Abstract
The CA1 pyramidal neurons are embedded in an intricate local circuitry that contains a variety of interneurons. The roles these interneurons play in the regulation of the excitatory synaptic plasticity remains largely understudied. Recent experiments showed that recurring cholinergic activation of α7 nACh receptors expressed in oriens-lacunosum-moleculare (OLMα2) interneurons can directly induce LTP in Schaffer collateral (SC)–CA1 synapses. Here, we pair in vitro studies with biophysically based modeling to uncover the underlying mechanisms. According to our model, α7 nAChR activation increases OLM GABAergic activity. This results in the inhibition of the fast-spiking interneurons that provide feedforward inhibition onto CA1 pyramidal neurons. This disinhibition, paired with tightly timed SC stimulation, can induce potentiation at the excitatory synapses of CA1 pyramidal neurons. Our work details the role of cholinergic modulation in disinhibition-induced hippocampal plasticity. It relates the timing of cholinergic pairing found experimentally in previous studies with the timing between disinhibition and hippocampal stimulation necessary to induce potentiation and suggests the dynamics of the involved interneurons plays a crucial role in determining this timing.
Significance Statement
We use a combination of experiments and mechanistic modeling to uncover the key role for cholinergic neuromodulation of feedforward disinhibitory circuits in regulating hippocampal plasticity. We found that cholinergic activation of α7 nAChR expressed in oriens-lacunosum-moleculare interneurons, when tightly paired with stimulation of the Schaffer collaterals, can cancel feedforward inhibition onto CA1 pyramidal cells, enabling the potentiation of the SC–CA1 synapse. Our work details how cholinergic action on GABAergic interneurons can tightly regulate the excitability and plasticity of the hippocampal network, unraveling the intricate interplay of the hierarchal inhibitory circuitry and cholinergic neuromodulation as a mechanism for hippocampal plasticity.
Introduction
The hippocampal networks are characterized by a variety of locally connected GABAergic interneurons exerting robust control on network excitability. Previous work has detailed the importance of inhibitory inputs in modulating local hippocampal synaptic plasticity (Wigström and Gustafsson, 1985; Meredith et al., 2003; Chevalerye and Piskorowski, 2014; Saudargienė and Graham, 2015). Furthermore, several experimental studies show that disinhibition facilitates the induction of long-term potentiation (LTP) at excitatory synapses (Ormond and Woodin, 2009; Yang et al., 2016). However, how the disinhibition controlling hippocampal excitatory synapses is modulated (e.g., by neuromodulators) is not clearly understood, and the precise circuitry and its dynamics underlying this type of plasticity remains an open question.
GABAergic interneurons receive significant cholinergic innervation from the medial septum. They are endowed with various subtypes of nicotinic ACh receptors (nAChRs) that regulate excitability, plasticity, and cognitive functions (Pitler and Alger, 1992; Behrends and Ten Bruggencate, 1993; Hasselmo et al., 1995; Alkondon et al., 1997; Patil et al., 1998; McQuiston and Madison, 1999; Patil and Hasselmo, 1999; Levin, 2002; Hasselmo, 2006; Parikh et al., 2007; Bell et al., 2011, 2015; Griguoli and Cherubini, 2012; Yakel, 2012; Desikan et al., 2018; Nicholson and Kullmann, 2021). Moreover, alterations of cholinergic action on hippocampal GABAergic interneurons have been implicated in cognitive dysfunction in Alzheimer’s disease (AD; Schmid, et al., 2016). These studies, among others, furnish clear evidence that cholinergic inputs exert a powerful role in regulating hippocampal activity. Still, because of the abundance of cholinergic receptors (both muscarinic and nicotinic) and the complexity of the networks in which they are embedded, it is difficult to access the exact mechanisms through which cholinergic action on the hippocampus modulates its microcircuits.
Previous studies showed that activation of α7 nACh receptors expressed in oriens-lacunosum-moleculare (OLMα2) interneurons increases Schaffer collateral (SC)–CA1 transmission and suggest that this happens through disinhibition by reducing the activity of stratum radiatum (s.r.) interneurons that in turn provide feedforward inhibition onto pyramidal (PYR) neurons (Leão et al., 2012). Consistent with these studies, Gu et al. (2020) found that repeated coactivation of α7 nAChR on OLMα2 interneurons and a local SC pathway increased CA1 EPSCs and reduced IPSCs. However, the mechanisms through which the activation of the OLMα2 interneurons regulates the activity of inhibitory interneurons targeting the CA1 pyramidal cell, and how this facilitates the increase of SC-evoked EPSPs of the CA1 pyramidal cells remain elusive.
In the CA1 region, α7 nAChR can be found on both presynaptic and postsynaptic sites of GABAergic synapses (Fabian-Fine, 2001). For this reason, the outcome of α7 nAChR activation and how it modulates OLMα2 interneuron activity is difficult to address. Activation of postsynaptic α7 nAChRs could increase the spiking frequency of OLMα2 interneurons, although, to our knowledge, OLMα2 spiking by nAChRs has not been clearly characterized, while presynaptic α7 nAChRs regulate the release of neurotransmitter by activating calcium-dependent pathways that lead to the fusion of neurotransmitter vesicles with the membrane of the neuron (Desikan et al., 2018).
In this work, we use a minimal biophysical circuit model, driven quantitatively by in vitro data, to show how modulation of OLM cells (O-cells) influences the activity of fast-spiking interneurons whose GABAergic inputs are colocalized with the SC glutamatergic synapses onto a CA1 pyramidal cell dendrite, and how this promotes the induction of plasticity at the SC–CA1 synapse. We seek to determine how cholinergic activation of the OLM cells through presynaptic α7 nAChRs can downregulate the GABAergic signaling onto the pyramidal cells, and how recurrent decreased inhibitory inputs can indirectly enhance the plasticity of the excitatory SC–CA1 synapse. We thus constructed a minimal circuit consisting of a single compartment spiking model of an OLM interneuron (O-cell) with α7 nAChRs, a fast-spiking interneuron (I-cell) with AMPA and GABAA receptors, and a pyramidal cell dendritic compartment (ED) with AMPA, NMDA, and GABAA receptors. They are connected as schematically shown in Figure 1.
Disynaptic disinhibition circuit for nAChR-modulated long-term plasticity in the CA1. A, Simplified wiring diagram of an interneuron network that mediates feedforward inhibition in the CA1 region of the hippocampus. Activation of the SC pathway leads to the activation of CA1 pyramidal cell dendrites and s.r. interneurons, which provide feedforward inhibition onto the pyramidal cell. Cholinergic activation of OLMα2 interneurons in s.o. leads to the inhibition of the s.r. interneurons, counteracting SC feedforward inhibition (Leão et al., 2012). B, Minimal network to investigate plasticity induced by the pairing of cholinergic and SC activation. Glutamate activates postsynaptic AMPARs and NMDARs at the pyramidal cell ED and postsynaptic AMPARs at I-cells, which in turn provide feedforward inhibition onto ED by activating postsynaptic GABAARs. Cholinergic inputs act on presynaptic α7 nAChRs of O-cells, which results in GABA release of the O-cells that it is going to bind to postsynaptic GABAARs of the I-cell.
Overwhelming evidence suggests that most types of LTP involve calcium influx through NMDARs and subsequent changes in the properties of postsynaptic AMPA receptors (AMPARs), namely changes in their number and phosphorylation state (Collingridge et al., 1983; Barria et al., 1997; Lüscher and Malenka, 2012). To reflect these mechanisms, we use the calcium-based synaptic plasticity model (proposed by Shouval et al., 2002) to model synaptic plasticity of the SC–CA1 excitatory synapse.
In this study, we use a combination of experiments with computational modeling to put together a coherent picture of the multiple mechanisms through which concurrent disinhibition directly induces local SC–CA1 plasticity. More specifically, we show how repeated concurrent disinhibition induces LTP by mediating AMPAR trafficking. Our modeling results also put together all the pieces of the puzzle to lay out how nAChR cholinergic action on OLM interneurons, working through calcium-dependent regulation of GABA neurotransmission, can downregulate the GABAergic signaling onto CA1 pyramidal cells and induce potentiation of the SC–CA1 synapse.
