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

Yi, Guosheng; Wang, Jiang; Wei, Xile; Deng, Bin

doi:10.1038/srep45684

Cited by 17 publications

(16 citation statements)

References 55 publications

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“…It is also well matched to the performance of a two 'compartment' model (e.g. Figure 5b of [32]) which shows that apical amplification depends strongly on calcium conductance in the apical trunk.…”

Section: Dependence Of Second Ap Probability On Apical and Basal Inputsupporting

confidence: 58%

Bayesian modeling of BAC firing as a mechanism for apical amplification in neocortical pyramidal neurons

Kay¹,

Phillips

Aru

et al. 2019

Preprint

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Pyramidal cells in layer 5 of the neocortex have two distinct integration sites. These cells integrate inputs to basal dendrites in the soma while integrating inputs to the tuft in a site at the top of the apical trunk. The two sites communicate by action potentials that backpropagate to the apical site and by backpropagation-activated calcium spikes (BAC firing) that travel from the apical to the somatic site. Six key messages arise from the probabilistic information-theoretic analyses of BAC firing presented here. First, we suggest that pyramidal neurons with BAC firing could convert the odds in favour of the presence of a feature given the basal data into the odds in favour of the presence of a feature given the basal data and the apical input, by a simple Bayesian calculation. Second, the strength of the cell's response to basal input can be amplified when relevant to the current context, as specified by the apical input, without corrupting the message that it sends. Third, these analyses show rigorously how this apical amplification depends upon communication between the sites. Fourth, we use data on action potentials from a very detailed multi-compartmental biophysical model to study our general model in a more realistic setting, and demonstrate that it describes the data well. Fifth, this form of BAC firing meets criteria for distinguishing modulatory from driving interactions that have been specified using recent definitions of multivariate mutual information. Sixth, our general decomposition can be extended to cases where, instead of being purely driving or purely amplifying, apical and basal inputs can be partly driving and partly amplifying to various extents. These conclusions imply that an advance beyond the assumption of a single site of integration within pyramidal cells is needed, and suggest that the evolutionary success of neocortex may depend upon the cellular mechanisms of context-sensitive selective amplification hypothesized here. Author summaryThe cerebral cortex has a key role in conscious perception, thought, and action, and is predominantly composed of a particular kind of neuron: the pyramidal cells. The distinct shape of the pyramidal neuron with a long dendritic shaft separating two regions of profuse dendrites allows them to integrate inputs to the two regions separately and combine the results non-linearly to produce output. Here we show how inputs to this more distant site strengthen the cell's output 1 when it is relevant to the current task and environment. By showing that such neurons have capabilities that transcend those of neurons with the single site of integration assumed by many neuroscientists, this 'splitting of the neuronal atom' offers a radically new viewpoint from which to understand the evolution of the cortex and some of its many pathologies. This also suggests that approaches to artificial intelligence using neural networks might come closer to something analogous to real intelligence, if, instead of basing them on processing elements with a single site of integra...

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Section: Dependence Of Second Ap Probability On Apical and Basal Inputsupporting

confidence: 58%

Bayesian modeling of BAC firing as a mechanism for apical amplification in neocortical pyramidal neurons

Kay¹,

Phillips

Aru

et al. 2019

Preprint

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“…However, such a quantitative approach is very challenging if biophysical models are used to simultaneously fit data from multiple experimental paradigms. In such cases, a qualitative trial/error approach based on electrophysiological knowledge about the effect that each ion channel produces on the data are more effective (Schaefer et al, 2003;Larkum et al, 2004;Yi et al, 2017). We will use the qualitative trial/error approach as a satisfying strategy to reproduce the six features of L5-PCs observed in various experimental paradigms (Table 3) without a meticulous quantitative description of the Na 1 -APs and Ca 21 spikes.…”

Section: Model Testing Approachmentioning

confidence: 99%

“…Previous simplified biophysical models explained some key features, that is, the I-f curves (Larkum et al, 2004) and the backpropagating AP-activated Ca 21 spike (BAC) firing (Chua et al, 2015;Yi et al, 2017). More complex biophysical models accounted for some combinations of the three major features: the BAC firing (Rapp et al, 1996;Schaefer et al, 2003;Hay et al, 2011;Bahl et al, 2012;Almog and Korngreen, 2014;Mäki-Marttunen et al, 2018), the f-I curves (Hay et al, 2011;Bahl et al, 2012;Mäki-Marttunen et al, 2018), and the CF of Ca 21 spikes (Schaefer et al, 2003;Hay et al, 2011;Bahl et al, 2012;Almog and Korngreen, 2014).…”

