Data-driven computational neuroscience facilitates the transformation of data into insights
into the structure and functions of the brain. This introduction for researchers and graduate …

Neuroinformatics presents cutting-edge techniques for the synergistic study of
neuroinformatics, thereby facilitating the efforts of discovery neuroscience through the …

Editorial introduction to a special issue of Current Opinion in Neurobiology on “Machine
learning, big data, and neuroscience”. The articles in this issue explore the growing use and …

Machine Learning (ML) is a well‐known paradigm that refers to the ability of systems to learn
a specific task from the data and aims to develop computer algorithms that improve with …

Bayesian networks are a type of probabilistic graphical models lie at the intersection
between statistics and machine learning. They have been shown to be powerful tools to …

The conference on Neural Circuit Reconstruction recently held at the Janelia Farm research
campus of the Howard Hughes Medical Institute (www. hhmi. org/janelia/conf-007. html) …

Computing the Brain provides readers with an integrated view of current informatics
research related to the field of neuroscience. This book clearly defines the new work being …

The grand challenge in neuroscience is—it would seem—the effort of understanding the
structure, function, and development of the nervous system in health and disease. Such …

The human brain is a biological organ, weighing about three pounds or 1.4 kg, that
determines our behaviors, thoughts, emotions and consciousness. Although comprising only …

A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics
from a computational perspective, tracing a path from cells and circuits to behavior and …