Materials and Methods
Animals and materials
All procedures related to the use of mice followed protocols approved by the Institutional Animal Care and Use Committees of the NIEHS. ChAT-cre mice [B6;129S6-Chattm2(cre)Lowl/J], Sst-cre mice [Ssttm2.1(cre)Zjh], and floxed α7 nAChR knock-out mice [B6(Cg)-Chrna7tm1.1Ehs/YakelJ] were originally purchased from The Jackson Laboratory and then bred at the National Institute of Environmental Health Sciences (NIEHS). OLMα2-cre mice [Tg(Chrna2cre)OE29Gsat/Mmucd] were originally obtained from Mutant Mouse Resource and Research Centers and then bred at NIEHS. Mice (of either sex) were used for slice culture from day 6 to 8.
Culture media were from Sigma-Aldrich and Thermo Fisher Scientific. Adeno-associated virus (AAV) serotype 9 helper plasmid was obtained from James Wilson (University of Pennsylvania, Philadelphia, PA). The AAV vector containing floxed ChR2 (catalog #20297, Addgene) and floxed enhanced NpHR (eNpHR; catalog #26966, Addgene) were obtained from Karl Deisseroth (Stanford University, Palo Alto, CA; Gradinaru et al., 2010; Witten et al., 2010). AAV viruses were packaged with serotype 9 helper at the Viral Vector Core facility at the NIEHS.
Brain slice culture and AAV infection
To study the effects of cholinergic coactivation on the plasticity of SC–CA1 synapses (Fig. 2C,E), coronal septal slices (350 μm) from ChAT-cre mice and horizontal hippocampal slices from floxed α7 nAChR mice or OLMα2-cre/floxed α7 nAChR mice (350 μm) were cut with a vibratome (model VT1000S, Leica). Medial septal tissue containing cholinergic neurons was then dissected out and placed next to the hippocampus on a six-well polyester Transwell insert (Corning) and cultured there for ∼2 weeks before being used for experiments, similar to those previously described (Gu and Yakel, 2017). AAVs containing a double-floxed ChR2 construct (5 nl) were microinjected to the septal tissue with a microinjector (Drummond Scientific) on the second day of culture. To study the effects of disinhibition on the plasticity of SC–CA1 synapses (see Fig. 4C), horizontal hippocampal slices from Sst-cre mice were cultured and AAVs containing double-floxed eNpHR construct were microinjected to the hippocampus the next day.
Cholinergic activation of OLM interneurons potentiates SC-evoked EPSCs. A, Scheme of in vitro induction of cholinergic pairing-induced hippocampal synaptic plasticity. EPSCs were recorded from CA1 pyramidal neurons. Cholinergic neurons were activated via channelrhodopsin-2 that was specifically expressed in ChAT-positive neurons. The SC pathway was activated by a stimulating electrode. Adapted from the study by Gu et al. (2017). B, Scheme of the minimal network used to study the role of cholinergic inputs in the potentiation of SC-evoked EPSCs. Glutamatergic inputs activate the pyramidal cell ED and the fast-spiking I-cell that projects to it. Square pulses of ACh activate the O-cell during the copairing period. The neural response of O-cell, I-cell, and ED when the system receives one pulse of glutamate paired or not with ACh is shown in Extended Data Figure 2-1. The release of GABA from the O-cells is calculated using the simplified model described by Equation 16. The Extended Data Figure 2-2 shows that the simplified neurotransmitter release model results in a similar synaptic activation function as the detailed model described in the study by Destexhe et al. (1998). Different ACh synaptic profiles are explored in Extended Data Figure 2-3. C, Normalized SC-evoked EPSC responses from CA1 pyramidal neurons showing that the enhancement of EPSCs was impaired in hippocampal slices from mice with selective α7 nAChR knockout in OLMα2 interneurons. Adapted from the study by Gu et al. (2020). D, Numerical simulation of normalized EPSC amplitude when glutamatergic inputs acting on the I-cell and ED are paired with cholinergic inputs acting on the O-cell (from t = 10 min to t = 18 min). The EPSCs are calculated as the sum of postsynaptic AMPA and NMDA currents, IAMPA and INMDA, resulting from 10 simulations with white noise on the ED membrane potential. Noisy membrane potentials of the O-cells and I-cells that induce spontaneous spiking are considered in Extended Data Figure 2-4. Normalization of the results was calculated according with the expression (100 + (EPSC – EPSCmin) · (150–100))/(EPSCmax – EPSCmin). Inset, Concentration of GABA released from fast-spiking interneurons (I), calculated according to Equation 15 (see Materials and Methods). E, Normalized SC-evoked EPSC responses from CA1 pyramidal neurons showing that enhancement of EPSCs during a copairing period of 5 min. F, Numerical simulation of normalized EPSC amplitude when glutamatergic inputs acting on the I-cell and ED are paired with cholinergic inputs acting on the O-cell (from t = 10 min to t = 15 min).
Figure 2-1
A, Before copairing, the α7 nAChR at OLM is not activated, and the OLM cell is not depolarized (dashed line). During copairing, OLM receives a square pulse of ACh with an amplitude of 1 mm and 5 ms of duration (solid line). The OLM is weakly depolarized (solid line). B, Before copairing, there are no changes in the intracellular calcium concentration Cai (dashed line). During copairing, calcium through α7 nAChR triggers CICR mechanisms that increase the intracellular calcium concentration of the O-cell (solid line). C, An increase in intracellular calcium results in GABA release from the O-cell (GABAO). The neurotransmitter concentration is calculated according to the simplified model (solid line). D, The release of GABAO during copairing suppresses spiking of the I-cell evoked by glutamatergic activation (solid line). E, Before copairing, the spiking of the I-cell is not suppressed and inhibits ED, which cannot depolarize a lot (dashed line). During copairing, ED does not receive inhibition, only excitation from glutamatergic stimulation, and it depolarizes (solid line). Download Figure 2-1, TIF file.
Figure 2-2
Simplified neurotransmitter release model. A, Square calcium pulse of 0.10 μm amplitude and 1 ms of duration. B, GABA concentration elicited by a calcium pulse of 0.10 μm amplitude and 1 ms of duration computed using the detailed model of transmitter release described in the study by Destexhe et al. (1998) and using Equation 16. C, Both models of GABA concentration elicit similar synaptic activation functions, rG (described by Eq. 14 with αG = 5 ms/m and βG = 0.18 ms). Download Figure 2-2, TIF file.
