FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2767528263> ?p ?o ?g. }

• W2767528263 endingPage "1561" @default.
• W2767528263 startingPage "1550" @default.
• W2767528263 abstract "•Local dendritic NMDA spike is finely modulated by timed, branch-specific inhibition•Dynamic system analysis explains the vulnerability of the NMDA spike to inhibition•Dendritic, but not spine, inhibition strongly shapes the NMDA-spike-mediated Ca2+ current•Sparse, weak distal inhibition finely sculpts NMDA-mediated output spike bursts The NMDA spike is a long-lasting nonlinear phenomenon initiated locally in the dendritic branches of a variety of cortical neurons. It plays a key role in synaptic plasticity and in single-neuron computations. Combining dynamic system theory and computational approaches, we now explore how the timing of synaptic inhibition affects the NMDA spike and its associated membrane current. When impinging on its early phase, individual inhibitory synapses strongly, but transiently, dampen the NMDA spike; later inhibition prematurely terminates it. A single inhibitory synapse reduces the NMDA-mediated Ca2+ current, a key player in plasticity, by up to 45%. NMDA spikes in distal dendritic branches/spines are longer-lasting and more resilient to inhibition, enhancing synaptic plasticity at these branches. We conclude that NMDA spikes are highly sensitive to dendritic inhibition; sparse weak inhibition can finely tune synaptic plasticity both locally at the dendritic branch level and globally at the level of the neuron’s output. The NMDA spike is a long-lasting nonlinear phenomenon initiated locally in the dendritic branches of a variety of cortical neurons. It plays a key role in synaptic plasticity and in single-neuron computations. Combining dynamic system theory and computational approaches, we now explore how the timing of synaptic inhibition affects the NMDA spike and its associated membrane current. When impinging on its early phase, individual inhibitory synapses strongly, but transiently, dampen the NMDA spike; later inhibition prematurely terminates it. A single inhibitory synapse reduces the NMDA-mediated Ca2+ current, a key player in plasticity, by up to 45%. NMDA spikes in distal dendritic branches/spines are longer-lasting and more resilient to inhibition, enhancing synaptic plasticity at these branches. We conclude that NMDA spikes are highly sensitive to dendritic inhibition; sparse weak inhibition can finely tune synaptic plasticity both locally at the dendritic branch level and globally at the level of the neuron’s output. The possibility that the nonlinear properties of the dendritic membrane might endow dendrites with enhanced computational and plastic capabilities was first suggested more than 50 years ago by Rall and Shepherd, 1968Rall W. Shepherd G.M. Theoretical reconstruction of field potentials and dendrodendritic synaptic interactions in olfactory bulb.J. Neurophysiol. 1968; 6: 884-915Crossref Scopus (508) Google Scholar, Rall et al., 1966Rall W. Shepherd G.M. Reese T.S. Brightman M.W. Dendrodendritic synaptic pathway for inhibition in the olfactory bulb.Exp. Neurol. 1966; 14: 44-56Crossref PubMed Scopus (508) Google Scholar, and Segev and Rall, 1988Segev I. Rall W. Computational study of an excitable dendritic spine.J. Neurophysiol. 1988; 60: 499-523Crossref PubMed Scopus (159) Google Scholar and, more recently, by Mel, 1992Mel B.W. NMDA-based pattern discrimination in a modeled cortical neuron.Neural Comput. 1992; 4: 502-517Crossref Google Scholar, Mel, 1993Mel B.W. Synaptic integration in an excitable dendritic tree.J. Neurophysiol. 1993; 70: 1086-1101Crossref PubMed Scopus (292) Google Scholar, Poirazi and Mel, 2001Poirazi P. Mel B.W. Impact of active dendrites and structural plasticity on the memory capacity of neural tissue.Neuron. 2001; 29: 779-796Abstract Full Text Full Text PDF PubMed Scopus (418) Google Scholar, and Poirazi et al., 2003aPoirazi P. Brannon T. Mel B.W. Pyramidal neuron as two-layer neural network.Neuron. 2003; 37: 989-999Abstract Full Text Full Text PDF PubMed Scopus (463) Google Scholar. Advances in molecular and optical techniques have demonstrated that dendrites are rich in a myriad of nonlinear membrane ion channels (Johnston and Narayanan, 2008Johnston D. Narayanan R. Active dendrites: colorful wings of the mysterious butterflies.Trends Neurosci. 