Enriched Environment and Social Isolation Affect Cognition Ability via Altering Excitatory and Inhibitory Synaptic Density in Mice Hippocampus

The purpose of the study was to examine whether the underlying mechanism of the alteration of cognitive ability and synaptic plasticity induced by the housing environment is associated with the balance of excitatory/inhibitory synaptic density. Enriched environment (EE) and social isolation (SI) are two different housing environment, and one is to give multiple sensory environments, the other is to give monotonous and lonely environment. Male 4-week-old C57 mice were divided into three groups: CON, EE and SI. They were housed in the different cage until 3 months of age. Morris water maze and novel object recognition were performed. Long term potentiation (LTP), depotentiation (DEP) and local field potentials were recorded in the hippocampal perforant pathway and dentate gyrus (DG) region. The data showed that EE enhanced the ability of spatial learning, reversal learning and memory as well as LTP/DEP in the hippocampal DG region. Meanwhile, SI reduced those abilities and the level of LTP/DEP. Moreover, there were higher couplings of both phase–amplitude and phase–phase in the EE group, and lower couplings of them in the SI group compared to that in the CON group. Western blot and immunofluorescence analysis showed that EE significantly enhanced the level of PSD-95, NR2B and DCX; however, SI reduced them but increased GABAARα1 and decreased DCX levels. The data suggests that the cognitive functions, synaptic plasticity, neurogenesis and neuronal oscillatory patterns were significantly impacted by housing environment via possibly changing the balance of excitatory and inhibitory synaptic density.


Introduction
Previous studies have shown that the housing environment can impact human being and animal behaviors and physiological functions. Enriched environment (EE) stimulation is a noninvasive strategy to enhance neuronal plasticity in vivo. Through multiple sensory stimulation (e.g. toys, wheels, bells and tunnels), EE promotes plasticity of experiment animal neuronal circuits, enhances learning and memory ability [1]. In the behavioral experiment, EE could enhance cognitive ability and decrease anxiety [2,3]. In the electrophysiological experiment, EE could induce facilitation of long-term potentiation (LTP) in the hippocampal CA1 [4]. Moreover, EE can cause morphological and structural changes in the nervous system, including the enhancement of the perikaryon volume, the reduction of spontaneous apoptosis of nerve cells and the increase of neurogenesis [5,6]. A number studies show that EE promotes plastic modifications of neuronal network including dendritic growth and branching, the formation of dendritic spines and the formation of new synaptic connections [7][8][9]. On the other hand, a few decades ago, it was well known that long-term social isolation (SI) would be detrimental to human health, such as increasing the risk of vascular and nervous system diseases [10], atherosclerosis, myocardial infarction, ischemic stroke and Alzheimer's disease. SI increases the risk of future cognitive impairment and enhances the rate of memory decline in old age [11,12]. Moreover, SI decreased spatial cognitive ability, synaptic plasticity and hippocampal neurogenesis [13][14][15].
It is well known that synaptic plasticity is the cellular basis of learning and memory [16], which depend on the generation of new junctions between neurons. Mechanisms of synaptic plasticity were related to changes in presynaptic vesicle release and the number, distribution, and sensitivity of postsynaptic receptors. LTP is a continuous increase in synaptic strength through repetitive electrical stimulation, which is believed to be important for mammalian hippocampus functions in the acquisition and consolidation of memories [17]. Depotentiation (DEP) is the reversal of LTP, which is induced immediately by Low-frequency afferent stimulation (LFS) after LTP induction in the hippocampus.
It is thought to correlate with several important physiological functions, such as prevention or elimination of memory storage [18].
Along with the continuous advancement of the electrophysiological studies of brain network, the synchronization of neuronal oscillations is associated with the functional changes of the neuronal network and related to cognitive processes [19]. Traditionally, neuronal oscillations are identified with different frequencies, delta 1-3 Hz, theta 3-8 Hz, alpha 8-13 Hz, beta 13-30 Hz and gamma 30-100 Hz [20]. Each oscillation has its particular physiological function. Recently, many studies showed that the coupling between different frequencies represented a specific physiological process, such as learning and memory, emotion and social behavior [21][22][23]. Compared with the coupling within an identical frequency, cross-frequency coupling directly reflects the process of neuronal network transmission [21]. Phase-amplitude coupling (PAC) and phase-phase coupling (PPC) are two types of cross-frequency coupling where the phase of low-frequency activity modulates the amplitude or phase of high-frequency activity [24,25].
The current study was designed to determine how housing environment affected the cognitive ability of mice and further explored the underlying mechanism. Morris water maze (MWM) and novel object recognition (NOR) were performed to evaluate the degree of cognitive ability in mice. The signals of local field potentials (LFPs) were recorded in the hippocampal DG and PP regions, while modulation index (MI) was applied to measure the phase-amplitude coupling (PAC) and n:m phase locking value (n:m PLV) was used to measure the phase-phase coupling (PPC). Following the recording of LFPs, both LTP and DEP were induced by either theta burst stimulation (TBS) or low frequency stimulation (LFS), respectively. HE staining was used to detect morphology and cell density of hippocampus DG region. The density of DCX and PSD-95 in the hippocampus was determined by immunofluorescence assay. Finally, Western blot was applied to investigate the level of synapse related proteins (SYP and PSD-95) and excitatory and inhibitory receptors (NR2A, NR2B and GABA A R α1 ).