Figure 2-3
Not much is known about the ACh profile in the synaptic cleft upon release from cholinergic neurons; more specifically, not much is known about the time it takes for ACh to be broken down by the cholinesterase and therefore, how long it is available to bind to the cholinergic receptors. We consider the observations made by Gu and Yakel (2011) that pairing cholinergic inputs 10 ms prior to SC stimulation induces depression of the SC–CA1 synapse, while if the cholinergic inputs are activated 100 ms prior to SC stimulation, potentiation is induced. A–D, A square pulse of ACh followed by a pulse of glutamate 10 and 100 ms after will induce, respectively, depression or potentiation if the duration of the ACh pulse is equal or greater than the glutamate. E–H, If ACh is described by an α function with an instantaneous rise time; the smaller the amplitude of the ACh pulse, the longer the decay time needs to be for the results to agree with those in the study by Gu and Yakel (2011). That being said, we model ACh as a square pulse with a duration of 5 ms and concentration of 1 mm, similar to glutamate. Please note that the decay and duration times, as well as the amplitude, of both the ACh and glutamate pulses serve merely as a guide to what types of neurotransmitter profiles we should consider. They are qualitative, and not quantitative, predictions of the synaptic profile of ACh. Copairing of one pulse of ACh (with different synaptic profiles) with one square pulse of glutamate (with a duration of 5 ms and amplitude of 1 mm) for a relative pairing time Δt of 10 and 100 ms. A, Left, One square pulse of ACh with a duration of 1 ms and concentration of 0.5 mm followed 10 ms after by a square pulse of glutamate produces no changes in the maximal conductance of AMPAR,
Figure 2-4
A, Time evolution of the membrane potential of the O-cell, I-cell, and ED with noisy background currents when cholinergic inputs are paired with SC inputs, and resultant EPSCs. B, Mean trace of normalized EPSCs after 10 simulations. Adding a noisy background current to the O-cell and I-cell induces spontaneous spiking. Copairing cholinergic and glutamatergic inputs from t = 10 min to t = 18 min induces potentiation of the pyramidal cell EPSC. The O-cell releases GABA when the intracellular calcium concentration is high enough (Eq. 16) and when the cell spikes (Eq. 15). All the remaining parameters are identical to the ones used to produce Figure 6. Noise was incorporated by adding a stochastic term
Whole-cell patch-clamp recordings
SC–CA1 EPSCs were recorded from hippocampal CA1 pyramidal neurons under whole-cell patch clamp, similar to recordings described in the studies by Gu and Yakel (2011, 2017). Briefly, 2–3 weeks after culturing, the slices were removed from transwell inserts and put into a submerged chamber, continuously perfused with 95% O2/5% CO2 balanced ACSF (in mm: 122 NaCl, 2.5 KCl, 2 MgCl2, 2 CaCl2, 1.2 NaH2PO4, 25 NaHCO3, and 25 glucose) at room temperature. EPSCs were recorded at −60 mV under voltage clamp through a glass pipette filled with an internal solution (in mm: 130 potassium gluconate, 2 MgCl2, 3 MgATP, 0.3 Na2GTP, 10 KCl, 10 HEPES, and 1 EGTA) at pH ∼7.2–7.3 and osmolarity of ∼280–290 mOsm. Whole-cell patch-clamp recordings were performed with a Multiclamp 700B amplifier (Molecular Devices). Data were digitized with an analog-to-digital signal converter (Digidata 1550) and collected with Clampex. The amplitudes of EPSCs were analyzed with Clampfit, and graphs were drawn with Excel. The amplitudes were normalized to the mean of the 10 min baseline recording before cholinergic pairing or disinhibition pairing. Values were presented as the mean ± SEM.
EPSCs were evoked every 60 s by stimulating the SC pathway with an electrode placed in the stratum radiatum through a stimulator (model S88X, Grass). The stimulation intensity was 1–10 μA for 0.1 ms. To study the effects of cholinergic coactivation on SC–CA1 synaptic plasticity (Fig. 2C,E), cholinergic terminals in the hippocampus were optogenetically activated (10 pulses at 10 Hz, 1 s before SC stimulation) through ChR2 that was selectively expressed in ChAT-cre-positive (cholinergic) neurons. ChR2 was activated with 488 nm laser light (5 mW, 20 ms) through a 40× objective over CA1 stratum oriens (s.o.) near the septum with an spinning disk confocal microscope (Andor Technology). To examine the effects of disinhibition on SC–CA1 synaptic plasticity (see Fig. 4C), somatostatin (Sst)-positive neurons were inhibited optogenetically through eNpHR which was activated through a 40× objective over CA1 stratum oriens with 530 nm laser light (20 mW) for 1 s flanking SC stimulation.
The amplitudes of EPSCs were analyzed with Clampfit, and graphs were drawn with Excel. The amplitudes were normalized to the mean of the 5 min baseline recording before cholinergic pairing or disinhibition pairing. Values were presented as the mean ± SEM EPSC amplitudes at 5 and 30 min after pairing were compared with the amplitude at 5 min before pairing. The effect at 5 min after pairing was considered to be a short-term effect, and the effect at 30 min after pairing was considered to be a long-term effect. Recordings were performed in five slices from three individual mice in each group. Statistical significance was tested by Student’s t test. The sample size was estimated by Student’s t test with an expected effect of 40% change, an expected SD of 15%, and an 80% confidence interval width.
Model
The minimal network used in this study consists of an O-cell, a fast-spiking I-cell, and a pyramidal cell. All the cells in the network are modeled as point neurons. Since we are interested in the local changes at the SC–CA1 synapse, the pyramidal cell is represented by a dendritic compartment (ED). The cells of the network are connected through feedforward connections. Although recurrent connections from the CA1 pyramidal cell and the fast-spiking interneurons may exist, adding this connection did not change our results. Adding connections between the CA1 pyramidal cell and the OLM interneuron also did not significantly alter our results. Therefore, we did not include synapses between the CA1 pyramidal and the OLM cells in our model. Our modeling choice is further supported by experimental studies showing that the IPSC elicited by an OLM interneuron has a small amplitude at the soma of CA1 pyramidal cells since these synapses are on the distal parts of the dendritic tree (Maccaferri, et al., 2000), and that an action potential in CA1 pyramidal cells is insufficient to make the OLM cell membrane potential (Vm) cross the action potential threshold (Ali et al., 1998; Müller and Remy, 2014). Although repeated firing of CA1 pyramidal cells with theta frequency can facilitate excitatory inputs onto OLM, a theta activation protocol of the CA1 cell is beyond the scope of this article.
Neuron dynamics models
The O-cells and I-cells are modeled following the Hodgkin–Huxley formalism [Hodgkin and Huxley, 1952; transient (INa), delayed rectifier potassium (IK), and leak (Ileak)], with synaptic currents (Isyn). Its Vm is described as follows:
Following Rotstein et al. (2005), we included an applied current (Iapp) = −260 pA, a persistent Na current (Ip), and a hyperpolarization-activated inward current (Ih; with a slow and fast component) on the O-cells, as follows:
While the gate variable p obeys Equation 5, hf and hs are described by the following equation:
For the O-cells:
For the I-cells:
The parameter values used in the simulations are the ones presented in Table 1.
Parameters of pyramidal cell, OLM interneuron, and fast-spiking interneuron dynamics
Since we are interested in studying local synaptic changes of the SC–CA1 synapse, we use the following equation to describe the activity of the pyramidal cell dendritic compartment:
The parameters C, gleak, and Eleak were set to 100 pF, 1 nS, and −68 mV, respectively.
For the simulations presented in Figure 2D, noise was added to the dendritic compartment ED to allow direct comparison with the experimental results portrait in Figure 2C. In addition to ED, white noise was added to the O-cells and I-cells to study plasticity induction when these cells show spontaneous spiking (Extended Data Figs. 2-1, 2-2, 2-3, 3-1, 3-2, 4-1). Since we used the Euler method to solve the differential equations describing VO, VI, and VED, (
Synaptic models
The O-cell model includes a current mediated by α7 nAChR channels, which in the real OLM neurons are presynaptic to the O-cell to I-cell synapse. The description of the current used is an adaptation of the model proposed in the study by Graupner et al. (2013), and it is given by the following equation:
The I-cell has excitatory AMPA and inhibitory GABAA synaptic currents, described by the following set of equations:
The gating variable rx is, as described in the study by Destexhe et al. (1998), given by the following:
The GABA released by the I-cell is described by using the Destexhe et al. (1998) simplified neurotransmitter release model. The intervening reactions in the release process are considered to be fast: a presynaptic action potential elicits a rapid influx of calcium, leading to the activation of transmitter-containing vesicles and neurotransmitter release. A stationary relationship between presynaptic voltage and neurotransmitter release is deduced by fitting the model to experimental results. The following equation gives the neurotransmitter release as a function of the presynaptic voltage:
Spiking of the OLM cells directly because of the nAChR activation has not been clearly characterized. Experimentally measured nicotinic responses of OLM cells are small (Leão et al., 2012), and, although they may modulate the firing rate of the neuron, it is unlikely they are causing spiking on their own (Fig. 2D). For that reason, we consider that GABA release by the O-cell results from the activation of presynaptic α7 nAChR on O–I GABAergic synapses.
