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Contemporary neuroscience has embraced network science to study the complex and self-organized structure of the human brain; one of the main outstanding issues is that of inferring from measure data, chiefly functional Magnetic Resonance…

Optimization and Control · Mathematics 2017-03-31 Giulia Prando , Mattia Zorzi , Alessandra Bertoldo , Alessandro Chiuso

In functional MRI (fMRI), effective connectivity analysis aims at inferring the causal influences that brain regions exert on one another. A common method for this type of analysis is structural equation modeling (SEM). We here propose a…

Quantitative Methods · Quantitative Biology 2024-09-10 G. Marrelec , A. Giron

Causal relations among neuronal populations of the brain are studied through the so-called effective connectivity (EC) network. The latter is estimated from EEG or fMRI measurements, by inverting a generative model of the corresponding…

Systems and Control · Computer Science 2018-02-16 Giulia Prando , Mattia Zorzi , Alessandra Bertoldo , Alessandro Chiuso

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

Dynamic functional connectivity (DFC) analysis involves measuring correlated neural activity over time across multiple brain regions. Significant regional correlations among neural signals, such as those obtained from resting-state…

With the advances in high resolution neuroimaging, there has been a growing interest in the detection of functional brain connectivity. Complex network theory has been proposed as an attractive mathematical representation of functional…

Neural and Evolutionary Computing · Computer Science 2018-09-18 Arash Golibagh Mahyari , Selin Aviyente

There has been increasing interests in learning resting-state brain functional connectivity of autism disorders using functional magnetic resonance imaging (fMRI) data. The data in a standard brain template consist of over 200,000 voxel…

Methodology · Statistics 2016-03-22 Jichun Xie , Jian Kang

Dynamic networks have been increasingly used to characterize brain connectivity that varies during resting and task states. In such characterizations, a connectivity network is typically measured at each time point for a subject over a…

Methodology · Statistics 2023-03-23 Maoyu Zhang , Biao Cai , Wenlin Dai , Dehan Kong , Hongyu Zhao , Jingfei Zhang

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

This study proposes an approach to estimate the functional localization and connectivity from CBF and BOLD signals simultaneously measured by ASL (arterial spin labeling) MRI, especially using exploratory Structural Equation Modeling…

Neurons and Cognition · Quantitative Biology 2017-04-11 Jiancheng Zhuang

Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or 'connectopies' in short, is crucial for understanding how…

Quantitative Methods · Quantitative Biology 2017-07-18 Koen V. Haak , Andre F. Marquand , Christian F. Beckmann

Resting-state brain functional connectivity quantifies the synchrony between activity patterns of different brain regions. In functional magnetic resonance imaging (fMRI), each region comprises a set of spatially contiguous voxels at which…

Methodology · Statistics 2025-11-07 Ruobin Liu , Chao Zhang , Chau Tran , Sophie Achard , Wendy Meiring , Alexander Petersen

The brain's functional connectivity fluctuates over time instead of remaining steady in a stationary mode even during the resting state. This fluctuation establishes the dynamical functional connectivity that transitions in a non-random…

Neurons and Cognition · Quantitative Biology 2022-03-28 Shikuang Deng , Jingwei Li , B. T. Thomas Yeo , Shi Gu

Functional connectivity (FC) analysis of resting-state fMRI data provides a framework for characterizing brain networks and their association with participant-level covariates. Due to the high dimensionality of neuroimaging data, standard…

Methodology · Statistics 2025-08-18 Wei Zhao , Brian J. Reich , Emily C. Hector

We investigate the relationship of resting-state fMRI functional connectivity estimated over long periods of time with time-varying functional connectivity estimated over shorter time intervals. We show that using Pearson's correlation to…

Neurons and Cognition · Quantitative Biology 2016-09-08 Richard F. Betzel , Makoto Fukushima , Ye He , Xi-Nian Zuo , Olaf Sporns

Traditional causal connectivity methods in task-based and resting-state functional magnetic resonance imaging (fMRI) face challenges in accurately capturing directed information flow due to their sensitivity to noise and inability to model…

Neurons and Cognition · Quantitative Biology 2025-04-03 Boseong Kim , Debashis Das Chakladar , Haejun Chung , Ikbeom Jang

In the last two decades, functional magnetic resonance imaging (fMRI) has emerged as one of the most effective technologies in clinical research of the human brain. fMRI allows researchers to study healthy and pathological brains while they…

Neurons and Cognition · Quantitative Biology 2022-12-06 Sadi Md. Redwan , Md Palash Uddin , Muhammad Imran Sharif , Anwaar Ulhaq

Functional connectivity (FC) refers to the investigation of interactions between brain regions to understand integration of neural activity in several regions. FC is often estimated using functional magnetic resonance images (fMRI). There…

Applications · Statistics 2023-01-24 Nathan Tung , Jerome Sanes , Eli Upfal , Ani Eloyan

This paper proposes a novel approach of integrating different neuroimaging techniques to characterize an autistic brain. Different techniques like EEG, fMRI and DTI have traditionally been used to find biomarkers for autism, but there have…

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
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