Section: Introductionmentioning

confidence: 99%

A Minimal Biophysical Model of Neocortical Pyramidal Cells: Implications for Frontal Cortex Microcircuitry and Field Potential Generation

et al. 2020

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Ca 21 spikes initiated in the distal trunk of layer 5 pyramidal cells (PCs) underlie nonlinear dynamic changes in the gain of cellular response, critical for top-down control of cortical processing. Detailed models with many compartments and dozens of ionic channels can account for this Ca 21 spike-dependent gain and associated critical frequency. However, current models do not account for all known Ca 21 -dependent features. Previous attempts to include more features have required increasing complexity, limiting their interpretability and utility for studying large population dynamics. We overcome these limitations in a minimal two-compartment biophysical model. In our model, a basal-dendrites/somatic compartment included fast-inactivating Na 1 and delayed-rectifier K 1 conductances, while an apical-dendrites/trunk compartment included persistent Na 1 , hyperpolarization-activated cation (I h ), slow-inactivating K 1 , muscarinic K 1 , and Ca 21 L-type. The model replicated the Ca 21 spike morphology and its critical frequency plus three other defining features of layer 5 PC synaptic integration: linear frequency-current relationships, back-propagation-activated Ca 21 spike firing, and a shift in the critical frequency by blocking I h . Simulating 1000 synchronized layer 5 PCs, we reproduced the current source density patterns evoked by Ca 21 spikes and describe resulting medial-frontal EEG on a male macaque monkey. We reproduced changes in the current source density when I h was blocked. Thus, a two-compartment model with five crucial ionic currents in the apical dendrites reproduces all features of these neurons. We discuss the utility of this minimal model to study the microcircuitry of agranular areas of the frontal lobe involved in cognitive control and responsible for event-related potentials, such as the error-related negativity.

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“…In vitro experiments have observed that dendritic Ca 2+ spike triggers a burst of APs in the soma/axon and switches the firing mode of the cell to bursting (Williams and Stuart, 1999 ; Larkum and Zhu, 2002 ; Larkum et al, 2004 ; Palmer et al, 2012 ; Larkum, 2013 ). With a two-compartment model, our earlier study (Yi et al, 2017 ) has successfully reproduced this observation and explained how dendritic spike participates in somatic AP initiation. In present study, we show that the activation of Ca 2+ current in apical dendrites makes Na + entry become efficiently used by APs for their depolarization, thus facilitating the effective utilization of metabolic energy.…”

Section: Discussionmentioning

confidence: 58%

“…Two-compartment model is the minimal neuronal unit for capturing the interaction between dendrites and soma/axon, which has been widely used to describe the input-output transfer of single pyramidal cell. In particular, our earlier studies (Yi et al, 2014a , b , 2015b , 2016b , 2017 ) have demonstrated that dendrite area, dendritic spike and coupling conductance all play crucial roles in determining the transfer function of two-compartment model neurons. For example, they could alter the dynamic basis of spike initiation (Yi et al, 2014a , 2017 ), the outcome of subthreshold competition between opposite currents (Yi et al, 2014a , b , 2015b ), the dynamics of AP threshold (Yi et al, 2016b ), the electric field threshold for triggering spikes (Yi et al, 2014b ), and the field-induced SFA (Yi et al, 2015b ).…”

Section: Discussionmentioning

confidence: 99%

Dendritic Properties Control Energy Efficiency of Action Potentials in Cortical Pyramidal Cells

Wang

Wei

et al. 2017

Front. Cell. Neurosci.

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Neural computation is performed by transforming input signals into sequences of action potentials (APs), which is metabolically expensive and limited by the energy available to the brain. The metabolic efficiency of single AP has important consequences for the computational power of the cell, which is determined by its biophysical properties and morphologies. Here we adopt biophysically-based two-compartment models to investigate how dendrites affect energy efficiency of APs in cortical pyramidal neurons. We measure the Na+ entry during the spike and examine how it is efficiently used for generating AP depolarization. We show that increasing the proportion of dendritic area or coupling conductance between two chambers decreases Na+ entry efficiency of somatic AP. Activating inward Ca2+ current in dendrites results in dendritic spike, which increases AP efficiency. Activating Ca2+-activated outward K+ current in dendrites, however, decreases Na+ entry efficiency. We demonstrate that the active and passive dendrites take effects by altering the overlap between Na+ influx and internal current flowing from soma to dendrite. We explain a fundamental link between dendritic properties and AP efficiency, which is essential to interpret how neural computation consumes metabolic energy and how biophysics and morphologies contribute to such consumption.

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

Cited by 17 publications

References 55 publications

Bayesian modeling of BAC firing as a mechanism for apical amplification in neocortical pyramidal neurons

Bayesian modeling of BAC firing as a mechanism for apical amplification in neocortical pyramidal neurons

A Minimal Biophysical Model of Neocortical Pyramidal Cells: Implications for Frontal Cortex Microcircuitry and Field Potential Generation

Dendritic Properties Control Energy Efficiency of Action Potentials in Cortical Pyramidal Cells

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