Sensory experience can shape cortical circuitry and function. One clear demonstration of this is seen the visual cortex during a postnatal critical period, when brief visual deprivation in one eye can reduce the cortical responsiveness to the deprived eye while increasing the responsiveness to the fellow eye (for recent reviews see Espinosa and Stryker, 2012; Hensch and Quinlan, 2018). It has been widely recognized that this type of neural plasticity requires Hebbian-like forms of long-term potentiation (LTP) and depression (LTD) and neuromodulatory signals conveying information on the organism’s behavioral state (for reviews see Gu, 2002; Gu, 2003; Hofer et al., 2006; Kasamatsu, 1991; Smith et al., 2009). How neuromodulators and Hebbian plasticity interact during cortical remodeling, however, is not fully understood.

Studies in vitro have demonstrated that neuromodulators can gate the induction of Hebbian plasticity by promoting excitability in cortical circuits (for reviews see Brzosko et al., 2019; Foncelle et al., 2018; Frémaux and Gerstner, 2015; Palacios-Filardo and Mellor, 2019; Pawlak et al., 2010). In addition, neuromodulators can also control the expression of synaptic plasticity, affecting its gain and polarity. These effects on the expression of synaptic plasticity result from the activation of distinct G-protein coupled receptors (GPCRs). A picture emerging from studies in the visual cortex is a simple rule in which Gs-coupled receptors that activate the adenylyl cyclase pathway and Gq-coupled receptors that activate the phospholipase-C (PLC) pathway have opposite effects on LTP and LTD (Huang et al., 2010; Seol et al., 2007). Gs-coupled promote LTP and suppress LTD, whereas Gq-coupled receptors promote LTD and suppress LTP. An attractive consequence of the pull-push rule is the wide range of possible outcomes, from and LTP-only state when activity of Gs dominates, to an LTD-only state when Gq dominates (Huang et al., 2010; Huang et al., 2012; Huang et al., 2013). Thus, the pull-push neuromodulation of LTP/D by the balance of Gs/Gq activity could serve as a metaplasticity mechanism allowing a rapid reconfiguration of the plastic state of cortical synapses.

Motivated by the considerations above we examined whether GPCRs can shape experience-dependent plasticity in mouse V1 in vivo via a pull-push mechanism. Our results show that targeting receptors coupled to Gs or Gq in conjunction with visual stimulation can increase or decrease cortical response in a manner consistent with the pull-push model. These cortical changes were robust, stable in the absence of further visual conditioning, could be induced in adults long after the termination of the critical period for ocular dominance plasticity and can reverse ocular dominance imbalance induced by prolonged monocular deprivation.

We evaluated the pull-push neuromodulation of plasticity in vivo in the mouse visual cortex. We asked whether combining monocular stimulation or deprivation with the manipulation of GPCRs affects visual cortical responses in a manner predicted by the pull-push model, that is Gq-coupled receptors promoting depression and Gs-coupled receptors promoting potentiation. Changes in visual responses were monitored with optical imaging of intrinsic signal in V1 (Kalatsky and Stryker, 2003), and GPCRs were specifically targeted with pharmacology and chemogenetics (see Materials and methods).

Systemic administration of GPCR agonists in conjunction with brief monocular visual conditioning induces bidirectional change of ocular dominance

We first tested whether brief monocular stimulation paired with activation of 5HT2c serotonergic receptors (paired to Gq) induces lasting depression of the visual responses, and whether the same visual stimulation, but paired with the activation of β-adrenergic receptors (βAR, coupled to Gs) potentiates the visual responses in juvenile mice (4 to 5 week old). We choose these particular receptors because in monocular deprivation, the disconnection of the deprived eye requires serotonin, while the potentiation of the fellow eye requires norepinephrine (Nakadate et al., 2013). In addition, βAR and 5HT2c are unique in supporting LTP and LTD, respectively, evoked with reinforcement like approaches (He et al., 2015).

The experimental schedule is depicted in Figure 1A. On the first day the cortical responses to either eye was measured in the binocular segment of V1 in one hemisphere. Next day the dominant eye (contralateral to the imaged hemisphere) was conditioned under isoflurane anesthesia with visual stimulation (1 hr. See Materials and methods for more details) in conjunction with systemic injection of one specific agonists (βAR: isoproterenol, 15 mg/kg, i.p.; 5-HT2c: Ro 60–0175, 10 mg/kg, i.p.). Following the visual conditioning, the mice were immediately brought into the dark to prevent visual experience until a later imaging session the following day.

Figure 1 with 1 supplement see all

Download asset Open asset

Figure 1—source data 1

https://cdn.elifesciences.org/articles/54455/elife-54455-fig1-data1-v2.xlsx

Download elife-54455-fig1-data1-v2.xlsx

In naïve mice the contralateral eye dominates the visual cortical response in the binocular zone, and the computed ocular dominance index is typically about 0.3 (see Materials and methods). In a first round of experiments we conditioned the contralateral eye in the presence of Ro 60–0175, the agonist for the Gq-coupled receptor 5-HT_2C. As shown in Figure 1B,C and in accordance with the role of Gq-coupled receptors in synaptic LTD, this conditioning specifically depressed the contralateral responses (before: 2.38 ± 0.23, after: 1.84 ± 0.21, p=0.037) without affecting the ipsilateral responses (before: 1.29 ± 0.11, after: 1.27 ± 0.13, p=0.75, n = 10), which translated in a significant decrease in the ODI magnitude (ODI, before: 0.28 ± 0.02, after: 0.14 ± 0.02, p=0.002, n = 10). In a similar fashion, visual conditioning paired with injection of an agonist for another Gq-coupled receptor (methoxamine:15 mg/kg, i.p., the α1-adrenergic receptor agonist), also lowered the ODI magnitude compared to those of the vehicle control group (ODI, methoxamine: 0.10 ± 0.04, n = 5; vehicle: 0.27 ± 0.02, n = 7, Wilcoxon rank sum test, p=0.001; Figure 1—figure supplement 1B). On the other hand, the same visual conditioning, but in the presence of isoproterenol, the agonist for Gs-coupled βAR, resulted in the opposite outcome in both the ODI and the response amplitude of the conditioned eye. The ODI increased after the visual conditioning, mainly by the potentiation of the conditioned eye, as the response amplitude from the other eye was not changed (response amplitude from conditioned eye, before: 2.74 ± 0.15, after: 3.52 ± 0.28, p=0.019; non-conditioned eye, before: 1.55 ± 0.09, after: 1.65 ± 0.12, p=0.344; ODI, before: 0.26 ± 0.02, after: 0.36 ± 0.03, p=0.011, n = 9; Figure 1D and E).

