Synapses are located throughout the often-elaborate dendritic tree of central neurons.
Hebbian models of plasticity require temporal association between synaptic input and …

Computational modeling has been indispensable for understanding how subcellular
neuronal features influence circuit processing. However, the role of dendritic computations …

Neurons are the fundamental units of the brain and nervous system. Developing a good
modeling of human neurons is very important not only to neurobiology but also to computer …

An artificial neural network (ANN) that mimics the information processing mechanisms and
procedures of neurons in human brains has achieved a great success in many fields, eg …

Pyramidal neurons integrate synaptic inputs arriving on a structurally and functionally
complex dendritic tree that has nonlinear responses. A study in this issue shows that …

One of the central questions in neuroscience is how particular tasks, or computations, are
implemented by neural networks to generate behavior. The prevailing view has been that …

A growing body of work underlines striking similarities between biological neural networks
and recurrent, binary neural networks. A relatively smaller body of work, however, addresses …

This study proposes voltage-dependent-synaptic plasticity (VDSP), a novel brain-inspired
unsupervised local learning rule for the online implementation of Hebb's plasticity …

Animal behaviour depends on learning to associate sensory stimuli with the desired motor
command. Understanding how the brain orchestrates the necessary synaptic modifications …

Despite an abundance of computational models for learning of synaptic weights, there has
been relatively little research on structural plasticity, ie, the creation and elimination of …