The Diferential Efects Of Brief Environmental Enrichment Following Social Isolation in Rats Part 2
Dec 15, 2023
Open field test
An open field (72 × 72 × 45 cm) was utilized to measure general locomotor activity levels. Each animal was taken to test room 5 before the test and placed in the OFT chamber for another 5 min.
In recent years, more and more scientific studies have shown that there is an inextricable link between motor activity and memory. Different types of sports activities have a significant effect on promoting memory for people of different ages, which is of great significance to our daily study, work, and life.
Exercise activities can stimulate the body's blood circulation and respiratory system and promote metabolism. In this way, the blood vessels in the brain will receive better blood supply, and more oxygen and nutrients will be provided to ensure the normal operation of brain cells. This good physical condition can help us focus better and improve learning and memory abilities. As a result, people who regularly engage in physical activity are generally better able to maintain their memory and mental vitality.
In addition, different types of exercise activities can affect different types of memory. For example, aerobic exercise such as long-distance running can promote the growth of the hippocampus, thereby improving people's spatial memory ability. Fast coordination activities such as playing table tennis can stimulate dance memory and short-term memory. For the elderly, participating in thinking sports such as chess can greatly improve memory in terms of intelligence and spatial cognition.
In addition, exercise activities can further improve memory by reducing stress and improving sleep quality. Stress and insomnia not only affect the blood supply and metabolism of the brain but also make people depressed and exhausted, making them unable to focus and concentrate. Appropriate exercise activities can distract attention, relieve stress on the body and brain, help improve our sleep quality, make it easier for us to focus on learning and work, and improve memory.
To sum up, exercise activities can promote blood circulation and metabolism, improve physical condition and mental health, and thus promote memory improvement. Therefore, we should participate in various types of sports activities in our daily lives to maintain the health of the body and brain and promote the improvement of memory. It can be seen that we need to improve our memory. Cistanche deserticola can significantly improve memory, because Cistanche deserticola can also regulate the balance of neurotransmitters, such as increasing the levels of acetylcholine and growth factors. These substances are very important for memory and learning. In addition, meat can also improve blood flow and promote oxygen delivery, which can ensure that the brain receives sufficient nutrients and energy, thus improving brain vitality and endurance.

Click know supplements to boost memory
Sessions were recorded on video by using the animal tracking software EthoVision (Noldus, Wageningen, NL) to assess the total duration of mobility and specific behavioral patterns, including rearing and thigmotaxis.
Elevated plus maze
An EPM (Handley & Mithani, 1984; Pellow et al., 1985; Pellow & File, 1986) set up at 51 cm above the ground level was used to assess anxiety-like behavior. It consists of a wooden base with four narrow arms (50 × 10 cm).
Two opposite arms are covered with transparent acrylic glass sides and are known as open arms, whereas the other two are closed with wooden sides, leading to substantially darker corridors.
Each animal was placed in the central compartment and left in the maze for 5 min. Total time spent in the center of the maze, in open arms and closed arms, was recorded and calculated with EthoVision. Time spent in open arms indicates an anxiolytic effect while closed arms are associated with anxiety-like behavior (Walf & Frye, 2007).
Water Y‑maze
We utilized a modified version of the water T-maze developed by Del Arco et al. (2007) and validated by Locchi et al. (2007). An acrylic glass Y-maze consisting of three 120° apart arms (45 × 15.5 × 45 cm each) was filled with 30 cm water at 24 ± 0.5 °C to assess spatial working memory performance via spontaneous alternation.
Each rat was tested for 5 days with six consecutive trials per day, separated by an intertrial interval of 30 s. Animals were brought to the test room 5 min before the first trial for familiarization with the environment. In each trial, animals were placed on the far side of the starting arm with their head pointing to the center of the maze, towards which they swam to choose one of the two target arms (Arm A or Arm B).
A small transparent platform was placed 1 cm below the water level in one of the target arms (Arm A or Arm B) in a counterbalanced fashion at the beginning of the first trial and alternated between the two target arms for each trial.

