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Brain network analysis is a useful approach to studying human brain disorders because it can distinguish patients from healthy people by detecting abnormal connections. Due to the complementary information from multiple modal neuroimages,…

Image and Video Processing · Electrical Eng. & Systems 2023-08-22 Qiankun Zuo , Yanfei Zhu , Libin Lu , Zhi Yang , Yuhui Li , Ning Zhang

Functional magnetic resonance imaging recordings in the resting-state (RS) from the human brain are characterized by spontaneous low-frequency fluctuations in the blood oxygenation level dependent signal that reveal functional connectivity…

Neurons and Cognition · Quantitative Biology 2013-02-21 Iwo Jerzy Bohr , Eva Kenny , Andrew Blamire , John T. O'Brien , Alan J. Thomas , Jonathan Richardson , Marcus Kaiser

Brain Functional Networks (BFNs), graph theoretical models of brain activity data, provide a systems perspective of complex functional connectivity within the brain. Neurological disorders are known to have basis in abnormal functional…

Quantitative Methods · Quantitative Biology 2016-08-30 Megha Singh , Rahul Badhwar , Ganesh Bagler

Brain connectome analysis commonly compresses high-resolution brain scans (typically composed of millions of voxels) down to only hundreds of regions of interest (ROIs) by averaging within-ROI signals. This huge dimension reduction improves…

Methodology · Statistics 2025-03-25 Tong Lu , Yuan Zhang , Peter Kochunov , Elliot Hong , Shuo Chen

Autism spectrum disorder (ASD) is regarded as a brain disease with globally disrupted neuronal networks. Even though fMRI studies have revealed abnormal functional connectivity in ASD, they have not reached a consensus of the disrupted…

Computer Vision and Pattern Recognition · Computer Science 2017-07-26 Hongyoon Choi

To understand the biological characteristics of neurological disorders with functional connectivity (FC), recent studies have widely utilized deep learning-based models to identify the disease and conducted post-hoc analyses via explainable…

Machine Learning · Computer Science 2023-10-09 Eunsong Kang , Da-woon Heo , Jiwon Lee , Heung-Il Suk

Schizophrenia is a severe mental health condition that requires a long and complicated diagnostic process. However, early diagnosis is vital to control symptoms. Deep learning has recently become a popular way to analyse and interpret…

Machine Learning · Computer Science 2022-04-01 Daniel Organisciak , Hubert P. H. Shum , Ephraim Nwoye , Wai Lok Woo

Objective: Schizophrenia seriously affects the quality of life. To date, both simple (linear discriminant analysis) and complex (deep neural network) machine learning methods have been utilized to identify schizophrenia based on functional…

Machine Learning · Computer Science 2021-05-11 Tian Wang , Anastasios Bezerianos , Andrzej Cichocki , Junhua Li

Schizophrenia (SCZ) is a brain disorder where different people experience different symptoms, such as hallucination, delusion, flat-talk, disorganized thinking, etc. In the long term, this can cause severe effects and diminish life…

Machine Learning · Computer Science 2023-01-19 Shradha Verma , Tripti Goel , M Tanveer , Weiping Ding , Rahul Sharma , R Murugan

Functional connectivity plays an essential role in modern neuroscience. The modality sheds light on the brain's functional and structural aspects, including mechanisms behind multiple pathologies. One such pathology is schizophrenia which…

Neurons and Cognition · Quantitative Biology 2022-06-07 Maksim Zhdanov , Saskia Steinmann , Nico Hoffmann

The human brain has a complex, intricate functional architecture. While many studies primarily emphasize pairwise interactions, delving into high-order associations is crucial for a comprehensive understanding of how functional brain…

Neurons and Cognition · Quantitative Biology 2023-10-30 Qiang Li , Vince D. Calhoun , Adithya Ram Ballem , Shujian Yu , Jesus Malo , Armin Iraji

Sleep disorder is a serious global public health issue, with cognitive-emotional dysfunction being a core symptom. The analysis of multimodal MRI data provides an effective method for detecting sleep deprivation-induced neural network…

Neurons and Cognition · Quantitative Biology 2025-12-02 Mengyuan Liu , Jing Hu , Zhenzhen Ru , Ruomeng Quan , Xu Zhang , Ning Qiang , Jin Li

Predicting disease states from functional brain connectivity is critical for the early diagnosis of severe neurodegenerative diseases such as Alzheimer's Disease and Parkinson's Disease. Existing studies commonly employ Graph Neural…

Machine Learning · Computer Science 2025-04-22 David Yang , Mostafa Abdelmegeed , John Modl , Minjeong Kim

Over the last years, increasing evidence has fuelled the hypothesis that Autism Spectrum Disorder (ASD) is a condition of altered brain functional connectivity. The great majority of these empirical studies rely on functional magnetic…

Neurons and Cognition · Quantitative Biology 2010-08-02 Pablo Barttfeld , Bruno Wicker , Sebastián Cukier , Silvana Navarta , Sergio Lew , Mariano Sigman

We have reported nanometer-scale three-dimensional studies of brain networks of schizophrenia cases and found that their neurites are thin and tortuous compared to healthy controls. This suggests that connections between distal neurons are…

Image and Video Processing · Electrical Eng. & Systems 2022-04-04 Ryuta Mizutani , Senta Noguchi , Rino Saiga , Yuichi Yamashita , Mitsuhiro Miyashita , Makoto Arai , Masanari Itokawa

Dynamic functional connectivity (dFC) using resting-state functional magnetic resonance imaging (rs-fMRI) is an advanced technique for capturing the dynamic changes of neural activities, and can be very useful in the studies of brain…

Image and Video Processing · Electrical Eng. & Systems 2025-01-29 Jing Zhang , Yanjun Lyu , Xiaowei Yu , Lu Zhang , Chao Cao , Tong Chen , Minheng Chen , Yan Zhuang , Tianming Liu , Dajiang Zhu

Digital phenotyping in mental health often consists of collecting behavioral and experience-based information through sensory and self-reported data from devices such as smartphones. Such rich and comprehensive data could be used to develop…

Social and Information Networks · Computer Science 2023-12-05 Andy Davies , Eiko Fried , Hane Aung , Omar Costilla-Reyes

Emerging evidence shows that cognitive deficits in Alzheimer disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing…

Neurons and Cognition · Quantitative Biology 2018-02-27 A. Kabbara , H. Eid , EL W. Falou , M. Khalil , F. Wendling , M. Hassan

Alzheimer's disease (AD) is the most prevalent form of dementia. Traditional methods cannot achieve efficient and accurate diagnosis of AD. In this paper, we introduce a novel method based on dynamic functional connectivity (dFC) that can…

Computer Vision and Pattern Recognition · Computer Science 2020-06-25 Xingwei An , Yutao Zhou , Yang Di , Dong Ming

The study's objective is to explore the distinctions in the functional brain network connectivity between Alzheimer's Disease (AD) patients and normal controls using Functional Magnetic Resonance Imaging (fMRI). The study included 590…

Neurons and Cognition · Quantitative Biology 2023-05-17 Yongcheng Yao