Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 May 24.
Published in final edited form as: Horm Behav. 2025 May 24;173:105761. doi: 10.1016/j.yhbeh.2025.105761

An oxytocin receptor gene polymorphism is associated with distinct neural responses to mating encounters in male prairie voles

Lanikea B King 1,2, Hasse Walum 1,2, Mike Xiao 1,2, Asha Y Caslin 1,2, Fuad C Haddad 1,2, Larry J Young 1,2, Zachary V Johnson 1,2,3
PMCID: PMC12465253  NIHMSID: NIHMS2086036  PMID: 40414117

Abstract

Oxytocin is a conserved neuropeptide that regulates social and reproductive behaviors in diverse species. Genetic variation in Oxtr, the gene encoding the oxytocin receptor (OXTR), is associated with variation in social attachment behaviors in rodents and humans; however, it is unclear how genetic variation in Oxtr shapes the function of specific neural systems during social contexts. Here we address this question using the socially monogamous prairie vole (Microtus ochrogaster), a species that expresses an array of OXTR-dependent social behaviors and possesses Oxtr gene polymorphisms that predict individual variation in brain region-specific OXTR expression. We test the neural and behavioral effects of an Oxtr gene polymorphism that has previously been associated with brain region-specific OXTR expression and social attachment behaviors in male prairie voles. Our results suggest that, during brief mating encounters, Oxtr genotype is not associated with differences in mating behavior or in expression levels of the activity-dependent immediate early gene product FOS within brain regions, but it is associated with differences in correlated FOS expression patterns across brain regions.

INTRODUCTION

Oxytocin is a conserved neuropeptide that regulates social and reproductive behavior across distantly related species, spanning nematode worms and humans (Donaldson and Young, 2008; Garrison et al., 2012; Lee et al., 2009). In mammals, oxytocin is synthesized in hypothalamic neurons that project peripherally to the posterior pituitary and centrally to a variety of hindbrain, midbrain, and forebrain nuclei (Knobloch and Grinevich, 2014; Ross et al., 2009). Oxytocin is released in a variety of reproductive contexts, including parturition, lactation, and mating (Lee et al., 2009), as well as in response to more subtle social stimuli, such as social vocalizations, eye contact, and touch (Nagasawa et al., 2015; Okabe et al., 2015; Seltzer et al., 2010). Following release, oxytocin drives changes in reproductive physiology and behavior by binding to its target receptors (oxytocin receptors, OXTRs) in the brain and periphery (Jurek and Neumann, 2018). Brain region-specific OXTR expression patterns vary strongly within and among vertebrate species, and this variation is associated with variation in social behavior among individuals and among species (Anacker and Beery, 2013; Goodson et al., 2009; Johnson and Young, 2017; Ophir et al., 2012). Although genetic variation in OXTR/Oxtr has been linked to variation in brain region-specific Oxtr expression in rodents (King et al., 2016) and humans (Genotype-Tissue Expression Project), we have a limited understanding of how this variation shapes neural responses to social stimuli.

The behavioral roles of OXTRs have been demonstrated in a variety of brain regions, many of which are embedded within a network of conserved limbic and mesolimbic regions that is thought to regulate social behaviors across all jawed vertebrates (Goodson et al., 2009; Mitre et al., 2016; Newman, 1999; O’Connell and Hofmann, 2011). Several examples include the ventral tegmental area (VTA) (Borland et al., 2019; Hung et al., 2017), nucleus accumbens (NAc) (Olazábal and Young, 2006a; Williams et al., 2020; Young et al., 2001), prelimbic cortex (PLC) (Nakajima et al., 2014; Sabihi et al., 2014; Young et al., 2001), and paraventricular nucleus of the hypothalamus (PVN) (Smith and Wang, 2014). It is thought that individual and species level variation in hormone and neuropeptide receptor (e.g. OXTR) expression across nodes of this network contributes to individual and species level variation in neural function and behavior during species-typical social encounters (Goodson and Kabelik 2009), but this idea remains largely untested.

