Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Oct 1.
Published in final edited form as: J Psychiatr Res. 2026 Jul 3;201:507–517. doi: 10.1016/j.jpsychires.2026.07.002

Parvalbumin and anxiety across development in female offspring of the MAM neurodevelopmental model of schizophrenia

Sofia E Gurgel 1,2, Cynthia Kumaran 1,3, Daniela L Uliana 1, Anthony A Grace 1
PMCID: PMC13617632  NIHMSID: NIHMS2209806  PMID: 42413186

1. Introduction

Schizophrenia is a neurodevelopmental disorder that affects ~1% of the population worldwide (Maynard et al., 2001). It is a condition marked by positive, negative, and cognitive symptoms often accompanied by heightened anxiety (Andreasen, 1995; Lodge & Grace, 2008). High levels of anxiety are reported in adolescents at high risk for schizophrenia (Owens et al., 2005; Yung et al., 2005), and adolescents who convert to psychosis later in life showed higher sensitivity and intolerance to stress as well as heightened anxiety levels (Corcoran et al., 2012; Devylder et al., 2013; Owens et al., 2005; Walker et al., 2010; Yung et al., 2005). Increased anxiety states are also observed in preclinical models relevant to the study of schizophrenia, such as the methylazoxymethanol acetate (MAM) developmental disruption model (Du & Grace, 2013). In this model, MAM is administered to pregnant rats at gestational day 17, leading to neurodevelopmental disruptions in the offspring that include reduced hippocampal volume, hyperdopaminergic activity, and anxiety, which mirror structural and physiological abnormalities observed in individuals with schizophrenia (Flagstad et al., 2004; Lodge & Grace, 2009, 2011; Moore et al., 2006). Anxiety-like behaviors in male MAM rats have been previously demonstrated to emerge during adolescence (Du & Grace, 2013). However, the preclinical research predominantly focused on male subjects, despite growing evidence that schizophrenia exhibits sex differences in age of onset, symptom severity, and response to treatment (Li et al., 2022).

Schizophrenia exhibits well-established sex differences, with males typically showing an earlier onset of symptoms usually in their early 20s and greater severity of negative and cognitive impairments, whereas females tend to have a later onset, with peak symptomatology less pronounced and more broadly distributed, with relatively higher incidence emerging again in midlife (Jauhar et al., 2022). This is typically associated with relatively higher levels of affective symptoms, including anxiety (Abel et al., 2010; Emsley et al., 1999; Li et al., 2022). These differences suggest that neurodevelopmental trajectories during puberty and adolescence may differentially influence disease progression across sexes. While neurobiological alterations are consistently observed in schizophrenia in both clinical and preclinical studies for the adult stage, the developmental timing and sex-specific mechanisms underlying these changes remain incompletely understood. For instance, female MAM rats differ from males in parvalbumin-expressing interneurons (PV) in the ventral hippocampus (vHIP) (Perez et al., 2019). PV interneurons regulate gamma rhythms essential for higher-order cognitive functions (Marín, 2024). These neurons are closely associated with perineuronal nets (PNNs) that are lattice-like three-dimensional structures that envelop and stabilize PV interneurons (Kaushik et al., 2021). Deficits in PV interneurons, along with abnormalities in gamma oscillations, are characteristic features of schizophrenia, contributing to cognitive and neural dysfunction (Kaushik et al., 2021). In fact, MAM gestational treatment decreases hippocampal PV levels in both sexes (Perez et al., 2019). However, the neurodevelopmental PV changes within the vHip and other areas are still understudied in females.

The vHIP is of particular interest in schizophrenia because it plays a central role in regulating emotional behavior and stress responses. For instance, hyperactivity in the vHIP is observed in female and male rats on the MAM model (Uliana et al., 2025) which is known to drive the hyperdopaminergic state in this model; a hallmark of psychosis-like states (Howes et al., 2009; Lodge & Grace, 2008, 2011; “Neurobiology of Dopamine in Schizophrenia,” 2007). Moreover, reductions in PV-expressing interneurons within the vHIP are associated with impaired inhibitory control (Hijazi et al., 2023), contributing to hippocampal disinhibition and downstream dopaminergic dysregulation. The PV dysfunctions in the vHip could be a product of changes in activity of it inputs areas during neurodevelopment, such as basolateral amygdala (BLA) and nucleus reuniens of thalamus (RE) (Huff et al., 2016; Vertes et al., 2007). Both the BLA and RE send direct projections to vHip and are associated with behavioral regulation, including anxiety. The RE is a thalamic area that is critically regulated by the thalamic reticular nucleus (TRN) (Abel et al., 2010; Li et al., 2022); a GABAergic region that provides inhibitory regulation of RE activity, as it has enriched expression of PV (Hou et al., 2016; Zimmerman & Grace, 2018a). Therefore, the neurodevelopmental disruption of TRN in regulating RE excitability could allow it to overexcite the vHip during critical period of development. That ultimately could be the source for its PV loss in the vHip. These findings support the rationale for assessing PV/PNN expression in these areas, as their dysfunction may contribute to broader hippocampal circuit alterations in schizophrenia.

Understanding the disruptions in PV and PNN structures offers key insights into the mechanisms underlying the pathophysiology of schizophrenia. This study aimed to evaluate the expression of PV/PNN in vHIP, BLA, and TRN areas along with the anxiety behaviors in female rats during development, as anxiety seems to be present early in the disease state. Moreover, our goal was to address the gap in the literature on sex differences in schizophrenia models.

2. Materials and Methods

2.1. Animals

All procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals by the USPHS and approved by the University of Pittsburgh Institutional Animal Care and Use Committee. Pregnant Sprague-Dawley dams were obtained from Envigo (Indianapolis) on GD 15 and administered the mitotoxin MAM (20 mg/kg, i.p.; Midwest Research Institute, Kansas City, MO) or saline (1 ml/Kg) on GD 17. Litters were weaned on postnatal day 21 (PD21) and housed in pairs. Only female offspring were used. Animals were housed in a normal light cycle (lights on 7 am to 7 pm), humidity and temperature (24°C) controlled-room, water and food available ad libitum.

Twelve animals (6 saline and 6 MAM rats) were used for EPM test and immunohistochemistry at each developmental time point (PD 31, PD 41, PD 51, and PD75; Figure 1a), totaling 48 animals. These time points were selected to capture key stages of neurodevelopment: PD31 corresponds to a peripubertal stage prior to puberty onset in females, PD41 and PD51 represent the periadolescent transition, and PD75 reflects young adulthood (Caballero et al., 2014; Drzewiecki et al., 2020). This design allows for the assessment of anxiety-like behavior and PV/PNN expression across critical developmental windows. For open field (OF) test, 19 saline and 22 MAM rats were used, totaling 41 rats. The OF experiment was carried out to evaluate further the anxiety and locomotion effects in female saline and MAM rats. Due to animal constraints, only the ages PD31, PD51, and PD75 were evaluated for the OF test. Two pups per litter were used for each experimental groups (2 saline-treated and 2 MAM-treated) to ensure a balanced representation across conditions.