As controls, we confirmed that the monocular visual conditioning alone did not induce significant changes in the ODI as well as the response amplitude (response amplitude from conditioned eye, before: 2.43 ± 0.16, after: 2.62 ± 0.39, p=1; from non-conditioned eye, before: 1.36 ± 0.11, after: 1.50 ± 0.24, p=0.687; ODI, before: 0.26 ± 0.02, after: 0.27 ± 0.02, p=1; n = 7) (Figure 1F and G). In addition, the agonists alone (without any visual stimulus) did not affect the responses and the ODI (ODI; naïve: 0.26 ± 0.01, n = 26; isoproterenol: 0.27 ± 0.02, n = 7; Ro 60–0175: 0.26 ± 0.03, n = 6; methoxamine: 0.26 ± 0.01, n = 6; F_3,41 = 0.09, p=0.964) (Figure 1—figure supplement 1). Altogether the results indicate that activation of GPCR signals can promote rapid and persistent bidirectional changes in ocular dominance. Importantly, the polarity of the changes is consistent with the pull-push model, with Gq-coupled receptors promoting depression, and Gs-coupled receptors promoting potentiation. Also, worth noting, only 1 hr of conditioning with neuromodulator induced changes in ODI of comparable magnitude of those induced by several days of monocular deprivation (Cang et al., 2005; Sato and Stryker, 2008).

Activation of gq- or Gs-coupled DREADD promotes pull-push neuromodulation

The systemic administration of agonists can stimulate receptors outside the visual cortex, and potentially outside the nervous system, complicating the interpretation of the results. To confirm the role of the cortex in the changes described above, we employed a chemogenetic approach and virally transfected the visual cortex to express designer receptors exclusively activated by designer drugs (DREADDs). Thus, the systemic administration of the DREADDs agonist will only affect the targeted region. In the case of Gq-DREADDs we injected an adeno-associated virus (AAVs) containing neuronal DREADDs gene; in the case of Gs-DREADDs we used Gs-DREADDs knock-in mice (Akhmedov et al., 2017) injected with AAVs containing pan-neuronal Cre recombinase gene (rAAV-hSyn-Cre) (see Materials and methods for more details).

First, we examined if the Gq- and Gs-DREADDs can promote LTD and LTP in a pull-push manner as the endogenous GPCRs do (Huang et al., 2012; Seol et al., 2007). The assessment was done in visual cortical slices, in layer 2/3 pyramidal cells expressing Gq- and Gs-DREADDs. We used a spike-timing dependent plasticity (STDP) protocol (Figure 2—figure supplement 1A and B; see Materials and methods for details) because in our standard experimental conditions this paradigm depends crucially of the addition of GPCR agonists. The STDP protocol was applied to two pathways, P1 and P2: in P1 the stimulation preceded a burst of postsynaptic action potentials and in P2 it occurred after. This STDP pairing was delivered at the end of a 10 min bath application of the agonist clozapine N-oxide (CNO, 10 µM). Consistent with the pull-push model and with previous results (Seol et al., 2007), this conditioning (CNO and STDP) induced a robust LTD in both pathways in cells expressing Gq-DREADDs (P1: 60.0 ± 7.4%, p=0.031, n = 6; P2: 65.5 ± 7.3%, p=0.031, n = 6), robust LTP in cells expressing Gs-DREADDs (P1: 123.5 ± 3.4%, p<0.001, n = 9; P2: 121.2 ± 5.4%, p=0.045, n = 8), and has no effect in Gq- or Gs-DREADDs negative cells (Gq-DREADDs, P1: 96.6 ± 1.2%, p=0.125, n = 4; P2: 101.8 ± 3.8%, p=0.063, n = 5; Gs-DREADD, P1: 89.8 ± 9.9%, p=0.125, n = 4; P2: 84.0 ± 4.1%, p=0.250, n = 3).

Altogether, the results above validated the use of DREADDs. Therefore, to ascertain the role of cortex in the pull-push neuromodulation of ODP, we tested if the systemic injection of CNO (10 mg/kg, i.p.) in conjunction with monocular stimulation can promote bidirectional change of ocular dominance in mice expressing Gq- or Gs-DREADDs in vivo. As depicted in Figure 2A, the experimental schedule was very similar to the one use for the agonist for endogenous GPCR. The results were similar to that obtained with pharmacology. Monocular stimulation of mice expressing Gq-DREADDS in V1 in conjunction with systemic injection of CNO significantly reduced the ODI in the contralateral binocular cortex (ODI, before: 0.21 ± 0.01, after: 0.06 ± 0.03, p=0.031, n = 6; Figure 2B and C). The injection of CNO alone in the dark did not change the ODI (ODI, before: 0.32 ± 0.04, after: 0.31 ± 0.03, p=0.875, n = 4). On the other hand, in the mice expressing the Gs-DREADDs monocular conditioning caused a lasting and significant increase in the responses of the conditioned eye (response amplitude from conditioned eye, before: 2.89 ± 0.25, after: 3.41 ± 0.36, p=0.042; non-conditioned eye, before: 1.73 ± 0.14, after: 1.80 ± 0.16, p=0.845) and an increase in the ODI (ODI, before: 0.24 ± 0.02, after: 0.30 ± 0.02, p=0.018, n = 11; Figure 2D and E). A subset of experimental mice failed to express Gs-DREADDs in V1; in these cases, the ODI did not change with conditioning (ODI, before: 0.26 ± 0.11; after: 0.24 ± 0.13, p=1, n = 4). Although we cannot rule out that the different transfection approaches might have enhanced or moderated the opposite effects obtained with the Gq and Gs-DREADDs, the simplest explanation for the outcome is that the DDREADs affected plasticity as predicted by the pull-push idea. Altogether these results from the Gq- or Gs-DREADDs expressing mice support the idea that the direct activation of the GPCRs in V1 neurons is sufficient to drive the neuromodulation of ocular dominance plasticity.