2008; 31: 309-316Abstract Full Text Full Text PDF PubMed Scopus (128) Google Scholar, Magee, 2016Magee J.C. Dendritic voltage-gated ion channels.in: Stuart G. Spruston N. Häusser M. Dendrites. Oxford University Press, 2016: 259-284Crossref Google Scholar) and that these channels are involved in specific plastic, computational, and cognitive processes (Cuntz et al., 2014Cuntz H. Remme M.W.H. Torben-Nielsen B. The Computing Dendrite. Springer, 2014Crossref Google Scholar, Hoffman et al., 1997Hoffman D.A. Magee J.C. Colbert C.M. Johnston D. K+ channel regulation of signal propagation in dendrites of hippocampal pyramidal neurons.Nature. 1997; 387: 869-875Crossref PubMed Scopus (30) Google Scholar, Poirazi et al., 2003bPoirazi P. Brannon T. Mel B.W. Arithmetic of subthreshold synaptic summation in a model CA1 pyramidal cell.Neuron. 2003; 37: 977-987Abstract Full Text Full Text PDF PubMed Scopus (318) Google Scholar). In that respect, of particular interest are the recently discovered Na+, Ca2+, and NMDA dendritic spikes (Golding et al., 2002Golding N.L. Staff N.P. Spruston N. Dendritic spikes as a mechanism for cooperative long-term potentiation.Nature. 2002; 418: 326-331Crossref PubMed Scopus (495) Google Scholar, Larkum et al., 1999Larkum M.E. Zhu J.J. Sakmann B. A new cellular mechanism for coupling inputs arriving at different cortical layers.Nature. 1999; 398: 338-341Crossref PubMed Scopus (777) Google Scholar, Schiller et al., 2000Schiller J. Major G. Koester H.J. Schiller Y. NMDA spikes in basal dendrites of cortical pyramidal neurons.Nature. 2000; 404: 285-289Crossref PubMed Scopus (484) Google Scholar). The latter NMDA spike was shown to be generated locally in multiple apical and basal dendritic branches of both cortical and hippocampal pyramidal neurons (Branco and Häusser, 2011Branco T. Häusser M. Synaptic integration gradients in single cortical pyramidal cell dendrites.Neuron. 2011; 69: 885-892Abstract Full Text Full Text PDF PubMed Scopus (210) Google Scholar, Lavzin et al., 2012Lavzin M. Rapoport S. Polsky A. Garion L. Schiller J. Nonlinear dendritic processing determines angular tuning of barrel cortex neurons in vivo.Nature. 2012; 490: 397-401Crossref PubMed Scopus (174) Google Scholar, Major et al., 2013Major G. Larkum M.E. Schiller J. Active properties of neocortical pyramidal neuron dendrites.Annu. Rev. Neurosci. 2013; 36: 1-24Crossref PubMed Scopus (259) Google Scholar, Milojkovic et al., 2004Milojkovic B.A. Radojicic M.S. Goldman-Rakic P.S. Antic S.D. Burst generation in rat pyramidal neurones by regenerative potentials elicited in a restricted part of the basilar dendritic tree.J. Physiol. 2004; 558: 193-211Crossref PubMed Scopus (51) Google Scholar, Nevian et al., 2007Nevian T. Larkum M.E. Polsky A. Schiller J. Properties of basal dendrites of layer 5 pyramidal neurons: a direct patch-clamp recording study.Nat. Neurosci. 2007; 10: 206-214Crossref PubMed Scopus (292) Google Scholar, Poleg-Polsky, 2015Poleg-Polsky A. Effects of neural morphology and input distribution on synaptic processing by global and focal NMDA-spikes.PLoS ONE. 2015; 10: e0140254Crossref PubMed Scopus (16) Google Scholar, Schiller et al., 2000Schiller J. Major G. Koester H.J. Schiller Y. NMDA spikes in basal dendrites of cortical pyramidal neurons.Nature. 2000; 404: 285-289Crossref PubMed Scopus (484) Google Scholar). It has been shown that dendritic Na+, Ca2+, and NMDA spikes can implement a variety of computational functions, including input pattern classification (Mel, 1992Mel B.W. NMDA-based pattern discrimination in a modeled cortical neuron.Neural Comput. 1992; 4: 502-517Crossref Google Scholar), coincidence detection (Larkum and Nevian, 2008Larkum M.E. Nevian T. Synaptic clustering by dendritic signalling mechanisms.Curr. Opin. Neurobiol. 2008; 18: 321-331Crossref PubMed Scopus (174) Google Scholar, Schiller and Schiller, 2001Schiller J. Schiller Y. NMDA receptor-mediated dendritic spikes and coincident signal amplification.Curr. Opin. Neurobiol. 2001; 11: 343-348Crossref PubMed Scopus (115) Google Scholar), and directional selectivity (Branco et al., 2011Branco T. Clark B.A. Häusser M. Dendritic discrimination of temporal input sequences in cortical neurons.Science. 2011; 329: 1671-1676Crossref Scopus (283) Google Scholar, Smith et al., 2013Smith S.L. Smith I.T. Branco T. Häusser M. Dendritic spikes enhance stimulus selectivity in cortical neurons in vivo.Nature. 