Figure 1.

Figure 1.

Open in a new tab

Experimental design and EPM results. (a) Timeline of experimental procedures. (b) Saline rats at PD 75 showed an increase in the percentage of entries into the open arms (OA) when compared to saline rats at PD 31, PD 41, and PD 51. MAM rats at PD75 showed a decrease in percentage of entries into the OA of the maze when compared to saline controls, however MAM rats at PD 51 showed an increase in percentage of entries into the OA when compared to saline controls. (c) Saline rats at PD 75 showed an increase in the percentage of time spent in the OA when compared to saline rats at PD 31, PD 41, and PD 51. MAM rats at PD 75 and PD 31 showed a decrease in percentage of time spent the OA of the maze when compared to saline controls. However, MAM rats at PD 41 showed an increase in percentage of time spent the OA of the maze when compared MAM rats at PD 31 and PD 51. (d). MAM rats at PD 51 showed an increase in total number of entries into either arm of the maze when compared to saline controls. Significant differences between conditions (saline vs. MAM) and age groups are denoted: *p<0.05, **p<0.01, ***p<0.001 for the same condition at different ages; #p<0.05 for saline vs. MAM within the same age group. Data points represent individual animals, and bars show group means ± SEM.

To avoid introducing additional stress that could confound behavioral/cellular outcomes and an insufficient number of rats to reach statistical power, pubertal stage was not directly assessed (e.g., via vaginal cytology, daily animal manipulation). Instead, animals were categorized using age-based developmental windows, with PD31 considered a pre-pubertal time point based on normative developmental data for female Sprague-Dawley rats. The estrous cycle was evaluated for the PD75 in the OF experiment due to the sufficient number of rats for this stage. The cycles were separated into Metestrus/Diestrus and Estrous/Proestrus based on the low and high levels, respectively, of estrogen and progesterone (Lovick & Zangrossi, 2021).

2.2. Elevated Plus Maze Test (EPM)

Animals were first habituated to the testing room for 30 minutes then run in the EPM. The apparatus had four elevated arms (50 cm above the floor), 50 cm long and 10 cm wide, arranged in a cross-like pattern, with two opposite arms enclosed by 40 cm high opaque walls, two open with a lip (1 mm thick and 5 mm high) and a central platform at their intersection (10 × 10 cm2) that permitted access to any of the four arms. Rats were introduced to the central area facing an open arm, and their movements were recorded for 5 minutes. The time spent in the open arms relative to that in the closed arms was used as an index of anxiety-like behavior. Time and entries were scored by 1 experimenter by hand. Brains were collected immediately after the EPM test.

2.3. Tissue Preparation and Immunohistochemistry

Rats were anesthetized after the EPM Test with Fatal Plus (0.1 mL/100g, i.p.; Vortech Pharmaceutical) and perfused transcardially with 0.1M phosphate-buffered saline (PBS) followed by 4% paraformaldehyde in 0.1M PBS using infusion pumps. Brain sections were processed based on previously published protocols (Zhu & Grace, 2023) and sliced using a cryostat (CryoStar NX50, Thermo Scientific) into 40 μm coronal sections. The primary antibodies included PV (1:500, Sigma, catalog #P3088-.2ML) and Wisteria floribunda agglutinin (WFA, 1:2000, Fisher, catalog #NC1042310). The secondary antibodies included goat anti-mouse 594 (G&M 594, 1:500, Abcam inc, catalog #ab150116–500ug) and streptavidin 488 (Strep 488, 1:500, Life Technologies Corp., catalog #S32354).

2.4. Image Acquisition

Images were acquired using an Olympus BX51 microscope with a Hamamatsu Orca-ER camera. Images were captured using a 4× objective lens to establish a reference for regional boundaries. For quantitative analysis, cell counting was performed under a 10× objective lens by a blinded researcher. On the 4x images, target regions were identified based on DAPI staining patterns, with reference to the Rat Brain in Stereotaxic Coordinates (Paxinos & Watson, 1982).

Colocalization analysis of PV and PNN wasn’t performed due to limitations in visualization. The staining didn’t provide sufficient clarity for identifying PV and PNN neurons without channel splitting.

2.5. Cell counting and quantification

On 10x images (size: 909 × 692 μm), a 0.2041 mm2 counting frame was applied to target the basal nucleus of the BLA, a 0.1823 mm2 counting frame was used to target the ventral subiculum of the vHIP, and a 0.2021 mm2 counting frame was used to target the TRN. Cell counting of PV and PNN was performed separately and manually with the use of Fiji, an open-source image analysis platform based on ImageJ. Cell counting was carried out bilaterally in a balanced manner, with equal region representation from the left and right hemispheres. A mean cell count (averaged across 5–6 images/rat) was calculated to indicate the expression of each marker in each animal.

2.6. Open Field (OF)

Rats were tested in an open-field chamber to determine their anxiety and locomotor activity. Beam breaks were recorded using TruScan software (Coulbourn Instruments) to measure total locomotion and locomotion pattern (center and margin). Spontaneous activity was recorded for 10 minutes. Distance travelled in the center of the arena was used as a measure of anxiety-like behavior, as rodents avoid open, exposed areas and preferentially remain along the periphery/margin of the field (Carter & Shieh, 2015; Kraeuter et al., 2019).

2.7. Statistical Analysis

Statistical tests were performed using Prism 10.4.0 (GraphPad, La Jolla, CA). All data were tested for normality using the Shapiro-Wilk test and were confirmed to meet the assumption of normal distribution. For datasets with more than two groups and a normal distribution, a two-way ANOVA was performed, with treatment (Saline vs. MAM) and age (PD 31, PD 41, PD 51, PD 75) as the main factors. Tukey’s post hoc tests were performed following significant differences discovered by ANOVA. Data is expressed as “mean −/+ standard error of the mean (SEM)” and p<0.05 was considered significant.

3. Results

Full statistical analyses, including F values, p values, degrees of freedom, and sample sizes, are presented in Table 1.

Table 1.

Statistical analysis for the behavioral and immunofluorescence endpoints.