Experimental studies revealed that the activation of α7 nAChRs trigger intracellular calcium rise and calcium-dependent signaling pathways—in particular calcium-induced calcium release (CICR) from intracellular stores—that enhance the release of neurotransmitter at presynaptic terminals (Tsuneki et al., 2000; Dajas-Bailador et al., 2002; Griguoli and Cherubini, 2012). To avoid the detailed computation of the mechanisms whereby calcium leads to exocytosis, we assume a sigmoid relationship between intracellular calcium and transmitter concentration given by the following:
The passive dendritic compartment of the pyramidal cell ED is modeled using synaptic GABAA, AMPA, and NMDA currents. The GABAA and AMPA currents are given by Equations 12 and 13, respectively. The following equation describes the NMDA current:
The parameters αA, βA, EA, αN, βN, EN, [Mg2+], αG, βG, and EG were estimated by Destexhe et al. (1998) by fitting the models of postsynaptic AMPA, NMDA and GABAA currents to experimental data. Regarding the synaptic currents of ED, the maximal conductances of AMPA and NMDA receptors were chosen such that at V = −70 mV, a glutamate pulse of 1 mm and 10 ms duration evoked AMPA and NMDA currents with amplitudes of 240 and 40 pA, respectively (Andrásfalvy et al., 2003). The maximal conductance of GABAA receptors was chosen such that at V = 0 mV a pulse of GABA with 1 ms duration and a concentration of 1 mm evokes a current with an amplitude of 500 pA (Schulz et al., 2018). For the I-cell, the AMPA receptor maximal conductance value is such that one pulse of glutamate coming from the SC evokes a volley of action potentials. Concerning the α7 nAChR postsynaptic current, the parameters EC50, τrα7, and n were taken from the study by Graupner et al. (2013), where the kinetics of α7 nAChR is described. The parameter Eα7 was deduced from the study by Castro and Albuquerque (1995), and gα7 was chosen such that activation of the α7 nAChR by a pulse of ACh evokes a current of 35 pA (Leão et al., 2012). The values of the parameters can be found in Table 2.
Parameter values of synaptic currents IAMPA, INMDA, IGABAA, and Iα7
CICR mechanism
Calcium entry through α7 nAChRs initiates calcium release from internal stores (Tsuneki et al., 2000; Dajas-Bailador et al., 2002; Griguoli and Cherubini, 2012). The calcium concentration in the cytosol of OLM cells (Cai) is described by the following equation:
Model of synaptic plasticity
To study plasticity induction at the SC–ED synapse, we use a calcium-based synaptic plasticity model based on the study by Shouval et al. (2002). We assume that changes in the AMPA receptor conductance reflect changes in the strength of the excitatory SC–CA1 synapse. Our synaptic plasticity model is formulated as follows:
The parameters θ↑ and θ↓ define the potentiation and depression onset (i.e., the calcium levels that trigger the removal and insertion of AMPAR in the membrane, respectively), and
We assume that the primary source of Ca2+ in ED is the calcium flux entering the cell through the NMDA receptor channels. The intracellular Ca2+ concentration evolves according to the following equation:
Stimulation protocol
ACh–SC pairing
We constructed a minimal feedforward circuit with an O-cell, a fast-spiking I-cell, and the pyramidal cell s.r. ED connected, as schematically shown in Figure 2B, to examine mechanistically how pairing cholinergic activation of the O-cell with glutamatergic activation of the I-cell and ED can potentiate the EPSCs of ED. We look at how the EPSC of ED, modeled as the sum of the postsynaptic AMPA current (IAMPA) and NMDA current (INMDA), changes when the glutamatergic inputs acting on the I-cell and ED are paired with the cholinergic inputs that act on the presynaptic α7 nAChR of the O-cell during a copairing period of 5 and 8 min, identical to the experimental protocol. The I-cell and ED receive one glutamate pulse per minute before, during, and after the copairing period. During the copairing period, the O-cell gets a pulse of ACh per minute, 100 ms before each glutamate pulse (Δt = 100 ms). Not much is known about the concentration profile of ACh in vivo, but it is believed that it can be cleared from the synaptic cleft within milliseconds. After testing different ACh profiles, we decided to model ACh as a square pulse with a duration of 5 ms and concentration of 1 mm, similar to glutamate, although similar results were obtained for a variety of profiles of ACh (Extended Data Fig. 2-3, for more details).
We explore the copairing temporal parameters that regulate plasticity by fixing the frequency of stimulations at 1 pulse/min while varying the copairing period tpair (Figs. 2, 3A, results). We also study how the frequency of stimulation modulates synaptic plasticity by fixing tpair at 4 min while changing the frequency of copaired stimulation (Fig. 3B). Finally, we consider different pairing times of ACh and glutamate (Δt; Fig. 3C,D).
Copairing temporal parameters determines the duration and polarity of synaptic plasticity: relative timing among cholinergic and glutamatergic stimulation, the extent of the copairing period, and the frequency of stimulation (model results). A, Synaptic strength transient duration is proportional to the extent of the pairing period. Here, the transient duration is defined as the time it takes the EPSC to go back to baseline after copairing is over. The I-cell and ED receive a pulse of glutamate per minute. During the copairing period, the O-cell receives a pulse of ACh per minute, 100 ms before the glutamate pulses. B, Synaptic strength transient duration is proportional to the ACh and glutamate pulses frequency during the copairing period. Before and after the copairing period, the I-cell and ED receive a pulse of glutamate per minute. During the copairing period (4 min), the frequency changes to 1/20, 1/60, or 1/30 s, and the O-cell receives a pulse of ACh 100 ms before the glutamate pulses with the same frequency. C, Relative pairing timing of single pulses provides a window of opportunity for plasticity. If glutamatergic inputs are administered within 10.4 ms < Δt < 131.1 ms, the ED excitatory synapse is potentiated. If glutamatergic inputs are administered within −19.9 ms < Δt < 10.4 ms or 10.4 ms < Δt < 131.1 ms, depression is induced. The change in the AMPAR conductance Δ
Figure 3-1
Tightly timed pairing of cholinergic to glutamatergic inputs can cancel the I-cell feedforward inhibition. For Δt = –30 ms (Region I), a pulse of glutamate activates the I-cell. When the OLM cell receives a pulse of ACh 30 ms after and releases GABA, the I-cell already emitted two spikes and inhibit ED, no plasticity is induced. For Δt =0 ms (Region II), the I-cell and OLM receive a pulse of glutamate and ACh, respectively, simultaneously. Due to its fast dynamics, the I-cell manages to emit one spike before being inhibited by GABAO. The I-cell inhibits ED only moderately and depression is induced. For Δt = 100 ms (Region III), OLM receives an ACh pulse at t = 0 ms and releases GABAO into the I-cell. When the I-cell receives glutamate 100 ms after, it is hyperpolarized and cannot spike; potentiation is induced. For Δt = 150 ms (Region IV), the hyperpolarization of the I-cell is starting to wear off and the cell manages to emit one spike, sending moderate inhibition to ED; depression is induced. For Δt = 300 ms (Region V), the I-cell can emit two spikes when it receives glutamate 300 ms after cholinergic activation; no plasticity is induced. Download Figure 3-1, TIF file.
Figure 3-2
Mean relative pairing timing of single pulses of ACh and glutamate with noisy membrane potential of ED after 10 simulations. Noise was incorporated by adding a stochastic term
Disinhibition–SC pairing
To study the disinhibitory mechanism of plasticity induction, we consider the dendritic compartment ED subjected to glutamate and GABA pulses, as schematically shown in Figure 4B. Both GABA and glutamate are modeled as square pulses with a duration of 1 ms and 1 mm of amplitude (Extended Data Fig. 4-2A, different durations and amplitudes of glutamate and GABA reproduce the same results), and a frequency of 1 pulse/min, with glutamate preceding GABA by 2 ms.