Animals and Treatment
Specific pathogen free male C57BL/6J mice, 4-week-old, purchased from Laboratory Animal Center, Academy of Military Medical Science of People's Liberation Army, and reared in the animal house of Medical School, Nankai University. All experiments were carried out according to the protocol approved by the Committee for Animal Care at Nankai University and in accordance with the practices outlined in the NIH Guide for the Care and Use of Laboratory Animals (20160004).
Animals were randomly divided into three groups, which were control (CON) group (n = 6); EE group (n = 6) and SI group (n = 6). Mice in the EE group were raised in large (60 × 40 × 35 cm) and multilayer space and various toys such as houses, running wheels, hammocks, scales, small bells, ladders and tunnels. Objects were changed twice a week. Animals in the CON group were housed in standard cages (36 × 18 × 14 cm) with six mice/cage without objects. Mice in the SI group were raised in standard cages with one mouse/cage without objects. All animals were housed in different cage until 3 months of age. The schematic representation of the experimental design and the living environment of mice in each group are shown in Fig. 1.

Morris Water Maze Test
Mice in each group were trained and tested with the MWM (RB-100A type, Beijing, China) to examine their spatial learning and memory ability. The test was performed in a circular plastic tank of 1.5 m diameter filled with water kept at 25 °C. A platform (10 cm diameter) was kept 1.5 cm under the surface of the water. The maze was divided into four equal quadrants (I-IV) with two imaginary perpendicular lines crossing in the center of tank.
The MWM test includes four consecutive stages: initial training (IT), space exploring test (SET), reversal training (RT) and reversal exploring test (RET). During the IT Fig. 1 Photograph of the control, enriched environment and social isolation housing cage. a The schematic representation of the experimental design. b Mice in CON group were housed in standard cages (36 × 18 × 14 cm) with 6 mice/cage. c Mice in the EE group were raised in large (60 × 40 × 35 cm) with 6 mice/cage and multilayer space and various toys such as houses, running wheels, hammocks, scales, small bells, ladders and tunnels. Objects were changed twice a week. d Mice in the SI group were raised in standard cages with one mouse/cage without objects (1-5 days) stage, animals were trained to find the hidden platform for 5 consecutive days, four training trials per day. In each trial, every animal was placed into the pool and permitted to search for the submerged platform for 60 s. If a mouse failed to find the platform in 60 s, it was gently guided to the platform location and allowed to stay on it for 10 s, and the escape latency was recorded as 60 s. On the 6th day of the test, the SET stage was carried out by using one trial without the platform after the last session of the IT stage at least 24 h later. After the platform was removed, the mice were released individually into the pool from one of the starting points and allowed to explore the pool for 60 s. The frequency with which each mouse passed the hidden platform and the resident time that each mouse spent in the target quadrant were noted as the result of the spatial memory function, namely platform crossings and time spent in target quadrant. In addition, the other two parameters of swimming speed and distance were also recorded. Finally, the RT stage was conducted for 2 days (7-8 days) in the same way and with the same parameters as that in the IT stage. The difference was that the platform was moved into the opposite quadrant. For the RET stage, the approach and the parameters were similar to those in the SET stage. The mouse's movement was monitored by a CCD camera connected to a personal computer, through which data were collected and analyzed (Ethovision 2.0, Noldus, Wagenigen, Netherlands).