Socially monogamous prairie voles provide an opportunity to understand how natural variation in brain region-specific OXTR expression influences neural responses to social stimuli (Johnson and Young, 2018; Walum and Young, 2018). Within prairie voles, individuals vary strongly in levels of brain-region specific OXTR expression, and this variation is associated with individual differences in social behavior (Olazábal and Young, 2006b; Ophir et al., 2012). In our wild-derived laboratory colony of prairie voles, a naturally occurring single nucleotide polymorphism (SNP; C/T at NT213739, and several other SNPs in linkage disequilibrium) in the prairie vole Oxtr robustly predicts variation in striatal OXTR expression levels (Inoue et al., 2022; King et al., 2016) and is more modestly associated with how quickly male prairie voles form social preferences for mating partners over an extended period of cohabitation (King et al., 2016). However, it is unclear how this SNP influences neural activity during social interactions, for example during initial and brief mating encounters like those that may occur in nature. Here we address this question by testing whether genotype at NT213739 is associated with individual variation in behavior and brain region-specific expression patterns of the immediate early gene product FOS, a molecular signature of recent neuronal excitation, during mating encounters in male prairie voles.

METHODS

Subjects

We previously identified a relationship between NT213739 and pair bonding in males, and so we focused on males in these experiments. All subject males and stimulus females were drawn from our laboratory breeding colony originally derived from field captured voles in Illinois. Subjects were sampled between the two aforementioned studies that replicated the same effect of NT213739 on brain region-specific Oxtr expression in this colony (Inoue et al., 2022; King et al., 2016). Experimental subjects (n=48) were either toe-clipped at post-natal day 7 (PND7) or ear-clipped at PND21 for individual identification and to collect tissue for genotyping. Subjects were weaned at PND21 and were then housed in groups of two or three until behavioral testing during adulthood (subjects were tested at 90–180 days of age). Housing consisted of a ventilated 26×18×19 cm Plexiglas cage filled with Bed-o-cobbs Laboratory Animal Bedding (The Andersons; Maumee, Ohio) under a 14:10 h light/dark cycle at 22°C with ad libitum access to food (Lab Rabbit Diet HF #5326, LabDiet) and water. Stimulus animals were sexually experienced, ovariectomized, estrogen-primed (see below), individually housed adult female prairie voles (90–240 days of age). Stimulus females were given at least 14 days between behavioral sessions. All procedures were conducted in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the Emory University Institutional Animal Care and Use Committee.

Genotyping

DNA was isolated from ear and toe clips using a Qiagen DNeasy Kit as previously described (King et al., 2016). A 117 bp amplicon including the intronic SNP at NT213739, based on the sequence from a prairie vole BAC clone (GenBank #DP001215.2) and described in detail previously (King et al., 2016), was amplified by PCR, using a Qiagen Taq PCR Master Mix Kit. The thermocycler program used included 1) initial denature at 94˚C for 5 min 30 s; 2) 35x cycles of denaturing at 94˚C for 30 s, annealing at 55˚C for 30 s, and elongation at 72˚C for 30 s; and 3) final elongation at 72˚C for 10 min. Amplicons were digested for 1.5 hours at 65˚C with the BsiHKAI restriction enzyme (New England Biolabs), which cuts the C-allele of NT213739 but not the T-allele. Thus, the resulting banding patterns for each subject were used to identify genotype. The primers used for this reaction were: forward: 5’- GGGACGTTCACGTTACATGG −3’, reverse: 5’- AGACGGGACAGAGTCTCCAG −3’.

Behavioral testing

Male subjects used in the behavioral exposure and FOS experiment underwent a 30-minute, video-recorded cohabitation with a sexually experienced, ovariectomized, estrogen-primed, adult stimulus female. In the three days preceding cohabitation, 1) male subjects were transferred, individually housed, and habituated to a new home cage; and 2) stimulus females were brought into estrus with daily subcutaneous injections of 4.0 μg estradiol benzoate dissolved in sesame oil (Sigma; St. Louis, MO; S3547). Cohabitation began with the introduction of the stimulus female into the male subject’s home cage with food hoppers removed to facilitate behavioral analysis. Lab chow pellets and water bottles were left in the home cage to allow ad libitum access to food and water. After 30 minutes, stimulus females were removed and subjects remained in their home cage for 45 minutes before transcardial perfusion. For unexposed control subjects (n=9), the cage was opened and a small amount of bedding was scooped and immediately returned by an experimenter at the beginning and end of the 30 minute session to control for experimenter activity during introduction/removal of stimulus females.