Figure 2 with 1 supplement see all

Download asset Open asset

Figure 2—source data 1

https://cdn.elifesciences.org/articles/54455/elife-54455-fig2-data1-v2.xlsx

Download elife-54455-fig2-data1-v2.xlsx

Intracortical pathways modified by pairing monocular stimulation with neuromodulators and by monocular deprivation

It was of interest to identify intracortical circuits within V1 affected by the neuromodulator pairing conditioning, and to compare them with the modifications induced by standard paradigms of experience dependent plasticity. Therefore, we evaluated in visual cortical slices the changes in postsynaptic strength induced by 1 hr conditioning in the presence of 5-HT2c agonist Ro 60–0175 and by 3 days of monocular deprivation (MD), as both manipulations result in a comparable decrease in the contralateral bias. The slices were prepared from the monocular V1 contralateral (MD, monocular deprived) or ipsilateral (ND, non-deprived) to the deprived eye in MD mice, and contralateral (C, conditioned) or ipsilateral (NC, non-conditioned) to the stimulated eye in mice conditioned with Ro 60–0175. Prior studies indicate that after p21 synaptic plasticity in V1 is restricted to non-granular layers, therefore we focused on inputs onto layer 2/3 pyramidal cells, specifically on the lateral inputs from other layer 2/3 cells and the ascending inputs from layer 4, both of which have been well studied in deprivation paradigms (Maffei and Turrigiano, 2008; Petrus et al., 2015). The experiments were done in slices from mice that express channelrhodopsin-2 (ChR2) in layer four neurons (Petrus et al., 2015), thus L4 inputs were stimulated optogenetically with blue light while L2/3 input were stimulated electrically (Figure 3A). For these two inputs we determined the quantal size (the postsynaptic response to the release of a single neurotransmitter vesicle) using the strontium (Sr²⁺) to desynchronize the release of presynaptic neurotransmitter vesicles (Bekkers and Clements, 1999). Under these conditions the average quantal size (the response evoked by a single vesicle) can be directly obtained from the isolated events recorded shortly after stimulation (400 ms windows, Figure 3B), after correcting for spontaneous events occurring before the stimulation (Petrus et al., 2015; Tran et al., 2019; see Materials and methods for details). The results are reported in Figure 3. Compared to cells from non-deprived (ND) hemisphere, in cells from deprived (MD) hemisphere the average amplitude of the computed evoked events is reduced in both L4 inputs (ND: 15.9 ± 0.7 pA, n = 7 mice, 10 cells; MD: 13.2 ± 0.8 pA, n = 6 mice, 12 cells, p=0.011; Figure 3C) and L2/3 inputs (ND: 15.5 ± 0.9 pA, n = 5 mice, 9 cells; MD: 12.5 ± 0.7 pA, n = 6 mice, 8 cells, p=0.027; Figure 3D). On the other hand, in the hemisphere conditioned (C) with monocular stimulation combined with injection of serotonergic agonist Ro 60–0175 the average amplitude of the events evoked by stimulating layer four inputs was severely reduced compared to the average in non-conditioned (NC) hemisphere (NC: 19.9 ± 1.3 pA, n = 5 mice, 8 cells; C: 14.2 ± 1.0 pA, n = 6 mice, 11 cells, p=0.002; Figure 3E). In contrast, the average amplitude of the events evoked by layer 2/3 stimulation was not affected by the conditioning (NC: 16.5 ± 1.4 pA, n = 5 mice, 12 cells; C: 15.1 ± 1.1 pA, n = 6 mice, 11 cells, p=0.926; Figure 3F). These results indicate that ascending excitatory inputs from layer 4 cells onto pyramidal cells in layer 2/3 are depressed by both type of conditioning. Lateral inputs, however, were significantly reduced only by MD, possibly because the neuromodulators conditioning was done under anesthesia (to minimize complications due to endogenous neuromodulatory tone), which would reduce the intracortical activity required for Hebbian plasticity. Nevertheless, the results are consistent with the idea that conditioning with neuromodulators act on pathways that are also affected by monocular deprivation.

Figure 3

Download asset Open asset

Figure 3—source data 1

https://cdn.elifesciences.org/articles/54455/elife-54455-fig3-data1-v2.xlsx

Download elife-54455-fig3-data1-v2.xlsx

Blockade of β-Adrenergic receptors during monocular deprivation induces ocular dominance shifts toward the visually deprived eye

According to the pull-push hypothesis of neuromodulation, the balance of the Gq/Gs-coupled receptor signals determines the polarity of the synaptic plasticity. This balance can be shifted to favor LTP or LTD not only by agonists for specific GPCRs but can also be altered with antagonists. Previously we showed that the pharmacological blockade of β-adrenergic receptors is sufficient to bring an LTD-only state in slices, and also in vivo (Huang et al., 2012). We asked therefore whether this intervention could also alter ocular dominance plasticity. We predicted that antagonizing β-adrenergic receptors during brief monocular deprivation (MD) would promote the depression of the responses to the most active eye: the non-deprived eye. This is exactly the opposite of the normal outcome of brief MD: depression of the derived eye. In these experiments we sutured one eyelid for 2 days in juvenile mice (P28-31) for 2 days, and at the same time we infused the βAR antagonist propranolol systemically with an osmotic pump (5 mg/kg/day, s.c.). The changes in cortical responsiveness were monitored in the hemisphere ipsilateral to the deprived eye to maximize detecting a depression of the non-deprived eye. Note that this arrangement is opposite to the one used in standard monocular deprivation studies that monitor the contralateral cortex. As shown in Figure 4B, in the vehicle control group the 2 days of MD increased the ODI (before: 0.24 ± 0.01, after: 0.37 ± 0.02, p=0.009, n = 10), largely due to a reduction of in the response to the deprived eye (before: 1.98 ± 0.11, after: 1.56 ± 0.08, p=0.027), and without changes in responses to the non-deprived eye (before: 3.22 ± 0.17, after: 3.44 ± 0.22, p=0.275) (Figure 4B). In contrast, in the propranolol-treated group MD decreased the ODI (before: 0.24 ± 0.01, after: 0.17 ± 0.03, p=0.013, n = 10) and reduced the responses to both the non-deprived eye (before: 2.85 ± 0.17, after: 2.15 ± 0.22, p=0.005) and the deprived eye (before: 1.74 ± 0.10, after: 1.48 ± 0.10, p=0.013). On other hand the propranolol treatment itself did not affect the ODI in non-deprived mice (before: 0.25 ± 0.01, after: 0.26 ± 0.03, p=0.800, n = 9. Figure 4D). The results indicate that manipulations that alter Gs/Gq-coupled signals can affect the outcome of MD in a manner predicted by the pull-push model. According to the model, the paradoxical shift in ocular dominance towards the deprived eye promoted by blocking Gs-coupled β-adrenergic receptors will be the consequence of a predominance of Gq-coupled signaling favoring an LTD-only state in the cortex. In that scenario, the most active the inputs, the one from the non-deprived eye, will undergo more LTD.