The Novel Object Recognition Test
The test apparatus was a white plastic box (40 × 40 × 35 cm). The objects used in this study were two cuboids (6 × 6 × 4 cm) and a cone (6 × 4 cm), which were different in shape and color but similar in size. Objects were placed in two opposite corners in the box. The mice were acclimated to the apparatus for 10 min one day before training and testing. For the training session, two cuboids were placed in the box and the exploring activity of the mouse was monitored for 10 min by using video camera. The retention session was carried out 2 h after the training session. For the training session, two objects were located in the open box, but a cone replaced one of the cuboid during training. The exploring activity was monitored for 5 min. The objects were cleaned with 10% ethanol between each mouse and session.

In Vivo Electrophysiological Test
Both long-term potentiation (LTP) and DEP between the hippocampal perforant pathway (PP) and dentate gyrus (DG) region were recorded in in vivo electrophysiological experiments, and signals of local field potential (LFPs) were collected as well. The mice were anesthetized with 30% urethane with a dosage of 4 ml/kg and positioned on a stereotaxic frame (SR-6N; Narishige, Japan) for surgery. A proper incision was cut in the scalp and a hole was drilled in the skull for both the recording and stimulating electrodes. According to the mouse brain atlas [26], a concentric bipolar stimulating electrode was carefully inserted into the PP region (3.8 mm posterior to the bregma, 3.0 mm lateral to midline, 1.5 mm ventral below the dura) and another monopolar extracellular stainless steel recording electrode was inserted into the DG region (2.0 mm anterior to the bregma, 1.4 mm lateral to midline, 1.5 mm ventral below the dura), respectively. Test stimuli were delivered to the PP every 30 s at an intensity that evoked a response of 70% of its maximum (range 0.3-0.5 mA, stimulus pulse with 0.2 ms, at 0.03 Hz). After about 10 min, LFPs in DG was recorded by Chart 5.3 software at a sampling rate of 1000 Hz for 10 min. Subsequently, sampling was made under lowfrequency stimulations (0.2 ms at 0.05 Hz) for 20 min as the baseline. After that, theta burst stimulation (TBS, 30 trains of 12 pulses at 200 Hz) was delivered to induce LTP. Following TBS stimulation, the amplitude of excitatory postsynaptic potentials (fEPSPs) was recorded every 60 s for 1 h. After LTP recording, low-frequency stimulation (LFS) (900 pulses of 1 Hz for 15 min) was delivered to induce DEP. Then, fEPSPs was resumed every 60 s for 60 min. All initial measurements were executed in a Clampfit 10.0 (Molecular Devices, Sunnyvale, CA).

Power Spectrum Density (PSD) Analysis
In this study, Multi-taper Spectral Estimations was used to measure the power in the hippocampal PP and DG regions (n = 6). This method applies Slepian sequences which are orthogonal tapers to estimate the power spectrum of a signal. Given a time sequence X t , t = 1, 2, … , N , the multi-taper spectral estimation is: K is the number of the Slepian sequences.u k n , n = 1, 2, ..., N is the kth Slepian sequence and A window length of 20,000 (20 s) with 50% overlap was used to estimate the power spectrum.

Phase-Phase Coupling (PPC)
Phase locking value (PLV) is an important index of phase synchronization, which is widely used to measure the degree of phase variance between two signals [27,28]. In this study, we used a window length of 20,000 (20 s) with 50% overlap to calculated PLV between PP and DG (n = 6).
Firstly, eegfilt.m from EEGLAB toolbox was applied to decompose the original PP and DG LFPs into theta frequency bands (3-8 Hz), alpha frequency bands (8-13 Hz), LG frequency bands  and HG frequency bands (50-80 Hz) [29]. The bandwidth is 1 Hz. The step is 1 Hz. Then, the instantaneous phases of the filtered LFPs in the above frequency bands were attracted by Hilbert transform and were signed as PP (f , t) and DG (f , t) . The frequencydependent PLV was defined as: N was the length of the LFP signal and 1 ∕ Δt was the sampling frequency.
Furthermore, we applied this method to measure the phase-phase coupling between PP alpha rhythm (8)(9)(10)(11)(12)(13) and DG LG  or HG (50-80 Hz) rhythms. The LFPs in PP area were filtered into alpha rhythm. The LFPs in DG area were filtered into LG and HG rhythms, respectively. Then, the instantaneous phases (t), t = 1, 2, … , N of the filtered LFPs in the above frequency bands were obtained by Hilbert transform. N was the length of the signal. Then the radial distance (r) value was defined as: In this study, we calculated the distribution of r n∶m for different rations (1:1,1:2,…,1:20). A larger value of radial distance (r) indicated a more unimodal distribution of n∶m (t) = m * alpha (t) − n * gamma (t) , and suggested a stronger phase coupling. Rayleigh test was used for the uniformity test [30,31].