Outcome measure Region / Task Effect df F value p value Significant post hoc comparisons (Tukey’s unless noted)
% Open-arm entries EPM Age 3,40 5.005 0.0049 Saline: PD75 > PD31 (p=0.0131), PD41 (p=0.0021), PD51 (p<0.0001)
Treatment 1,40 0.06759 0.7962 None
Age × Treatment 3,40 4.795 0.006 PD75: Saline > MAM (p=0.0158); PD51: MAM > Saline (p=0.0223)
% Time in open arms EPM Age 3,40 6 0.0017 Saline: PD75 > PD31 (p=0.0031), PD41 (p=0.0015), PD51 (p=0.0048)
Treatment 1,40 11.71 0.0014 PD75: Saline > MAM (p=0.0002); PD31: Saline > MAM (p=0.0498)
Age × Treatment 3,40 4.9 0.0053 MAM: PD41 > PD31 (p=0.0229), PD51 (p=0.0445)
Total entries EPM Treatment 1,40 1.676 0.2029 PD51: MAM > Saline (p=0.0398)
Age 3,40 0.3302 0.8035 None
Age × Treatment 3,40 1.382 0.2621 None
PV density BLA Age 3,40 1 0.3919 None
Treatment 1,40 0.7 0.399 PD41: MAM > Saline (p=0.0304)
Age × Treatment 3,40 1.5 0.2067 None
PNN density BLA Age 3,40 4 0.0129 None
Treatment 1,40 2.1 0.1517 None
Age × Treatment 3,40 0.3 0.7862 None
PV density TRN Age 3,40 26.16 <0.0001 Saline: PD51 > PD31 (p<0.0001), PD41 (p<0.0001); PD75 > PD31 (p=0.0014), PD41 (p=0.0013)
Treatment 1,40 0.5331 0.4696 None
Age × Treatment 3,40 3.867 0.0161 PD51: Saline > MAM (p<0.01)
PNN density TRN Age 3,40 15 <0.0001 Saline: PD31 < PD41 (p=0.0132), PD75 (p=0.0258); MAM: PD31 < PD41 (p=0.0008), PD51 (p<0.0001), PD75 (p=0.0002)
Treatment 1,40 4.5 0.0392 PD31: Saline > MAM (p<0.05)
Age × Treatment 3,40 2.9 0.0426 —
PV density vHIP Age 3,39 0.7 0.5251 None
Treatment 1,39 4 0.052 PD75: Saline > MAM (p<0.01)
Age × Treatment 3,39 2 0.1162 None
PNN density vHIP Age 3,39 12.8 <0.0001 Saline: PD75 > PD31 (p=0.0350), PD41 (p<0.0001), PD51 (p=0.0105); MAM: PD75 > PD41 (p=0.0122)
Treatment 1,39 5.6 0.0221 PD75: Saline > MAM (p<0.05)
Age × Treatment 3,39 0.9 0.4209 None
Open in a new tab

Two-way ANOVA was used to assess the effects of age and treatment, followed by Tukey’s post hoc tests where appropriate. Only statistically significant post hoc comparisons are reported. Exact p values are shown unless p < 0.0001.

3.1. Percentage of Entries into Open Arms - EPM

Age significantly influenced the percentage of entries into the open arms of the EPM, with a treatment-dependent effect (Table 1). In saline-treated rats, PD75 animals showed a higher proportion of open-arm entries compared to all younger ages (Figure 1b). In contrast, no age-dependent differences were observed within the MAM group. Between-group comparisons revealed reduced open-arm entries in MAM-treated rats relative to saline controls at PD75, whereas MAM-treated rats exhibited increased open-arm entries at PD51 (Figure 1b).

3.2. Percentage of Time Spent on Open Arms - EPM

Both age and MAM treatment significantly affected the percentage of time spent in the open arms, with a significant interaction between these factors (Table 1). Within the saline group, PD75 rats spent more time in the open arms compared to all earlier developmental stages (Figure 1c). In the MAM group, time spent in the open arms was reduced at PD31 and PD51 relative to PD41. Between-group comparisons showed that MAM-treated rats spent less time in the open arms than saline controls at PD75 and PD31, with no significant differences at PD41 or PD51 (Figure 1c).

3.3. Total Number of Entries - EPM

Total arm entries in the EPM were not significantly influenced by age or treatment overall (Table 1). However, MAM-treated rats exhibited a higher number of total entries compared to saline-treated controls at PD51 (Figure 1d). No other within-group or between-group differences were observed.

3.4. Changes in PV neurons and PNN in the BLA

The density of PV-expressing neurons in the BLA did not show significant overall effects of age or MAM treatment (Table 1). Nevertheless, MAM-treated rats displayed a higher PV neuron density compared to saline-treated controls at PD41 (Figure 2c).

Figure 2.

Figure 2.

Open in a new tab

PV and PNN densities in the BLA across developmental periods in saline- and MAM-treated rats. (a) immunofluorescence image of the BLA in 2x magnification (b) immunofluorescence image of the BLA in 10x magnification (c) PV neuron density (PV/mm2) decreased from PD 31 to PD 51 in both groups. At PD 41, MAM-treated rats exhibited significantly higher PV density compared to saline-treated rats (*p < 0.05). (d) PNN density (PNN/mm2) also declined from PD 31 to PD 51. No significant differences were observed between saline- and MAM-treated groups for PNN density at any time point. Data are expressed as mean ± SEM.

PNN density in the BLA varied across development but did not differ between treatment groups at any developmental stage (Figure 2d). No significant age-dependent differences were observed within treatment groups.

3.5. Changes in PV neurons and PNN in the TRN

In the TRN, PV neuron density exhibited robust age-dependent changes and a significant interaction between age and treatment (Table 1). Saline-treated rats showed increased PV density at later developmental stages compared to earlier time points, whereas MAM-treated rats displayed a blunted developmental increase. Between-group differences were evident at PD51, with MAM-treated rats exhibiting reduced PV density relative to saline controls (Figure 3c).

Figure 3.

Figure 3.

Open in a new tab

PV and PNN densities in the TRN across developmental periods in saline- and MAM-treated rats. (a) immunofluorescence image of the TRN in 2x magnification (b) immunofluorescence image of the TRN in 10x magnification (c) PV density (PV/mm2) increased progressively from PD 31 to PD 75 in both groups. MAM-treated rats showed significantly lower PV density compared to saline-treated controls at PD 51 (*p < 0.05). (d) PNN density (PNN/mm2) also increased across development, with MAM-treated rats exhibiting significantly lower PNN density compared to saline-treated rats at PD 31 (*p < 0.05). By PD 75, no significant differences in PNN density were observed between groups. Data are presented as mean ± SEM.

PNN density in the TRN was also significantly modulated by age and treatment (Table 1). MAM-treated rats showed reduced PNN density compared to saline controls at PD31, while no treatment differences were observed at later ages (Figure 3d). Within-group analyses revealed a developmental increase in PNN density in both saline- and MAM-treated rats.

3.6. Changes in PV neurons and PNN in the vHIP

PV neuron density in the vHIP did not show significant overall effects of age or treatment (Table 1). However, saline-treated rats exhibited higher PV density compared to MAM-treated rats at PD75 (Figure 4c). No age-dependent differences were observed within either treatment group.

Figure 4.

Figure 4.

Open in a new tab

PV and PNN densities in the (vHIP) across developmental periods in saline- and MAM-treated rats. (a) immunofluorescence image of the vHIP in 2x magnification (b) immunofluorescence image of the vHIP in 10x magnification (c) PV neuron density (PV/mm2) remained relatively stable in MAM-treated rats but increased significantly in saline-treated rats by PD 75, but not MAM-treated group (*p < 0.01). (d) PNN density (PNN/mm2) increased steadily across development in both groups, but MAM-treated rats exhibited significantly lower PNN density compared to saline-treated controls at PD 75 (*p < 0.05). Data are presented as mean ± SEM.

