Circuit Architectures How can artificial neural networks help us understand the brain

In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and ... ... system can become highly synergistic; and (b) how informational states map onto artificial neural networks in various learning modes. Here we employ an ... Sep 5, 2024 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure in ... Sep 14, 2016 ... Feed forward neural networks (FF or FFNN) and perceptrons (P) are very straight forward, they feed information from the front to the back (input ... Oct 6, 2022 ... Our results show that synergy increases as neural networks learn multiple diverse tasks. Furthermore, performance in tasks requiring integration ... Jan 29, 2024 ... We will see how ANN-assisted mixture space exploration can adapt to dynamic mixtures and balance the local and global information. Section 3 ... Sep 10, 2019 ... Using a genetic algorithm approach to find optimal neural network structures for model-free policy learning in reinforcement learning; Using ... Feb 7, 2018 ... ... information than excitatory connections, known to enhance entropy in the network. ... Neural information · Neuronal dynamics · Topological tools ... It is an intrinsic phenomenon unrelated to cardiac rhythm or neural and hormonal regulation. Vasomotion is found to be particularly prominent under conditions ... The human brain is often used as an analogy to explain neural networks, however this is not particularly helpful as it implies machines understand information ...