Phase Amplitude Coupling (PAC)
Modulation index (MI) was used to measure the phase-amplitude coupling (PAC) between PP low frequency rhythm and DG high frequency rhythm (n = 6). The method produced a complex signal Z fph,fam (t) = A fam (t) * exp(i * fph (t)) . In this study, fph (t) represented the instantaneous phase of the low frequency rhythm and A fam (t) represented the instantaneous amplitude of the high frequency rhythm. The MI value is: Surrogate data are produced by shuffling the amplitude time series with a time lag between fph (t) and A fam (t).
The normalized MI was defined as: was the mean value and was the standard deviation of the surrogate data, respectively.
In the study, we used the convolution with complex Morlet wavelets of the depth 7 to generate the phase of PP low frequency bands ( (t) , 1-15 Hz, band = 1 Hz, step = 1 Hz) and DG gamma frequency bands ( A gamma (t) , 30-80 Hz, band = 1 Hz, step = 1 Hz). A window length of 40 s (40,000) with 50% overlap was adopted.

Hematoxylin/Eosin Staining
Their brains were immediately washed with 0.1 M phosphate buffer (pH 7.4). Subsequently, the brains were embedded in OCT compound (Tissue-Tek, Miles) at − 20 °C for tissue sectioning. The coronary sliced in 20 μm thick coronary slices for hematoxylin and eosin (HE) staining. Finally, the sections were photographed on a Leica microscope (Wetzlar, Germany). The density of DG cells was presented by the number of cells per mm 2 area. The results were counted in 3 randomly chosen fields from one slide, with 5 slides of one mouse, and there were 5 mice for each group.

Immunofluorescence
The brains were embedded in OCT compound (Tissue-Tek, Miles) at − 20 °C for tissue sectioning (n = 3). The coronary sliced in 20 μm thick coronary slices for Immunofluorescence staining. And then they were washed with PBS, and then permeabilized with 0.5% Triton X-100 and blocked with 10% NGS for 2 h at room temperature. Subsequently, the cells were incubated with primary antibody (1:500). After washing with PBS, they were incubated with the Alexa 488 or 594 conjugated goat anti-mouse IgG secondary antibody (1:1000). Thereafter, the cell nuclei were stained by DAPI. Samples were examined under a fluorescence microscope (Olympus FV1000, Japan).

Western Blot Assay
The hippocampus of mouse was separated and stored at − 80 °C for the preparation of tissue lysates. The method of protein extraction was described in our previous studies [32,33]. Each hippocampus was mashed with a grinder and 200 μl lysis buffer (Beyotime Biotechnology, Haimen, China) containing 1% Phenyl methane sulfonyl fluoride (PMSF). The Lysates were centrifuged at 12,000 r/min for 20 min at 4 °C. And then the protein concentration was determined using the BCA Protein Assay Kits (Beyotime Biotechnology, Haimen, China). Finally, the supernatant was mixed with loading buffer (ratio is 4:1) and boiled at 100 °C for 10 min.
The method of western blotting was modified on the basis of previous studies [34]. Total proteins were subjected to electrophoresis in 10-13% SDS−PAGE gel, after which they were transferred to a poly vinylidene fluoride (PVDF) membrane. Membranes were then incubated in a 5% milk solution in TBST (Tris-buffered saline with 0.05% Tween 20) at 25 °C, washed and incubated in primary antibody (1:1000) overnight at 4 °C. After washing four times with TBST and once with TBS for 10 min each time, the membranes were incubated with horseradish peroxidase (HRP)conjugated secondary antibodies (1:2000) for 40 min at 25 °C. After washing four times with TBST and once with TBS for 10 min each time, protein band intensities were detected with HRP substrate (Millipore, USA) by using Tanon 5500 chemiluminescent imaging system (Tanon Science & Technology, China). Finally, the quantitation analysis was performed by Photoshop CS6 and compared to the loading control proteins β-actin.

Data and Statistical Analysis
All data were presented as mean ± SEM. Two-way repeated measures ANOVA was used to analyze the results of MWM test and NOR test. All the LFP results, such as PLV, MI and n:m PLV were analyzed by Student's t-test. The statistical differences of the Western blot results, such as PSD-95, SYP, NR 2A, NR 2B, GABA A R α1 were detected by one way ANOVA and post-hoc comparison was done by LSD test. All the analyses were performed using SPSS 17.0 software. Significant differences were taken when P < 0.05.

