Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model

Farinella, Matteo; Ruedt, Daniel T.; Gleeson, Padraig; Lanore, Frédéric; Silver, R. Angus

doi:10.1371/journal.pcbi.1003590

Cited by 32 publications

(43 citation statements)

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“…Previous theoretical studies have predicted that dendritic inhibition in cortical pyramidal neurons could prevent initiation (31) or completely shut down the dendritic plateau potential (30). Here, we provided mechanistic insights on how inhibition interacts with dendritic nonlinearities.…”

Section: Discussionmentioning

confidence: 82%

“…GABAergic SPNs receive perisomatic inhibition mediated by parvalbumin (PV)-positive fast-spiking (FS) interneurons (20)(21)(22), as well as dendritically targeted inhibition from somatostatin (SST)-and neuropeptide Y (NPY)-positive lowthreshold spike (LTS) interneurons (23)(24)(25)(26)(27) and dendritically targeted collateral inhibition from neighboring SPNs (22,28,29). How somatic and dendritic inhibition interacts with nonlinear integration of excitatory inputs in the presence of dendritic plateau potentials remains largely unexplored (30,31).…”

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confidence: 99%

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Cell-type–specific inhibition of the dendritic plateau potential in striatal spiny projection neurons

Lindroos

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Striatal spiny projection neurons (SPNs) receive convergent excitatory synaptic inputs from the cortex and thalamus. Activation of spatially clustered and temporally synchronized excitatory inputs at the distal dendrites could trigger plateau potentials in SPNs. Such supralinear synaptic integration is crucial for dendritic computation. However, how plateau potentials interact with subsequent excitatory and inhibitory synaptic inputs remains unknown. By combining computational simulation, two-photon imaging, optogenetics, and dualcolor uncaging of glutamate and GABA, we demonstrate that plateau potentials can broaden the spatiotemporal window for integrating excitatory inputs and promote spiking. The temporal window of spiking can be delicately controlled by GABAergic inhibition in a celltype-specific manner. This subtle inhibitory control of plateau potential depends on the location and kinetics of the GABAergic inputs and is achieved by the balance between relief and reestablishment of NMDA receptor Mg 2+ block. These findings represent a mechanism for controlling spatiotemporal synaptic integration in SPNs.O ne of the principal functions of neurons is to integrate excitatory and inhibitory synaptic inputs and transform subthreshold membrane potential fluctuations into suprathreshold spiking activities. Both theoretical and experimental works have proposed that a single neuron can process inputs as a multilayer computational device in which individual dendritic branches function as a computational unit and can generate dendritic spikes or plateau potentials (1-4). In vivo studies have demonstrated that dendritic plateau potentials evoked by coincident inputs can amplify excitatory signals and enhance the capacity of learning and information storage at a specific branch (5-7). However, a majority of the understanding of dendritic computation is based on studies focusing on pyramidal cells of hippocampal and cortical areas. It is relatively less known whether these conclusions apply to the striatal neurons (8).The striatum, the main input nucleus of the basal ganglia, receives convergent glutamatergic inputs from the cortex and thalamus (9-11). The integration of these functionally distinct inputs is critical for fine movement control and action selection (12, 13). The principal neurons in the striatum-spiny projection neurons (SPNs)-display hyperpolarized membrane potentials (∼−80 mV) at rest, often referred to as the "down-state" (14, 15). It is generally believed that coherent cortical inputs can effectively depolarize SPNs and promote membrane potential transitions from a hyperpolarized down-state to a depolarized "up-state" (∼−55 mV), at which point action potentials can be generated (14-16). To achieve this ∼20-to 30-mV state transition, it has been estimated that a large number (hundreds to thousands) of active inputs would be required (14-17). Interestingly, striatal SPNs are capable of producing long-lasting plateau potentials following activation of spatially clustered and temporally synchronized excit...

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Section: Discussionmentioning

confidence: 82%

mentioning

confidence: 99%

Cell-type–specific inhibition of the dendritic plateau potential in striatal spiny projection neurons

Lindroos

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…During SPWs, the population activity internally recreates sequential activity patterns experienced earlier during exploratory behavior and theta activity (Foster, 2017). We expected the critical cluster size to be smaller during SPWs than during theta activity, as elevated excitatory activity can facilitate the generation of dendritic spikes (Farinella et al, 2014).…”

Section: Larger Synaptic Clusters Can Lead To Clustering-based Tuningmentioning

confidence: 99%

“…This is substantially less than the 10-20 inputs required to trigger dendritic spikes under in vitro conditions (Mel, 1993;Losonczy & Magee, 2006;Makara & Magee, 2013;Branco & Häusser, 2011) leaving the potential impact of the clusters elusive. The high background activity, characteristic for the in vivo states, can markedly change the integrative properties of the cell (London & Segev, 2001;Destexhe et al, 2003;Ujfalussy et al, 2018), but it is not clear how it influences the effect of functional clustering, ie., whether the facilitation of dendritic spikes (Farinella et al, 2014;Basak & Narayanan, 2018), or other effects, such as saturation (Longordo et al, 2013), shunting (Mel, 1993;Palmer et al, 2012) or increased trial-to-trial variability (Gómez-Laberge et al, 2016) are stronger.…”