PNN density in the vHIP increased across development and was reduced in MAM-treated rats relative to saline controls (Table 1). Post hoc analyses indicated that this treatment difference emerged at PD75 (Figure 4d). Developmental increases in PNN density were observed within both treatment groups.

3.7. Correlation

To investigate potential relationships between significant immunohistochemical findings and behavioral outcomes in the EPM, we performed correlation analysis. Among the various comparisons (Table 2), we found no significant correlations except for the relationship between PNN expression in TRN and anxiety-related behavior represented by an increase in the percentage of time spent on the open arms of the EPM at PD31 in the MAM-treated group (Figure 5).

Table 2.

Statistical analysis of the correlation between statistically significant PV, PNN immuno endpoints, and the EPM measures.

Variables % of Time in the Open Arms % of Entries in the Open Arms Total Entries (N)
PD31 Saline: r = 0.126, r = 0.125, r = 0.306,
 PNN TRN R2 = 0.0159, R2 = 0.0156, R2 = 0.0939,
 (n = 6) p = 0.812 p = 0.814 p = 0.555
PD31 MAM: r¼0.822, r = 0.697, r = 0.354,
 PNN TRN R2¼0.676, R2 = 0.486, R2 = 0.125,
 (n = 6) p¼0.045 * p = 0.123 p = 0.491
PD41 Saline: r = 0.0012, r = 0.406, r = 0.00098,
 PV BLA R2 = 1.42e-006, R2 = 0.165, R2 = 9.68e-007,
 (n = 6) p = 0.998 p = 0.424 p = 0.998
PD41 MAM: r = 0.655, r = −0.031, r = −0.359,
 PV BLA R2 = 0.429, R2 = 0.00095, R2 = 0.129,
 (n = 6) p = 0.158 p = 0.954 p = 0.483
PD51 Saline: r = 0.795, r = 0.497, r = 0.675,
 PV TRN R2 = 0.632, R2 = 0.247, R2 = 0.456,
 (n = 6) p = 0.059 p = 0.316 p = 0.141
PD51 MAM: r = −0.544, r = −0.263, r = −0.508,
 PV TRN R2 = 0.296, R2 = 0.069, R2 = 0.258,
 (n = 6) p = 0.264 p = 0.614 p = 0.303
PD75 Saline: r = −0.067, r = 0.508, r = −0.063,
 PV vHip R2 = 0.0045, R2 = 0.258, R2 = 0.0039,
 (n = 6) p = 0.899 p = 0.303 p = 0.905
PD75 MAM: r = −0.259, r = −0.275, r = 0.473,
 PV vHip R2 = 0.067, R2 = 0.075, R2 = 0.224,
 (n = 6) p = 0.621 p = 0.598 p = 0.343
PD75 Saline: r = −0.678, r = −0.057, r = −0.384,
 PNN vHip R2 = 0.459, R2 = 0.0033, R2 = 0.148,
 (n = 6) p = 0.139 p = 0.914 p = 0.452
PD75 MAM: r = 0.0095, r = 0.434, r = −0.452,
 PNN vHip R2 = 8.99e-005, R2 = 0.189, R2 = 0.204,
 (n = 6) p = 0.986 p = 0.389 p = 0.368
Open in a new tab

PD: postnatal day; MAM: methylazoxymethanol acetate; PV: parvalbumin in-terneurons; PNN: perineuronal nets; EPM: elevated plus maze.

Figure 5.

Figure 5.

Open in a new tab

A linear regression analysis revealed a significant positive correlation between PNN count in the TRN and the percentage of time spent in the open arms (% Time OA) of the elevated plus maze. Higher PNN expression was associated with increased % Time OA (R2 = 0.6762), indicative of reduced anxiety-like behavior. No significant correlations were found with % Entries OA or Total Entries (N).

Our analysis revealed a positive correlation between the percentage of time spent in the open arms (% Time OA) of the EPM and PNN expression in the TRN (r=0.822R2 = 0.676, p=0.045).

3.8. Total locomotion – OF

Analysis of total locomotion in the OF demonstrated a significant effect of treatment (MAM) and interaction between age and treatment (Table 1). Poshoc indicated that female MAM rats had increased total distance travelled compared with saline at PD31 and PD51 (Figure 6b). At PD75, saline rats had a higher total distance travelled compared with PD31 female saline rats (Figure 6b).

Figure 6.

Figure 6.

Open in a new tab

Open field (OF) behavioral performance in saline- and MAM-treated rats across development and the influence of the estrous cycle in adults. (a) Timeline of the OF experimental procedures conducted at postnatal days (PD) 31, 51, and 75. (b) Total distance traveled was significantly higher in MAM-treated rats compared to saline controls at PD 31 and PD 51. In saline rats, total distance traveled increased from PD 31 to PD 75. (c) Margin distance was significantly higher in MAM rats compared to saline rats at PD 31. Both saline and MAM rats exhibited a significant developmental decrease in margin distance by PD 75 compared to PD 31. (d) Center distance traveled increased with age in both groups. At PD 75, MAM-treated rats showed a significant decrease in distance traveled in the center compared to age-matched saline controls. (e) At PD 75, the total distance traveled did not vary across the estrous cycle (Metestrus/Diestrus vs. Estrus/Proestrus) for either treatment group. (f) At PD 75, MAM-treated rats in the Estrus/Proestrus phase showed a significant increase in margin distance compared to MAM rats in the Metestrus/Diestrus phase. (g) Center distance at PD 75 was not affected by the estrous cycle in either group. Significant differences between conditions (saline × MAM) within the same age group are denoted by #p<0.05. Significant differences within the same condition across different ages or between estrous cycle phases are denoted by *p<0.05. Data points represent individual animals, and bars show group means ± SEM.

At PD75, the estrous cycle analysis did not reveal any significant effects of age, treatment, or their interaction (Table 1; Figure 6e).

3.9. Margin Locomotion – OF

Distance travelled in the margin portion of the OF demonstrated significant effects of age and treatment but no interaction (Table 1). Poshoc analysis indicated that MAM female rats had higher margin distance traveled than saline rats at PD31 (Figure 6c). The margin distance decreased with age and was lower at PD75 for either saline and MAM compared to PD31 (Figure 6c).

The analysis for the margin distance at PD75 for estrous cycle demonstrated a significant effect of estrous cycle but not treatment or interaction effect (Table 1). Poshoc indicated that MAM rats during the Estrus/Proestrus cycle had a higher margin distance travelled than MAM during the Metestrus/Diestrus cycle (Figure 6f).