Animals that were not able to locate the platform in 60 s were gently guided toward it by their tail. Following the last trial, they were placed in a small cage to dry for 40 min before being returned to their home cages. Each session was recorded on video using EthoVision. Latency to locate the hidden platform in each trial and the number of wrong arm entries (errors) were coded.
Perfusion‑fixation, tissue processing, and immunohistochemistry
Perfusion fixation of the animals was performed on Day 41, 24 hours after the last behavioral test (WYM Day 5). Animals were removed from their (SI or EE) cages, deeply anesthetized with a ketamine-xylazine solution (100-15 mg/kg, IP), and perfused with 4% depolymerized paraformaldehyde (pH 7.4).
Following overnight post-fixation in the same solution, coronal sections (40-50 μm) were cut with a vibratome (VT1000 S, Leica Biosystems, Nussloch, Germany) and rinsed in phosphate-buffered saline (PBS; pH 7.4).
Expression of the c-Fos protein was revealed by immunohistochemistry to assess the effect of housing conditions on the number of spontaneously active neurons in various brain regions.
Tissue penetration was achieved by adding 0.05% Triton X-100 (pH 7.4) to PBS (PBS-Tx). Sections were treated with hydrogen peroxide (0.6%) for 30 min at room temperature (RT) before being transferred to the blocking solution.
They were blocked with 20% normal goat serum (NGS; Vector Laboratories) in PBS-Tx for 30 min at RT and incubated with an anti-c-Fos antibody (mouse monoclonal, Santa Cruz 8047, 1:500 concentration) in PBS-Tx with 1% NGS for 3 nights at 4 °C. Sections were then rinsed in PBS (3 × 10 min), transferred to a secondary antibody solution (biotinylated anti-mouse IgG, 1:250 in PBS-Tx with 1% NGS), and incubated for 2 h at RT.
Following another series of rinsing, they were incubated with avidin-biotinylated peroxidase (ABC kit, Vector Laboratories) in PBS for 20 min at RT. The peroxidase product emerged with a nickel-enhanced 3,30-Diaminobenzidine tetrahydrochloride hydrate (DAB, Sigma-Aldrich D5637).
Microscopy and cell counting
We processed a total of 48 sections from 12 animals (6 Continuous SI and 6 SI to EE; 4 sections per animal) with good perfusion quality. The number of c-Fos-immunopositive (c-Fos+) nuclei was quantified for the retrosplenial cortex (RSC), agranular perirhinal cortex (Area 35; PRC), lateral nucleus of the amygdala (LA), and basolateral nucleus of the amygdala (BL).
Regions of interest were located by cytological comparison with a rat brain atlas (Paxinos & Watson, 2006). Images were obtained with an epifluorescent microscope (Olympus BX53) equipped with a monochrome CCD camera (Olympus XM10). Analyses were restricted to the tissue selected before immunohistochemistry and no additional sections were processed after data acquisition.
Labeled cells were counted in a semi-automatic fashion. First, the number of c-Fos+ cells in the aforementioned regions was detected and quantified with a cell-counting plugin (ITCN) in ImageJ (Schneider et al., 2012).
The ITCN produced output images showing the detected cells within each region. Two independent scorers blind to the experimental conditions evaluated these images to identify and count false-negative cases (i.e., faintly labeled cells missed by the software). The arithmetic average of these two false-negative cell counts was added to the total number of cells detected by the ITCN for each section.

Results
Weight change
The body weight of the animals was recorded at four-time points, both before (Days 1, 15, and 31) and after the EE manipulation (Day 41). We found an effect of time on body weight (F (3, 42) = 7.69, p < 0.001) and a weighing time group interaction (F (3, 42) = 3.30, p = 0.029, 2 × 4 two-way mixed ANOVA), pointing to a significant weight loss in EE animals following enrichment: weights on Day 1 (M = 324.6, SD = 15.7), Day 15 (M = 334.6, SD = 13.3), and Day 31 (M = 325.5, SD = 21.6) were higher than that of Day 41 (M = 311.9, SD = 14; all ps < 0.05).
There was no such change in the continuous SI group (Day 1, M = 321, SD = 12.5; Day 15, M = 325, SD = 15.5; Day 31, M = 322.3, SD = 15.5; Day 41, M = 320.1, SD = 12.9).
Behavioral despair
We assessed the effects of brief EE manipulation on behavioral despair following SI-induced stress by recording and comparing the overall FST-2 immobility scores (Slattery & Cryan, 2012; Yankelevitch-Yahav et al., 2015).
The immobility level of the SI to EE group (M = 49.04, SD = 21.77) was significantly higher than that observed in the continuous SI group (M = 29.47, SD = 13.04; t (14) = 2.18, p = 0.047, d = 1.09, independent samples t-test; Fig. 2), pointing to behavioral despair in animals exposed to brief EE, and a relative antidepressant effect of continuous SI.
It should be noted that the baseline, i.e., FST-1, immobility scores of the continuous SI (M = 41.32, SD = 17.02) and SI to EE animals (M = 38.18, SD = 11.42) were very similar. Hence, the difference observed in the test phase of the FST was not due to a baseline difference in locomotor activity. Likewise, no alternation in general locomotor activity levels was observed following FST-2, as assessed in the OFT (below).