Perfusion, post-fixation, and sectioning

For the subjects used in the FOS study, 45 minutes following the end of cohabitation (or control sessions), subjects were administered an overdose of isoflurane and were immediately perfused transcardially at a rate of approximately 4 mL/minute with 40 mL of 1x phosphate buffered saline (PBS; pH=7.4; diluted to 1x with distilled, deionized water from 10x PBS stock; Teknova; Hollister, CA; P0401) followed by 40 mL of 4% paraformaldehyde (Polysciences; Warrington, PA; 00380) in 1X PBS using an Easy-Load II MASTERFLEX pump (Cole-Palmer; Vernon Hills, IL). Immediately after perfusion, brains were extracted and post-fixed in 4% paraformaldehyde dissolved in 1X PBS overnight before storage in 30% sucrose in 1x PBS solution (4°C) until sectioning. Brains were cut into 40 μm sections using a Microm HM 440E freezing microtome and were stored in 1x PBS with 0.05% sodium azide at 4°C until immunohistochemical staining.

Immunohistochemistry

Sections underwent three washes in 1x PBS, 10-minute incubation in 1% sodium hydroxide in 1x PBS, and three washes in 1x PBS with 0.5% Triton-X (Sigma) (PBST) before treatment with 5% normal goat serum (Fitzgerald; Acton, MA) in PBST for one hour at room temperature. Sections were then incubated for 48 hours in primary rabbit polyclonal anti-FOS antibody (1:20,000; Calbiochem ABE457) on an orbital shaker at 4°C. Following primary incubation sections were washed five times in 1x PBS, once in 1x PBST, and were incubated in secondary biotinylated goat anti-rabbit IgG antibody (1:500; Vector Labs BA-1000) for two hours. After secondary incubation, sections were treated with an avidin-biotin peroxidase system (Vectastain Elite ABC System; Vector Labs: PK6100) for one hour before staining with a Nickel-DAB peroxidase substrate kit (Vector Labs; SK4100). Sections were mounted onto Superfrost Plus slides (Fisher Scientific; 12–550-150) and allowed to dry. After drying, sections were dehydrated in a series of increasingly concentrated ethanol solutions (five minutes in 70% EtOH, ten minutes in fresh 95% EtOH twice, ten minutes in fresh 100% EtOH twice), bathed in Xylenes (15 minutes in Xylenes twice), and coverslipped using Krystalon (EMD Chemicals Inc., Gibbstown, NJ).

Behavioral Scoring

Intromission behavior was quantified from video recordings using Observer XT 10 behavioral scoring software (Noldus Information Technology Inc.; Leesburg, VA). Intromission was defined by stereotypical patterns of pelvic movement during copulation bouts with the female, and the latency to first intromission, total duration of intromission, and total number of intromission bouts was determined for each subject. All scoring was conducted by experimenters blind to treatment groups. To mitigate the risk of behavioral or neural effects caused by lack of female receptivity, trials in which the male did not mate with the female were excluded from downstream analyses, consistent with previous studies (Johnson et al., 2017, 2016).

Selection of brain nuclei

FOS expression was analyzed in eight brain regions selected based on their 1) known expression of OXTRs, 2) known innervation by oxytocinergic fibers, 3) demonstrated interconnectivity with one another, and 4) hypothesized and/or demonstrated roles in social and mating behaviors. These regions included the anterior olfactory nucleus (AON), prefrontal cortex (PFC), nucleus accumbens core (NAc), the nucleus accumbens shell (NAs), medial amygdala (MeA), basolateral amygdala (BLA), paraventricular hypothalamic nucleus (PVN), and ventral tegmental area (VTA).

Analysis of FOS expression

Images were captured through a Nikon E800 microscope and a 10x objective using MCID Core imaging software (InterFocus Ltd; Cambridge, UK). The Mouse Brain (Franklin and Paxinos; 3rd Edition) atlas was used as a reference to determine anatomical boundaries. For each brain region, FOS was quantified in both left and right hemispheres across three consecutive sections for all subjects. Sections or hemispheres with damaged or absent tissue in the target region were excluded. FOS-positive nuclei were quantified within each region using the MCID grain count function with constant size, density, and shape thresholds applied across all subjects. For each subject, FOS expression counts within each region were averaged, yielding a single mean FOS count per brain region per subject.