3.10. Center Locomotion - OF

The distance traveled within the center portion of OF demonstrated a significant effect of age and an interaction between age and treatment, but not treatment alone (Table 1). Poshoc indicated that female MAM rats at PD75 had a decreased distance traveled in the center compared to age-matched saline group (Figure 6d). A developmental effect was also observed, with both female saline and MAM rats showing an increasing distance traveled in the center with age. Saline PD75 was significantly higher than PD31 and 51, and female MAM PD75 and PD51 were significantly higher than PD31 (Figure 6d).

For center distance, analysis of the estrous cycle at PD75 revealed a significant effect of the estrous cycle, but neither treatment nor the interaction between the two factors had a significant effect (Table 1). However, post hoc analysis did not indicate any difference between the groups (Figure 6g).

4. Discussion

This study investigated the effects of prenatal MAM exposure on anxiety-like behaviors and PV/PNN expression in female rats across key developmental periods (PD31, PD41, PD51, and PD75), based on our previous findings showing their importance in modeling anxiety onset and pharmacological sensitivity (Du & Grace, 2013; Gomes et al., 2020). The results demonstrate developmental period-specific alterations in behavior and cellular markers, contributing to a better understanding of MAM’s effects on female neurodevelopment.

Female MAM-treated rats exhibited heightened anxiety-like behaviors at PD31 and PD75, as evidenced by significant reductions in the percentage of entries and the percentage of time spent on the open arms compared to saline-treated controls (Figures 1b, 1c). Indeed, female MAM rats exhibited a decreased center distance at PD75 (Figure 6d) in the OF test. This suggests that PD75 represent an age when MAM rats may be more susceptible to anxiety responses. While this aligns with findings in male MAM models (Du & Grace, 2013, 2016), it appears to contrast with previous studies in females, that reported no significant EPM differences in adult female MAM rats (Perez et al., 2019). However, their assessment was limited to a single time point in adulthood, whereas our study employed a cross-sectional design spanning key developmental stage. This broader approach allowed us to detect age-specific and potentially transient anxiety phenotypes; effects that may have been missed in adult-only testing. Furthermore, although estrous cycle phase can influence behavior, previous studies found that EPM performance did not significantly vary across cycle stages (Perez et al., 2019). Notably, our PD75 cohort demonstrated the most robust anxiety-like phenotype, with both reduced open-arm time and entries compared to controls. To further investigate the divergence in the EPM data, we conducted an OF test in adult female Saline and MAM rats (PD75). Female MAM rats exhibited decreased center distance compared to the Saline group, which may be indicative of heightened anxiety (Carter & Shieh, 2015; Kraeuter et al., 2019)(Figure 6d). Notably, the estrous cycle had a significant influence on margin distance at PD75, with MAM females in estrus/proestrus showing greater margin distance than those in metestrus/diestrus. This could confound the margin distance measurements when MAM rats were analyzed as a single group. As the OF experiment was better statistically powered to allow estrous cycle comparison, this covariate was not captured in the EPM dataset, where group sizes were insufficient to stratify animals by cycle. It is therefore possible that the EPM results at PD75 reflect a sampling bias in which a disproportionate number of rats were tested during estrus/proestrus, which represent the phase associated with greater anxiety-like behavior in the OF data. This thereby amplifies the apparent anxiety phenotype in the EPM cohort. The discrepancy of our EPM and OF data with prior findings may reflect differences in experimental procedure, environmental changes, cohort variability, or sensitivity to detect behavioral changes at specific developmental stages

PD41 and PD51 were found to have a different dynamic with respect to anxiety levels as measured in the EPM. At PD 41, female MAM rats displayed less anxiety when compared to PD 31 and PD 51 MAM rats as evidenced by an increase in the percentage of time spent on the open arms of the maze (Figure 1c). In contrast, at PD51, MAM-treated rats exhibited a significant increase in the percentage of open-arm entries compared to saline controls (Figure 1b). However, this effect was accompanied by a corresponding increase in total arm entries (Figure 1d), suggesting elevated locomotor activity rather than a true reduction in anxiety-like behavior. In the EPM, total arm entries are used as an index of locomotor activity, while the open arm entries, along with time spent in the open arms, often are considered the primary measures of anxiety-like behavior (Walf & Frye, 2007). Importantly, the percentage of time spent in the open arms did not differ between groups at this time point (Figure 1c), which is typically considered a more robust indicator of anxiety-like behavior in the EPM. Locomotion was also measured in the OF test, where female MAM rats at PD31 and PD51 showed an increased total distance travelled across a 10-min period. This suggests that the hyperlocomotion is present during development in MAM rats and may be driving the increased margin distance in the OF test at PD31 of MAM rats and the increased open-arm entries in the EPM.

Additionally, adult saline-treated female rats demonstrated a developmental reduction in anxiety as evidenced by increased open-arm exploration at PD75 when compared to earlier ages, which is consistent with the findings that adult female rats tend to demonstrate reduced anxiety behavior even when compared to younger female rats (Lynn & Brown, 2010). The OF test supports this finding, demonstrating that female saline and MAM rats exhibit a consistent decrease in the margin distance and an increase in the center distance traveled across PD31 to PD75. While the EPM is a well-established measure of anxiety-like behavior, it may be less sensitive to capture changes in females compared to other assays. EPM was selected to facilitate comparison with previous data in the MAM model and establish a correlation between this and PV and PNN measures in the same individual. The OF test was used to further explore the locomotion and anxiety behaviors observed during the most pertinent developmental age determined by the EPM test. Therefore, our data derived from EPM and OF highly align with the female anxiety dynamic during development.

The EPM behavioral observations were accompanied by changes at the cellular level. We found that the vHIP displayed a significant reduction in PV and PNN densities at PD75 in MAM-treated rats compared to saline controls (Figures 4c, 4d). This is consistent with what is observed in adult male MAM rats, as they displayed significant reductions in the average number of PV-expressing neurons in the dentate region of the vHIP when compared to saline-treated rats (Gill & Grace, 2014). Interestingly, male MAM rats exhibit a reduction in PV expression in the vHip starting from postnatal day 25 (Gill & Grace, 2014). In contrast, our data show no significant PV loss in female MAM rats at PD31. One possible explanation for this sex difference may relate to pubertal hormonal influences. Female rats enter puberty earlier than males, and PD31 may coincide with increasing estradiol levels. Estradiol has been shown to modulate interneuron maturation and could therefore attenuate the effects observed in males. Future studies could directly test this hypothesis by manipulating pubertal hormonal exposure, for example through prepubertal ovariectomy followed by assessment of PV interneuron development. Supporting this, Gill et al. 2014 observed that PV loss in the vHip of male MAM rats was progressive, with significant reductions in cell number only emerging in adulthood. Thus, our findings may reflect a delayed trajectory of PV vulnerability in females, possibly modulated by differences in pubertal timing or neuroprotective hormonal influences. Additional longitudinal studies across sex and developmental stages are warranted to further clarify these dynamics.