Locomotor activity and exploratory behavior
We utilized the OFT to assess potential differences in locomotor activity between the continuous SI and SI to EE animals. There was no difference between the control (M = 160.05, SD = 53.95) and experimental animals (M = 206.93, SD = 76.36; t (14) = 1.42, p = 0.178, independent samples t-test; Fig. 3), showing that the metabolic (i.e., weight change) effect of brief EE did not alter overall locomotor activity and interfere with the FST.
Rearing behavior, an indicator of exploratory behavior, did not show a significant difference between the groups either, although SI to EE animals often displayed more rearing (M = 38.75, SD = 31.91) compared with continuous SI animals (M = 18.75, SD = 11.83; t (14) = 1.66, p = 0.119, independent samples t-test). The result did not change when the observations were restricted to the center (SI to EE M = 2.25, SD = 1.75 vs.
continuous SI M = 2.38, SD = 2.77) or the periphery (SI to EE M = 34.25, SD = 34.44 vs. continuous SI M = 16.38, SD = 9.93) of the OFT (all ps > 0.05). Irrespective of the groups, the majority of the rearing behavior was displayed at the periphery, often against the walls (M = 25.31, SD = 25.34) as opposed to the center (i.e., free-standing rearing; M = 2.31, SD = 2.17; t (15) = 3.54, p = 0.003, d = 1.28, paired samples t-test).
Anxiety
Differential rearing and total duration spent at the center versus the periphery of the OFT indicate an alteration in general anxiety levels. Following this observation, we employed a standard anxiety measure-the EPM-and compared the anxiety-like behavior of the continuous SI and SI to EE animals.
We found that the SI to EE group spent significantly more time in the open arms (M = 169.25, SD = 106.59) compared with control animals (M = 60.87, SD = 77.51; t (14) = −2.33, p = 0.036, d = 1.16, independent samples t-test; Fig. 4), indicating an anxiolytic effect of brief enrichment following SI-induced stress.
Spatial working memory
Spatial working memory performance was assessed across five consecutive days in the WYM. We found a significant effect on the test day, as measured by mean latency to locate the hidden escape platform (F (1.47, 20.64) = 12.95, p = 0.001, 2 × 5 two-way mixed ANOVA), revealing that learning was achieved.
Bonferroni corrected posthoc tests showed that latency to locate the platform was significantly higher on the first day (M = 15.26, SD = 10.13) compared with the third (M = 6.79, SD= 2.25), fourth (M = 4.73, SD = 1.44), and fifth (M = 6.29, SD = 2.03) days of the WYM (all ps < 0.05; Fig. 5).
Neither a test day-condition interaction (F (1.47, 20.64) = 2.54, p = 0.115) nor a main effect of the experimental condition (F (1, 14) = 3.87, p = 0.069, 2 × 5 two-way mixed ANOVA) was found.
We analyzed the total number of wrong arm entries (i.e., errors) across trials as an additional measure of working memory performance and found a significant effect of the test day (F (4, 56) = 4.71, p = 0.002, 2 × 5 two-way mixed ANOVA). Bonferroni corrected post-hoc tests revealed that the total number of errors decreased significantly on the fourth day (M = 8.69, SD = 1.82) compared with the first day of the WYM (M = 12.69, SD = 4.27; p < 0.05), indicating learning was achieved.
There was no main effect of the experimental condition (F (1, 14) = 2.46, p = 0.139, 2 × 5 two-way mixed ANOVA) or a test day-condition interaction (F (4, 56) = 1.34, p = 0.269). The error rate analyses indicate that learning was achieved by both groups on the fourth day. However, the SI to EE animals displayed a seemingly better performance in the first 2 days of the WYM (Fig. 5).

This difference in latency to locate the platform became significant on the second day of WYM (SI to EE M = 7.13, SD = 2.63 vs. continuous SI M = 11.09, SD = 4.47; t (14) = 2.17, p = 0.048, d = 1.08, independent samples t-test), pointing to faster learning in the early phase of the memory task.

For more information:1950477648nn@gmail.com