Statistics

All statistical analyses were performed in R version 4.3.2. For all linear models the residual error term was assumed to be Gaussian. Model fit and assumptions were evaluated by visually inspecting model diagnostic plots (with focus on homoscedasticity, normality of residuals and potential presence of highly influential observations). In the few cases where we deemed model assumptions to be violated, statistical significance was re-evaluated using randomization (permutation tests, code written by the authors). When comparing results from parametric and non-parametric methods, p-values did not differ to an extent where conclusions based on statistical inference changed. Hence, all p-values reported below are from model output based on normal theory.

Data transformation for analysis of FOS

Two batch variables were significantly associated with FOS expression across regions. The first was a variable corresponding to the first versus second wave of the experiment, that were associated with differences in the duration of post-fixation storage at 4ºC prior to sectioning (longer duration was associated with less FOS expression), and the second corresponded to the four immunohistochemistry batches (trays) for FOS staining. To remove these batch effects, we used an empirical Bayes framework implemented in the R function ComBat (available in the “sva” package for R) (Johnson et al., 2007). These transformed values were used for all downstream analyses of FOS expression.

Analysis of mating behavior

Eight male subjects that were exposed to a stimulus female did not mate (2 T/T, 3 C/T, 3 C/C), and were excluded from downstream analyses in accordance with our methodology in previous studies (Johnson et al., 2017, 2016). Among animals that interacted and mated with a female, behavioral data from the 30 minute cohabitation period were analyzed using linear regression, with each behavioral outcome as the dependent variable and the number of C alleles at NT213739 (associated with high OXTR expression; 0 for T/T, n=10; 1 for C/T, n=10; 2 for C/C, n=11) treated as a continuous independent variable.

Analysis of FOS expression within brain regions

Brain region-specific FOS expression was analyzed by fitting a linear mixed-effects regression model (using the “nlme” package in R) to FOS data separately for each brain region, in which 1) FOS expression was the dependent variable and 2) mating context (categorical variable corresponding to exposure to and mating with a female versus not being exposed to a female, hereafter referred to as “mating”), the number of C alleles at NT213739 (a continuous variable; 0 for T/T, n=10; 1 for C/T, n=10; 2 for C/C, n=11), and the interaction between mating and the number of C alleles at NT213739 were treated as independent variables, and 3) individual was treated as a random effect (random intercept).. Benjamini-Hochberg adjustment was used to correct for multiple comparisons.

Analysis of mating- and genotype-associated FOS expression covariance across all brain regions

To analyze mating- and genotype-associated differences in FOS expression covariance patterns between genotypes, we first correlated FOS expression for each pairwise combination of brain regions, organized as a correlation matrix, within each group of interest (e.g. unexposed versus mated, and among genotypes within mated animals). We then used the cortest.normal function within the ‘Psych’ package in R to test if the correlation matrices differed significantly between groups by testing whether their differences are significant. Briefly, this test stabilizes variance using a Fisher z-transformation of correlation coefficients into z-scores that are approximately normally distributed. It then calculates a z-statistic for each pairwise correlation difference between groups and aggregates these differences into a single chi-squared statistic which is used to evaluate the null hypothesis that two correlation matrices are equal. Benjamini-Hochberg adjustment was used to correct for multiple comparisons.

Influence of mating behavior on FOS expression covariance across all brain regions

Although we did not observe genotype-associated differences in mating behavior, we also performed follow-up analyses to control for possible effects of mating behavior on FOS expression covariance among genotypes. To do this, we fit linear models separately for each brain region with FOS expression values as the dependent variable and mating behavior as the independent variable. We then used the residuals from these models to recalculate FOS expression covariance matrices for each genotype, thereby controlling for variance in FOS expression explained by mating behavior.