Section: Introductionmentioning

confidence: 99%

Impact of functional synapse clusters on neuronal response selectivity

Ujfalussy

Makara

2019

Preprint

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Clustering of functionally similar synapses in dendrites is thought to affect input-output transformation by inducing dendritic nonlinearities. However, neither the in vivo impact of synaptic clusters on somatic membrane potential (sVm), nor the rules of cluster formation are elucidated. We developed a computational approach to measure the effect of functional synaptic clusters on sVm response of biophysical model CA1 and L2/3 pyramidal neurons to behaviorally relevant in vivo-like inputs. Large-scale dendritic spatial inhomogeneities in synaptic tuning properties did influence sVm, but small synaptic clusters appearing randomly with unstructured connectivity did not. With structured connectivity, ∼10-20 synapses per cluster was optimal for clustering-based tuning, but larger responses were achieved by 2-fold potentiation of the same synapses. We further show that without nonlinear amplification of the effect of random clusters, action potential-based, global plasticity rules can not generate functional clustering. Our results suggest that clusters likely form via local synaptic interactions, and have to be moderately large to impact sVm responses.

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“…In both cases, a similar number of excitatory synapses were required for generating a somatic spike with 50% probability, 133 ± 16 (n=6) synapses in the distributed case and 136 ± 38 in the clustered case. However, the clustered case is shallower, implying that in some instances fewer synapses were sufficient for generating a somatic spike (left part of the pink curve in Figure 8A) and in some cases more synapses where required to generate a somatic spike (right part of the pink curve in Figure 8A, see also Farinella et al, 2014). In the former cases, the clustered inputs (with their corresponding prominent NMDA current) were located at proximal branches and in the latter case they were clustered either at distal branched (as in Figures 6 B,C and see also examples in Figure S6A) or in branches with small input resistance, such that the threshold for NMDA spike was not reached.…”

Section: Relatively Small Number Of L2/l3 -L2/l3 Synapses Ignite Somamentioning

confidence: 99%

Human cortical pyramidal neurons: From spines to spikes via models

Eyal

Verhoog²,

Testa-Silva³

et al. 2018

Preprint

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We present the first-ever detailed models of pyramidal cells from human neocortex, including models on their excitatory synapses, dendritic spines, dendritic NMDA-and somatic/axonal-Na + spikes that provided new insights into signal processing and computational capabilities of these principal cells. Six human layer 2 and layer 3 pyramidal cells (HL2/L3 PCs) were modeled, integrating detailed anatomical and physiological data from both fresh and post mortem tissues from human temporal cortex. The models predicted particularly large AMPA-and NMDA-conductances per synaptic contact (0.88 nS and 1.31nS, respectively) and a steep dependence of the NMDA-conductance on voltage. These estimates were based on intracellular recordings from synaptically-connected HL2/L3 pairs, combined with extra-cellular current injections and use of synaptic blockers. A large dataset of high-resolution reconstructed HL2/L3 dendritic spines provided estimates for the EPSPs at the spine head (12.7 ± 4.6 mV), spine base (9.7 ± 5.0 mV) and soma (0.3 ± 0.1 mV), and for the spine neck resistance (50 -80 MΩ). Matching the shape and firing pattern of experimental somatic Na + -spikes provided estimates for the density of the somatic/axonal excitable membrane ion channels, predicting that 134 ± 28 simultaneously activated HL2/L3-HL2/L3 synapses are required for generating (with 50% probability) a somatic Na + spike. Dendritic NMDA spikes were triggered in the model when 20 ± 10 excitatory spinous synapses were simultaneously activated on individual dendritic branches. The particularly large number of basal dendrites in HL2/L3 PCs and the distinctive cable elongation of their terminals imply that ~25 NMDA-spikes could be generated independently and simultaneously in these cells, as compared to ~14 in L2/3 PCs from the rat temporal cortex. These multi-sites nonlinear signals, together with the large (~30,000) excitatory synapses/cell, equip human L2/L3 PCs with enhanced computational capabilities. Our study provides the most comprehensive model of any human neuron to-date demonstrating the biophysical and computational distinctiveness of human cortical neurons.

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Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model

Cited by 32 publications

References 100 publications

Cell-type–specific inhibition of the dendritic plateau potential in striatal spiny projection neurons

Cell-type–specific inhibition of the dendritic plateau potential in striatal spiny projection neurons

Impact of functional synapse clusters on neuronal response selectivity

Human cortical pyramidal neurons: From spines to spikes via models

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