Figure 4

Download asset Open asset

Figure 4—source data 1

https://cdn.elifesciences.org/articles/54455/elife-54455-fig4-data1-v2.xlsx

Download elife-54455-fig4-data1-v2.xlsx

Systemic administration of GPCR agonists in conjunction with brief monocular visual conditioning induces bidirectional change of ocular dominance after critical period

Experience dependent cortical plasticity diminishes as the animal mature (Heimel et al., 2007; Lehmann and Löwel, 2008; Pizzorusso et al., 2002; Sato and Stryker, 2008; Sawtell et al., 2003). In juvenile mice MD induces depression of the responses evoked by the occluded eye and potentiation of responses to the open eye, but only during at the early stages of the critical period. MD does not depress the responses to the occluded eye in mice older than ~p35, and it does not potentiate the responses to the open eye in mice older than p90 (Lehmann and Löwel, 2008; Sato and Stryker, 2008; Sawtell et al., 2003). It was of interest, therefore, to examine whether stimulation of GPCRs can promote bidirectional changes in ocular dominance after the end of the critical period. We first tested in adult mice (P130-140) the effects of monocular visual conditioning (1 hr) in conjunction with systemic injection of the α1 adrenergic agonist (coupled to Gq) methoxamine (15 mg/kg, i.p.), which effectively reduced ODI in juveniles (Figure 1—figure supplement 1B). Like in juveniles, in the adults the conditioning induced a robust and significant decrease in the ODI (ODI, before: 0.30 ± 0.02, after: 0.15 ± 0.03, p=0.003, n = 9; Figure 5A).

Figure 5

Download asset Open asset

Figure 5—source data 1

https://cdn.elifesciences.org/articles/54455/elife-54455-fig5-data1-v2.xlsx

Download elife-54455-fig5-data1-v2.xlsx

Next, we tried the complementary manipulation, to enhance the contralateral bias in adults by pairing the same visual conditioning with the β-adrenergic agonist (coupled to Gs) isoproterenol (15 mg/kg, i.p.). Unlike what we previously observed in juveniles (see Figure 1A), the pairing with isoproterenol did not affect the ODI in adults (ODI, before: 0.31 ± 0.02, after: 0.32 ± 0.01, p=0.5, n = 4; Figure 5B). We reasoned that one factor that could have obscured the outcome is the age-dependent increase in the contralateral bias (Lehmann and Löwel, 2008). Indeed, in naïve adult mice (>P130) the ODI is significantly higher in the juvenile mice (p28 ~p35) and comparable to the ODI value in juveniles after monocular visual conditioning with isoproterenol (ODI, juvenile: 0.26 ± 0.01, n = 43; old: 0.30 ± 0.01, n = 18; juvenile after Iso: 0.35 ± 0.01, n = 9; F_2,67 = 9.59, p=0.008; post hoc Holm-Šídák test p=0.029; Figure 5C). These results suggest a ceiling effect. The contralateral bias of the visual response might be already saturated in adult mice, thus occluding further increases in ODI.

We examined possible ceiling effects in two ways. In one set of studies, we first preconditioned eight mice with methoxamine to ‘unsaturate’ the ODI, then after confirming 24 hr later the reduction in ODI, we tested the effects of isoproterenol conditioning (Figure 5D). As shown in Figure 5E, and consistent with the ceiling hypothesis, preconditioning reduced the ODI from 0.322 ± 0.018 to 0.136 ± 0.018, and conditioning with isoproterenol increased the ODI to 0.200 ± 0.024. A repeated measures ANOVA followed by a Bonferroni’s test confirmed the significance of the differences (n = 8, F_6,12 = 3.238, p=0.039; post hoc Bonferroni’s test, Before-After Mtx, p=0.002; After Mtx-After Iso, p=0.027). In another set of studies, we performed the isoproterenol-conditioning in mice subjected to long-term monocular deprivation (LTMD). This deprivation paradigm induces a profound reduction of the contralateral bias that is not fully reversed by reopening the deprived eye (He et al., 2007; Pizzorusso et al., 2006; Sale et al., 2007). In these experiments we closed one eye at p21 and reopened it after p130. Cortical responses were imaged in the cortex contralateral to the deprived eye as shown in Figure 5F, first shortly after eye reopening and 3 days later, to assess spontaneous recovery. Then the conditioning with isoproterenol was performed and the responses were imaged again, and after a day in the dark to assess the stability of the induced changes. Mice subjected to LTMD exhibited a very low ODI (−0.04 ± 0.02, n = 14), compared to age matched naïve mice (Figure 5G). Seven mice that showed no signs of spontaneous recovery were conditioned with monocular visual conditioning paired with systemic isoproterenol, which resulted in an increased ODI (Figure 5H, Before: −0.01 ± 0.04; After: 0.11 ± 0.05: p=0.031, n = 7). In four of these mice we confirmed that the changes were maintained after one day in the dark (After1d: ODI: 0.11 ± 0.04, n = 4). Altogether the results indicate that the activation of Gs- and Gq-coupled receptors can promote experience-dependent bidirectional changes in ocular dominance in adults in accordance with the pull-push model, and long after the termination of the critical period.

Previously we proposed that the pull-push neuromodulation of Hebbian plasticity by the balance of Gs- and Gq-coupled receptors is a metaplasticity mechanism that allows rapid reconfiguration of the plastic state of cortical synapses over a wide range of possibilities, from LTP-only to LTD-only states (Huang et al., 2012). Here we validated the pull-push model in vivo in V1 by demonstrating that manipulations of GPCR signals promote shifts in ocular dominance in the directions predicted by the model. Pairing brief monocular stimulation with the activation of Gq-coupled receptors, predicted to induce an LTD-only state, reduced the cortical responses to the stimulated eye. Conversely, pairing the same monocular stimulation paired with the activation of Gs-coupled receptors, predicted to induce an LTP-only state, enhanced the cortical response to the stimulated eye. The rapid changes induced by these Gq- and Gs-pairings were stable and affected the stimulated eye only, changing ocular dominance in a G-protein specific manner. Importantly, these modifications of cortical responses can be induced in adults, after the end of the critical period, and can ameliorate the imbalance in ocular dominance resulting from prolonged monocular deprivation.

