A functional neuron has been developed from a simple neural circuit by incorporating a
phototube and a thermistor in different branch circuits. The physical field energy is controlled …

Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of
underlying causes. However, determining which model parameters agree with complex and …

Mechanistic models of single-neuron dynamics have been extensively studied in
computational neuroscience. However, identifying which models can quantitatively …

A large variety of neuron models are used in theoretical and computational neuroscience,
and among these, single-compartment models are a popular kind. These models do not …

Modern graphics cards contain hundreds of cores that can be programmed for intensive
calculations. They are beginning to be used for spiking neural network simulations. The goal …

The ever‐increasing processing power demands of digital computers cannot continue to be
fulfilled indefinitely unless there is a paradigm shift in computing. Neuromorphic computing …

Large-scale numerical simulations of detailed brain circuit models are important for
identifying hypotheses on brain functions and testing their consistency and plausibility. An …

Physiological experiments have highlighted how the dendrites of biological neurons can
nonlinearly process distributed synaptic inputs. However, it is unclear how aspects of a …

Neurons encode information in sequences of spikes, which are triggered when their
membrane potential crosses a threshold. In vivo, the spiking threshold displays large …

The adaptive leaky integrate-and-fire (ALIF) model is fundamental within computational
neuroscience and has been instrumental in studying our brains $\textit {in silico} $. Due to …