analysis (ICA) to eliminate noise and artifacts. …”
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Acupuncture Reversible Effects on Altered Default Mode Network of Chronic Migraine Accompanied with Clinical Symptom Relief by Yan Zou, Weijun Tang, Xiang Li, Manwen Xu, Ji Li

“…Resting-state functional magnetic resonance imaging (fMRI) data from 14 CM patients treated with longitudinal pre- and postacupuncture treatment (PPAT) and data of 18 age- and gender-matched healthy controls (HCs) were analyzed using independent component analysis (ICA) and seed-based correlation analysis (SCA) to investigate connectivity within the DMN. …”
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Large-Scale Neuronal Network Dysfunction in Diabetic Retinopathy by Xin Huang, Yan Tong, Chen-Xing Qi, Han-Dong Dan, Qin-Qin Deng, Yin Shen

“…The purpose of this study was to investigate the intranetwork functional connectivity (FC) and functional network connectivity (FNC) of RSN changes in DR patients using independent component analysis (ICA). Thirty-four DR patients (18 men and 16 women; mean age, 53.53±8.67 years) and 38 nondiabetic healthy controls (HCs) (15 men and 23 women; mean age, 48.63±11.83 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. …”
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The Efficacy and Brain Network Mechanism of Acupuncture for Knee Osteoarthritis: A Study Protocol for Randomized Controlled Neuroimaging Trial by Sun YY, Wang ML, Zhao RH, Hao MY, Song S, Zhou Y, Zhang N

“…The primary efficacy indicator will be the change in NRS score after four weeks of treatment, with secondary outcomes including WOMAC, STAI, and safety assessments. fMRI observations will employ independent component analysis, brain network construction, and functional connectivity, complemented by Pearson correlation analysis to explore the relationship between brain responses and clinical improvements.Conclusion: This study will initially uncover how acupuncture intervention for chronic KOA pain centrally regulates and exerts therapeutic effects through the modulation of abnormal brain network functional connectivity patterns, with a demonstrated long-term effect.Ethics and Dissemination: This study has been approved by the ethics committee of Shandong University of Traditional Chinese Medicine Affiliated Hospital ((2024) Lunshen No. (028) - KY).Clinical Trial Registration: This study has been approved by registered in the Chinese Clinical Trial Registry (ChiCTR2400083695).Keywords: acupuncture, knee osteoarthritis, neuroimaging, RCT, protocol…”
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Revealing the Neuroimaging Mechanism of Acupuncture for Poststroke Aphasia: A Systematic Review by Boxuan Li, Shizhe Deng, Bomo Sang, Weiming Zhu, Bifang Zhuo, Menglong Zhang, Chenyang Qin, Yuanhao Lyu, Yuzheng Du, Zhihong Meng

“…Based on blood oxygen level-dependent (BOLD) and diffusion tensor imaging (DTI) technologies, 4 neuroimaging analysis methods were used including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), seed-based analysis, and independent component analysis (ICA). Two studies reported the instant acupuncture effect, and 14 studies reported the constant acupuncture’s effect on poststroke aphasia patients. 5 studies analyzed the correlation between the neuroimaging outcomes and the clinical language scales. …”
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Effect of Acupuncture Stimulation of Hegu (LI4) and Taichong (LR3) on the Resting-State Networks in Alzheimer’s Disease: Beyond the Default Mode Network by Shaozhen Ji, Hao Zhang, Wen Qin, Ming Liu, Weimin Zheng, Ying Han, Haiqing Song, Kuncheng Li, Jie Lu, Zhiqun Wang

“…In addition to the DMN, five other resting-state networks were identified by independent component analysis (ICA), including left frontal parietal network (lFPN), right frontal parietal network (rFPN), visual network (VN), sensorimotor network (SMN), and auditory network (AN). …”
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Functional Connectivity Alterations in Children with Spastic and Dyskinetic Cerebral Palsy by Yun Qin, Yanan Li, Bo Sun, Hui He, Rui Peng, Tao Zhang, Jianfu Li, Cheng Luo, Chengyan Sun, Dezhong Yao

“…Resting-state networks (RSNs) were established based on the independent component analysis (ICA), and the functional network connectivity (FNC) was performed on the fMRI data from 16 DCP, 18 bilateral SCP, and 18 healthy children. …”
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Segmentation of Dynamic Total-Body [18F]-FDG PET Images Using Unsupervised Clustering by Maria K. Jaakkola, Maria Rantala, Anna Jalo, Teemu Saari, Jaakko Hentilä, Jatta S. Helin, Tuuli A. Nissinen, Olli Eskola, Johan Rajander, Kirsi A. Virtanen, Jarna C. Hannukainen, Francisco López-Picón, Riku Klén

“…We combined k-means with two different preprocessing approaches, namely, principal component analysis (PCA) and independent component analysis (ICA). Then, we selected a suitable number of clusters using 10 images. …”
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Multiparameter resting-state functional magnetic resonance imaging as an indicator of neuropsychological changes in Binswanger’s disease with mild cognitive impairment by Haiyi Zhang, Lu Zhang, Juan Lu, Jiajun Yue, Zhengzhen Yuan, Jidan Hu, Qi Yao, Yuting Fu, Guiquan Chen, Jiliang Fang, Jie Zhao

“…The multiparameter functional magnetic resonance imaging (fMRI) including amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), independent component analysis (ICA), and edge-link analysis was utilized to explore the abnormal brain networks of BD-MCI patients. …”
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Dynamic functional connectivity patterns predict early antidepressant treatment response in drug-naïve, first-episode adolescent MDD by Maojia Ran, Hang Zhang, Meijiang Jin, Yuanmei Tao, Hanmei Xu, Shoukang Zou, Zhujun Wang, Fang Deng, Lijuan Huang, Hong Zhang, Xiaowei Tang, Yanping Wang, Xia Fu, Li Yin, Li Yin, Li Yin

“…Resting state and T1 MRI data were collected in MDD adolescents before and after treatment and in HCs. Independent component analysis (ICA) was used to compare the different dFC pattern between MDD adolescents and HCs at baseline, as well as which between before and after treatment in MDD adolescents. …”
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