2013; 503: 115-120Crossref PubMed Scopus (239) Google Scholar). Importantly, the Ca2+ influx associated with dendritic spikes plays a key role in modulating the plasticity of dendritic synapses (Gambino et al., 2014Gambino F. Pagès S. Kehayas V. Baptista D. Tatti R. Carleton A. Holtmaat A. Sensory-evoked LTP driven by dendritic plateau potentials in vivo.Nature. 2014; 515: 116-119Crossref PubMed Scopus (154) Google Scholar, Gordon et al., 2006Gordon U. Polsky A. Schiller J. Plasticity compartments in basal dendrites of neocortical pyramidal neurons.J. Neurosci. 2006; 26: 12717-12726Crossref PubMed Scopus (131) Google Scholar, Sandler et al., 2016Sandler M. Shulman Y. Schiller J. A novel form of local plasticity in tuft dendrites of neocortical somatosensory layer 5 pyramidal neurons.Neuron. 2016; 90: 1028-1042Abstract Full Text Full Text PDF PubMed Scopus (21) Google Scholar, Villa et al., 2016Villa K.L. Berry K.P. Subramanian J. Cha J.W. Oh W.C. Kwon H.-B. Kubota Y. So P.T.C. Nedivi E. Inhibitory synapses are repeatedly assembled and removed at persistent sites in vivo.Neuron. 2016; 89: 756-769Abstract Full Text Full Text PDF PubMed Scopus (98) Google Scholar). Nonlinear dendritic signals could be effectively modulated by dendritic inhibition. Theoretical studies have shown that a well-located dendritic inhibition, when preceding its respective dendritic/somatic spikes, could either completely abolish these spikes or modulate their amplitude (Gidon and Segev, 2012Gidon A. Segev I. Principles governing the operation of synaptic inhibition in dendrites.Neuron. 2012; 75: 330-341Abstract Full Text Full Text PDF PubMed Scopus (132) Google Scholar, Jadi et al., 2012Jadi M. Polsky A. Schiller J. Mel B.W. Location-dependent effects of inhibition on local spiking in pyramidal neuron dendrites.PLoS Comput. Biol. 2012; 8: e1002550Crossref PubMed Scopus (75) Google Scholar, Rhodes, 2006Rhodes P. The properties and implications of NMDA spikes in neocortical pyramidal cells.J. Neurosci. 2006; 26: 6704-6715Crossref PubMed Scopus (71) Google Scholar). It was recently demonstrated that NMDA spikes, and their resultant somatic bursts of Na+ spikes, are regulated by SOM+ interneurons (Lovett-Barron et al., 2012Lovett-Barron M. Turi G.F. Kaifosh P. Lee P.H. Bolze F. Sun X.-H. Nicoud J.-F. Zemelman B.V. Sternson S.M. Losonczy A. Regulation of neuronal input transformations by tunable dendritic inhibition.Nat. Neurosci. 2012; 15 (S1–S3): 423-430Crossref PubMed Scopus (283) Google Scholar). Müllner et al., 2015Müllner F.E. Wierenga C.J. Bonhoeffer T. Precision of inhibition: dendritic inhibition by individual GABAergic synapses on hippocampal pyramidal cells is confined in space and time.Neuron. 2015; 87: 576-589Abstract Full Text Full Text PDF PubMed Scopus (51) Google Scholar show that a single GABAergic contact can strongly, and locally, reduce the influx of Ca2+ current originating from the backpropagating action potential. These studies show that sparse dendritic inhibition can effectively modulate dendritic excitability and its associated plasticity-inducing signals. It is worth noting in this context that, in both the cerebral cortex and the hippocampus, different classes of inhibitory interneurons target pyramidal neuron dendrites in different dendritic domains (Klausberger, 2009Klausberger T. GABAergic interneurons targeting dendrites of pyramidal cells in the CA1 area of the hippocampus.Eur. J. Neurosci. 2009; 30: 947-957Crossref PubMed Scopus (167) Google Scholar, Markram et al., 2004Markram H. Toledo-Rodriguez M. Wang Y. Gupta A. Silberberg G. Wu C. Interneurons of the neocortical inhibitory system.Nat. Rev. Neurosci. 2004; 5: 793-807Crossref PubMed Scopus (2105) Google Scholar, Stokes et al., 2014Stokes C.C. Teeter C.M. Isaacson J.S. Single dendrite-targeting interneurons generate branch-specific inhibition.Front. Neural Circuits. 2014; 8: 139Crossref PubMed Scopus (11) Google Scholar) and are activated in different behavioral states (e.g., sleep cycles). This raises the interesting possibility that the various types of interneurons might selectively control different nonlinear dendritic signals. For instance, Martinotti cells that mostly target the distal apical tree might selectively control NMDA spikes in distal apical dendrites; basket inhibition might selectively control the Ca2+ generated at the main apical branch of layer 5 (L5) and L2/3 pyramidal cells; and chandelier inhibition (targeting the initial segment of the axon of pyramidal neurons) could selectively control the somatic/axonal Na+ spike (Gidon and Segev, 2012Gidon A. Segev I. Principles governing the operation of synaptic inhibition in dendrites.Neuron. 