Performance of EE and SI Mice in MWM Experiment
To evaluate the impact of EE and SI on hippocampal-depend learning and memory ability, the MWM task was performed (Fig. 2a).
During the IT stages, a two-way mixed ANOVA showed a significant effect of housing environment [F (2, 15) = 74.032, P < 0.001] and day [F (4, 12) = 43.081, P < 0.001], but no significant interaction effect among housing environment × day [F (8, 26) = 0.686, P > 0.05]. In the IT stage, animals received 5 days consecutive training to learn the location of a hidden platform. As shown in Fig. 2b, there were lower latencies at day 2-5 (P < 0.05) in the EE group and higher latencies at day 4-5 (P < 0.05) in the SI group than that in the CON group. During the RT stages, a twoway mixed ANOVA showed a significant effect of housing environment [F (2, 15) = 13.866, P < 0.001] and day [F (1, 15) = 20.112, P < 0.001], but no significant interaction effect among housing environment × day [F (8, 26) = 0.212, P > 0.05]. In the RT stage, there was lower latency at day 2 (P < 0.05) in the EE group and higher latency at day 2 (P < 0.05) in the SI group compared to that in the CON group. In addition, there were no significant differences of the average swim speed among these three groups for both days (Fig. 2c, P > 0.05). In the SET and RET stages ( Fig. 2d-g), EE mice preformed higher quadrant occupancy and platform crossing (P < 0.05), while SI mice preformed lower quadrant occupancy and platform crossing (P < 0.01).

Performance of EE and SI Mice in the NOR Test
To examine the effect of EE and SI on object recognition memory, a NOR test was carried out. In both rodents' and primates' brains, recognition memory is strongly related to the hippocampal functional integrity (Fig. 2h) [35]. In the retention session, the time for mice to explore new objects was T1, and the time to explore old objects was T2. The level of recognition index (RI) calculated through the formula: RI = T1/(T1 + T2) × 100% [36]. It was found that there was higher recognition index in the EE group (P < 0.01) and lower recognition index (P < 0.01) in the SI group compared to that in the CON (Fig. 2i). Moreover, the visit times and latency to novel object are higher in the EE group and lower in the SI group than that in the CON group (Figs. 1k and 2j). In addition, there was no statistical difference of the walking speed among these three groups (Fig. 2l).

Measurement of LTP and DEP in the PP-DG Pathway
As shown in Fig. 3a, during 20 min of low-frequency test stimulations, the fEPSPs baseline before TBS was quite stable. After TBS stimulation, the fEPSPs slopes were obviously increased in the following 1 h in each group. Meanwhile, the fEPSPs slopes were visibly decreased in the following 1 h in each group after LFS stimulation. Both LTP and DEP at the last 10 min of fEPSPs slopes were measured. It can be seen that there is higher LTP and lower DEP in the EE group (Fig. 3b-e, P < 0.05) compared to that in the CON group. However, SI mice exhibited lower LTP and higher DEP (Fig. 3b-e, P < 0.01) compared with normal animals.

Power Spectrum of LFP
With the purpose of investigating the power distribution at different frequency bands in either PP or DG area, PSD analysis was performed. As shown in Fig. S1, it was found that there were observable stripes in mice, suggesting that there were relatively stable neuronal activities in these three developmental stages.

Effect of EE and SI on Phase Synchronization Between PP and DG
Synchronous oscillations in physiological rhythms play crucial roles in neuronal communication between different regions. Consequently, the phase synchronization between PP and DG regions in theta, alpha, LG and HG frequency bands was measured by PLV method. As shown in Fig. 4a, the value of PLV at alpha frequency band was higher in the EE group (P < 0.05) and lower in the SI group (P < 0.05) Walking speed in NOR test. *P < 0.05, **P < 0.01, compared with the CON group; ## P < 0.01, ### P < 0.001, compared with the EE group, n = 6 in each group than that in the CON group. There was no significant difference of phase locking values at theta, LG and HG frequency bands in the three groups (P > 0.05).

