Single neuron dynamics and computation

- LNP models provide a precise description of the static and dynamic responses of neurons.
- Dynamic responses depend on neuron electrophysiological properties and support various computations.
- Various modes of dendritic input summation enrich neuron computational repertoires.
- Synaptic dynamics further provides differential and frequency-dependent signalling.

At the single neuron level, information processing involves the transformation of input spike trains into an appropriate output spike train. Building upon the classical view of a neuron as a threshold device, models have been developed in recent years that take into account the diverse electrophysiological make-up of neurons and accurately describe their input-output relations. Here, we review these recent advances and survey the computational roles that they have uncovered for various electrophysiological properties, for dendritic arbor anatomy as well as for short-term synaptic plasticity.