2012; 75: 330-341Abstract Full Text Full Text PDF PubMed Scopus (132) Google Scholar). Yet little is known about how synaptic inhibition interacts with the NMDA spike after it has been initiated. Because the NMDA spike is long-lasting (Major et al., 2008Major G. Polsky A. Denk W. Schiller J. Tank D.W. Spatiotemporally graded NMDA spike/plateau potentials in basal dendrites of neocortical pyramidal neurons.J. Neurophysiol. 2008; 99: 2584-2601Crossref PubMed Scopus (136) Google Scholar), it is likely that synaptic activity in vivo will bombard the NMDA during its plateau phase particularly because in vivo inhibition is activated at a relatively high frequency and is often activated following excitation (Ma et al., 2010Ma W.P. Liu B.H. Li Y.T. Huang Z.J. Zhang L.I. Tao H.W. Visual representations by cortical somatostatin inhibitory neurons--selective but with weak and delayed responses.J. Neurosci. 2010; 30: 14371-14379Crossref PubMed Scopus (159) Google Scholar, Pouille and Scanziani, 2001Pouille F. Scanziani M. Enforcement of temporal fidelity in pyramidal cells by somatic feed-forward inhibition.Science. 2001; 293: 1159-1163Crossref PubMed Scopus (829) Google Scholar, Silberberg and Markram, 2007Silberberg G. Markram H. Disynaptic inhibition between neocortical pyramidal cells mediated by Martinotti cells.Neuron. 2007; 53: 735-746Abstract Full Text Full Text PDF PubMed Scopus (513) Google Scholar, Wehr and Zador, 2003Wehr M. Zador A.M. Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex.Nature. 2003; 426: 442-446Crossref PubMed Scopus (1001) Google Scholar). How would the NMDA spike react to such timed inhibition? Would it be completely abolished, or would the NMDA spike, and its associated current influx, be finely tuned by such inhibition? We explored these questions by using various models of the NMDA spike, realistic dendritic morphology, and the properties of inhibitory synapses. We applied dynamic system theory combined with computer simulations to explore how inhibition interacts with and affects the dynamics of the NMDA spike. Our results suggest that because of the slow kinetics and unique membrane mechanisms underlying the NMDA spike, it could be sensitively modulated by well-timed local dendritic inhibition. This inhibition may gradually tune both the spiking output of the neuron and the plasticity of synapses at the level of individual dendritic branches and their respective dendritic spines. Figure 1 illustrates the strong impact that timed weak dendritic inhibition can have on the NMDA spike. The modeled NMDA spike was initiated by simultaneously activating 20 excitatory AMPA- and NMDA-based synapses (0.4 nS peak conductance each) impinging on a distal apical branch of a 3D-reconstructed L5 neocortical pyramidal cell. A single GABAA-mediated inhibitory synapse (1 nS peak conductance) located in the center of the excitatory synapses was activated at various times relative to the excitatory synapses. As expected, this rather small inhibitory conductance had a very small effect on the voltage trajectory of the NMDA spike when it preceded excitation. The same weak inhibition generated stronger hyperpolarization when activated at the plateau phase of the NMDA spike, at a delay of Δt = 10 ms after excitation. Surprisingly, the NMDA spike fully recovered to its original trajectory from this hyperpolarization (Figure 1B, blue trace). When inhibition was further delayed (Δt = 20 ms), the NMDA spike was prematurely terminated (Figure 1B, lower right), and the voltage continued to hyperpolarize after the inhibitory input. To quantify this sensitivity of the NMDA spike to timed inhibition riding on its plateau potential, we plotted the time integrals of the NMDA spike normalized to control conditions (without inhibition, dashed traces in Figure 1B) as a function of Δt (Figure 1C). We term this the “vulnerability function” of the NMDA spike to inhibition. The effect of inhibition during the time course of the NMDA spike could be