A dissipative network model with neighboring activation

We propose a network model with dissipative structure taking into consideration the effect of neighboring activation and individual dissipation. Nodes may feel tired of interactions with new nodes step by step, and drop out of the network evolution. However, these dormant nodes can become active again following neighbors. During the whole evolution only active nodes have opportunities to receive new links. We analyze user behavior of a real Internet forum, and the statistical characteristics of this forum are analogous to our model. Under the influence of motivation and dissipation, the degree distribution of our network model decays as a power law with a diversity of tunable power exponents. Furthermore, the network has high clustering, small average path length and positive assortativity coefficients

A guide to the BRAIN initiative cell census network data ecosystem

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain with demonstration of prototype feasibility for human and nonhuman primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed by the BICCN, and to accessing and using these data and extensive resources, including the BRAIN Cell Data Center (BCDC), which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted toward Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.Horizon 2020 (H2020)R01 NS096720Radiolog