Analysis of correlated FOS expression between individual brain regions

For post-hoc analysis of differences in correlated FOS expression between brain regions, we used the Fisher’s z-test, a test designed to determine if two correlation coefficients are statistically different, using the cocor.indep.groups function within the cocor package in R. These tests were performed for each pairwise combination of brain regions for the three genotype comparisons that were found to be significant in the Chi squared test (mated T/T versus C/T males, mated T/T versus C/C males, and mated T/T versus C/T and C/C males). To estimate overall significance of genotype-associated correlation differences, we used the resulting p-values from these three comparisons to calculate an adjusted harmonic mean p-value (hmpadj). Briefly, the hmpadj reflects a combined test of the null hypothesis that none of a set of dependent p-values is significant while controlling for the false discovery rate as well as strong- and weak-sense family-wise error rates. Because correlation differences do not necessarily reflect differences in the slope of a relationship, we used additional linear regression analyses to test if the slope of each relationship differed in association with number of C alleles at NT213739. These analyses were conducted for all pairwise combinations of brain regions. In each model, 1) FOS expression in the first region was treated as the dependent variable and 2) FOS expression in the second region, the number of C alleles at NT213739, and the interaction between FOS expression in the second region and the number of C alleles at NT213739 were treated as independent variables. Benjamini-Hochberg adjustment was used to correct for multiple comparisons.

RESULTS

Association between Oxtr genotype and male mating behavior

Because the C allele at NT213739 is associated with more rapid partner preference formation in male prairie voles, and because mating is also associated with accelerated partner preference formation, we reasoned that genetic variation in Oxtr may be associated with differences in male mating behaviors during initial social encounters with females. Linear regression did not support significant associations between the number of C alleles at NT213739 (Figure 1A-C, Supplementary Table 1; 0 for T/T, n=10; 1 for C/T, n=10; 2 for C/C, n=11) and latency to mate (R2=0.052, p=0.22), frequency of mating bouts (R2=0.005, p=0.70), or total time spent mating (R2=0.001, p=0.85) during the test. A follow-up set of ANOVA analyses, for which genotype was coded as a categorical variable rather than numeric, did not reveal any significant associations between NT213739 genotype and mating behavior (p≥0.22 for all three tests). Taken together, these data suggest that the C allele at NT213739 was not strongly associated with variation in mating behavior in this paradigm, consistent with previous studies using selective OXTR antagonism (Johnson, Walum et al. 2016).

Figure 1. Association between Oxtr genotype and mating behavior in male prairie voles.

Figure 1.

Open in a new tab

Linear regression models showing the relationship between number of C alleles at NT213739 and (A) number of mating bouts per 30 minutes, (B) latency to mate, and (C) total time spent mating per 30 minutes. All three relationships have a non-significant slope (pBH > 0.05). In each plot, blue lines represent linear regression fits and shaded areas show 95% confidence intervals

Mating-associated FOS expression within brain regions

We previously showed that sociosexual interaction and mating with a female is associated with increased FOS expression across an array of OXTR-expressing brain regions in male prairie voles (Johnson et al., 2017, 2016). Briefly, FOS is the protein product of the immediate early gene c-fos, which is transcribed in response to calcium influx and downstream molecular cascades associated with neuronal excitation. After translation, FOS dimerizes with JUN to form the AP-1 transcription factor, which regulates expression of genes involved in processes like synaptic plasticity (Lyons and West, 2011). FOS has thus become a widely-used molecular tool for identifying cell populations and brain regions that are selectively activated in response to specific stimuli or during specific contexts (Guzowski et al., 2005). Within this framework, group differences in FOS expression within a brain region are typically interpreted as group differences in neuronal excitation in that region. We tested if mating encounters are associated with increased FOS expression in eight OXTR-expressing brain regions: the anterior olfactory nucleus (AON), prelimbic cortex (PLC), nucleus accumbens shell (NAcS), nucleus accumbens core (NAcC), medial amygdala (MeA), basolateral amygdala (BLA), paraventricular nucleus of the hypothalamus (PVN), and ventral tegmental area (VTA). A linear mixed-effects regression in which 1) FOS expression was the dependent variable, 2) mating, brain region, and the interaction between mating and brain region were treated as independent variables, and 3) individual was treated as a random effect revealed significant main effects of brain region (F7,246=79.2; p=2.05×10−59), mating (F1,38=25.9; p=1.01×10−5), and the interaction between brain region and mating (F7,246=4.16; p=2.38×10−4) on FOS expression. After adjustment for multiple comparisons, post-hoc t-tests supported mating-associated increases in FOS expression in every brain region (Benjamini-Hochberg adjusted p-value, pBH≤0.013) except for the PVN, in which the effect was directionally aligned with the other regions but was not statistically significant (pBH=0.134; transformed FOS data shown in Figure 2, mated versus unexposed animals correspond to “Yes” versus “No”; see complete results in Supplementary Table 2). Taken together, these data support widespread mating-associated increases in FOS expression across OXTR-expressing brain regions, consistent with our own and others’ previous work.

