ArticleAdvances in experimental medicine and biology2026
Network Diffusion Modeling in Computational Neuroscience.
Article in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
Neurodegenerative diseases present progressive loss of structure or function of neurons (cognitive impairment), which eventually leads to neuron death. Neurodegeneration affects brain connectivity, leading to disrupted communication between different regions. Brain itself is an extremely complex structure and thanks to cutting-edge imaging modalities; one way to picture it as a study framework is through a set of discrete gray matter regions connected structurally and functionally to each other (brain connectomics). Studying neurodegeneration using graph theory and diffusion models involves understanding how brain networks deteriorate over time and how this deterioration can be quantified and analyzed. This work focuses on (graph) network diffusion models, on how they blueprint the diffusion and aggregation of matter across the connectome.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.