divided into two distinct regimes, which we call the “regeneration” and “termination” phases. In the “regeneration” phase, the NMDA plateau hyperpolarizes because of the inhibition and then fully recovers to its original trajectory at the cessation of inhibition (light blue region in Figure 1C). In this regenerative phase, the time integral of the NMDA spike voltage dropped continuously to up to ∼55% of its original time integral (at about Δt = 15 ms, Figure 1). For later Δt values, the NMDA spike was prematurely terminated by the inhibition (red region in Figure 1C, Δt = 20 ms in Figure 1B). After the NMDA spike entered the “termination” phase, its time integral increased almost linearly with progressively later inhibition. For larger GABAergic conductance, the termination phase started earlier and the time integral of the NMDA spike was further reduced by inhibition (Figure 1D). This two-regime sensitivity of the NMDA spike to timed inhibition was robust across different parameter ranges and across different models of the NMDA receptor current (Figure S1). Next, we examined how the location and activation timing of the inhibitory synapse affect the NMDA spike. As in Figure 1A, the NMDA synapses were placed in the center of the dendritic branch, but the location of the inhibitory GABAA synapse was shifted with respect to the location of the excitatory synapses (Figure 2A). The inhibitory synapse was placed either at 35 μm distal to the center of the dendritic branch, in its center, or 35 μm proximal to it (Figure 2A). The weak inhibitory synapse, when located more distal to the soma relative to the NMDA synapses and activated at Δt = 20 ms, terminated the NMDA spike (red NMDA spike in Figure 2B); inhibition more proximal to the soma hardly affected the NMDA spike (blue NMDA spike in Figure 2B). Furthermore, the timing of the inhibition that maximally affected the time integral of the NMDA spike was earlier for the distal synapse and later (and less effective) for the proximal synapse (Figure 2B, bottom). The vulnerability function deepened significantly when the inhibitory synapse was located either directly at x = 0 or distally to the NMDA synapses, at x = 35 μm (Figure 2C). This finding is consistent with the results of Gidon and Segev, 2012Gidon A. Segev I. Principles governing the operation of synaptic inhibition in dendrites.Neuron. 2012; 75: 330-341Abstract Full Text Full Text PDF PubMed Scopus (132) Google Scholar, who studied the impact of dendritic inhibition on the more global dendritic Ca2+ spike generated at the main branch of the apical dendrite (see also Figure S7). We studied the behavior of the voltage-current (V-I) relationship of the NMDA spike in the presence of synaptic inhibition as a dynamical system, using a single compartment neuron model consisting of leak ion channels and AMPA-, NMDA-, and GABAA-based synapses. As was shown by Jadi et al., 2012Jadi M. Polsky A. Schiller J. Mel B.W. Location-dependent effects of inhibition on local spiking in pyramidal neuron dendrites.PLoS Comput. Biol. 2012; 8: e1002550Crossref PubMed Scopus (75) Google Scholar and Sanders et al., 2013Sanders H. Berends M. Major G. Goldman M.S. Lisman J.E. NMDA and GABAB (KIR) conductances: the “perfect couple” for bistability.J. Neurosci. 2013; 33: 424-429Crossref PubMed Scopus (30) Google Scholar, the NMDA current, when accompanied by the leak current, creates a bistable dynamical system with three fixed points (Figure 3A). At these fixed points, the net membrane current is zero. By perturbing the voltage around the fixed points, the leftmost intersection (“lower stable” in Figure 3A) emerges as a stable fixed point, because a small hyperpolarization from this point will produce an inward current that will result in depolarization back to the fixed point, whereas a small depolarization will produce an outward current that will result in hyperpolarization back to the fixed point (arrows around the blue circle, Figure 3A). Similarly, the rightmost intersection (“upper stable” in Figure 3A) is also a stable fixed point. The middle intersection, however, is an unstable fixed point; a small depolarization will produce an inward current that will further depolarize the membrane and a small hyperpolarization from this point will produce an outward current that will result in further hyperpolarization. This point was thus dubbed the “unstable threshold”; i.e., the critical voltage beyond which, due to depolarization, the membrane voltage will change regeneratively, thus initiating the NMDA spike (Jack et al., 1975Jack J.J.B. Noble D. Tsien R.W. Electric Current Flow in Excitable Cells. Clarendon Press, 1975Google Scholar, Figure 8.11; see also, e.g., Major et al., 2013Major G. Larkum M.E. Schiller J. Active properties of neocortical pyramidal neuron dendrites.Annu. Rev. Neurosci. 