Figure 2. Effects of mating context and Oxtr genotype on FOS expression in OXTR-expressing brain regions in male prairie voles.

Figure 2.

Open in a new tab

(A) Schematic of brain regions that were imaged for FOS expression and representative images of brain region-specific FOS staining in unexposed control (top row, all C/T at NT213739) and mated (bottom row, all C/T at NT213739) males. (B) Box and whisker plots showing how batch corrected FOS expression in eight OXTR-expressing brain regions relates to mating context (No=unexposed, Yes=mated) and the number of C alleles at NT213739. Mating was associated with increased FOS expression in all regions except the PVN (pBH<0.05), but the number of C alleles at NT213739 was not associated with FOS expression in any of the analyzed regions (pBH>0.05 in all regions). In all box and whisker plots, the center line indicates the median, the bounds of the box indicate the upper and lower quartiles, and the whiskers indicate 1.5x interquartile range. Abbreviations: AON=anterior olfactory nucleus, PLC=prelimbic cortex, NAcS=nucleus accumbens shell, NAcC=nucleus accumbens core, PVN=paraventricular nucleus of the hypothalamus, MeA=medial amygdala, BLA=basolateral amygdala, VTA=ventral tegmental area. Created in BioRender. Budreckas, I. (2025) https://BioRender.com/blq6qcs.

Oxtr genotype-associated FOS expression within brain regions

We next investigated whether brain region-specific FOS expression levels were associated with the C allele at NT213739. To test this, we fit a separate linear regression model for each brain region in which 1) FOS expression was treated as the dependent variable and 2) genotype (presence of the C allele at NT213739; 0 for T/T, n=13; 1 for C/T, n=13; 2 for C/C, n=14), mating, and the interaction between genotype and mating were treated as independent variables. These analyses did not support an association between the number of C alleles at NT213739 (pBH≥0.31 for all brain regions) or the interaction between mating and the number of C alleles at NT213739 (pBH≥0.35 for all brain regions) on FOS expression in any of the analyzed brain regions (transformed FOS data shown in Figure 2, complete results available in Supplementary Table 3A). Follow-up ANOVA analyses, for which genotype was coded as a categorical variable rather than numeric, also did not support a positive association between genotype or the interaction between mating and genotype on FOS expression in any of the analyzed brain regions (genotype: pBH≥0.25 for all regions, and genotype:mating interaction: pBH≥0.67 for all regions). Consistent with this result, when the analysis was restricted to mated animals only, we again found no evidence for associations between the number of C alleles at NT213739 and FOS expression in any of the analyzed brain regions among mated animals (linear regression, pBH≥0.75 for all brain regions, complete results available in Supplementary Table 3B; ANOVA, pBH≥0.90 for all brain regions). These results suggest that genotype at NT213739 is not associated with differences in FOS expression during mating encounters in any of the analyzed OXTR-expressing regions in male prairie voles.

Association between mating and FOS expression covariance among OXTR-expressing brain regions

In addition to analyzing differences in mean FOS expression between groups, we analyzed differences in correlated FOS expression between groups. Briefly, group differences in correlated FOS expression between two regions are usually interpreted as differences in how excitation in one region is related to excitation in the other (Ben-Ami Bartal et al., 2021; Gossman et al., 2021; Kimbrough et al., 2020; Leal Santos et al., 2021; Rogers-Carter et al., 2018; Tanimizu et al., 2017; Vetere et al., 2017). We previously observed that mating was associated with strongly and positively correlated FOS expression across OXTR-expressing brain regions in male prairie voles, such that subjects with greater FOS expression in one brain region tended to also have greater FOS expression in the other regions (Johnson et al., 2016). Recent work has replicated and extended this effect to many additional brain regions (Gustison et al., 2024). We investigated this effect by estimating FOS expression covariance between each pairwise combination of brain regions among mated (n=31, genotypes pooled) versus unexposed control (n=9, genotypes pooled) animals. Consistent with previous work, we observed a general pattern whereby FOS expression was, on average, modestly more positively correlated across brain regions among males that mated (mean Pearson’s R=0.32) compared to unexposed controls (mean Pearson’s R=0.25; see heatmaps in Supplementary Figure 1). We also tested if patterns of FOS expression covariance differed significantly between mated versus unexposed control males, regardless of the direction of differences, by comparing the underlying FOS expression covariance matrices (see Methods section “Analysis of FOS expression covariance across all brain regions”). This analysis supported distinct patterns of FOS expression covariance among mated versus unexposed control males (χ228 =50.31, p=5.97×10−3). Taken together with our earlier results, these data suggest that mating encounters are associated with correlated increases in FOS expression across OXTR-expressing brain regions in male prairie voles, consistent with previous work (Gustison et al., 2024; Johnson et al., 2016).

