The Tripod neuron: a minimal structural reduction of the dendritic tree

Neuron models with explicit dendritic dynamics have shed light on mechanisms for coincidence detection, pathway selection and temporal filtering. However, it is still unclear which morphological and physiological features are required to capture these phenomena. In this work, we introduce the Tripod neuron model and propose a minimal structural reduction of the dendritic tree that is able to reproduce these computations. The Tripod is a three-compartment model consisting of two segregated passive dendrites and a somatic compartment modelled as an adaptive, exponential integrate-and-fire neuron. It incorporates dendritic geometry, membrane physiology and receptor dynamics as measured in human pyramidal cells. We characterize the response of the Tripod to glutamatergic and GABAergic inputs and identify parameters that support supra-linear integration, coincidence-detection and pathway-specific gating through shunting inhibition. Following NMDA spikes, the Tripod neuron generates plateau potentials whose duration depends on the dendritic length and the strength of synaptic input. When fitted with distal compartments, the Tripod encodes previous activity into a dendritic depolarized state. This dendritic memory allows the neuron to perform temporal binding, and we show that it solves transition and sequence detection tasks on which a single-compartment model fails. Thus, the Tripod can account for dendritic computations previously explained only with more detailed neuron models or neural networks. Due to its simplicity, the Tripod neuron can be used efficiently in simulations of larger cortical circuits. KEY POINTS: We present a neuron model, called the Tripod, with two segregated dendritic branches that are connected to an axosomatic compartment. Each branch implements inhibitory GABAergic and excitatory glutamatergic synaptic transmission, including voltage-gated NMDA receptors. Dendrites are modelled on relevant geometric and physiological parameters measured in human pyramidal cells. The neuron reproduces classical dendritic computations, such as coincidence detection and pathway selection via shunting inhibition, that are beyond the scope of point-neuron models. Under some conditions, dendritic NMDA spikes cause plateau potentials, and we show that they provide a form of short-term memory which is useful for sequence recognition. The dendritic structure of the Tripod neuron is sufficiently simple to be integrated into efficient network simulations and studied in a broad functional context.