2013; 36: 1-24Crossref PubMed Scopus (259) Google Scholar). Because the inward NMDA current changes over time, the fixed points also change over time (Figure 3B). We define the “regenerative” region of the NMDA spike as the regime whereby, following small voltage perturbations (that remain above the middle fixed point), the voltage will converge to the upper fixed point (shaded light red region in Figure 3B). The complementary shaded blue region in Figure 3B was termed the “termination” region of the NMDA spike because a small perturbation of the voltage inside this region will result in further hyperpolarization toward the lower fixed point. Examination of the trajectories of the fixed points shows that during the time course of the NMDA spike, the threshold (the green curve in Figure 3B) is relatively hyperpolarized in the early stages and progressively becomes more depolarized with time. This accounts for the recovery of the NMDA spike in the case of early inhibition and the premature termination of the NMDA spike following later inhibition, since inhibition-induced hyperpolarization that does not cross the threshold in its early hyperpolarized state may still cross the threshold when arriving later in its depolarized state. This behavior is depicted in more detail in Figure 3C, which illustrates the case of early inhibition arriving at Δt = 10 ms following the initiation of the NMDA spike. The three momentary V-I curves (top) and the respective voltage trajectories (bottom) were sampled at t = 9, 15, and 35 ms during the NMDA spike. At t = 9 ms (before inhibition was activated), the NMDA spike was in the regeneration region and was still depolarizing. Following the activation of inhibition, the GABAA current was added to the outward leak current, thus shifting the dashed blue curve (the leak current) to the steeper solid blue line (Figure 3C, top middle frame). At t = 15 ms, the additional inhibitory current gave rise to only a single hyperpolarized intersection point with the red V-I curves resulting in further hyperpolarization of the NMDA spike (Figure 3C, bottom middle frame). This inhibitory current continued to hyperpolarize the NMDA spike transiently, until the GABAA current ended. At later times (e.g., t = 35 ms), the outward current converged back to the leak current (solid and dashed blue lines are superimposed in Figure 3C, top right). In this case, the early inhibition hyperpolarized the NMDA spike voltage to −30 mV (black circle in Figure 3C, middle frames), which was still more depolarized than the threshold (green line in Figure 3C, bottom frames). Consequently, the voltage remained in the “regeneration” region, allowing the NMDA spike to recover back to the upper stable fixed point (Figure 3C, bottom right). In contrast, when the inhibition arrived later, at Δt = 40 ms (Figure 3D), the NMDA spike threshold was more depolarized. In this case, the hyperpolarization due to inhibition crossed the threshold for the NMDA spike (green circle in middle top and green curve in bottom middle of Figure 3D, respectively). The voltage perturbation due to inhibition resided in the “termination” region that further hyperpolarized the NMDA spike until its premature termination. Figure 4 shows that for a fixed NMDA conductance, the NMDA spikes in dendritic branches with large input resistance were longer-lasting and more resilient to GABAA inhibition as compared to branches with small input resistance. In Figure 4A, a long-lasting (61 ms) NMDA spike was generated in a distal apical branch with large input resistance (1,285 MΩ), whereas a briefer (25 ms) spike was generated in an oblique branch with input resistance of 810 MΩ. The former NMDA spike recovered after GABAergic inhibition at Δt = 10 ms, whereas the latter NMDA spike terminated for the same inhibition, suggesting that the NMDA spikes in branches with larger input resistance are