We presented several lines of evidence supporting a role for the pull-push model in cortical plasticity. First, the experiments with applied exogenous agonists and chemogenetics (DREADDs) showing the predicted shifts in ocular dominance indicated that the Gs/Gq-based pull-push metaplasticity can be recruited in vivo. On the other hand, the non-conventional shift in ocular dominance induced by the infusion of a β-adrenergic antagonist during monocular deprivation (see Figure 4), is consistent with a role of endogenous Gs/Gq in controlling the polarity of experience-dependent plasticity. This non-conventional decrease of the open eye response, instead of the typical reduction of the closed-eye response, resembles a similar non-conventional shift in ocular dominance reported to occur when the visual cortex is silenced with GABAergic agonists during the MD (Reiter and Stryker, 1988). However, in our experiment, the β-adrenergic antagonist (propranolol) did not silence the cortical responses. We surmise that, in agreement with a previous study of us (Huang et al., 2012), blocking β-adrenergic receptors was sufficient to shift the endogenous cortical Gs/Gq balance towards Gq enough to bring an LTD-only state. In that scenario, the most active inputs (from the open eye) will be reduced the most. The complementary experiment, inducing an LTP-only state by blocking Gq-GPCRs was not attempted because different Gq-GPCRs, including cholinergic, adrenergic, serotonergic and glutamatergic receptors can substitute each other in enabling LTD (Choi et al., 2005). Consequently, achieving an LTP-only state would require the blockade of too many types of receptors, precluding a simple interpretation of the results. Finally, the cortical nature of the changes underlying the neuromodulators-induced ocular dominance shifts is supported by the ex vivo experiments showing that neuromodulator pairings and monocular deprivation do affects a common set of intracortical synapses. Moreover, in the chemogenetics approach to induce ocular dominance shifts, DREADD transfection was restricted to cortex, indicating that neuromodulation of cortical plasticity is sufficient to alter visual responses.

The crucial role of neuromodulators in experience-dependent plasticity in sensory cortices has been well recognized since the initial observations made by Kasamatsu and Pettigrew, 1976, Pettigrew and Kasamatsu, 1978 that in kittens the depletion of catecholamines prevent deprivation-induced ocular dominance shifts, and that superfusion of norepinephrine promote these changes even in adult cats (Heggelund et al., 1987; Imamura and Kasamatsu, 1988; Imamura and Kasamatsu, 1991). Subsequent studies confirmed similar permissive roles for other neuromodulators, including acetylcholine and serotonin (Bear and Singer, 1986; Gu and Singer, 1995), and also extended these observations to rodent models and to other sensory cortices (Engineer et al., 2013; Golovin and Ward, 2016; Kang et al., 2014; Meunier et al., 2017; Shepard et al., 2015; Weinberger, 2015). The prevailing interpretation emerging from these studies is that neuromodulators gate cortical plasticity by enhancing sensory perception, and by promoting patterns of cortical activity suitable for plasticity induction via controlling network excitability. This is consistent with a wealth of studies documenting that neuromodulators improve perception in vivo (see Gelbard-Sagiv et al., 2018; Jacob and Nienborg, 2018; McBurney-Lin et al., 2019; Nadim and Bucher, 2014 for reviews) also affect cellular intrinsic excitability and synaptic inhibition to gate the induction of Hebbian plasticity in vitro (see Brzosko et al., 2019; Palacios-Filardo and Mellor, 2019; Pawlak et al., 2010 for reviews). We propose an additional and different mode of action: direct control of the expression, not the induction, of Hebbian plasticity via the Gq/Gs based pull-push metaplasticity mechanism that we previously demonstrated in vitro, in slices. The exact contribution of these three distinct types of neuromodulation to naturally occurring plasticity remains to be determined. This is a challenging task considering that the neuromodulatory systems can interact between them, can substitute each other in promoting plasticity (Bear and Singer, 1986), and can stimulate multiple GPCRs, often with opposite actions. One clear example is the case of adrenergic receptors, where the α1- and the β-adrenoreceptors can promote respectively depression or potentiation of the same activated inputs (Figure 1 and Figure 1—figure supplement 1).

The demonstration that the pull-push metaplasticity is operational in vivo has consequences beyond deepening our understanding of how neuromodulators shape cortical plasticity. Pairing monocular stimulation with GPCR agonists could be developed as a tool to bidirectionally manipulate the strength of targeted cortical circuits in a rapid and controlled manner. The neuromodulator pairing elicit stable changes in cortical response comparable in magnitude with those induced by classical deprivation paradigms like MD, but on a faster time scale: hours instead of days (Lehmann and Löwel, 2008). Importantly, the neuromodulator approach readily works in post-critical period adults, at an age when the deleterious effects of long-term monocular deprivation, an established animal model of amblyopia, cannot be reversed by simple manipulations of visual experience. The end of the critical period is thought to result from the maturation of mechanisms that constrain the recruitment of Hebbian and homeostatic plasticity, like the strengthening of GABAergic circuitry, for example (reviewed by Hensch and Quinlan, 2018; Jiang et al., 2005). Consequently, manipulations aimed to restore ocular dominance in adults almost always target the removal of these constrains (Hensch and Quinlan, 2018; Stryker and Löwel, 2018). In contrast, instead of removing constrains, the targeting of specific GPCRs described here is unique, as it is aimed at selecting the polarity and to increase the gain of the expression of synaptic plasticity. Importantly, several other non-invasive manipulations reported to enhance adult cortical plasticity after the critical period, seemingly do it through other mechanisms. For example, dark exposure (He et al., 2007), environmental enrichment (Sale et al., 2007), chronic block of serotonin reuptake (Maya Vetencourt et al., 2008), locomotion (Kaneko et al., 2017), and retinal inactivation (Duffy et al., 2018), are thought to rejuvenate cortical plasticity by decreasing the intracortical inhibition, while cross-modal deprivation is thought to reactivate thalamocortical plasticity (Rodríguez et al., 2018; Teichert et al., 2019). It would be of therapeutical interest to explore complementary synergies between these manipulations and the neuromodulatory pairings in the recovery from long-term monocular deprivation.

All data generated or analysed during this study are included in the manuscript and supporting files.

1. 1. Akhmedov D
   2. Mendoza-Rodriguez MG
   3. Rajendran K
   4. Rossi M
   5. Wess J
   6. Berdeaux R

   (2017) Gs-DREADD Knock-In mice for Tissue-Specific, temporal stimulation of cyclic AMP signaling

   Molecular and Cellular Biology 37:e00584-16.

   https://doi.org/10.1128/MCB.00584-16

   • PubMed
   • Google Scholar
2. 1. Bear MF
   2. Singer W

   (1986) Modulation of visual cortical plasticity by acetylcholine and noradrenaline

   Nature 320:172–176.

   https://doi.org/10.1038/320172a0

   • PubMed
   • Google Scholar
3. 1. Bekkers JM
   2. Clements JD

   (1999) Quantal amplitude and quantal variance of strontium-induced asynchronous EPSCs in rat dentate granule neurons

   The Journal of Physiology 516 ( Pt 1:227–248.

   https://doi.org/10.1111/j.1469-7793.1999.227aa.x

   • PubMed
   • Google Scholar
4. 1. Brzosko Z
   2. Mierau SB
   3. Paulsen O

   (2019) Neuromodulation of Spike-Timing-Dependent plasticity: past, present, and future