Effect of EE and SI on Cross Frequency Phase Synchronization Between PP and DG Region
To detect the cross frequency alpha-gamma phase coupling quantitatively, the radial distance values (r) of the circular distribution was measured from the phase differences between m*alpha frequency bands in the PP region and n*LG and n*HG frequency bands in the DG region phases for 20 ratios. As shown in Fig. S2a, there was a distinct peak at n:m = 4:1 ratio, suggesting that there were 4 DG low gamma circles in one PP alpha ring in these three groups. As shown in Fig. 4b, post hoc LSD test showed that at 4:1 ratio, n:m PLV strength significantly increased in EE mice compared with that in CON mice (P < 0.05). At 3:1 and 4:1 ratios, SI mice significantly decreased n:m PLV strength both compared with CON and EE mice (P < 0.05). At 5:1 ratios, SI mice significantly increased n:m PLV strength both compared with CON and EE mice (P < 0.01). As shown in Fig. 4c, EE mice significantly increased the total n:m PLV strength both compared with CON and SI mice (P < 0.05). Moreover, SI mice decreased the total n:m PLV strength compared with CON mice, although the changes did not reach significance (Fig. 4c, P = 0.09).As shown in Fig. S2b there were a distinct peak at n:m = 7:1 and 8:1 ratios between alpha in PP region and HG in DG region in three groups. As shown in Fig. 4d, post hoc LSD test showed that at 8:1 and 9:1 ratios EE mice significantly increased n:m PLV strength both compared with CON and SI mice (P < 0.05). At 7:1 ratio, SI mice significantly decreased n:m PLV strength both compared with CON and EE mice (P < 0.05). As shown in Fig. 4e, EE mice significantly increased the total n:m PLV strength both compared with CON and SI mice (P < 0.001). Moreover, SI mice decreased the total n:m PLV strength compared with CON mice, although the changes did not reach significance (Fig. 4e, P = 0.07).

Effect of EE and SI on Cross Frequency Phase-Amplitude Coupling Between PP and DG Region
In order to measure the cross frequency phase-amplitude coupling between low frequency bands (1-20 Hz) in the Moreover, it was found that the strength of alpha-gamma PAC was much stronger in the EE mice (P < 0.05) and Larger value indicates stronger coupling. g The MI strength of PP alpha and DG gamma in three groups. Data are expressed as mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001, compared with the CON group; # P < 0.05, ## P < 0.01, ### P < 0.001, compared with the EE group, n = 6 in each group visibly weaker in the SI group (P < 0.05) compared to that in the CON group (Fig. 4g).

Effect of EE and SI on Neuronal Density and Neurogenesis of DG Region
HE staining was used to detect the cell density of neurons in DG region. As showed in Fig. 5a, the density of DG cells has no significantly change in the mice reared in different housing environment.
In order to evaluate neurogenesis, immunofluorescence staining was used to detect the DCX density in the hippocampus DG region. As showed in Fig. 5b, the red fluorescence representing DCX is higher in the EE group and lower in the SI group than that in the CON group.

Effect of EE and SI on the Level of SYP and PSD-95
In order to detect the underlying molecular mechanism of the effect of EE and SI on synaptic plasticity in C57 mice, we measured the levels of synaptophysin (SYP) and postsynaptic density protein 95 (PSD-95), which were two commonly used presynaptic and postsynaptic markers, respectively (Fig. 5c). It can be seen that the level of PSD-95 is higher in the EE group and lower in the SI group than that in the CON group (Fig. 5d, P < 0.01). Meanwhile, there were no significant differences of the SYP level between the three groups ( Fig. 5e, P > 0.05).
Furthermore, immunofluorescence staining was used to detect the PSD-95 density in the hippocampus DG and CA3 regions. As showed in Fig. 5f, the green fluorescence representing PSD-95 is higher in the EE group and lower in the SI group than that in the CON group.

Effect of EE and SI on the Level of NR2A, NR2B and GABA A R α1
To examine the effects of EE and SI on the level of postsynaptic excitatory and inhibitory receptors, two excitatory receptors NR2A and NR2B and one inhibitory receptor GABA A R α1 were distinguished (Fig. 6a). As shown in Fig. 6b, the NR2B level was higher in the EE group compared to that in the CON group (P < 0.05). There was no significant difference of NR2A between the EE group and the CON group (Fig. 6c, P = 0.072). In addition, the level of both NR2A (P < 0.05) and NR2B (P < 0.01) was much lower in the SI group than that in the EE group (Fig. 6b,  c). As shown in Fig. 6d, GABA A R α1 levels were higher in the SI group compared to that in the CON group (P < 0.05), but there was no significant difference of the GABA A R α1 level between the EE group and the CON group. The above data suggested that EE mainly influenced excitatory synaptic density and SI mainly affected inhibitory synaptic density.

