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Neuronal brain activity in response to repeated stimuli can be perceived using functional magnetic resonance imaging (fMRI). In this paper, we develop a statistical model for fMRI data that estimates both the associated haemodynamic…

Applications · Statistics 2015-01-26 Christopher J. Brignell , William J. Browne , Ian L. Dryden , Susan T. Francis

Functional magnetic resonance imaging (fMRI) is a neuroimaging technique known for its ability to capture brain activity non-invasively and at fine spatial resolution (2-3mm). Cortical surface fMRI (cs-fMRI) is a recent development of fMRI…

Applications · Statistics 2023-12-29 Huy Dang , Marzia Cremona , Nicole Lazar , Francesca Chiaromonte

This technical note presents a framework for investigating the underlying mechanisms of neurovascular coupling in the human brain using multi-modal magnetoencephalography (MEG) and functional magnetic resonance (fMRI) neuroimaging data.…

Quantitative Methods · Quantitative Biology 2019-03-19 Amirhossein Jafarian , Vladimir Litvak , Hayriye Cagnan , Karl J. Friston , Peter Zeidman

In contrast to conventional, univariate analysis, various types of multivariate analysis have been applied to functional magnetic resonance imaging (fMRI) data. In this paper, we compare two contemporary approaches for multivariate…

Applications · Statistics 2018-02-08 Ethan C. Jackson , James Alexander Hughes , Mark Daley

We consider the challenges in extracting stimulus-related neural dynamics from other intrinsic processes and noise in naturalistic functional magnetic resonance imaging (fMRI). Most studies rely on inter-subject correlations (ISC) of…

Neurons and Cognition · Quantitative Biology 2021-02-23 Chee-Ming Ting , Jeremy I. Skipper , Steven L. Small , Hernando Ombao

When no arterial input function is available, quantification of dynamic PET images requires a previous step devoted to the extraction of a reference time-activity curve (TAC). Factor analysis is often applied for this purpose. This paper…

Image and Video Processing · Electrical Eng. & Systems 2020-11-23 Yanna Cruz Cavalcanti , Thomas Oberlin , Vinicius Ferraris , Nicolas Dobigeon , Maria Ribeiro , Clovis Tauber

Graphical models have been used extensively for modeling brain connectivity networks. However, unmeasured confounders and correlations among measurements are often overlooked during model fitting, which may lead to spurious scientific…

Methodology · Statistics 2020-12-10 Yanxin Jin , Yang Ning , Kean Ming Tan

Dynamic functional connectivity (dFC) derived from resting-state functional magnetic resonance imaging (fMRI) has been extensively utilized in brain science research. The sliding window correlation (SWC) method is a widely used approach for…

Neurons and Cognition · Quantitative Biology 2026-03-27 Jinlong Hu , Jiatong Huang , Zijian Cai

Functional magnetic resonance imaging or functional MRI (fMRI) is a very popular tool used for differing brain regions by measuring brain activity. It is affected by physiological noise, such as head and brain movement in the scanner from…

Methodology · Statistics 2023-10-30 Fangyijie Wang , Michael Salter-Townshend

We conduct an imaging genetics study to explore how effective brain connectivity in the default mode network (DMN) may be related to genetics within the context of Alzheimer's disease and mild cognitive impairment. We develop an analysis of…

Neurons and Cognition · Quantitative Biology 2020-06-03 Yunlong Nie , Eugene Opoku , Laila Yasmin , Yin Song , Jie Wang , Sidi Wu , Vanessa Scarapicchia , Jodie Gawryluk , Liangliang Wang , Jiguo Cao , Farouk S. Nathoo

We present a computational framework for analysis and visualization of non-linear functional connectivity in the human brain from resting state functional MRI (fMRI) data for purposes of recovering the underlying network community structure…

Neural and Evolutionary Computing · Computer Science 2014-07-16 Axel Wismüller , Xixi Wang , Adora M. DSouza , Mahesh B. Nagarajan

Demystifying effective connectivity among neuronal populations has become the trend to understand the brain mechanisms of Parkinson's disease, schizophrenia, mild traumatic brain injury, and many other unlisted neurological diseases.…

Quantitative Methods · Quantitative Biology 2019-09-27 Po-Ya Hsu

Finding an appropriate representation of dynamic activities in the brain is crucial for many downstream applications. Due to its highly dynamic nature, temporally averaged fMRI (functional magnetic resonance imaging) can only provide a…

Machine Learning · Computer Science 2022-08-18 Sikun Lin , Shuyun Tang , Scott Grafton , Ambuj Singh

Functional magnetic resonance imaging (fMRI) data is characterized by its complexity and high--dimensionality, encompassing signals from various regions of interests (ROIs) that exhibit intricate correlations. Analyzing fMRI data directly…

Applications · Statistics 2024-01-18 Yeseul Jeon , Jeong-Jae Kim , SuMin Yu , Junggu Choi , Sanghoon Han

The contribution of structural connectivity to functional brain states remains poorly understood. We present a mathematical and computational study suited to assess the structure--function issue, treating a system of Jansen--Rit neural-mass…

Neurons and Cognition · Quantitative Biology 2020-07-10 Michael Forrester , Stephen Coombes , Jonathan J. Crofts , Stamatios N. Sotiropoulos , Reuben D. O'Dea

Functional MRI is a neuroimaging technique that analyzes the functional activity of the brain by measuring blood-oxygen-level-dependent signals throughout the brain. The derived functional features can be used for investigating brain…

Neurons and Cognition · Quantitative Biology 2026-02-16 Giorgio Dolci , Silvia Saglia , Lorenza Brusini , Vince D. Calhoun , Ilaria Boscolo Galazzo , Gloria Menegaz

Brain function emerges from coordinated activity across anatomically connected regions, where structural connectivity (SC) -- the network of white matter pathways - provides the physical substrate for functional connectivity (FC) -- the…

Neurons and Cognition · Quantitative Biology 2025-07-09 Sam Frank Kelemen , Joaquín Gõni , Sérgio Pequito , Arian Ashourvan

Capturing dynamic spatiotemporal neural activity is essential for understanding large-scale brain mechanisms. Functional magnetic resonance imaging (fMRI) provides high-resolution cortical representations that form a strong basis for…

Image and Video Processing · Electrical Eng. & Systems 2026-04-01 Wanying Qu , Jianxiong Gao , Wei Wang , Yanwei Fu

Functional connectivity (FC) has become a primary means of understanding brain functions by identifying brain network interactions and, ultimately, how those interactions produce cognitions. A popular definition of FC is by statistical…

Alzheimer's disease (AD) progresses from asymptomatic changes to clinical symptoms, emphasizing the importance of early detection for proper treatment. Functional magnetic resonance imaging (fMRI), particularly dynamic functional network…

Computational Engineering, Finance, and Science · Computer Science 2024-08-02 Yuxiang Wei , Anees Abrol , James Lah , Deqiang Qiu , Vince D. Calhoun
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