Additionally, the decrease in PV content likely disrupts the inhibitory-excitatory balance in the vHIP driving the increase of pyramidal excitatory activity that ultimately leads to the increase in dopamine activity in the ventral tegmental area (Grace, 2016). The absence of similar reductions at earlier ages, combined with the progressive decline in PNN density, suggests that vHIP alterations emerge gradually and become pronounced in adulthood in MAM females. This pattern highlights the vHIP as a key contributor to the anxiety-like behaviors observed in female MAM-treated rats during adulthood. Notably, Perez et al. 2019 also reported robust decreases in gamma oscillations in the vHIP of female MAM-treated rats that did not vary across the estrous cycle, along with reductions in PV interneuron number. These findings reinforce the idea that network-level dysfunction in this model stems primarily from PV cell loss, rather than fluctuations in PV expression or hormonal state, leading to deficits in synchronous vHIP activity (Perez et al., 2019).

In the BLA, no significant differences in PV or PNN densities were observed between MAM- and saline-treated females at most ages. However, an increase in PV density was observed at PD41 in MAM-treated rats (Figure 2c). Thus, the BLA does not seem to be the driver for PV/PNN vHIP damage, as proposed to occur in males (Du & Grace, 2016). This increase may represent a compensatory mechanism aimed at suppressing BLA activity, potentially preventing it from exacerbating vHIP dysfunction during adolescence in females. This may also provide a protective effect to peripubertal stress-induced pathology observed in adult males (Gomes et al., 2020) but to which females are resilient (Klinger et al., 2019). The lack of sustained alterations in PV or PNN expression in the BLA suggests that it may play a smaller role in driving vHIP dysfunction in female MAM rats, contrasting with findings in males where BLA hyperactivity significantly contributes to vHIP dysregulation (Du & Grace, 2016).

The TRN exhibited significant reductions in PNN density at PD31 and PV density at PD51 in MAM-treated rats compared to saline controls (Figure 3c, 3d). The early reduction in PNN density may increase the vulnerability of TRN PV neurons, contributing to their subsequent decline by PD51. As an inhibitory structure, the TRN regulates activity of the RE, which provides excitatory input to the vHip (Zimmerman & Grace, 2018b). A previous study in males revealed that the degradation of PNN in the TRN leads to a hyperdopaminergic state, similar to what is observed in the MAM model (Zhu et al., 2021). This PNN degradation is proposed to increase the vulnerability of PV in the TRN, which would subsequently drive the increase in dopaminergic neuron activity via the RE-vHip pathway. Thus, reduced PV expression in the TRN may weaken inhibitory control over the RE, leading to increased excitatory drive onto ventral hippocampal circuits during development.

One potential explanation for the delayed emergence of ventral hippocampal PV deficits is a circuit-level mechanism involving this TRN–RE–vHIP pathway. In females, a stress model of hyperdopaminergic state leads to increased activity in the RE, both short-term and long-term after stress (Uliana & Grace, 2025). This suggests a key upstream driver in females that differs from mechanisms described in males. Increased excitatory input from a dysregulated RE onto vHip PV interneurons could contribute to their eventual impairment and the hyperexcitability observed in adulthood. Together, these findings suggest that early TRN alterations may precede and contribute to later vHIP dysfunction in MAM females. Interestingly, this developmental pattern differs from findings in male MAM rats, where reductions in PV and PNN within the TRN are primarily observed in adulthood (Zhu et al., 2021). This divergence raises the possibility that earlier TRN alterations in females may act as precursors to later circuit dysfunction, potentially involving additional structures such as the RE. However, this proposed mechanism remains to be directly tested.

The role of the TRN in fear-related behavior provides important context for interpreting these findings. Notably, the rostroventral TRN has been shown to modulate fear extinction, with optogenetic inhibition of TRN PV neurons disrupting fear extinction memory retrieval and resulting in persistently elevated freezing responses (Lee et al., 2019). This implicates TRN activity in the regulation of fear-related limbic circuits, though direct evidence linking TRN dysfunction specifically to anxiety-like behavior in classical assays remains limited. Given that the TRN exerts inhibitory control over midline thalamic nuclei, including the RE, which modulates vHip activity, reductions in TRN PV expression observed in MAM-treated females may contribute to dysregulated limbic output by diminishing thalamic gating, potentially enhancing excitatory drive to the vHIP. While this mechanistic interpretation remains speculative in the absence of direct causal evidence, it is consistent with our behavioral observations, in which reduced TRN integrity is associated with heightened anxiety-like behavior at later developmental stages. Together, these findings raise the possibility that early TRN dysfunction may not only contribute to circuit-level alterations in the vHIP but may also play a role in the later emergence of fear- and anxiety-related phenotypes.

Our analysis also revealed a positive correlation between the percentage of time spent in the open arms (% Time OA) of the EPM and PNN expression in the TRN. This finding may suggest that higher PNN expression in the TRN at PD 31 could be associated with increased % of time in the OA, which is indicative of reduced anxiety-like behavior. We propose that interventions that increase plasticity, by favoring PNN formation, could have beneficial consequences in preventing the behavioral and neuropathological state observed later on in the adult phase.

We acknowledge that including a male comparator group would have allowed for direct assessment of sex-specific effects of MAM exposure on behavior and cellular outcomes. However, our decision to focus exclusively on females was guided by ethical considerations aligned with the NIH’s principles of reducing animal use (i.e., the 3Rs: Replacement, Reduction, Refinement) and the fact that the male studies were performed previously by our group (Du & Grace, 2013). Given the extensive body of literature already characterizing MAM-induced changes in males, including behavioral, molecular, and electrophysiological data, we sought to avoid unnecessary duplication and instead address a critical gap in the literature regarding female vulnerability. By concentrating on females, we were able to allocate our resources toward deeper developmental analysis across multiple time points, offering novel insights into the temporal trajectory of anxiety-related behaviors and interneuron marker expression in this underrepresented population.

An additional limitation of this study is that we did not quantify the colocalization of PV and PNN. Prior studies have demonstrated that early-life perturbations may differentially affect the proportion of PV neurons surrounded by PNN, particularly in the neocortex, even in the absence of changes in total PV or PNN density (Paylor et al., 2016). While our previous work in the vHip, BLA, and TRN has not consistently shown this distinction, the lack of colocalization analysis in the present study may limit interpretation of PV/PNN interactions. It’s possible that PV/PNN information could further support our hypothesis and provide more details, particularly for the measures that did not evidence changes in PV/PNN. Future studies incorporating higher-resolution imaging approaches will be important to better characterize these relationships. However, previous studies conducted in the MAM model with males have shown that PV represents a significant change in vHIP and TRN (Lodge et al., 2009; Zhu et al., 2021). This finding aligns with the data obtained from females and provides valuable insights into the developmental dynamics between males and females.

