Optimization principles of dendritic structure

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The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites

Conductance-based neuron models are frequently employed to study the dynamics of biological neural networks. For speed and ease of use, these models are often reduced in morphological complexity. Simplified dendritic branching structures may process inputs differently than full branching structures, however, and could thereby fail to reproduce important aspects of biological neural processing. It is not yet well understood which processing capabilities require detailed branching structures. Therefore, we analyzed the processing capabilities of full or partially branched reduced models. These models were created by collapsing the dendritic tree of a full morphological model of a globus pallidus (GP) neuron while preserving its total surface area and electrotonic length, as well as its passive and active parameters. Dendritic trees were either collapsed into single cables (unbranched models) or the full complement of branch points was preserved (branched models). Both reduction strategies allowed us to compare dynamics between all models using the same channel density settings. Full model responses to somatic inputs were generally preserved by both types of reduced model while dendritic input responses could be more closely preserved by branched than unbranched reduced models. However, features strongly influenced by local dendritic input resistance, such as active dendritic sodium spike generation and propagation, could not be accurately reproduced by any reduced model. Based on our analyses, we suggest that there are intrinsic differences in processing capabilities between unbranched and branched models. We also indicate suitable applications for different levels of reduction, including fast searches of full model parameter space

Dendritic Morphology Predicts Pattern Recognition Performance in Multi-compartmental Model Neurons with and without Active Conductances

This is an Open Access article published under the Creative Commons Attribution license CC BY 4.0 which allows users to read, copy, distribute and make derivative works, as long as the author of the original work is citedIn this paper we examine how a neuron’s dendritic morphology can affect its pattern recognition performance. We use two different algorithms to systematically explore the space of dendritic morphologies: an algorithm that generates all possible dendritic trees with 22 terminal points, and one that creates representative samples of trees with 128 terminal points. Based on these trees, we construct multi-compartmental models. To assess the performance of the resulting neuronal models, we quantify their ability to discriminate learnt and novel input patterns. We find that the dendritic morphology does have a considerable effect on pattern recognition performance and that the neuronal performance is inversely correlated with the mean depth of the dendritic tree. The results also reveal that the asymmetry index of the dendritic tree does not correlate with the performance for the full range of tree morphologies. The performance of neurons with dendritic tapering is best predicted by the mean and variance of the electrotonic distance of their synapses to the soma. All relationships found for passive neuron models also hold, even in more accentuated form, for neurons with active membranesPeer reviewedFinal Published versio

Combining Membrane Potential Imaging with l-Glutamate or GABA Photorelease

Combining membrane potential imaging using voltage sensitive dyes with photolysis of l-glutamate or GABA allows the monitoring of electrical activity elicited by the neurotransmitter at different sub-cellular sites. Here we describe a simple system and some basic experimental protocols to achieve these measurements. We show how to apply the neurotransmitter and how to vary the dimension of the area of photolysis. We assess the localisation of photolysis and of the recorded membrane potential changes by depolarising the dendrites of cerebellar Purkinje neurons with l-glutamate photorelease using different experimental protocols. We further show in the apical dendrites of CA1 hippocampal pyramidal neurons how l-glutamate photorelease can be used to calibrate fluorescence changes from voltage sensitive dyes in terms of membrane potential changes (in mV) and how GABA photorelease can be used to investigate the phenomenon of shunting inhibition. We also show how GABA photorelease can be used to measure chloride-mediated changes of membrane potential under physiological conditions originating from different regions of a neuron, providing important information on the local intracellular chloride concentrations. The method and the proof of principle reported here open the gateway to a variety of important applications where the advantages of this approach are necessary

Characterization of Voltage-Gated Ca2+ Conductances in Layer 5 Neocortical Pyramidal Neurons from Rats

Neuronal voltage-gated Ca2+ channels are involved in electrical signalling and in converting these signals into cytoplasmic calcium changes. One important function of voltage-gated Ca2+ channels is generating regenerative dendritic Ca2+ spikes. However, the Ca2+ dependent mechanisms used to create these spikes are only partially understood. To start investigating this mechanism, we set out to kinetically and pharmacologically identify the sub-types of somatic voltage-gated Ca2+ channels in pyramidal neurons from layer 5 of rat somatosensory cortex, using the nucleated configuration of the patch-clamp technique. The activation kinetics of the total Ba2+ current revealed conductance activation only at medium and high voltages suggesting that T-type calcium channels were not present in the patches. Steady-state inactivation protocols in combination with pharmacology revealed the expression of R-type channels. Furthermore, pharmacological experiments identified 5 voltage-gated Ca2+ channel sub-types – L-, N-, R- and P/Q-type. Finally, the activation of the Ca2+ conductances was examined using physiologically derived voltage-clamp protocols including a calcium spike protocol and a mock back-propagating action potential (mBPAP) protocol. These experiments enable us to suggest the possible contribution of the five Ca2+ channel sub-types to Ca2+ current flow during activation under physiological conditions