   Neuron 103:563–581.

   https://doi.org/10.1016/j.neuron.2019.05.041

   • PubMed
   • Google Scholar
5. 1. Cang J
   2. Kalatsky VA
   3. Löwel S
   4. Stryker MP

   (2005) Optical imaging of the intrinsic signal as a measure of cortical plasticity in the mouse

   Visual Neuroscience 22:685–691.

   https://doi.org/10.1017/S0952523805225178

   • PubMed
   • Google Scholar
6. 1. Choi SY
   2. Chang J
   3. Jiang B
   4. Seol GH
   5. Min SS
   6. Han JS
   7. Shin HS
   8. Gallagher M
   9. Kirkwood A

   (2005) Multiple receptors coupled to phospholipase C gate long-term depression in visual cortex

   Journal of Neuroscience 25:11433–11443.

   https://doi.org/10.1523/JNEUROSCI.4084-05.2005

   • PubMed
   • Google Scholar
7. 1. Duffy KR
   2. Fong MF
   3. Mitchell DE
   4. Bear MF

   (2018) Recovery from the anatomical effects of long-term monocular deprivation in cat lateral geniculate nucleus

   Journal of Comparative Neurology 526:310–323.

   https://doi.org/10.1002/cne.24336

   • PubMed
   • Google Scholar
8. 1. Engineer ND
   2. Møller AR
   3. Kilgard MP

   (2013) Directing neural plasticity to understand and treat tinnitus

   Hearing Research 295:58–66.

   https://doi.org/10.1016/j.heares.2012.10.001

   • PubMed
   • Google Scholar
9. 1. Espinosa JS
   2. Stryker MP

   (2012) Development and plasticity of the primary visual cortex

   Neuron 75:230–249.

   https://doi.org/10.1016/j.neuron.2012.06.009

   • PubMed
   • Google Scholar
10. 1. Foncelle A
    2. Mendes A
    3. Jędrzejewska-Szmek J
    4. Valtcheva S
    5. Berry H
    6. Blackwell KT
    7. Venance L

    (2018) Modulation of Spike-Timing dependent plasticity: towards the inclusion of a third factor in computational models

    Frontiers in Computational Neuroscience 12:49.

    https://doi.org/10.3389/fncom.2018.00049

    • PubMed
    • Google Scholar
11. 1. Frémaux N
    2. Gerstner W

    (2015) Neuromodulated Spike-Timing-Dependent plasticity, and theory of Three-Factor learning rules

    Frontiers in Neural Circuits 9:85.

    https://doi.org/10.3389/fncir.2015.00085

    • PubMed
    • Google Scholar
12. 1. Gelbard-Sagiv H
    2. Magidov E
    3. Sharon H
    4. Hendler T
    5. Nir Y

    (2018) Noradrenaline modulates visual perception and late visually evoked activity

    Current Biology 28:2239–2249.

    https://doi.org/10.1016/j.cub.2018.05.051

    • PubMed
    • Google Scholar
13. 1. Golovin RM
    2. Ward NJ

    (2016) Neuromodulatory influence of norepinephrine during developmental experience-dependent plasticity

    Journal of Neurophysiology 116:1–4.

    https://doi.org/10.1152/jn.00461.2015

    • PubMed
    • Google Scholar
14. 1. Gu Q

    (2002) Neuromodulatory transmitter systems in the cortex and their role in cortical plasticity

    Neuroscience 111:815–835.

    https://doi.org/10.1016/S0306-4522(02)00026-X

    • Google Scholar
15. 1. Gu Q

    (2003) Contribution of acetylcholine to visual cortex plasticity

    Neurobiology of Learning and Memory 80:291–301.

    https://doi.org/10.1016/S1074-7427(03)00073-X

    • PubMed
    • Google Scholar
16. 1. Gu Q
    2. Singer W

    (1995) Involvement of serotonin in developmental plasticity of kitten visual cortex

    European Journal of Neuroscience 7:1146–1153.

    https://doi.org/10.1111/j.1460-9568.1995.tb01104.x

    • PubMed
    • Google Scholar
17. 1. He HY
    2. Ray B
    3. Dennis K
    4. Quinlan EM

    (2007) Experience-dependent recovery of vision following chronic deprivation amblyopia

    Nature Neuroscience 10:1134–1136.

    https://doi.org/10.1038/nn1965

    • PubMed
    • Google Scholar
18. 1. He K
    2. Huertas M
    3. Hong SZ
    4. Tie X
    5. Hell JW
    6. Shouval H
    7. Kirkwood A

    (2015) Distinct eligibility traces for LTP and LTD in cortical synapses

    Neuron 88:528–538.

    https://doi.org/10.1016/j.neuron.2015.09.037

    • PubMed
    • Google Scholar
19. 1. Heggelund P
    2. Imamura K
    3. Kasamatsu T

    (1987) Reduced binocularity in the noradrenaline-infused striate cortex of acutely anesthetized and paralyzed, otherwise normal cats

    Experimental Brain Research 68:593–605.

    https://doi.org/10.1007/BF00249802

    • PubMed
    • Google Scholar
20. 1. Heimel JA
    2. Hartman RJ
    3. Hermans JM
    4. Levelt CN

    (2007) Screening mouse vision with intrinsic signal optical imaging

    European Journal of Neuroscience 25:795–804.

    https://doi.org/10.1111/j.1460-9568.2007.05333.x

    • PubMed
    • Google Scholar
21. 1. Hensch TK
    2. Quinlan EM

    (2018) Critical periods in amblyopia

    Visual Neuroscience 35:E014.

    https://doi.org/10.1017/S0952523817000219

    • PubMed
    • Google Scholar
22. 1. Hofer SB
    2. Mrsic-Flogel TD
    3. Bonhoeffer T
    4. Hübener M

    (2006) Lifelong learning: ocular dominance plasticity in mouse visual cortex

    Current Opinion in Neurobiology 16:451–459.

    https://doi.org/10.1016/j.conb.2006.06.007

    • PubMed
    • Google Scholar
23. 1. Huang S
    2. Gu Y
    3. Quinlan EM
    4. Kirkwood A

    (2010) A refractory period for rejuvenating GABAergic synaptic transmission and ocular dominance plasticity with dark exposure

    Journal of Neuroscience 30:16636–16642.

    https://doi.org/10.1523/JNEUROSCI.4384-10.2010

    • PubMed
    • Google Scholar
24. 1. Huang S
    2. Treviño M
    3. He K
    4. Ardiles A
    5. Pasquale R
    6. Guo Y
    7. Palacios A
    8. Huganir R
    9. Kirkwood A

