Microelectrode arrays and microprobes have been widely utilized to measure neuronal
activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate …

Neuromorphic systems, which emulate neural functionalities of a human brain, are
considered to be an attractive next‐generation computing approach, with advantages of …

Brian 2 allows scientists to simply and efficiently simulate spiking neural network models.
These models can feature novel dynamical equations, their interactions with the …

Spiking neural networks (SNNs) that enables energy efficient implementation on emerging
neuromorphic hardware are gaining more attention. Yet now, SNNs have not shown …

Memristive devices are promising candidates to emulate biological computing. However, the
typical switching voltages (0.2-2 V) in previously described devices are much higher than …

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 …

This paper presents a comprehensive overview of modelling, simulation and implementation
of neural networks, taking into account that two aims have emerged in this area: the …

One goal of researchers in neuroscience, psychology, and artificial intelligence is to build
theoretical models that are able to explain the flexibility and adaptiveness of biological …

This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with
the foundations of the theory and building it up, this is essential reading for any scientists …

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