Intracellular chloride concentration influences the GABAA receptor subunit composition

GABAA receptors (GABAARs) exist as different subtype variants showing unique functional properties and defined spatio-temporal expression pattern. The molecular mechanisms underlying the developmental expression of different GABAAR are largely unknown. The intracellular concentration of chloride ([Cl−]i), the main ion permeating through GABAARs, also undergoes considerable changes during maturation, being higher at early neuronal stages with respect to adult neurons. Here we investigate the possibility that [Cl−]i could modulate the sequential expression of specific GABAARs subtypes in primary cerebellar neurons. We show that [Cl−]i regulates the expression of α3-1 and δ-containing GABAA receptors, responsible for phasic and tonic inhibition, respectively. Our findings highlight the role of [Cl−]i in tuning the strength of GABAergic responses by acting as an intracellular messenger

Axons Amplify Somatic Incomplete Spikes into Uniform Amplitudes in Mouse Cortical Pyramidal Neurons

BACKGROUND: Action potentials are the essential unit of neuronal encoding. Somatic sequential spikes in the central nervous system appear various in amplitudes. To be effective neuronal codes, these spikes should be propagated to axonal terminals where they activate the synapses and drive postsynaptic neurons. It remains unclear whether these effective neuronal codes are based on spike timing orders and/or amplitudes. METHODOLOGY/PRINCIPAL FINDINGS: We investigated this fundamental issue by simultaneously recording the axon versus soma of identical neurons and presynaptic vs. postsynaptic neurons in the cortical slices. The axons enable somatic spikes in low amplitude be enlarged, which activate synaptic transmission in consistent patterns. This facilitation in the propagation of sequential spikes through the axons is mechanistically founded by the short refractory periods, large currents and high opening probability of axonal voltage-gated sodium channels. CONCLUSION/SIGNIFICANCE: An amplification of somatic incomplete spikes into axonal complete ones makes sequential spikes to activate consistent synaptic transmission. Therefore, neuronal encoding is likely based on spike timing order, instead of graded analogues

Effects of Active Conductance Distribution over Dendrites on the Synaptic Integration in an Identified Nonspiking Interneuron

The synaptic integration in individual central neuron is critically affected by how active conductances are distributed over dendrites. It has been well known that the dendrites of central neurons are richly endowed with voltage- and ligand-regulated ion conductances. Nonspiking interneurons (NSIs), almost exclusively characteristic to arthropod central nervous systems, do not generate action potentials and hence lack voltage-regulated sodium channels, yet having a variety of voltage-regulated potassium conductances on their dendritic membrane including the one similar to the delayed-rectifier type potassium conductance. It remains unknown, however, how the active conductances are distributed over dendrites and how the synaptic integration is affected by those conductances in NSIs and other invertebrate neurons where the cell body is not included in the signal pathway from input synapses to output sites. In the present study, we quantitatively investigated the functional significance of active conductance distribution pattern in the spatio-temporal spread of synaptic potentials over dendrites of an identified NSI in the crayfish central nervous system by computer simulation. We systematically changed the distribution pattern of active conductances in the neuron's multicompartment model and examined how the synaptic potential waveform was affected by each distribution pattern. It was revealed that specific patterns of nonuniform distribution of potassium conductances were consistent, while other patterns were not, with the waveform of compound synaptic potentials recorded physiologically in the major input-output pathway of the cell, suggesting that the possibility of nonuniform distribution of potassium conductances over the dendrite cannot be excluded as well as the possibility of uniform distribution. Local synaptic circuits involving input and output synapses on the same branch or on the same side were found to be potentially affected under the condition of nonuniform distribution while operation of the major input-output pathway from the soma side to the one on the opposite side remained the same under both conditions of uniform and nonuniform distribution of potassium conductances over the NSI dendrite

Tonic excitation or inhibition is set by GABAA conductance in hippocampal interneurons

Inhibition is a physiological process that decreases the probability of a neuron generating an action potential. The two main mechanisms that have been proposed for inhibition are hyperpolarization and shunting. Shunting results from increased membrane conductance, and it reduces the neuron-firing probability. Here we show that ambient GABA, the main inhibitory neurotransmitter in the brain, can excite adult hippocampal interneurons. In these cells, the GABAA current reversal potential is depolarizing, making baseline tonic GABAA conductance excitatory. Increasing the tonic conductance enhances shunting-mediated inhibition, which eventually overpowers the excitation. Such a biphasic change in interneuron firing leads to corresponding changes in the GABAA-mediated synaptic signalling. The described phenomenon suggests that the excitatory or inhibitory actions of the current are set not only by the reversal potential, but also by the conductance

Active dendrites enhance neuronal dynamic range

Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the last decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of active dendritic trees is a highly non-linear function of their afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease of dynamic range.Comment: 20 pages, 6 figure