    (2012) Pull-push neuromodulation of LTP and LTD enables bidirectional experience-induced synaptic scaling in visual cortex

    Neuron 73:497–510.

    https://doi.org/10.1016/j.neuron.2011.11.023

    • PubMed
    • Google Scholar
25. 1. Huang S
    2. Huganir RL
    3. Kirkwood A

    (2013) Adrenergic gating of hebbian spike-timing-dependent plasticity in cortical interneurons

    Journal of Neuroscience 33:13171–13178.

    https://doi.org/10.1523/JNEUROSCI.5741-12.2013

    • PubMed
    • Google Scholar
26. 1. Imamura K
    2. Kasamatsu T

    (1988) Acutely induced shift in ocular dominance during brief monocular exposure: effects of cortical noradrenaline infusion

    Neuroscience Letters 88:57–62.

    https://doi.org/10.1016/0304-3940(88)90315-1

    • PubMed
    • Google Scholar
27. 1. Imamura K
    2. Kasamatsu T

    (1991) Ocular dominance plasticity restored by NA infusion to aplastic visual cortex of anesthetized and paralyzed kittens

    Experimental Brain Research 87:309–318.

    https://doi.org/10.1007/BF00231848

    • PubMed
    • Google Scholar
28. 1. Jacob SN
    2. Nienborg H

    (2018) Monoaminergic neuromodulation of sensory processing

    Frontiers in Neural Circuits 12:51.

    https://doi.org/10.3389/fncir.2018.00051

    • PubMed
    • Google Scholar
29. 1. Jiang B
    2. Huang ZJ
    3. Morales B
    4. Kirkwood A

    (2005) Maturation of GABAergic transmission and the timing of plasticity in visual cortex

    Brain Research Reviews 50:126–133.

    https://doi.org/10.1016/j.brainresrev.2005.05.007

    • PubMed
    • Google Scholar
30. 1. Kalatsky VA
    2. Stryker MP

    (2003) New paradigm for optical imaging: temporally encoded maps of intrinsic signal

    Neuron 38:529–545.

    https://doi.org/10.1016/s0896-6273(03)00286-1

    • PubMed
    • Google Scholar
31. 1. Kaneko M
    2. Fu Y
    3. Stryker MP

    (2017) Locomotion induces Stimulus-Specific response enhancement in adult visual cortex

    The Journal of Neuroscience 37:3532–3543.

    https://doi.org/10.1523/JNEUROSCI.3760-16.2017

    • PubMed
    • Google Scholar
32. 1. Kang JI
    2. Huppé-Gourgues F
    3. Vaucher E

    (2014) Boosting visual cortex function and plasticity with acetylcholine to enhance visual perception

    Frontiers in Systems Neuroscience 8:172.

    https://doi.org/10.3389/fnsys.2014.00172

    • PubMed
    • Google Scholar
33. 1. Kasamatsu T

    (1991) Adrenergic regulation of visuocortical plasticity: a role of the locus coeruleus system

    Progress in Brain Research 88:599–616.

    https://doi.org/10.1016/s0079-6123(08)63837-6

    • PubMed
    • Google Scholar
34. 1. Kasamatsu T
    2. Pettigrew JD

    (1976) Depletion of brain catecholamines: failure of ocular dominance shift after monocular occlusion in kittens

    Science 194:206–209.

    https://doi.org/10.1126/science.959850

    • PubMed
    • Google Scholar
35. 1. Lehmann K
    2. Löwel S

    (2008) Age-dependent ocular dominance plasticity in adult mice

    PLOS ONE 3:e3120.

    https://doi.org/10.1371/journal.pone.0003120

    • PubMed
    • Google Scholar
36. 1. Maffei A
    2. Turrigiano GG

    (2008) Multiple modes of network homeostasis in visual cortical layer 2/3

    Journal of Neuroscience 28:4377–4384.

    https://doi.org/10.1523/JNEUROSCI.5298-07.2008

    • PubMed
    • Google Scholar
37. 1. Maya Vetencourt JF
    2. Sale A
    3. Viegi A
    4. Baroncelli L
    5. De Pasquale R
    6. O'Leary OF
    7. Castrén E
    8. Maffei L

    (2008) The antidepressant fluoxetine restores plasticity in the adult visual cortex

    Science 320:385–388.

    https://doi.org/10.1126/science.1150516

    • PubMed
    • Google Scholar
38. 1. McBurney-Lin J
    2. Lu J
    3. Zuo Y
    4. Yang H

    (2019) Locus coeruleus-norepinephrine modulation of sensory processing and perception: a focused review

    Neuroscience & Biobehavioral Reviews 105:190–199.

    https://doi.org/10.1016/j.neubiorev.2019.06.009

    • PubMed
    • Google Scholar
39. 1. Meunier CN
    2. Chameau P
    3. Fossier PM

    (2017) Modulation of synaptic plasticity in the cortex needs to understand all the players

    Frontiers in Synaptic Neuroscience 9:2.

    https://doi.org/10.3389/fnsyn.2017.00002

    • PubMed
    • Google Scholar
40. 1. Nadim F
    2. Bucher D

    (2014) Neuromodulation of neurons and synapses

    Current Opinion in Neurobiology 29:48–56.

    https://doi.org/10.1016/j.conb.2014.05.003

    • PubMed
    • Google Scholar
41. 1. Nakadate K
    2. Imamura K
    3. Watanabe Y

    (2013) c-Fos activity mapping reveals differential effects of noradrenaline and serotonin depletion on the regulation of ocular dominance plasticity in rats

    Neuroscience 235:1–9.

    https://doi.org/10.1016/j.neuroscience.2013.01.013

    • PubMed
    • Google Scholar
42. 1. Palacios-Filardo J
    2. Mellor JR

    (2019) Neuromodulation of hippocampal long-term synaptic plasticity

    Current Opinion in Neurobiology 54:37–43.

    https://doi.org/10.1016/j.conb.2018.08.009

    • PubMed
    • Google Scholar
43. 1. Pawlak V
    2. Wickens JR
    3. Kirkwood A
    4. Kerr JN

    (2010) Timing is not everything: neuromodulation opens the STDP gate

    Frontiers in Synaptic Neuroscience 2:146.

    https://doi.org/10.3389/fnsyn.2010.00146

    • PubMed
    • Google Scholar
44. 1. Petrus E
    2. Rodriguez G
    3. Patterson R
    4. Connor B
    5. Kanold PO
    6. Lee HK

    (2015) Vision loss shifts the balance of feedforward and intracortical circuits in opposite directions in mouse primary auditory and visual cortices

    Journal of Neuroscience 35:8790–8801.

