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Functional magnetic resonance imaging (fMRI) is a notoriously noisy measurement of brain activity because of the large variations between individuals, signals marred by environmental differences during collection, and spatiotemporal…

Functional magnetic resonance imaging (fMRI) is a powerful tool for probing brain function, yet reliable clinical diagnosis is hampered by low signal-to-noise ratios, inter-subject variability, and the limited frequency awareness of…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Junhao Jia , Yifei Sun , Yunyou Liu , Cheng Yang , Changmiao Wang , Feiwei Qin , Yong Peng , Wenwen Min

The human brain dynamically integrated and configured information to adapt to the environment. To capture these changes over time, dynamic second-order functional connectivity was typically used to capture transient brain patterns. However,…

Neurons and Cognition · Quantitative Biology 2025-07-01 Qiang Li , Vince D. Calhoun , Armin Iraji

The autism dataset is studied to identify the differences between autistic and healthy groups. For this, the resting-state Functional Magnetic Resonance Imaging (rs-fMRI) data of the two groups are analyzed, and networks of connections…

Image and Video Processing · Electrical Eng. & Systems 2022-12-05 Ramchandra Rimal , Mitchell Brannon , Yingxin Wang , Xin Yang

Resting State Networks (RSNs) of the brain extracted from Resting State functional Magnetic Resonance Imaging (RS-fMRI) are used in the pre-surgical planning to guide the neurosurgeon. This is difficult, though, as expert knowledge is…

Functional Magnetic Resonance Imaging (fMRI) is a primary modality for studying brain activity. Modeling spatial dependence of imaging data at different scales is one of the main challenges of contemporary neuroimaging, and it could allow…

Applications · Statistics 2016-06-16 Stefano Castruccio , Hernando Ombao , Marc G. Genton

While differences in patterns of functional connectivity and neural synchronization have been reported between individuals on the autism spectrum and neurotypical peers at various age stages, these differences appear to be subtle and may…

Neurons and Cognition · Quantitative Biology 2025-07-15 Sungwoo Ahn , Leonid L Rubchinsky , Evie A Malaia

Magnetic resonance imaging (MRI) is a crucial tool to identify brain abnormalities in a wide range of neurological disorders. In focal epilepsy MRI is used to identify structural cerebral abnormalities. For covert lesions, machine learning…

Mental and cognitive representations are believed to reside on low-dimensional, non-linear manifolds embedded within high-dimensional brain activity. Uncovering these manifolds is key to understanding individual differences in brain…

Machine Learning · Computer Science 2025-05-02 Eloy Geenjaar , Vince Calhoun

Fractals are self-similar and scale-invariant patterns found ubiquitously in nature. A lot of evidences implying fractal properties such as 1/f power spectrums have been also observed in resting state fMRI time series. To explain the…

Applications · Statistics 2012-08-07 Wonsang You , Jörg Stadler

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

This study investigated the dynamic connectivity patterns between EEG and fMRI modalities, contributing to our understanding of brain network interactions. By employing a comprehensive approach that integrated static and dynamic analyses of…

Machine Learning · Computer Science 2024-12-02 Guiran Liu , Binrong Zhu

Purpose: Functional Magnetic Resonance Imaging (fMRI) data acquired through resting-state studies have been used to obtain information about the spontaneous activations inside the brain. One of the approaches for analysis and interpretation…

Image and Video Processing · Electrical Eng. & Systems 2022-02-24 Harshit Parmar , Brian Nutter , Rodney Long , Sameer Antani , Sunanda Mitra

Functional magnetic resonance imaging (fMRI) is used to extract {\em functional networks} connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that: (a) the distribution of functional…

Disordered Systems and Neural Networks · Physics 2007-05-23 Victor M. Eguiluz , Dante R. Chialvo , Guillermo A. Cecchi , Marwan Baliki , A. Vania Apkarian

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder impacting social and behavioral development. Resting-state fMRI, a non-invasive tool for capturing brain connectivity patterns, aids in early ASD diagnosis and differentiation…

Machine Learning · Computer Science 2025-02-27 Ziqiao Weng , Weidong Cai , Bo Zhou

Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses have limited its clinical…

In this paper, we present a novel and versatile method to study the dynamics of resting-state fMRI brain connectivity with a high temporal sensitivity. Whereas most existing methods often rely on dividing the time-series into larger…

Neurons and Cognition · Quantitative Biology 2016-01-14 William Hedley Thompson , Peter Fransson

Functional Magnetic Resonance Imaging (fMRI) is an imaging technique widely used to study human brain activity. fMRI signals in areas across the brain transiently synchronise and desynchronise their activity in a highly structured manner,…

Machine Learning · Computer Science 2025-08-12 Yiran Huang , Amirhossein Nouranizadeh , Christine Ahrends , Mengjia Xu

Fetal functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful tool for investigating brain development in utero, holding promise for generating developmental disease biomarkers and supporting prenatal diagnosis. However, to…

Structural magnetic resonance imaging (sMRI) has shown great clinical value and has been widely used in deep learning (DL) based computer-aided brain disease diagnosis. Previous approaches focused on local shapes and textures in sMRI that…

Image and Video Processing · Electrical Eng. & Systems 2023-06-09 Gongshu Wang , Ning Jiang , Yunxiao Ma , Tiantian Liu , Duanduan Chen , Jinglong Wu , Guoqi Li , Dong Liang , Tianyi Yan