Disinhibition of CA1 pyramidal cell facilitates the induction of hippocampal synaptic plasticity. A, Scheme of in vitro induction of hippocampal synaptic plasticity through concurrent Sst inhibition. EPSCs were recorded from CA1 pyramidal neurons. Sst neurons were inhibited via eNpHR that was specifically expressed in Sst-positive neurons. The SC pathway was activated by a stimulating electrode. B, Schematic representation of a CA1 pyramidal neuron dendritic compartment ED with postsynaptic GABAA, AMPA, and NMDA receptors used to study the disinhibitory mechanisms for induction of plasticity at the SC–CA1 excitatory synapse. The dendritic compartment of the pyramidal cell receives one pulse of both glutamate and GABA per minute, except during the disinhibition period, where it only receives pulses of glutamate. The GABA pulse, presumably from the I-cell, is described by a square function with similar amplitude and duration as the glutamate pulse (see Materials and Methods; Extended Data Figs. 4-1, 4-2, justification). Glutamate binds to the excitatory AMPA and NMDA receptors, while GABA binds to the inhibitory GABAA receptor. The synaptic currents and membrane potential of ED when a pulse of glutamate is paired (or not) with a pulse of GABA are shown in Extended Data Figure 4-3. C, Experimental measurements showing the effects of inhibition of Sst and OLMα2 interneurons in s.o. on SC-evoked EPSCs (n = 5 slices for each group). Inhibition of Sst interneurons from t = 5 min to t = 10 min enhanced the SC-evoked EPSC amplitude of the CA1 pyramidal cell, followed by a return to the baseline after the inhibition period (blue line). Inhibition of Sst interneurons from t = 5 min to t = 13 min increased SC-evoked amplitude EPSCs, which remained potentiated after the inhibition period (orange line). D, Numerical simulation of normalized EPSCs of ED for a disinhibition period of 5 min (from t = 5 min to t = 10 min) and 8 min (from t = 5 min to t = 13 min). Normalization of the results was calculated according with the expression (100 + (EPSC – EPSCmin) · (150–100))/(EPSCmax – EPSCmin).
Figure 4-1
I-cell GABA release evoked can be approximated by a square function. A, Membrane potential of the I-cell when it receives two pulses of glutamate (with an amplitude of 1 mm and a duration of 3 ms) with a frequency of 0.2 ms. B, GABA release from I-cell when it receives the action potentials described in A, calculated using Equation 15. Download Figure 4-1, TIF file.
Figure 4-2
Sets of parameters that qualitatively reproduce Figure 4D. A, Numerical simulations of normalized EPSCs of ED for varying the amplitude and duration of the glutamate and GABA pulses. B, Parameters of maximum depression (γ↓), maximum potentiation (γ↑), synaptic plasticity decay constant (σ), and potentiation threshold (θ↑) from the shaded areas qualitatively reproduce Figure 4D. The quality of EPSC traces generated with different parameters was evaluated by measuring the relative variations of EPSC amplitude (in non-normalized and non-noisy simulations) from 5 to 30 min after the disinhibition period was over for a 5 and 8 min disinhibition period. Simulations were the variation (percentage of plasticity) was<4% and >22% for the long and short disinhibition periods, respectively, and were considered to conserve the shape of the experimental EPSC trace. This ensures that, for the long disinhibition period, the EPSCs do not decay faster than the experimental EPSCs observed, or slower, for the case of the short period, and therefore have a similar shape. Experimental measures describe the relative increase in EPSC amplitude from the baseline value to 5 min (%(5-B)) and 30 min (%(30-B)) after the disinhibition period is over (see the Results section for the values of %(5-B) and %(30-B) for 5 and 8 min disinhibition periods). This allows us to derive the relative changes from 5 to 30 min [%(30-5) = (%(30-B) – %(5-B))/(100 + %(5-B)) × 100]. By considering the relative changes between 5 and 30 min after the disinhibition period instead of the changes between the baseline and 5 and 30 min, we decrease the number of conditions to evaluate and the computational cost of performing the parameter exploration. The gray and beige areas represent the parameter space where both conditions are met. Note that increasing the synaptic plasticity decay constant σ decreases the robustness of the model to variations of the maximum depression and potentiation, γ↓ and γ↑ (B, beige area). On the other hand, increasing the potentiation threshold θ↑ changes the robustness of the model to changes in γ↑. As θ↑ approaches the depression threshold θ↓ or the maximum calcium amplitude Camax, the robustness in γ↑ decreases. b1, Gray and beige area: parameter space γ↓ – γ↑ where the percentage of plasticity is<4% for an 8 min disinhibition period and >22% for a 5 min disinhibition period for σ = 0.004 and σ = 0.005, respectively. b2, Relative variation of EPSC amplitude from 5 to 30 min after disinhibition period (percentage plasticity) for a disinhibition period of 5 min and σ = 0.005 for different values of γ↓ and γ↑. b3, Relative variation of EPSC amplitude from 5 to 30 min after disinhibition period (percentage plasticity) for a disinhibition period of 8 min and σ = 0.005 for different values of γ↓ and γ↑. b4, Relative variation of EPSC amplitude from 5 to 30 min after disinhibition period (percentage plasticity) for a disinhibition period of 5 min and σ = 0.004 for different values of γ↓ and γ↑. b5, Relative variation of EPSC amplitude from 5 to 30 min after disinhibition period (percentage plasticity) for a disinhibition period of 8 min and σ = 0.004 for different values of γ↓ and γ↑. b6, Gray area: parameter region γ↑ – θ↑ where the percentage plasticity is<4% for an 8 min disinhibition period and >22% for a 5 min disinhibition period for σ = 0.004. b7, Relative variation of EPSC amplitude from 5 to 30 min after the disinhibition period (percentage plasticity) for a disinhibition period of 5 min for different values of γ↑ and θ↑. b8, Relative variation of EPSC amplitude from 5 to 30 min after the disinhibition period (percentage plasticity) for a disinhibition period of 8 min for different values of γ↑ and θ↑. b9, Numerical simulations of normalized EPSCs of ED for different points of the parameter space γ↓ – γ↑ and γ↑ – θ↑. Download Figure 4-2, TIF file.
Figure 4-3
A square GABA pulse with 1 mm amplitude and 1 ms of duration evokes a GABAA current at ED, and decrease NMDA current and depolarization. A, One square pulse of GABA with 1 mm amplitude and 1 ms of duration evokes an inhibitory GABAA current at ED (IGABAA). B, When ED receives a GABA square pulse, glutamatergic activation of ED only evokes a depolarization of –63.56 mV (dashed line). C, When ED does not receive GABA inputs, glutamate inputs evoke a depolarization of –58.25 mV (solid line). When ED does not receive GABA inputs, glutamatergic activation evokes a NMDA current of 7.90 pA (solid line). When it receives a GABA square pulse, the evoked NMDA current is 6.75 pA (dashed line). Download Figure 4-3, TIF file.
Parameters of the model
We used experimentally determined values or values from previous modeling studies for most of the parameters. Parameters that could not be set experimentally were determined by experimental constraints imposed on the model, namely, the maximal conductances
Parameter values for calcium dynamics and synaptic plasticity
All the parameter values are defined in Tables 1, 2, and 3. We strived to constrain the parameters to physiological values based on literature, those parameters that we could not directly constrain, were optimized to ranges that ensure that our simulations showed that the measurable variables used are within the physiological range.
We note that different sets of parameters can reproduce our results (Extended Data Fig. 4-2), and that they can be more finely tuned as more experimental data are collected and more constraints are imposed on the model. This also applies for the description of the neurotransmitters ACh, GABA, and glutamate. Despite not having access to data regarding their profile in the synaptic cleft during the experiments performed, we note that the profiles of different neurotransmitters can reproduce our results. In some cases, it may require that free parameters such as ξ and ξ′, the parameters that convert currents into the calcium concentration, are readjusted to keep calcium within the electrophysiological range. In addition, for the particular case of the ACh dynamics, much higher concentrations than the ones considered here may require a more detailed description of the CICR mechanism by, for example, adding a calcium pump to the membrane of the internal stores and the OLM neuron to control the calcium flux into the intracellular medium.
We approximate the solutions of the differential equations with the Euler’s method. We use a step size of 0.02 ms, which is the biggest value for which we have nonerratic solutions. To ensure the stability of our numerical method, we ran a number of pilot simulations with a smaller time step. We found that, for example, a timestep of 0.01 ms did not produce different results, while increasing considerably the time of computation.
Code accessibility
The code described in the article is freely available at https://github.com/inesCompleto/Hippocampal_Plasticity.
Data availability
The data that support the findings of this study (Gu et al., 2020) are available from the corresponding author on reasonable request.
Results
Coactivation of cholinergic and glutamatergic inputs modifies the SC-CA1 synaptic transmission
First, we set out to study the cholinergic mechanisms by which activation of α7 nAChRs on OLMα2 neurons facilitates the potentiation of SC–CA1 synapses. We designed a biophysical model to reproduce the experimental results reported in the study by Gu et al. (2020; Fig. 2A,C) using the minimal network scheme presented in Figure 2B.