Discussion
In this study, we performed a wide-ranging analysis of the potential mechanism about the effects of housing environment on cognitive ability. It showed that EE improved learning and memory but SI impaired them, while EE significantly enhanced synaptic plasticity and neurogenesis but SI damaged them. Moreover, EE considerably increased both phase-synchronization and crossfrequency coupling but SI effectively decreased them. In addition, Western data showed that EE increased the level of postsynaptic excitatory receptors, and SI increased the level of postsynaptic inhibitory receptors. It suggests that housing environment performs a significant intervention on the cognitive functions through changing the balance of excitatory and inhibitory synaptic density.

The Effect of Synaptic Plasticity and Neurogenesis on Cognition Ability
A large number of previous studies showed that housing environment could affect the cognitive ability and synaptic plasticity of experimental animals [4,37,38]. The data, obtained from the present study, are in accord with the above results. Moreover, our results showed that housing environment affected the cognitive flexibility. In the RT stage of MWM, the platform was artificially moved into the contralateral quadrant, the mice in the SI group stuck to search the original platform, but the animals in the EE group were able to change the strategy to search the moved platform. Furthermore, housing environment was not only involved in previously acquired behavior strategies but also related to establishing new strategies. LTP and DEP are thought to regulate learning and memory, and other types of experience-dependent plasticity in the mammalian brain [17,39,40]. In addition, LTP is the key to the formation and storage of memory, and long-term depression (LTD) or DEP (LTP reversal) is the mechanism for removing unwanted or pathological memories [41][42][43]. In the present study, either EE or SI significantly modified both LTP and DEP of mice. The results suggested that the regulation of LTP and DEP by housing environment was the fundamental mechanism of the change of cognitive ability and cognitive flexibility in behavioral experiments.
DG is a special region of the hippocampus where neurogenesis persists in this region of adult animal [44]. Dysfunctional hippocampal neurogenesis has been shown to be an important mechanism of cognitive impairment associated with aging and neurodegenerative diseases [45]. In this study, there was no change in the cell density of the DG region in the three groups, suggesting that housing environment did not affect the number of neurons. PSD-95/β-actin band density ratio was measured in the three groups. e SYP/β-actin band density ratio was measured in the three groups. f Representative images of PSD-95 density in DG and CA3 region. PSD-95 was stained with green, and nuclei were stained with blue. Scale bar: 20 μm. *P < 0.05, **P < 0.01, compared with the CON group; ## P < 0.01, compared with the EE group, n = 3 in each group Furthermore, we quantified immature neurons by staining DCX to evaluate neurogenesis. The level of DCX in the hippocampus DG region was significantly affected by EE and SI, suggesting that housing environment regulated the hippocampal neurogenesis neuronal turnover. It is well known that N-methyl-d-aspartate (NMDA) receptor subunit is mainly expressed in immature neurons [46]. The level of NR2B expression in the EE group was higher than that in either the CON group or the SI group, implying that housing environment was involved in neurogenesis.
SYP and PSD-95 were closely related to synaptic plasticity and learning and memory [47,48]. SYP is an important synaptic vesicle membrane protein, and its expression is closely related to the number of presynaptic vesicles [49]. PSD-95 is a postsynaptic scaffold protein, which plays a role in the support and anchoring of postsynaptic receptors such as a-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) and NMDA receptors [50]. In the present study, it was found that both EE and SI changed the level of PSD-95, suggesting that the postsynaptic mechanism was involved in the effect of hosing environment on synaptic plasticity of mice.

The Effect of Neuronal Oscillations on Cognition Ability
The distributed neuronal activity is coordinated by neuronal oscillations, which underlies cognitive processing [20,51]. Previous studies have mostly focused on the coupling between alpha and gamma rhythms on neuronal communication and synaptic plasticity [52]. However, in the present study, we found that the coupling of the alpha-gamma rhythms was more pronounced in the mice reared in different environments. Alpha rhythm plays an important role in inhibiting task-irrelevant brain regions [53,54]. Moreover, alpha rhythms are directly or indirectly associated with the process of working memory, conscious somatosensory perception, visuospatial attention and creative idea generation [55][56][57][58]. In perceptual learning, 64% of the observed variability in the learning outcome can be ascribed to the activity of ongoing alpha frequency band [59]. The evidence show that alpha rhythm is possible to be a potential underlying mechanism of perceptual learning. Moreover, gamma frequency band is closely related to various cognitive processes, including consciousness, perception, attention and memory [60][61][62]. These cognitive processes are possibly associated with alpha-gamma cross frequency PAC [63][64][65]. Therefore, enhancing neuronal coupling between alpha and gamma rhythms plays a significant role in the learning and memory.

