Computing with active dendrites

Multilayer Processing of Spatiotemporal Spike Patterns in a Neuron with Active Dendrites

With the advent of new experimental evidence showing that dendrites play an active role in processing a neuron's inputs, we revisit the question of a suitable abstraction for the computing function of a neuron in processing spatiotemporal input patterns. Although the integrative role of a neuron in relation to the spatial clustering of synaptic inputs can be described by a two-layer neural netw...

Development of modified cable models to simulate accurate neuronal active behaviors.

In large network and single three-dimensional (3-D) neuron simulations, high computing speed dictates using reduced cable models to simulate neuronal firing behaviors. However, these models are unwarranted under active conditions and lack accurate representation of dendritic active conductances that greatly shape neuronal firing. Here, realistic 3-D (R3D) models (which contain full anatomical d...

Spike-Timing Dependent Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites

Presented is a model of an integrate-and-fire neuron with active dendrites and a spike-timing dependent Hebbian learning rule. The learning algorithm effectively trains the neuron when responding to several types of temporal encoding schemes: temporal code with single spikes, spike bursts and phase coding. The neuron model and learning algorithm are tested on a neural network with a self-organi...

Travelling waves in a model of quasi-active dendrites with active spines

Noisy Dendrites: Models of Dendritic Integration In Vivo

H. Cuntz et al. (eds.), The Computing Dendrite: From Structure to Function, Springer Series in Computational Neuroscience 11, DOI 10.1007/978-1-4614-8094-5_11, © Springer Science+Business Media New York 2014 Abstract While dendritic processing has been well characterized in vitro, there is little experimental data and models available about the integrative properties of dendrites in vivo. Here,...