Understanding how the brain anticipates future states and transmits or reconstructs information remains a central challenge in neuroscience. This Research ...

Learn how forward propagation works in neural networks using Python! This tutorial explains the process of passing inputs ...

Abstract: Nonlinear and non-Gaussian characteristics are common in industrial processes. Artificial neural correlation analysis (ANCA) is a good nonlinear process monitoring algorithm, which combines ...

Summary: The simple act of breathing shapes how and when memories are successfully retrieved. Participants recalled learned word-image pairs more accurately when reminder cues were presented during or ...

Department of Computing, Imperial College London, London SW7 2AZ, U.K. Sargent Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ, U.K. Department of Computing, Imperial ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

Neuroscientists from around the world have worked in parallel to map, for the first time, the entire brain activity of mice while they were making decisions. This achievement involved using electrodes ...

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...

Assessment of pharmacological intervention on in vitro neural systems often emphasises molecular and structural changes. However, neural systems fundamentally process and act on information. For ...

ABSTRACT: An algorithm is being developed to conduct a computational experiment to study the dynamics of random processes in an asymmetric Markov chain with eight discrete states and continuous time.