In our model, similar to what was reported in the study by Gu et al. (2020), repeated coactivation of cholinergic and glutamatergic inputs potentiates the SC–CA1 synapse (Fig. 2D). The longer the coactivation period, the longer lasting are these changes.
From Figure 2D, we see that during the copairing period (from t = 10 min to t = 18 min), the EPSC is increased. This increase in our model is maintained for an extended period after the copairing period is over (black line), matching experimental results. We also see that GABA release from the I-cells, GABAI, decreases significantly (Fig. 2D, inset). Before the copairing period, glutamatergic inputs activate the I-cell. This results in the inhibition of the pyramidal cell dendritic compartment ED, which shows an SC-evoked depolarization immediately followed by hyperpolarization of its membrane potential. During the copairing period, activation of α7 nAChRs 100 ms before SC stimulation results in a flux of calcium into the OLM cell that will initiate CICR from internal stores exerting a positive feedback. The increase in intracellular calcium concentration induces the release of GABA, as described by Equation 16. GABAergic inputs from the OLM cell disable the SC-evoked activation of the I-cell. As a result, ED does not receive GABAergic inputs (Extended Data Fig. 2-1).
If we reduce the maximal conductance of the α7 nAChR,
We then examined how the key parameters of the copairing protocol influence the plasticity of the SC–CA1 EPSCs. According to our model, the duration of the copairing period, the relative time between the cholinergic and glutamatergic inputs, as well as their frequency during the copairing period can modulate the efficiency and direction of plasticity. Our simulations show that the longer the copairing period, the longer it takes the EPSCs to return to the baseline value once the copairing period is over (Figs. 2D,F, 3A). We observe a positive relationship between the frequency of the glutamatergic and cholinergic inputs during a fixed period of paring protocol and the potentiation transient duration (Fig. 3B). Interestingly, our simulations suggested that while changing the copairing period and the frequency of stimulation modulates the efficiency of the induction of potentiation, it does not change the direction of plasticity. Only when varying the relative time between the ACh and glutamate pulses could we induce a change in the plasticity direction. For single-pulse pairing, potentiation will be induced if the glutamatergic inputs arrive at I and ED within 10.4< Δt < 131.1 ms following the ACh pulse. If −19.9< Δt < 10.4 ms or 131.1< Δt < 177.4 ms, depression is induced (Fig. 3C). If we pair doublets of glutamate and ACh with a frequency of 2 Hz instead of single pulses, the potentiation window is 10.9< Δt < 149.9 ms, while the depression window is −19.9< Δt < 10.9 ms and 149.9< Δt < 320 ms (Fig. 3D). In both cases, the potentiation and depression window are well defined. These results agree with experimental findings by Gu and Yakel (2011) showing that the activation of cholinergic inputs 100 and 10 ms before SC stimulation induced SC to CA1 long-term potentiation and short-term depression, respectively.
In the simulations performed to reproduce Figure 3, C and D, we do not consider noisy membrane potentials. As a result, we obtain sharp transition between the regions of depression and potentiation—the timing at which GABAO is released from the O-cell finely tunes the number of spikes emitted by the I-cell. As we show in Extended Data Figure 3-2, adding a noisy background induces spontaneous spiking of the O-cells and I-cells, which results in smoother transitions.
Disinhibition of the CA1 pyramidal cell dendritic compartment enables potentiation of the SC–CA1 synaptic transmission
Our model shows a decrease in GABA release from I-cells during the copairing period (Fig. 2D, inset) that results in disinhibition of the ED. To study the role of this disinhibition in the potentiation of the SC–CA1 excitatory synapse, we used a model of ED submitted to a pulse of glutamate followed by a pulse of GABA, except during a disinhibition period when it only receives pulses of glutamate (Fig. 4B, scheme). This corresponds to experiments where we paired, in vitro, the inhibition of Sst interneurons (analogous to the I-cells in the model) with SC stimulation that provides the glutamatergic inputs (Fig. 4A).
We would like to note that, according to our model, the rise and decay time of GABA concentration release that results from the spiking of the I-cells is almost instantaneous (Extended Data Fig. 4-1). Therefore, in this section, the GABAergic inputs into ED are modeled as square pulses. For simplicity, both glutamate and GABA release pulses are modeled as square pulses with a duration of 1 ms and 1 mm of amplitude. It is important to note that pulses with amplitudes and durations different from the ones considered here would reproduce the same results, as long as the duration and amplitude of glutamate and GABA match each other (Extended Data Fig. 4-2A). ED receives one pulse of glutamate per minute, followed by a pulse of GABA 2 ms after, except during a disinhibition period when it only receives pulses of glutamate. We note that this simulated stimulation and pairing choice directly follows the experimental protocol (see Materials and Methods).
In our model simulations, we observe that before the disinhibition period, there were no changes in the simulated EPSC amplitude of ED. During the disinhibition period, the EPSC amplitude increases, and the longer the disinhibition period lasts, the longer these changes last. More specifically, for a disinhibition period of 5 min, the EPSC returns to baseline once the disinhibition period is over. For a longer disinhibition period of 8 min, the EPSC remains potentiated long after the disinhibition period is over (Fig. 4D). These results hold for different values of the plasticity parameters (Extended Data Fig. 4-2B). After 5 min of ED disinhibition, the EPSC amplitude was increased from 169.40 to 285.34 pA. After 8 min of disinhibition, the EPSC amplitude increased to 361.33 pA. This is in accordance with experimental results, where inhibition of Sst interneurons projecting to CA1 pyramidal cells was paired with SC stimulation for a short and long period (Fig. 4C). Inhibition of Sst interneurons via eNpHR resulted in increased SC–CA1 EPSC amplitude not only during the Sst inhibition but also after the end of Sst inhibition. The EPSC enhancement after the Sst inhibition lasted ∼10 min after 5 min of Sst inhibition and >30 min after 8 min of Sst inhibition. After 5 min of Sst inhibition, the EPSC amplitude was significantly increased at 5 min after the end of Sst inhibition (31.8% increase compared with baseline, p = 0.0003) but returned to baseline at 30 min after Sst inhibition (2.8% increase compared with baseline, p = 0.79). After 8 min of Sst inhibition, the EPSC amplitude was significantly increased at both 5 min after the end of Sst inhibition (37.3% increase compared with baseline, p < 0.0001) and 30 min after Sst inhibition (32.5% increase compared with baseline, p < 0.0001). Experiments showed that the inhibition of OLMα2 interneurons via eNpHR did not change the amplitude of SC–CA1 EPSC, indicating that the Sst interneurons inducing potentiation do not include OLM (Fig. 4C, gray line).
AMPARs are known to play an important role in regulating and expressing synaptic plasticity in the hippocampus (Barria et al., 1997). From Figure 5, we see that there is an increase of
Calcium dynamic is key for the induction of synaptic plasticity. A, Time course of maximal AMPAR conductance,
In this study, we focused on a calcium-based synaptic plasticity model to describe changes in the excitatory SC–CA1 synapse. To gain a more detailed understanding on how the evolution of the calcium levels relate to the changes in the synaptic strengths, we can examine the calcium dynamics before, during, and after the disinhibition period.
Figure 5, C and D, shows that the calcium concentration increases significantly during the disinhibition period, crossing the potentiation onset θ↑ with a significant margin. Immediately after the end of the disinhibition period, the calcium levels decrease, yet they remain above θ↑. We can see a clear difference in calcium dynamics for the short and the long disinhibition periods. In the case of a short disinhibition period, each pairing of GABA and glutamate after the disinhibition period will elicit a calcium pulse with a smaller amplitude than the previous one. Eventually, at t = 25 min, the calcium concentration from the pairing is not enough to cross the potentiation onset θ↑. By t = 30 min, calcium does not cross either the potentiation (θ↑) or the depression onset (θ↓), having a similar amplitude as before the disinhibition period. In the case of a long disinhibition period, each pairing performed after the disinhibition period evokes a calcium pulse with a constant amplitude. In other words, long disinhibition periods ensure that the consequent pairings yield calcium responses that do not drop below the onset thresholds.