longer-lasting and more resilient to inhibition (Figure 4B). We computed the Pearson correlation coefficient between various passive properties of the branch and the critical GABAA conductance required to terminate the NMDA spike (Figure 4C). This critical GABAA conductance was strongly correlated with the input conductance of the dendritic branch; the smaller the input conductance, the larger the GABAA conductance required to terminate the NMDA spike. The critical GABAA conductance was also weakly correlated with the distance of the dendritic branch from the soma (Figure 4C). These results imply that NMDA spike-based plasticity is more likely to take place at distal branches with large input resistance. This result is explained in Figure S3A and the related text. Recent work has shown that the effect of synaptic inhibition is highly localized when it impinges on a dendritic spine together with an excitatory synapse located on the same spine (Chiu et al., 2013Chiu C.Q. Lur G. Morse T.M. Carnevale N.T. Ellis-Davies G.C.R. Higley M.J. Compartmentalization of GABAergic inhibition by dendritic spines.Science. 2013; 340: 759-762Crossref PubMed Scopus (186) Google Scholar, Higley, 2014Higley M.J. Localized GABAergic inhibition of dendritic Ca(2+) signalling.Nat. Rev. Neurosci. 2014; 15: 567-572Crossref PubMed Scopus (57) Google Scholar). How would spine inhibition interact with the NMDA spike when generated by a clustered group of excitatory spine synapses when compared to dendritic inhibition? Figures 5A–5C show shows that when placed on the dendritic branch (as is typically the case), timed inhibition could terminate the NMDA spike at all activated spines (Δt = 30 ms, red trace in Figure 5B). When the same inhibitory synapse was placed at the spine head (Figure 5D), in the case of both high spine neck and dendritic input resistance (∼0.8 and ∼1.9GΩ, respectively), the NMDA spike was not terminated at any of the activated spines for time delays ≤35 ms (Figure 5E). This was true despite the observation that inhibition on the spine head hyperpolarized that spine voltage more than inhibition on the dendrite. In other words, the cooperative NMDA spike, generated collaboratively at all 20 activated spines, protected the NMDA spikes at individual spines from local inhibitory input. Furthermore, the concentration of Ca2+ flowing into the spine head through the NMDA receptors maximally dropped by ∼40% when inhibition impinged on the dendrite (Figure 5C) but only by 30% when the inhibition was located on the spine head (Figure 5F). The vulnerability function for both the NMDA voltage time integral (Figure 5G) and the time integral of the total Ca2+ concentration entering through the NMDA channels (Figure 5H) demonstrate the increased effect of dendritic versus spine inhibition. This has important implications for branch-specific plasticity processes as elaborated on in the Discussion. As shown in Figure S4, for spines with large neck resistance, the local inhibitory shunt at the spine head membrane does not propagate well to the adjacent spines. This implies that the collective NMDA current generated by the adjacent dendritic spines is only weakly affected by inhibition on a single spine. However, this collective NMDA-mediated current does effectively flow from the dendrite into the spine head membrane (in this case the spine base and the spine head are essentially isopotential) (Segev and Rall, 1988Segev I. Rall W. Computational study of an excitable dendritic spine.J. Neurophysiol. 1988; 60: 499-523Crossref PubMed Scopus (159) Google Scholar). In contrast, when inhibition is located directly on the stem dendrite, it shunts more effectively the spine head membrane (A. Gidon and I. Segev, unpublished data), and it also electrically decouples the sp" @default.
• W2767528263 created "2017-11-17" @default.
• W2767528263 creator A5013123926 @default.
• W2767528263 creator A5020058004 @default.
• W2767528263 creator A5025022011 @default.
• W2767528263 creator A5069964239 @default.
• W2767528263 creator A5091722347 @default.
• W2767528263 date "2017-11-01" @default.
• W2767528263 modified "2023-10-14" @default.
• W2767528263 title "Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons" @default.
• W2767528263 cites W1243663029 @default.
• W2767528263 cites W1549050411 @default.
• W2767528263 cites W1575357711 @default.