The Key Role of Excitatory and Inhibitory Synaptic Density Balance in Synaptic Plasticity
As major postsynaptic excitatory amino acid receptors in the central neuron system, NMDA receptors play vital role in learning and memory [66]. Activation of NMDA receptors can increase the concentration of postsynaptic Ca 2+ and eventually induce LTP and LTD [67,68]. The level of NMDA receptors at the synapse was directly regulated by PSD-95 [69,70]. The cytoplasmic tails of NMDA receptor subunits interact with a prominent PSD-95 [71]. PSD-95 enhances NMDA receptors surface expression by increasing the rate of channel insertion and decreasing Fig. 6 Changes of excitatory/ inhibitory synaptic density balance in three groups. a Results are immunoblots from single representative experiments of NR2B, NR 2A and GABA A R α1 . b NR2B/β-actin band density ratio was measured in the three groups. c NR2A/βactin band density ratio was measured in the three groups. d GABA A R α1 /β-actin band density ratio was measured in the three groups. Data are expressed as mean ± SEM. *P < 0.05, **P < 0.01, compared with the CON group; # P < 0.05, ## P < 0.01, compared with the EE group, n = 3 in each group the rate of channel internalization [72]. It can be seen that EE enhances the level of NMDA receptors, especially for NR2B, which may be associated with the increase of PSD-95 density.
GABA A receptors are involved in cognitive processes. The enhancement of GABA A receptors significantly impaired memory ability and the reduction of GABA A receptors effectively facilitate it in mice [73]. The synaptic density in the visual cortex pyramidal GABAergic neurons of the dark reared mice was significantly enhanced [74]. In addition, the activation of GABAergic neurons caused depression symptoms in mice, while the inhibition of GABAergic neurons in depression model mice significantly improved depression symptoms [75]. In addition, knocking out the α4 subunit of the GABA A receptors could improve the decline in synaptic plasticity and spatial cognitive ability in adolescence [76]. In this study, the increase of GABA A receptors level may be a possible mechanism of synaptic plasticity and learning and memory impairment in SI mice.
Excitatory and inhibitory synapses have a large difference in distribution and structure. Glutamatergic synapses are mainly found in the dendritic spines [77], while GABAergic synapses mainly distributed in the dendritic skeleton, the cell body and the neurite [78]. Excitatory synapses contain a postsynaptic density (PSD) region, whereas inhibitory synapses do not have this characteristic [79]. The information transfer in the brain depends on the balance between excitatory and inhibitory functions of the neuronal network [80]. The excitatory and inhibitory balance is essential for brain function and may be of particular importance to cognition ability. At the level of a single neuron, the balance is involved in the ratio of excitatory and inhibitory synaptic density. The activity of glutamatergic synapses can make the cell polarization and increase the probability of action potential evoked; and the GABAergic synapses are just the opposite [81]. Moreover, GABAergic neurons are involved in the generation of gamma oscillations [82]. The interaction between glutamatergic and GABAergic neurons has great relevance for oscillation coupling in low-frequency and high-frequency [83]. Thus, the balance of excitatory and inhibitory synaptic density is directly related to synaptic plasticity and neuronal phase-coupling in the housing environment.
However, neuromodulation systems such as that operated by adenosine A2AR can format memory and plasticity in the absence of any alterations of synapse morphology or of glutamatergic mediators [84][85][86]. Therefore, a further study is to explore whether there are other mechanisms involved in the change of animal behavior caused by housing environment. Considering that EE is not a clear concept, more studies have used short-term or intermittent EE [87]. Therefore, we need to investigate the effects of EE on cognition and synaptic plasticity at the term that is different from the present study.

Conclusion
In summary, the study aimed to investigate the effects of housing environment on cognitive ability and synaptic plasticity in C57 mice, and to explore its potential molecular mechanism. The data suggested that the cognitive ability, synaptic plasticity, neurogenesis and the pattern of neuronal activities were significantly impacted by housing environment through changing the balance of excitatory and inhibitory synaptic density. The results will help to explore the formation mechanism and a safe and effective treatment in certain nerve injuries and neurodegenerative diseases.