To better visualize the synaptic and calcium dynamics immediately after the disinhibition period in both cases, we plot the trajectory of the system in the Ca-
We do note that the fixed potential threshold θpot is not an ideal indicator of potentiation, as it may need to be recalculated depending on a specific case of calcium dynamics timescales and/or the induction protocol. As seen in Figure 5E, the dynamics of calcium is important in the induction of plasticity. Therefore, changing these by, for example, changing the calcium decay rate, can alter the θpot by changing the time calcium spends in the depression/potentiation onset region. This kind of analysis can also fail to identify mechanisms of the induction of potentiation. As shown in Figure 6B, if we consider a second calcium source that becomes activated at t = 80 ms, neither of the two pulses of calcium generated crosses θpot; however, the synapse is potentiated. These examples suggest that it is not the peak calcium concentration that is a key indicator of potentiation, but a measure that is based on the total amount of calcium that exceeds the onset levels. We suggest that a better quantity that can be used more generally as an indicator of plasticity is the ratio between the integral of calcium when its concentration is above the potentiation onset θ↑, which we will call the area of AMPAR insertion (Extended Data Fig. 6-1, orange area, Fig. 6, corresponding graphs) and the integral of calcium when its concentration is above the depression onset θ↓ and below the potentiation onset θ↑, the area of AMPAR removal (Extended Data Fig. 6-1, gray area, Fig. 6, corresponding graphs) weighted by the calcium-dependent learning rate η, which we named (A↑/A↓)w (for more details, see Materials and Methods). If this ratio is<3.0, depression is induced in our model; if the ratio is >3.0, potentiation is induced.
The weighted ratio (A↑/A↓)w can accurately be used as a predictor of induction of depression or potentiation. The depression and potentiation areas A↓ and A↑ are as defined in Extended Data Figure 6-1. A, Different values of
Figure 6-1
Area of potentiation (orange) and area of depression (gray) considered to calculate the (A↑/A↓)w. For the description of the labels, please refer to Figure 6 in the main text. From t0 to t1 and t2 to t3, calcium is above θ↓ and below θ↑. These regions constitute the area of depression A↓. From t1 to t2, calcium is above θ↑. This region constitutes the area of potentiation A↑. While the calcium concentration is above the depression onset θ↓ (but below the potentiation onset θ↑), the maximal conductance of the AMPARs
GABA amplitude and Glu–GABA pairing timing control membrane potential
Disinhibition of the pyramidal cell (i.e., reduction of GABAergic inputs), can facilitate the depolarization of the cell, which can control plasticity, as we have shown in the previous section. Therefore, we hypothesize that the amplitude of the GABA pulse, GABAmax, and the relative time between the glutamate and GABA pulses, Δt(GABA-Glu), can modulate plasticity. To explore this hypothesis, we pair glutamatergic inputs with GABAergic inputs into ED. We vary the relative time between the inputs, Δt(GABA-Glu), and the amplitude of the GABAergic inputs, GABAmax, to measure changes induced in
Amplitude of GABA pulse, GABAmax, and relative time between GABA and glutamate pulses, Δt(GABA−Glu), control the direction and efficiency of the induction of synaptic plasticity. A, Depression and potentiation regions for
Model predictions and implications
Results of model simulations and analysis make several testable predictions. First, while experiments so far have not identified precisely the exact type of s.o. interneurons that provide the feedforward inhibition to the CA1 pyramidal cell, our model predicts that it should be an interneuron type with fast dynamics (i.e., with dynamics comparable to the pyramidal cells). More specifically, we expect that EPSC on the hippocampal parvalbumin (PV)-positive interneurons in the stratum radiatum would decrease during cholinergic pairing because of the inhibition provided by the OLM neurons. Consequently, GABAA-mediated IPSCs on the proximal dendrites of CA1 pyramidal cells would also decrease.
In this work (both in modeling and experimentally), modulation of the OLM cells is because of cholinergic activation of α7 nAChRs. Our model more specifically suggests that the GABA release by the OLM cells is regulated by activating α7 nACh receptors, without necessarily altering the OLM firing. However, GABA release can also be controlled by the depolarization of the OLM cells and/or by modulation of their spiking activity by somatic nAChRs.
Our model predicts a relationship between the relative timing of the septal and hippocampal stimulus pairing and the synaptic plasticity direction at the SC–PYR synapse. According to our simulations, increasing the frequency of septal and hippocampal paired stimulation can induce plasticity more efficiently (i.e., fewer pairings would be required to induce LTP). At the same time, we predict that changing the relative time between septal and hippocampal activation can induce long-term depression instead of LTP.
Finally, our modeling results suggest that for the plasticity to be induced, the excitatory NMDA and AMPA receptors and the inhibitory GABAA receptors should be located sufficiently proximal to each other in the pyramidal dendritic compartment.
Discussion
This work set out to explain how nicotinic cholinergic modulation of hippocampal OLM interneurons paired with hippocampal stimulation can potentiate CA1 pyramidal cell EPSC responses. Our modeling results suggest that copairing cholinergic activation of α7 nAChRs on the OLM interneurons results in disinhibition of CA1 pyramidal cells. We also show by mathematical analysis how synaptic plasticity is controlled by the disinhibition of the postsynaptic pyramidal membrane through a disynaptic GABAergic circuit. To our knowledge, this is the first report to reveal how repeated disinhibition can directly induce short-term or long-term potentiation, depending on the duration of the disinhibition period (both experimentally and computationally). It is also the first computational study that explicitly shows how cholinergic action on OLM interneurons can directly induce SC–CA1 plasticity through disinhibition.
OLM cells are a major class of GABAergic interneurons located in the stratum oriens hippocampal layer that inhibit pyramidal cells dendritic compartment located in the stratum lacunusom-moleculare layer, reducing the strength of EC inputs. OLM cells also target bistratified interneurons, expressing PV and somatostatin (Sst), that receive feedforward excitatory inputs from the Schaffer collaterals (Müller and Remy, 2014). Recent findings show that activation of OLM cells can facilitate LTP in the SC–CA1 pathway, likely by inhibiting s.r. interneurons that synapse on the same dendritic compartment as the SC, counteracting SC feedforward inhibition (Leão et al., 2012). We found that repeated pairing of cholinergic inputs with hippocampal stimulation can induce plasticity if the inputs are tightly timed. The time window for potentiation depends significantly on the dynamics of the O-cells and I-cells, and calcium dynamics. This agrees with experimental findings showing that activating cholinergic inputs to the hippocampus can directly induce different forms of synaptic plasticity depending on the input context of the hippocampus, with a timing precision in the millisecond range (McKay et al., 2007; Gu and Yakel, 2011). Our model also shows that the longer the copairing period and the higher the frequency of stimulation during the copairing period, the longer lasting is the potentiation of the synapse.
According to our model, the key mechanism behind paired cholinergic induction of synaptic plasticity is the disinhibition of the pyramidal cell dendritic compartment. Cholinergic activation of the O-cell synapses inhibits the fast-spiking I-cell that projects to the dendritic compartment ED. The disinhibition of ED paired with glutamatergic stimulation allows for the depolarization of the pyramidal dendritic compartment. This increases NMDAR activation and intracellular calcium concentration sufficient to upregulate postsynaptic AMPAR permeability and potentiate the excitatory synapse. Our model puts together all the elements to give the following sequence of events: SC stimulation results in the activation of CA1 fast-spiking interneurons, I, and the subsequent release of GABA. At the same time, it evokes an EPSP mediated by AMPAR on the CA1 pyramidal cell dendritic compartment, ED. Since I and ED have comparable dynamics, the EPSP is closely followed by a GABAA-mediated IPSP. Because of slow kinetics and voltage dependence, at that time, the NMDAR receptors are not in the open state and there is no significant influx of calcium. When the SC inputs are tightly timed with cholinergic inputs acting on OLM interneurons, GABA release from I-cells is suppressed. The pyramidal cell membrane at (or sufficiently near to) the glutamatergic synapse can depolarize enough to relieve the Mg2+ block from the NMDA receptors, allowing calcium to permeate through the receptor channel (Fig. 8). Therefore, every time the pyramidal cell receives a glutamate pulse during the disinhibition period, the intracellular calcium concentration crosses the potentiation outset θ↑, and
Scheme of the cholinergic and disinhibitory mechanisms that drive SC–CA1 potentiation. A, Glutamatergic activation of I-cells lead to spiking activity and consequent GABA release. Subsequently, glutamate inputs acting on ED evoke an EPSP mediated by AMPAR immediately followed by an IPSP-mediated GABA acting on GABAA receptors. B, Cholinergic activation of α7 nAChR on OLM interneuron initiates a CICR process mediated by calcium internal stores (IS). This result in GABA release that inhibits the I-cell. The dendritic compartment does not receive GABAergic inhibition. The dendritic compartment can depolarize enough—and remain depolarized for long enough—to relieve Mg2+ block from NMDA receptors, allowing calcium to permeate through the receptor channel. C, CICR mechanism. The entry of calcium through α7 nAChRs induces calcium release form internal stores by activating IP3 receptors.