• W2767528263 cites W1587372183 @default.
• W2767528263 cites W1587725414 @default.
• W2767528263 cites W1645542202 @default.
• W2767528263 cites W1758735213 @default.
• W2767528263 cites W1763296052 @default.
• W2767528263 cites W1940417817 @default.
• W2767528263 cites W1955528861 @default.
• W2767528263 cites W1963750875 @default.
• W2767528263 cites W1967648834 @default.
• W2767528263 cites W1971977136 @default.
• W2767528263 cites W1972759447 @default.
• W2767528263 cites W1974719053 @default.
• W2767528263 cites W1974971758 @default.
• W2767528263 cites W1983372683 @default.
• W2767528263 cites W1987510656 @default.
• W2767528263 cites W1989223014 @default.
• W2767528263 cites W1991762922 @default.
• W2767528263 cites W1996456984 @default.
• W2767528263 cites W1997662501 @default.
• W2767528263 cites W2000509838 @default.
• W2767528263 cites W2020587316 @default.
• W2767528263 cites W2025603247 @default.
• W2767528263 cites W2031903132 @default.
• W2767528263 cites W2035774707 @default.
• W2767528263 cites W2036021747 @default.
• W2767528263 cites W2040319898 @default.
• W2767528263 cites W2040841203 @default.
• W2767528263 cites W2040943946 @default.
• W2767528263 cites W2047878451 @default.
• W2767528263 cites W2048962026 @default.
• W2767528263 cites W2057613746 @default.
• W2767528263 cites W2061960110 @default.
• W2767528263 cites W2065469428 @default.
• W2767528263 cites W2067501282 @default.
• W2767528263 cites W2072230901 @default.
• W2767528263 cites W2077040167 @default.
• W2767528263 cites W2084100886 @default.
• W2767528263 cites W2088955805 @default.
• W2767528263 cites W2091984887 @default.
• W2767528263 cites W2100061696 @default.
• W2767528263 cites W2106700142 @default.
• W2767528263 cites W2110016065 @default.
• W2767528263 cites W2130832907 @default.
• W2767528263 cites W2133340863 @default.
• W2767528263 cites W2141964964 @default.
• W2767528263 cites W2145935269 @default.
• W2767528263 cites W2146368230 @default.
• W2767528263 cites W2150753693 @default.
• W2767528263 cites W2152781875 @default.
• W2767528263 cites W2153436148 @default.
• W2767528263 cites W2154045630 @default.
• W2767528263 cites W2156222687 @default.
• W2767528263 cites W2159381912 @default.
• W2767528263 cites W2161432648 @default.
• W2767528263 cites W2164274277 @default.
• W2767528263 cites W2164649534 @default.
• W2767528263 cites W2168025484 @default.
• W2767528263 cites W2287764147 @default.
• W2767528263 cites W2310174140 @default.
• W2767528263 cites W2405724708 @default.
• W2767528263 cites W2423540713 @default.
• W2767528263 cites W2555072090 @default.
• W2767528263 cites W2736039329 @default.
• W2767528263 cites W2747517156 @default.
• W2767528263 doi "https://doi.org/10.1016/j.celrep.2017.10.035" @default.
• W2767528263 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29117560" @default.
• W2767528263 hasPublicationYear "2017" @default.
• W2767528263 type Work @default.
• W2767528263 sameAs 2767528263 @default.
• W2767528263 citedByCount "59" @default.
• W2767528263 countsByYear W27675282632018 @default.
• W2767528263 countsByYear W27675282632019 @default.
• W2767528263 countsByYear W27675282632020 @default.
• W2767528263 countsByYear W27675282632021 @default.
• W2767528263 countsByYear W27675282632022 @default.
• W2767528263 countsByYear W27675282632023 @default.
• W2767528263 crossrefType "journal-article" @default.
• W2767528263 hasAuthorship W2767528263A5013123926 @default.
• W2767528263 hasAuthorship W2767528263A5020058004 @default.
• W2767528263 hasAuthorship W2767528263A5025022011 @default.
• W2767528263 hasAuthorship W2767528263A5069964239 @default.
• W2767528263 hasAuthorship W2767528263A5091722347 @default.
• W2767528263 hasBestOaLocation W27675282631 @default.
• W2767528263 hasConcept C169760540 @default.
• W2767528263 hasConcept C170493617 @default.

• next