Additionally, we acknowledge that estrous cycle stage can influence PV interneuron function and expression, and that the lack of cycle data in adult animals due to constraints in the animal number to attain enough statistical power represents a limitation of this study. However, we observed low inter-individual variability in PV and PNN density at PD75, which would not be expected if hormonal fluctuations were introducing substantial variability across subjects. Indeed, reductions in PV interneuron number in MAM female rats, measured by immunohistochemistry, and associated network dysfunction, do not exhibit significant variations across estrous cycle stages in adult females (Perez et al., 2019). This suggests that these alterations are stable pathological changes rather than transient, cycle-dependent effects. Nonetheless, future studies incorporating estrous cycle monitoring will be important to further clarify potential hormonal modulation of these findings.

Overall, our findings indicate that MAM-exposed female rats exhibit a unique dynamic anxiety pattern, characterized by both early and late manifestations of anxiety-related behavior. This pattern appears to be driven by early dysregulation within the TRN, which in turn contributes to long-term impairments in vHip-PV interneuron function in adulthood.

References

  1. Abel KM, Drake R, & Goldstein JM. (2010). Sex differences in schizophrenia. International Review of Psychiatry, 22(5), 417–428. 10.3109/09540261.2010.515205 [DOI] [PubMed] [Google Scholar]
  2. Andreasen NC. (1995). Symptoms, signs, and diagnosis of schizophrenia. Lancet (London, England), 346(8973), 477–481. 10.1016/s0140-6736(95)91325-4 [DOI] [PubMed] [Google Scholar]
  3. Caballero A, Flores-Barrera E, Cass DK, & Tseng KY. (2014). Differential regulation of parvalbumin and calretinin interneurons in the prefrontal cortex during adolescence. Brain Structure & Function, 219(1), 395–406. 10.1007/s00429-013-0508-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Carter M, & Shieh J. (2015). Animal Behavior. In Guide to Research Techniques in Neuroscience (pp. 39–71). Elsevier. 10.1016/B978-0-12-800511-8.00002-2 [DOI] [Google Scholar]
  5. Corcoran CM, Smith C, McLaughlin D, Auther A, Malaspina D, & Cornblatt B. (2012). HPA axis function and symptoms in adolescents at clinical high risk for schizophrenia. Schizophrenia Research, 135(1–3), 170–174. 10.1016/j.schres.2011.11.035 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Devylder JE, Ben-David S, Schobel SA, Kimhy D, Malaspina D, & Corcoran CM. (2013). Temporal association of stress sensitivity and symptoms in individuals at clinical high risk for psychosis. Psychological Medicine, 43(2), 259–268. 10.1017/S0033291712001262 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Drzewiecki CM, Willing J, & Juraska JM. (2020). Influences of age and pubertal status on number and intensity of perineuronal nets in the rat medial prefrontal cortex. Brain Structure & Function, 225(8), 2495–2507. 10.1007/s00429-020-02137-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Du Y, & Grace AA. (2013). Peripubertal diazepam administration prevents the emergence of dopamine system hyperresponsivity in the MAM developmental disruption model of schizophrenia. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 38(10), 1881–1888. 10.1038/npp.2013.101 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Du Y, & Grace AA. (2016). Amygdala Hyperactivity in MAM Model of Schizophrenia is Normalized by Peripubertal Diazepam Administration. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 41(10), 2455–2462. 10.1038/npp.2016.42 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Emsley RA, Oosthuizen PP, Joubert AF, Roberts MC, & Stein DJ. (1999). Depressive and anxiety symptoms in patients with schizophrenia and schizophreniform disorder. The Journal of Clinical Psychiatry, 60(11), 747–751. 10.4088/jcp.v60n1105 [DOI] [PubMed] [Google Scholar]
  11. Flagstad P, Mørk A, Glenthøj BY, van Beek J, Michael-Titus AT, & Didriksen M. (2004). Disruption of neurogenesis on gestational day 17 in the rat causes behavioral changes relevant to positive and negative schizophrenia symptoms and alters amphetamine-induced dopamine release in nucleus accumbens. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 29(11), 2052–2064. 10.1038/sj.npp.1300516 [DOI] [PubMed] [Google Scholar]
  12. Gill KM, & Grace AA. (2014). Corresponding decrease in neuronal markers signals progressive parvalbumin neuron loss in MAM schizophrenia model. The International Journal of Neuropsychopharmacology / Official Scientific Journal of the Collegium Internationale Neuropsychopharmacologicum (CINP), 17(10), 1609–1619. 10.1017/S146114571400056X [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Gomes FV, Zhu X, & Grace AA. (2020). The pathophysiological impact of stress on the dopamine system is dependent on the state of the critical period of vulnerability. Molecular Psychiatry, 25(12), 3278–3291. 10.1038/s41380-019-0514-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Grace AA. (2016). Dysregulation of the dopamine system in the pathophysiology of schizophrenia and depression. Nature Reviews Neuroscience, 17(8), 524–532. 10.1038/nrn.2016.57 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hijazi S, Smit AB, & van Kesteren RE. (2023). Fast-spiking parvalbumin-positive interneurons in brain physiology and Alzheimer’s disease. Molecular Psychiatry, 28(12), 4954–4967. 10.1038/s41380-023-02168-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Hou G, Smith AG, & Zhang Z-W. (2016). Lack of Intrinsic GABAergic Connections in the Thalamic Reticular Nucleus of the Mouse. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 36(27), 7246–7252. 10.1523/JNEUROSCI.0607-16.2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Howes OD, Montgomery AJ, Asselin M-C, Murray RM, Valli I, Tabraham P, Bramon-Bosch E, Valmaggia L, Johns L, Broome M, McGuire PK, & Grasby PM. (2009). Elevated Striatal Dopamine Function Linked to Prodromal Signs of Schizophrenia. Archives of General Psychiatry, 66(1), 13–20. 10.1001/archgenpsychiatry.2008.514 [DOI] [PubMed] [Google Scholar]
  18. Huff ML, Emmons EB, Narayanan NS, & LaLumiere RT. (2016). Basolateral amygdala projections to ventral hippocampus modulate the consolidation of footshock, but not contextual, learning in rats. Learning & Memory, 23(2), 51–60. 10.1101/lm.039909.115 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Jauhar S, Johnstone M, & McKenna PJ. (2022). Schizophrenia. The Lancet, 399(10323), 473–486. 10.1016/S0140-6736(21)01730-X [DOI] [PubMed] [Google Scholar]
  20. Kaushik R, Lipachev N, Matuszko G, Kochneva A, Dvoeglazova A, Becker A, Paveliev M, & Dityatev A. (2021). Fine structure analysis of perineuronal nets in the ketamine model of schizophrenia. European Journal of Neuroscience, 53(12), 3988–4004. 10.1111/ejn.14853 [DOI] [PubMed] [Google Scholar]
