愤慨一下
发表于 2025-3-23 12:46:23
Robert Urbanancestor, is important to the understanding of emergence and evolution of brain functions, cognitions and behaviors. However, recent works largely relied on the scheme that one species is used as the “reference” to which another is aligned and contrasted, whereas a more reasonable “reference” could
Hyperopia
发表于 2025-3-23 14:06:32
Robert Urbanlities are not able to accurately acquire high-resolution hemodynamic information that would be required to assess complex neurovascular pathologies. Instead, computational fluid dynamics (CFD) simulations can be applied to tomographic reconstructions to obtain clinically relevant information. Howev
pulmonary-edema
发表于 2025-3-23 18:28:48
Robert Urbanacterize spontaneous functional fluctuations, little attention has been paid to the functional mechanisms of neural interactions. Inspired by the notion of holography, we propose an explainable machine learning approach to establishing a novel underpinning of self-organized cross-frequency coupling
Flavouring
发表于 2025-3-24 01:28:07
Robert Urbane trajectory of disease progression. The ordering of events is usually inferred from the data using optimization, hence may suffer from local optima and computational complexity. This paper mathematically proves that this ordering can be directedly determined by the cumulative distribution function
不透气
发表于 2025-3-24 05:06:29
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Amplify
发表于 2025-3-24 07:08:57
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GEON
发表于 2025-3-24 12:04:40
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flex336
发表于 2025-3-24 15:21:29
Robert Urbanpatial locations of the two entities in the biological specimen. Measuring colocalization between two entities relies on fluorescence imaging of the specimen using two fluorescent chemicals, each of which indicates the presence/absence of one of the entities at any pixel location. State-of-the-art m
存心
发表于 2025-3-24 19:29:21
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专心
发表于 2025-3-25 03:11:24
Robert Urbanhole-brain connectivity analysis, a critical stage is the computation of a set of network nodes that can effectively represent cortical regions. To address this problem, we present a robust cerebral cortex parcellation method based on spectral graph theory and resting-state fMRI correlations that ge