Downregulation of the GABAergic signaling during disinhibition leads to increased NMDAR activation. We see that when we reduced GABA concentration, glutamatergic activation of ED results in postsynaptic NMDA currents with 7.90 pA of amplitude—with depolarization of −58.25 mV, as opposed to the 6.75 pA that results from the pairing of glutamate and GABA inputs—with depolarization of −63.56 mV (Extended Data Fig. 4-3). Because of the high calcium permeability of receptor, there is an elevation in intracellular calcium concentration large enough to initiate molecular mechanisms that result in the insertion/phosphorylation of the AMPAR. In our model, this translates into an increase in the AMPAR maximal conductance
The more times we pair disinhibition with SC stimulation (i.e., the longer the disinhibition period), the higher the value of
We asked how the results of our simulations depend on the parameters chosen. We found that our model remains robust to changes of parameters as long as we maintain the same ratio of insertion/removal of AMPARs. Thus, for example, for different values of the
In our modeling study, we strived to ensure that parameters for which physiological ranges can be identified agree with these ranges. At the same time, there were a number of them that could not be constrained directly, and we chose to optimize them to obtain model responses that qualitatively agreed with our data. For example, the calcium amplitude in our model is of the same order of magnitude as measured in the dendritic spines in the studies by Sabatini et al. (2002) and Rubin et al. (2005). While we do see that the optimized Cap parameter is below the calcium resting value, we consider that calcium concentration decays to zero, similar to what is done in the studies by Graupner and Brunel (2005, 2012), Higgins et al. (2014), Rubin et al. (2005), and Shouval et al. (2002). Despite not being an exhaustively detailed description of what happens in the dendritic spine, changing the resting value of the calcium does not alter our results as long as it is below the depression threshold. Concerning the K(Ca)p parameter, it determines the steepness of the GABAO(Ca) function. The vesicular release of neurotransmitter has a steep dependence on the intracellular calcium concentration Schneggenburger and Forsythe (2006). Thus, we believe it to be appropriate to consider a steep relationship between the intracellular calcium and the concentration of GABA available for binding, and that these two parameters are examples for functionally optimized values.
It is worth noting that the parity of the synaptic plasticity induced depends on the value of maximal conductance of the postsynaptic AMPAR,
Earlier studies pointed out that reduced inhibition (disinhibition) can facilitate LTP induction under various conditions (Wigström and Gustafsson, 1985; Ormond and Woodin, 2009; Yang et al., 2016). Our results show that repeated temporally precise concurrent disinhibition can directly induce SC to CA1 LTP, providing a novel mechanism for inhibitory interneurons to modify glutamatergic synaptic plasticity directly. This expands the original spike timing-dependent plasticity that concerns the concurrent activation of two excitatory pathways to include the interneuron network. Furthermore, our modeling work implies that GABAergic neurotransmission should control the local pyramidal voltage in the vicinity of the glutamatergic synapses, thereby the inhibitory synapses critically modulate excitatory transmission and the induction of plasticity at excitatory synapses. This points toward the importance of dendritic GABA and glutamate colocation in shaping local plasticity rules. Our work also suggests a cholinergic mechanism for controlling GABA release at the pyramidal dendrites and the subsequent potentiation of excitatory synapses, unraveling the intricate interplay of the hierarchal inhibitory circuitry and cholinergic neuromodulation as a mechanism for hippocampal plasticity.
Previous work by Gu et al. (2017) showed that copaired activation of the cholinergic input pathway from the septum to the hippocampus with stimulation of the Schaffer collateral pathway could readily induce theta oscillations in a coculture septal–hippocampal–entorhinal preparation. Moreover, after performing copaired activation several times, not only was the SC–PYR synapse potentiated, but it became easier to evoke the theta rhythm in the preparation (one pulse stimulus of the SC is sufficient to generate theta oscillations in the circuit with the same characteristics as before; Gu and Yakel, 2017; Gu et al., 2017). Therefore, induction of hippocampal plasticity, particularly potentiation of the CA1 EPSPs, appears to facilitate the generation of the theta rhythm. Moreover, previous studies directly linked OLMα2 interneurons to theta oscillations (Rotstein, et al., 2005; Mikulovic, et al., 2018) and suggest that OLM cells can regulate the robustness of the hippocampal theta rhythm (Chatzikalymniou and Skinner, 2018). Thus, we may speculate that the action of ACh on the α7 nAChRs at the OLMα2 neurons potentiates the SC–CA1 synapses to close the critical link in the synaptic chain of events, enabling recurrent reverberation excitation in the hippocampal–entorhinal theta-generating circuit. Understanding the mechanisms underlying the induction of hippocampal plasticity by this copairing mechanism will allow future studies of how changes on the synaptic level can propagate to the network level and change the mechanisms of theta generation.
Our results are also relevant to understanding the neural circuit origins of pathologic conditions and uncovering potential targets for therapeutic intervention in disorders linked to memory deficits. For example, the hippocampus is one of the earliest brain structures to develop neurodegenerative changes in AD (Arriagada et al., 1992). Furthermore, numerous studies suggest that cognitive deficits in AD, such as memory impairment, are caused in part by the dysfunction of cholinergic action on hippocampal GABAergic interneurons (Schmid, et al., 2016; Haam and Yakel, 2017). Here, we have shown that a decrease in the conductance of cholinergic α7 nAChRs on OLM interneurons caused the impairment of induction of hippocampal synaptic plasticity.
Model caveats
As with any modeling studies we had to compromise between a realistic description of the neural networks and the simplicity of the model that allows for computational analysis. While some of the aspects could be performed using simplified integrate-and-fire neuron models, we felt that multiple aspects focused on biophysical mechanisms (e.g., the ability of the cholinergic activation of OLM cells to suppress spiking of fast-spiking interneurons in a tightly timed manner). The simplified one-compartment biophysical model used in this study allows us to analyze how detailed biophysical mechanisms, such as CICR and the dynamics of neurotransmitter release, control cholinergic induction of plasticity, while maintaining the simplicity and flexibility necessary to carry out computational analysis and study similar mechanisms in other neural networks.
The assumptions and ad hoc simplifications made in this study introduce some limitations in the model. Namely, the description of the ACh pulse that, because of a lack of knowledge of the neurotransmitter profile in the synaptic cleft, is described as a square with 1 mm magnitude and a duration of 5 ms. We have shown that our results still hold up when considering different cholinergic profiles (Extended Data Fig. 2-3); however, a magnitude or duration considerably higher (lower) than what is considered here can lead to calcium concentrations that are too high (low). This can lead to nonphysiological calcium concentrations and, consequently, unrealistic GABA profile. In that case, one would have to consider a more detailed description of the CICR mechanism with calcium pumps on the internal stores and the membrane of the neuron. The same adjustment would be necessary if the resting calcium concentrations in the internal stores and intracellular medium induce a greater calcium flux.
Footnotes
The authors declare no competing financial interests.
This research was supported by the Intramural Research Program of the National Institutes of Health (NIH) and the NIH/National Institute of Environmental Health Sciences. I.G. and B.S.G. were supported by Fondation pour la recherche sur Alzheimer; Centre National de la Recherche Scientifique; Institut National de la Santé et de la Recherche Médicale; and Agence Nationale de la Recherche Grants ANR-17-EURE-0017 and ANR-10-IDEX-0001-02. B.S.G. was supported by the Basic Research Program at the National Research University Higher School of Economics.
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
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