Neural Networks with Probabilistic Weights What is the relationship between neural networks and cognitive science

Information integration is a measure, developed by Tononi and co-researchers, of the capacity for dynamic neural networks to be in informational states ... 01/01/2024 Maryam Shanechi is elevated to IEEE Fellow. 12/11/2023 Our Nature Biomedical Engineering paper on neural network models with dynamical flexible ... a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process. The semantic network ROI spanned a large swathe of heteromodal cortex, including most of the aforementioned cortical areas. The neural similarity structure of ... ... neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of ... Here we employ an information-decomposition framework to investigate neural networks performing cognitive tasks. Our results show that synergy increases as ... Nov 23, 2010 ... ... information processing by neural networks, using a simple cultured neural network. 5. Conclusion. Many useful paradigms and engineering ... Feb 22, 2023 ... We compare this control to a regularly-trained neural network, and show that perturbations on nodes carrying relay information cause failures in ... ... information transmission by single neurons but not by the entire network. Most surprisingly, addition of a delay can change the dependence of the information ... Feb 26, 2021 ... We developed a context-aware graph neural network (GNN) model utilizing the pairwise relationship among participants to investigate the ...