This book illustrates the thrust of the scientific community to use machine learning concepts
for tackling a complex problem: given time series of neuronal spontaneous activity which is
the underlying connectivity between the neurons in the network? The contributing authors also
develop tools for the advancement of neuroscience through machine learning techniques with a
focus on the major open problems in neuroscience. While the techniques have been developed for
a specific application they address the more general problem of network reconstruction from
observational time series a problem of interest in a wide variety of domains including
econometrics epidemiology and climatology to cite only a few.< The book is designed for the
mathematics physics and computer science communities that carry out research in neuroscience
problems. The content is also suitable for the machine learning community because it
exemplifies how to approach the same problem from different perspectives.
