Synchronous rhythms represent a core mechanism for sculpting temporal coordination of
neural activity in the brain-wide network. This review focuses on oscillations in the cerebral …

Most current Artificial Neural Network (ANN) models are based on highly simplified brain
dynamics. They have been used as powerful computational tools to solve complex pattern …

Neuromorphic networks of artificial neurons and synapses can solve computationally hard
problems with energy efficiencies unattainable for von Neumann architectures. For image …

What happens in our brain when we make a decision? What triggers a neuron to send out a
signal? What is the neural code? This textbook for advanced undergraduate and beginning …

A major goal of neuroscience, statistical physics, and nonlinear dynamics is to understand
how brain function arises from the collective dynamics of networks of spiking neurons. This …

Neurophysiological field-potential signals consist of both arrhythmic and rhythmic patterns
indicative of the fractal and oscillatory dynamics arising from likely distinct mechanisms …

This textbook is aimed at newcomers to nonlinear dynamics and chaos, especially students
taking a first course in the subject. The presentation stresses analytical methods, concrete …

Theoretical neuroscience provides a quantitative basis for describing what nervous systems
do, determining how they function, and uncovering the general principles by which they …

Neurons in the brain communicate by short electrical pulses, the so-called action potentials
or spikes. How can we understand the process of spike generation? How can we …

In order to model neuronal behavior or to interpret the results of modeling studies,
neuroscientists must call upon methods of nonlinear dynamics. This book offers an …