    https://doi.org/10.1523/JNEUROSCI.4975-14.2015

    • PubMed
    • Google Scholar
45. 1. Pettigrew JD
    2. Kasamatsu T

    (1978) Local perfusion of noradrenaline maintains visual cortical plasticity

    Nature 271:761–763.

    https://doi.org/10.1038/271761a0

    • PubMed
    • Google Scholar
46. 1. Phifer CB
    2. Terry LM

    (1986) Use of hypothermia for general anesthesia in preweanling rodents

    Physiology & Behavior 38:887–890.

    https://doi.org/10.1016/0031-9384(86)90058-2

    • PubMed
    • Google Scholar
47. 1. Pizzorusso T
    2. Medini P
    3. Berardi N
    4. Chierzi S
    5. Fawcett JW
    6. Maffei L

    (2002) Reactivation of ocular dominance plasticity in the adult visual cortex

    Science 298:1248–1251.

    https://doi.org/10.1126/science.1072699

    • PubMed
    • Google Scholar
48. 1. Pizzorusso T
    2. Medini P
    3. Landi S
    4. Baldini S
    5. Berardi N
    6. Maffei L

    (2006) Structural and functional recovery from early monocular deprivation in adult rats

    PNAS 103:8517–8522.

    https://doi.org/10.1073/pnas.0602657103

    • PubMed
    • Google Scholar
49. 1. Reiter HO
    2. Stryker MP

    (1988) Neural plasticity without postsynaptic action potentials: less-active inputs become dominant when kitten visual cortical cells are pharmacologically inhibited

    PNAS 85:3623–3627.

    https://doi.org/10.1073/pnas.85.10.3623

    • PubMed
    • Google Scholar
50. 1. Rodríguez G
    2. Chakraborty D
    3. Schrode KM
    4. Saha R
    5. Uribe I
    6. Lauer AM
    7. Lee HK

    (2018) Cross-Modal reinstatement of thalamocortical plasticity accelerates ocular dominance plasticity in adult mice

    Cell Reports 24:3433–3440.

    https://doi.org/10.1016/j.celrep.2018.08.072

    • PubMed
    • Google Scholar
51. 1. Sale A
    2. Maya Vetencourt JF
    3. Medini P
    4. Cenni MC
    5. Baroncelli L
    6. De Pasquale R
    7. Maffei L

    (2007) Environmental enrichment in adulthood promotes amblyopia recovery through a reduction of intracortical inhibition

    Nature Neuroscience 10:679–681.

    https://doi.org/10.1038/nn1899

    • PubMed
    • Google Scholar
52. 1. Sato M
    2. Stryker MP

    (2008) Distinctive features of adult ocular dominance plasticity

    Journal of Neuroscience 28:10278–10286.

    https://doi.org/10.1523/JNEUROSCI.2451-08.2008

    • PubMed
    • Google Scholar
53. 1. Sawtell NB
    2. Frenkel MY
    3. Philpot BD
    4. Nakazawa K
    5. Tonegawa S
    6. Bear MF

    (2003) NMDA receptor-dependent ocular dominance plasticity in adult visual cortex

    Neuron 38:977–985.

    https://doi.org/10.1016/S0896-6273(03)00323-4

    • PubMed
    • Google Scholar
54. 1. Seol GH
    2. Ziburkus J
    3. Huang S
    4. Song L
    5. Kim IT
    6. Takamiya K
    7. Huganir RL
    8. Lee HK
    9. Kirkwood A

    (2007) Neuromodulators control the polarity of spike-timing-dependent synaptic plasticity

    Neuron 55:919–929.

    https://doi.org/10.1016/j.neuron.2007.08.013

    • PubMed
    • Google Scholar
55. 1. Shepard KN
    2. Liles LC
    3. Weinshenker D
    4. Liu RC

    (2015) Norepinephrine is necessary for experience-dependent plasticity in the developing mouse auditory cortex

    Journal of Neuroscience 35:2432–2437.

    https://doi.org/10.1523/JNEUROSCI.0532-14.2015

    • PubMed
    • Google Scholar
56. 1. Smith GB
    2. Heynen AJ
    3. Bear MF

    (2009) Bidirectional synaptic mechanisms of ocular dominance plasticity in visual cortex

    Philosophical Transactions of the Royal Society B: Biological Sciences 364:357–367.

    https://doi.org/10.1098/rstb.2008.0198

    • Google Scholar
57. 1. Stryker MP
    2. Löwel S

    (2018) Amblyopia: new molecular/pharmacological and environmental approaches

    Visual Neuroscience 35:E018.

    https://doi.org/10.1017/S0952523817000256

    • PubMed
    • Google Scholar
58. 1. Teichert M
    2. Isstas M
    3. Liebmann L
    4. Hübner CA
    5. Wieske F
    6. Winter C
    7. Lehmann K
    8. Bolz J

    (2019) Visual deprivation independent shift of ocular dominance induced by cross-modal plasticity

    PLOS ONE 14:e0213616.

    https://doi.org/10.1371/journal.pone.0213616

    • PubMed
    • Google Scholar
59. 1. Tran T
    2. Bridi M
    3. Koh MT
    4. Gallagher M
    5. Kirkwood A

    (2019) Reduced cognitive performance in aged rats correlates with increased excitation/inhibition ratio in the dentate gyrus in response to lateral entorhinal input

    Neurobiology of Aging 82:120–127.

    https://doi.org/10.1016/j.neurobiolaging.2019.07.010

    • PubMed
    • Google Scholar
60. 1. Weinberger NM

    (2015)

    Handbook of Clinical Neurology

    117–147, New perspectives on the auditory cortex: learning and memory, Handbook of Clinical Neurology, 129, Elsevier, 10.1016/B978-0-444-62630-1.00007-X.

    • Google Scholar

Author details

1. Su Z Hong

   Mind/Brain Institute, Johns Hopkins University, Baltimore, United States

   Contribution

   Conceptualization, Investigation, Visualization, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

2. Shiyong Huang

   Mind/Brain Institute, Johns Hopkins University, Baltimore, United States

   Present address

   Program in Neuroscience, Hussman Institute, Baltimore, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

3. Daniel Severin

   Mind/Brain Institute, Johns Hopkins University, Baltimore, United States

   Contribution

   Investigation

   Competing interests

   No competing interests declared

4. Alfredo Kirkwood

   1. Mind/Brain Institute, Johns Hopkins University, Baltimore, United States
   2. Department of Neuroscience, Johns Hopkins University, Baltimore, United States

   Contribution

   Conceptualization, Resources, Funding acquisition, Writing - review and editing

   For correspondence

   kirkwood@jhu.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9148-9742

• 1,170

  views

• 166

  downloads

• 10

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.