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Human learning is a complex process in which future behavior is altered via the reorganization of brain activity and connectivity. It remains unknown whether activity and connectivity differentially reorganize during learning, and, if so,…

The connectome, or the entire connectivity of a neural system represented by network, ranges various scales from synaptic connections between individual neurons to fibre tract connections between brain regions. Although the modularity they…

Neurons and Cognition · Quantitative Biology 2014-10-01 Jinseop S. Kim , Marcus Kaiser

Experimental fMRI studies have shown that spontaneous brain activity i.e. in the absence of any external input, exhibit complex spatial and temporal patterns of co-activity between segregated brain regions. These so-called large-scale…

Adaptation and Self-Organizing Systems · Physics 2015-06-23 Vesna Vuksanović , Philipp Hövel

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is…

Neurons and Cognition · Quantitative Biology 2013-10-31 Danielle S. Bassett , Nicholas F. Wymbs , M. Puck Rombach , Mason A. Porter , Peter J. Mucha , Scott T. Grafton

Network control theory has recently emerged as a promising approach for understanding brain function and dynamics. By operationalizing notions of control theory for brain networks, it offers a fundamental explanation for how brain dynamics…

Quantitative Methods · Quantitative Biology 2020-03-20 Shikuang Deng , Shi Gu

We investigated how the organization of functional brain networks was related to cognitive reserve (CR) during a memory task in healthy aging. We obtained the magnetoencephalographic functional networks of 20 elders with a high or low CR…

Structural and functional heterogeneity are hallmarks of cortical circuits, from broad degree distributions in the mouse connectome to diverse intrinsic neuronal timescales. Yet a mechanistic link between connectivity heterogeneity and…

Neurons and Cognition · Quantitative Biology 2026-03-05 Marco Zenari , Luca Taffarello , Luca Mazzucato , Amos Maritan , Samir Suweis

Understanding the relationship between the dynamics of neural processes and the anatomical substrate of the brain is a central question in neuroscience. On the one hand, modern neuroimaging technologies, such as diffusion tensor imaging,…

In this paper, we propose a novel unsupervised learning method to learn the brain dynamics using a deep learning architecture named residual D-net. As it is often the case in medical research, in contrast to typical deep learning tasks, the…

Machine Learning · Statistics 2019-03-01 Youngjoo Seo , Manuel Morante , Yannis Kopsinis , Sergios Theodoridis

We present a didactic introduction to spectral Dynamic Causal Modelling (DCM), a Bayesian state-space modelling approach used to infer effective connectivity from non-invasive neuroimaging data. Spectral DCM is currently the most widely…

Neurons and Cognition · Quantitative Biology 2023-09-07 Leonardo Novelli , Karl Friston , Adeel Razi

The brain is a complex organ characterized by heterogeneous patterns of structural connections supporting unparalleled feats of cognition and a wide range of behaviors. New noninvasive imaging techniques now allow these patterns to be…

Neurons and Cognition · Quantitative Biology 2020-04-03 Christopher W. Lynn , Danielle S. Bassett

Understanding the human brain remains the Holy Grail in biomedical science, and arguably in all of the sciences. Our brains represent the most complex systems in the world (and some contend the universe) comprising nearly one hundred…

Quantitative Methods · Quantitative Biology 2016-02-03 Sean L. Simpson , Paul J. Laurienti

Schizophrenia (SZ) is a brain disorder leading to detached mind's normally integrated processes. Hence, the exploration of the symptoms in relation to functional connectivity (FC) had great relevance in the field. FC can be investigated on…

Neurons and Cognition · Quantitative Biology 2026-04-08 Davide Coluzzi , Giuseppe Baselli

Connectomes are spatially embedded networks whose architecture has been shaped by physical constraints and communication needs throughout evolution. Using a decentralized navigation protocol, we investigate the relationship between the…

Neurons and Cognition · Quantitative Biology 2020-02-07 Antoine Allard , M. Ángeles Serrano

Randomly connected neural networks have long served as a theoretical tool for studying collective dynamics in neural populations, yet quantitative comparisons to experiments remain limited. Recent technological advances have made it…

Neurons and Cognition · Quantitative Biology 2026-05-27 Zehui Zhao , Michael J Pasek , Ilya M Nemenman

At rest, human brain functional networks display striking modular architecture in which coherent clusters of brain regions are activated. The modular account of brain function is pervasive, reliable, and reproducible. Yet, a complementary…

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the…

Neurons and Cognition · Quantitative Biology 2018-11-01 Gorka Zamora-López , Yuhan Chen , Gustavo Deco , Morten L. Kringelbach , Changsong Zhou

Brain areas' functional repertoires are shaped by their incoming and outgoing structural connections. In empirically measured networks, most connections are short, reflecting spatial and energetic constraints. Nonetheless, a small number of…

Neurons and Cognition · Quantitative Biology 2022-06-08 Richard F. Betzel , Danielle S. Bassett

Activity in the human brain moves between diverse functional states to meet the demands of our dynamic environment, but fundamental principles guiding these transitions remain poorly understood. Here, we capitalize on recent advances in…

Alzheimer's disease (AD) is the most prevalent form of dementia. Traditional methods cannot achieve efficient and accurate diagnosis of AD. In this paper, we introduce a novel method based on dynamic functional connectivity (dFC) that can…

Computer Vision and Pattern Recognition · Computer Science 2020-06-25 Xingwei An , Yutao Zhou , Yang Di , Dong Ming
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