Contribution of sublinear and supralinear dendritic integration to neuronal computations

Abstract

Nonlinear dendritic integration is thought to increase the computational ability of neurons. Most studies focus on how supralinear summation of excitatory synaptic responses arising from clustered inputs within single dendrites result in the enhancement of neuronal firing, enabling simple computations such as feature detection. Recent reports have shown that sublinear summation is also a prominent dendritic operation, extending the range of subthreshold input-output (sI/O) transformations conferred by dendrites. Like supralinear operations, sublinear dendritic operations also increase the repertoire of neuronal computations, but feature extraction requires different synaptic connectivity strategies for each of these operations. In this article we will review the experimental and theoretical findings describing the biophysical determinants of the three primary classes of dendritic operations: linear, sublinear, and supralinear. We then review a Boolean algebra-based analysis of simplified neuron models, which provides insight into how dendritic operations influence neuronal computations. We highlight how neuronal computations are critically dependent on the interplay of dendritic properties (morphology and voltage-gated channel expression), spiking threshold and distribution of synaptic inputs carrying particular sensory features. Finally, we describe how global (scattered) and local (clustered) integration strategies permit the implementation of similar classes of computations, one example being the object feature binding problem.

Action potential initiation in a two-compartment model of pyramidal neuron mediated by dendritic Ca2+ spike

“…As mentioned in Introduction, dendritic Ca 2+ spike is the voltage transient caused by the activation of dendritic Ca 2+ conductance5671123. It is a local regenerative response involving the positive feedback loop between dendritic voltage and Ca 2+ influx67.…”

“…Their function is not solely to receive information from connected input cells and transmit it to the axon. Each dendritic branch is also a basic signalling unit for integrating synaptic inputs467891011, which determines how the receiving signals propagate to the axon. Such nonlinear integration operated by dendrites has a profound influence on neuronal and cortical computation1245678910.…”

“…The dendrites of pyramidal cells rely on their intrinsic nonlinearities, including voltage-gated channels and complex morphology, to integrate synaptic signals4567891011. The active ionic channels in their apical dendrites are particularly important in synaptic integration.…”

“…A common channel is the voltage-dependent Ca 2+ current that flows into the cell14567121314. The activation of its conductance could cause a threshold-dependent, all-or-none regenerative response in dendrites, which is often referred to as dendritic Ca 2+ spike471114151617. The existence of active Ca 2+ channel in apical dendrites make pyramidal neurons operate in either global or two-stage integration mode1819.…”

Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity

“…http://dx.doi.org/10.1101/023200 doi: bioRxiv preprint first posted online Jul. 24, 2015; branch (five per location) interact sub-linearly due to reduced driving force at synapses (Koch et al, 1982;Tran-van Minh et al, 2015). Even if the depolarization at the soma is weak, locally, the membrane voltage within a branch reaches the equilibrium voltage (0 mV) because of the branch small diameter 1 µm (see Movie S1).…”