Highlights•Generalized integrate-and-fire (GIF) models permit efficient extraction of point
neuron parameters, which reproduce the spiking behavior of multiple cell types and are …

The neural dynamics generating sensory, motor, and cognitive functions are commonly
understood through field theories for neural population activity. Classic neural field theories …

Spiking neural networks have attracted increasing attention in recent years due to their
potential of handling time-dependent data. Many algorithms and techniques have been …

Neural mass models is a general name for various models describing the collective
dynamics of large neural populations in terms of averaged macroscopic variables. Recently …

Simulations of neural activity at different levels of detail are ubiquitous in modern
neurosciences, aiding the interpretation of experimental data and underlying neural …

Understanding the mechanisms that lead to oscillatory activity in the brain is an ongoing
challenge in computational neuroscience. Here, we address this issue by considering a …

The macroscopic dynamics of large populations of neurons can be mathematically analyzed
using low-dimensional firing-rate or neural-mass models. However, these models fail to …

Neural computations emerge from myriad neuronal interactions occurring in intricate spiking
networks. Due to the inherent complexity of neural models, relating the spiking activity of a …

It is essential to understand the complex structure of the human brain to develop new
treatment approaches for neurodegenerative disorders (NDDs). This review paper …

Can we use spiking neural networks (SNN) as generative models of multi-neuronal
recordings, while taking into account that most neurons are unobserved? Modeling the …