  21. Klinger K, Gomes FV, Rincón-Cortés M, & Grace AA. (2019). Female rats are resistant to the long-lasting neurobehavioral changes induced by adolescent stress exposure. European Neuropsychopharmacology: The Journal of the European College of Neuropsychopharmacology, 29(10), 1127–1137. 10.1016/j.euroneuro.2019.07.134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kraeuter A-K, Guest PC, & Sarnyai Z. (2019). The Open Field Test for Measuring Locomotor Activity and Anxiety-Like Behavior. Methods in Molecular Biology, 1916, 99–103. 10.1007/978-1-4939-8994-2_9 [DOI] [PubMed] [Google Scholar]
  23. Lee J-H, Latchoumane C-FV, Park J, Kim J, Jeong J, Lee K-H, & Shin H-S. (2019). The rostroventral part of the thalamic reticular nucleus modulates fear extinction. Nature Communications, 10(1), 4637. 10.1038/s41467-019-12496-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Li X, Zhou W, & Yi Z. (2022). A glimpse of gender differences in schizophrenia. General Psychiatry, 35(4), e100823. 10.1136/gpsych-2022-100823 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lodge DJ, & Grace AA. (2008). Hippocampal dysfunction and disruption of dopamine system regulation in an animal model of schizophrenia. Neurotoxicity Research, 14(2–3), 97–104. 10.1007/BF03033801 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Lodge DJ, & Grace AA. (2009). Gestational methylazoxymethanol acetate administration: A developmental disruption model of schizophrenia. Behavioural Brain Research, 204(2), 306–312. 10.1016/j.bbr.2009.01.031 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lodge DJ, & Grace AA. (2011). Developmental pathology, dopamine, stress and schizophrenia. International Journal of Developmental Neuroscience : The Official Journal of the International Society for Developmental Neuroscience, 29(3), 207–213. 10.1016/j.ijdevneu.2010.08.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Lovick TA, & Zangrossi H. (2021). Effect of Estrous Cycle on Behavior of Females in Rodent Tests of Anxiety. Frontiers in Psychiatry, 12, 711065. 10.3389/fpsyt.2021.711065 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lynn DA, & Brown GR. (2010). The ontogeny of anxiety-like behavior in rats from adolescence to adulthood. Developmental Psychobiology, 52(8), 731–739. 10.1002/dev.20468 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Marín O. (2024). Parvalbumin interneuron deficits in schizophrenia. European Neuropsychopharmacology: The Journal of the European College of Neuropsychopharmacology, 82, 44–52. 10.1016/j.euroneuro.2024.02.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Maynard TM, Sikich L, Lieberman JA, & LaMantia AS. (2001). Neural development, cell-cell signaling, and the “two-hit” hypothesis of schizophrenia. Schizophrenia Bulletin, 27(3), 457–476. 10.1093/oxfordjournals.schbul.a006887 [DOI] [PubMed] [Google Scholar]
  32. Moore H, Jentsch JD, Ghajarnia M, Geyer MA, & Grace AA. (2006). A neurobehavioral systems analysis of adult rats exposed to methylazoxymethanol acetate on E17: Implications for the neuropathology of schizophrenia. Biological Psychiatry, 60(3), 253–264. 10.1016/j.biopsych.2006.01.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Neurobiology of Dopamine in Schizophrenia. (2007). In International Review of Neurobiology (Vol. 78, pp. 1–39). Academic Press. 10.1016/S0074-7742(06)78001-1 [DOI] [PubMed] [Google Scholar]
  34. Owens DGC, Miller P, Lawrie SM, & Johnstone EC. (2005). Pathogenesis of schizophrenia: A psychopathological perspective. The British Journal of Psychiatry: The Journal of Mental Science, 186, 386–393. 10.1192/bjp.186.5.386 [DOI] [PubMed] [Google Scholar]
  35. Paxinos G, & Watson C. (1982). The rat brain in stereotaxic coordinates. Academic Pr. [DOI] [PubMed] [Google Scholar]
  36. Paylor JW, Lins BR, Greba Q, Moen N, de Moraes RS, Howland JG, & Winship IR. (2016). Developmental disruption of perineuronal nets in the medial prefrontal cortex after maternal immune activation. Scientific Reports, 6, 37580. 10.1038/srep37580 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Perez SM, Donegan JJ, & Lodge DJ. (2019). Effect of estrous cycle on schizophrenia-like behaviors in MAM exposed rats. Behavioural Brain Research, 362, 258–265. 10.1016/j.bbr.2019.01.031 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Uliana DL, & Grace AA. (2025). Age- and sex-dependent effects of stressors on activity of the nucleus reuniens of the thalamus. Schizophrenia Research, 285, 155–164. 10.1016/j.schres.2025.09.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Uliana DL, Walsh RA, Fabris D, & Grace AA. (2025). Evenamide reverses schizophrenia-related dysfunction in a neurodevelopmental animal model. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 50(11), 1631–1642. 10.1038/s41386-025-02188-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Vertes RP, Hoover WB, Szigeti-Buck K, & Leranth C. (2007). Nucleus reuniens of the midline thalamus: Link between the medial prefrontal cortex and the hippocampus. Brain Research Bulletin, 71(6), 601–609. 10.1016/j.brainresbull.2006.12.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Walf AA, & Frye CA. (2007). The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nature Protocols, 2(2), 322–328. 10.1038/nprot.2007.44 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Walker EF, Brennan PA, Esterberg M, Brasfield J, Pearce B, & Compton MT. (2010). Longitudinal changes in cortisol secretion and conversion to psychosis in at-risk youth. Journal of Abnormal Psychology, 119(2), 401–408. 10.1037/a0018399 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Yung AR, Yuen HP, McGorry PD, Phillips LJ, Kelly D, Dell’Olio M, Francey SM, Cosgrave EM, Killackey E, Stanford C, Godfrey K, & Buckby J. (2005). Mapping the onset of psychosis: The Comprehensive Assessment of At-Risk Mental States. The Australian and New Zealand Journal of Psychiatry, 39(11–12), 964–971. 10.1080/j.1440-1614.2005.01714.x [DOI] [PubMed] [Google Scholar]
  44. Zhu X, Cabungcal J-H, Cuenod M, Uliana DL, Do KQ, & Grace AA. (2021). Thalamic reticular nucleus impairments and abnormal prefrontal control of dopamine system in a developmental model of schizophrenia: Prevention by N-acetylcysteine. Molecular Psychiatry, 26(12), 7679–7689. 10.1038/s41380-021-01198-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Zhu X, & Grace AA. (2023). Sex- and exposure age-dependent effects of adolescent stress on ventral tegmental area dopamine system and its afferent regulators. Molecular Psychiatry, 28(2), 611–624. 10.1038/s41380-022-01820-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Zimmerman EC, & Grace AA. (2018a). Prefrontal cortex modulates firing pattern in the nucleus reuniens of the midline thalamus via distinct corticothalamic pathways. The European Journal of Neuroscience, 48(10), 3255–3272. 10.1111/ejn.14111 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Zimmerman EC, & Grace AA. (2018b). Prefrontal cortex modulates firing pattern in the nucleus reuniens of the midline thalamus via distinct corticothalamic pathways. The European Journal of Neuroscience, 48(10), 3255–3272. 10.1111/ejn.14111 [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES