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Recently, there has been increased interest in fusing multimodal imaging to better understand brain organization. Specifically, accounting for knowledge of anatomical pathways connecting brain regions should lead to desirable outcomes such…

Applications · Statistics 2018-03-02 Ixavier A. Higgins , Suprateek Kundu , Ying Guo

Brain functional connectivity (FC), the temporal synchrony between brain networks, is essential to understand the functional organization of the brain and to identify changes due to neurological disorders, development, treatment, and other…

Applications · Statistics 2025-06-18 Amanda Mejia , David Bolin , Daniel Spencer , Ani Eloyan

The connectome, a map of the structural and/or functional connections in the brain, provides a complex representation of the neurobiological phenotypes on which it supervenes. This information-rich data modality has the potential to…

Modeling the behavior of coupled networks is challenging due to their intricate dynamics. For example in neuroscience, it is of critical importance to understand the relationship between the functional neural processes and anatomical…

Machine Learning · Computer Science 2021-04-20 Hongyuan You , Sikun Lin , Ambuj K. Singh

Brain functional connectome, the collection of interconnected neural circuits along functional networks, is one of the most cutting edge neuroimaging traits, and has a potential to play a mediating role within the effect pathway between an…

Methodology · Statistics 2022-01-28 Yize Zhao , Tianqi Chen , Jiachen Cai , Sarah Lichenstein , Marc Potenza , Sarah Yip

Structural and functional neuroimaging modalities provide complementary windows into brain organization: structural imaging characterizes neural tissue anatomy and microstructure, while functional imaging captures dynamic patterns of neural…

Methodology · Statistics 2026-03-24 Sakul Mahat , Sharmistha Guha , Jessica Bernard

The characterisation of the brain as a "connectome", in which the connections are represented by correlational values across timeseries and as summary measures derived from graph theory analyses, has been very popular in the last years.…

Machine Learning · Computer Science 2020-03-13 Tiago Azevedo , Luca Passamonti , Pietro Liò , Nicola Toschi

Functional connectomes capture brain interactions via synchronized fluctuations in the functional magnetic resonance imaging signal. If measured during rest, they map the intrinsic functional architecture of the brain. With task-driven…

Neurons and Cognition · Quantitative Biology 2013-04-16 Gaël Varoquaux , R. C. Craddock

In structural brain networks the connections of interest consist of white-matter fibre bundles between spatially segregated brain regions. The presence, location and orientation of these white matter tracts can be derived using diffusion…

Neurons and Cognition · Quantitative Biology 2012-02-09 M. Hinne , T. Heskes , M. A. J. van Gerven

Brain-Computer Interface (BCI) is a rapidly developing technology that allows direct communications between the human brain and external devices, such as robotic arms and computers. Bayesian Networks is a powerful tool in machine learning…

Signal Processing · Electrical Eng. & Systems 2022-06-16 Pingsheng Li

Brain activation and connectivity analyses in task-based functional magnetic resonance imaging (fMRI) experiments with multiple subjects are currently at the forefront of data-driven neuroscience. In such experiments, interest often lies in…

Applications · Statistics 2019-04-02 Daniel Spencer , Rajarshi Guhaniyogi , Raquel Prado

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper…

Brain-computer interfaces (BCIs) make possible to interact with the external environment by decoding the mental intention of individuals. BCIs can therefore be used to address basic neuroscience questions but also to unlock a variety of…

Neurons and Cognition · Quantitative Biology 2021-02-12 Juliana Gonzalez-Astudillo , Tiziana Cattai , Giulia Bassignana , Marie-Constance Corsi , Fabrizio De Vico Fallani

One of the crucial questions in neuroscience is how a rich functional repertoire of brain states relates to its underlying structural organization. How to study the associations between these structural and functional layers is an open…

Neurons and Cognition · Quantitative Biology 2018-02-22 Enrico Amico , Joaquín Goñi

The problem of jointly analysing functional connectomics and behavioral data is extremely challenging owing to the complex interactions between the two domains. In addition, clinical rs-fMRI studies often have to contend with limited…

Machine Learning · Computer Science 2023-01-18 Niharika Shimona D'Souza

Multimodal neuroimaging modeling has becomes a widely used approach but confronts considerable challenges due to heterogeneity, which encompasses variability in data types, scales, and formats across modalities. This variability…

Neurons and Cognition · Quantitative Biology 2025-04-15 Gang Qu , Ziyu Zhou , Vince D. Calhoun , Aiying Zhang , Yu-Ping Wang

Functional connectivity fingerprints are among today's best choices to obtain a faithful sampling of an individual's brain and cognition in health and disease. Here we make a case for key advantages of analyzing such connectome profiles…

Methodology · Statistics 2019-09-06 Danilo Bzdok , Dorothea L. Floris , Andre F. Marquand

Deducing the structure of neural circuits is one of the central problems of modern neuroscience. Recently-introduced calcium fluorescent imaging methods permit experimentalists to observe network activity in large populations of neurons,…

Applications · Statistics 2011-07-22 Yuriy Mishchencko , Joshua T. Vogelstein , Liam Paninski

Integrating brain imaging data with clinical reports offers a valuable opportunity to leverage complementary multimodal information for more effective and timely diagnosis in practical clinical settings. This approach has gained significant…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Jing Zhang , Xiaowei Yu , Minheng Chen , Lu Zhang , Tong Chen , Yan Zhuang , Chao Cao , Yanjun Lyu , Li Su , Tianming Liu , Dajiang Zhu

Action, cognition, emotion and perception can be mapped in the brain by using set of techniques. Translating unimodal concepts from one modality to another is an important step towards understanding the neural mechanisms. This paper…

Other Computer Science · Computer Science 2012-12-18 Revati Shriram , Dr. M. Sundhararajan , Nivedita Daimiwal
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