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Decoding neural algorithms is one of the major goals of neuroscience. It is generally accepted that brain computations rely on the orchestration of neural activity at local scales, as well as across the brain through long‐range connections. Understanding the relationship between brain activity and connectivity is therefore a prerequisite to cracking ...
Timothy E.J. Behrens+2 more
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FARCI: Fast and Robust Connectome Inference
The inference of neuronal connectome from large-scale neuronal activity recordings, such as two-photon Calcium imaging, represents an active area of research in computational neuroscience.
Saber Meamardoost+7 more
doaj +1 more source
Disruption of structural connectome hierarchy in age-related hearing loss. [PDF]
IntroductionAge-related hearing loss (ARHL) is a common sensory disability among older adults and is considered a risk factor for the development of dementia.
Zhen Y+5 more
europepmc +2 more sources
Brain cells communicate with one another via local and long-range synaptic connections. Structural connectivity is the foundation for neural function. Brain-wide connectivity can be described at macroscopic, mesoscopic and microscopic levels. The mesoscale connectome represents connections between neuronal types across different brain regions. Building
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A 4D infant brain volumetric atlas based on the UNC/UMN baby connectome project (BCP) cohort
Spatiotemporal (four-dimensional) infant-dedicated brain atlases are essential for neuroimaging analysis of early dynamic brain development. However, due to the substantial technical challenges in the acquisition and processing of infant brain MR images,
Liangjun Chen+8 more
doaj
Navigation of brain networks [PDF]
Understanding the mechanisms of neural communication in large-scale brain networks remains a major goal in neuroscience. We investigated whether navigation is a parsimonious routing model for connectomics. Navigating a network involves progressing to the
Heuvel, Martijn P. van den+2 more
core +4 more sources
The brainstem connectome database
AbstractConnectivity data of the nervous system and subdivisions, such as the brainstem, cerebral cortex and subcortical nuclei, are necessary to understand connectional structures, predict effects of connectional disorders and simulate network dynamics. For that purpose, a database was built and analyzed which comprises all known directed and weighted
Schmitt, Oliver+5 more
openaire +3 more sources
Simultaneous Matrix Diagonalization for Structural Brain Networks Classification
This paper considers the problem of brain disease classification based on connectome data. A connectome is a network representation of a human brain. The typical connectome classification problem is very challenging because of the small sample size and ...
A Kurkumov+13 more
core +1 more source
Columnar connectome: toward a mathematics of brain function [PDF]
Understanding brain networks is important for many fields, including neuroscience, psychology, medicine, and artificial intelligence. To address this fundamental need, there are multiple ongoing connectome projects in the United States, Europe, and Asia ...
Anna Wang Roe
doaj +1 more source
Disambiguating the role of blood flow and global signal with partial information decomposition [PDF]
Global signal (GS) is an ubiquitous construct in resting state functional magnetic resonance imaging (rs-fMRI), associated to nuisance, but containing by definition most of the neuronal signal.
Calhoun, Vince D.+5 more
core +2 more sources