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Estimating brain effective connectivity (EC) from functional magnetic resonance imaging (fMRI) data can aid in comprehending the neural mechanisms underlying human behavior and cognition, providing a foundation for disease diagnosis.…

Machine Learning · Computer Science 2025-03-17 Wen Xiong , Jinduo Liu , Junzhong Ji , Fenglong Ma

Functional Magnetic Resonance Images acquired during resting-state provide information about the functional organization of the brain through measuring correlations between brain areas. Independent components analysis is the reference…

Neurons and Cognition · Quantitative Biology 2014-12-15 Alexandre Abraham , Elvis Dohmatob , Bertrand Thirion , Dimitris Samaras , Gael Varoquaux

Accurate fMRI analysis requires sensitivity to temporal structure across multiple scales, as BOLD signals encode cognitive processes that emerge from fast transient dynamics to slower, large-scale fluctuations. Existing deep learning (DL)…

Signal Processing · Electrical Eng. & Systems 2026-01-06 Furkan Genç , Boran İsmet Macun , Sait Sarper Özaslan , Emine U. Saritas , Tolga Çukur

Functional magnetic resonance imaging or functional MRI (fMRI) is a non-invasive way to assess brain activity by detecting changes associated with blood flow. In this work, we propose a full Bayesian procedure to analyze fMRI data for…

Functional MRI data exhibit high-dimensional spatiotemporal structure, making both prediction and decoding challenging. In this work, we investigate neural integral-operator-based models for encoding and decoding tasks in fMRI, with…

Machine Learning · Computer Science 2026-05-21 Andreas Kramer , Saugat Acharya , Alice Giola , Emanuele Zappala

Functional magnetic resonance imaging (fMRI) enables non-invasive brain disorder classification by capturing blood-oxygen-level-dependent (BOLD) signals. However, most existing methods rely on functional connectivity (FC) via Pearson…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Guoqi Yu , Xiaowei Hu , Angelica I. Aviles-Rivero , Anqi Qiu , Shujun Wang

Functional magnetic resonance imaging (fMRI) is a powerful tool for investigating human brain function. However, the high cost of data acquisition and the inherent subjectivity of psychiatric rating scales often lead to datasets with small…

Machine Learning · Computer Science 2026-05-29 Jiyao Wang , Peiyu Duan , Nicha C. Dvornek , Lawrence H. Staib , Denis Sukhodolsky , Pamela Ventola , James S. Duncan

In neuroscience, understanding inter-individual differences has recently emerged as a major challenge, for which functional magnetic resonance imaging (fMRI) has proven invaluable. For this, neuroscientists rely on basic methods such as…

Computer Vision and Pattern Recognition · Computer Science 2020-04-07 Akrem Sellami , François-Xavier Dupé , Bastien Cagna , Hachem Kadri , Stéphane Ayache , Thierry Artières , Sylvain Takerkart

Magnetic Resonance Imaging (MRI) is a noninvasive imaging technique that provides exquisite soft-tissue contrast without using ionizing radiation. The clinical application of MRI may be limited by long data acquisition times; therefore, MR…

Image and Video Processing · Electrical Eng. & Systems 2020-07-10 Shen Zhao , Lee C. Potter , Kiryung Lee , Rizwan Ahmad

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

Functional magnetic resonance imaging (fMRI) enables noninvasive investigation of brain function, while short clinical scan durations, arising from human and non-human factors, usually lead to reduced data quality and limited statistical…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yunlong Gao , Jinbo Yang , Li Xiao , Haiye Huo , Yang Ji , Hao Wang , Aiying Zhang , Yu-Ping Wang

Functional magnetic resonance imaging (fMRI) plays a crucial role in neuroimaging, enabling the exploration of brain activity through complex-valued signals. These signals, composed of magnitude and phase, offer a rich source of information…

Methodology · Statistics 2024-01-15 Zhengxin Wang , Daniel B. Rowe , Xinyi Li , D. Andrew Brown

Bayesian whole-brain functional magnetic resonance imaging (fMRI) analysis with three-dimensional spatial smoothing priors has been shown to produce state-of-the-art activity maps without pre-smoothing the data. The proposed inference…

Methodology · Statistics 2020-10-02 Per Sidén , Finn Lindgren , David Bolin , Anders Eklund , Mattias Villani

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

We present a novel method, Fractal Space-Curve Analysis (FSCA), which combines Space-Filling Curve (SFC) mapping for dimensionality reduction with fractal Detrended Fluctuation Analysis (DFA). The method is suitable for multidimensional…

Coordinate-based meta-analysis combines evidence from a collection of Neuroimaging studies to estimate brain activation. In such analyses, a key practical challenge is to find a computationally efficient approach with good statistical…

Functional brain imaging allows measuring dynamic functionality in all brain regions. It is broadly used in clinical cognitive neuroscience as, well as in research. It will allow the observation of neural activities in the brain…

Medical Physics · Physics 2016-04-01 Saman Sarraf , Jian Sun

Neuronal electrical activity underlies human cognition including perception, attention, memory, language, and decision-making. Yet its direct, noninvasive measurement in the living human brain remains a fundamental challenge. Existing…

Contemporary neuroimaging methods can shed light on the basis of human neural and cognitive specializations, with important implications for neuroscience and medicine. Different MRI acquisitions provide different brain networks at the…

Neurons and Cognition · Quantitative Biology 2016-02-23 C. Alonso-Montes , I. Diez , L. Remaki , I. Escudero , B. Mateos , Y. Rosseel , D. Marinazzo , S. Stramaglia , J. Cortes

Many fMRI analyses examine functional connectivity, or statistical dependencies among remote brain regions. Yet popular methods for studying whole-brain functional connectivity often yield results that are difficult to interpret. Factor…

Methodology · Statistics 2024-09-24 Kyle Stanley , Nicole Lazar , Matthew Reimherr