Association between Oxtr genotype and FOS expression covariance among OXTR-expressing brain regions

By blocking OXTRs during mating, we previously showed that OXTRs play a role in coordinating FOS responses to mating across OXTR-expressing brain regions. Based on these results, as well as the strong association between the C allele at NT213739 and brain region-specific OXTR expression (King et al., 2016), we reasoned that genotype at NT213739 may be associated with distinct patterns of correlated FOS expression across OXTR-expressing brain regions during mating. Indeed, homozygotes lacking the C allele displayed a stronger, more positive, and more homogeneous pattern of correlated FOS expression across brain regions (Figure 3A) compared to heterozygotes (Figure 3B) and homozygotes carrying the C allele (Figure 3C). Further analyses revealed that patterns of correlated FOS expression differed significantly between mated T/T versus C/C males (χ228 =45.16, p =0.043) and between mated T/T versus C/T males (χ228 =42.98, pBH=0.047), but not between mated C/T versus C/C males (χ228 =24.45, pBH=0.66). Based on the similar patterns between T/T versus C/T and T/T versus C/C males, as well as the lack of differences between C/T versus C/C males, we tested the effect when C/T and C/C males were pooled together (T/T versus C/T and C/C). Indeed, this analysis reinforced genotype-associated differences in FOS expression among mated males (χ228 =69.38, p =9.08×10−5; Supplementary Figure 2). Follow-up analyses suggested that differences in FOS expression covariance among genotypes was unlikely to be related to variation in mating behaviors among subjects (see Methods section “Influence of mating behavior on FOS expression covariance across brain regions” and Supplementary Figure 3).

Figure 3. Oxtr genotype is associated with distinct patterns of correlated FOS expression across OXTR-expressing brain regions during mating encounters in male prairie voles.

Figure 3.

Open in a new tab

(A-C) Heatmaps show the strength of correlated FOS expression among pairwise combinations of OXTR-expressing brain regions in males that are (A) T/T, (B) C/T, and (C) C/C at NT213739. The pattern of correlated FOS expression among these regions differed between T/T males and C/T males and also between T/T males and C/C males (pBH<0.05 in both comparisons), but did not differ between C/T males and C/C males (pBH>0.05). Abbreviations: AON=anterior olfactory nucleus, PLC=prelimbic cortex, NAcS=nucleus accumbens shell, NAcC=nucleus accumbens core, PVN=paraventricular nucleus of the hypothalamus, MeA=medial amygdala, BLA=basolateral amygdala, VTA=ventral tegmental area.

To better understand the influence of genotype on correlated FOS expression between specific brain regions, we used post-hoc Fisher’s z-tests and complementary linear regression analyses (see Methods section “Analysis of correlated FOS expression between individual brain regions”). Briefly, the Fisher’s z-tests mirrored the comparisons described above (mated T/T versus C/T males, mated T/T versus C/C males, and mated T/T versus C/T and C/C males) and were used to test whether FOS expression was differentially correlated between each pairwise combination of brain regions in association with the C allele. In contrast, linear regression was used to test if the slope of the relationship of FOS expression between regions differed in association with the number of C alleles at NT213739. After accounting for multiple comparisons (see Methods “Analysis of correlated FOS expression between individual brain regions”), these analyses supported associations between the C allele and differences in correlated FOS expression between PLC and VTA (FDR-adjusted harmonic mean p-value across Fisher’s z-tests, hmpadj=0.0019), VTA and NAcC (hmpadj=0.0054), PVN and NAcC (hmpadj=0.022), and PLC and NAcC (hmpadj=0.044; scatter plots shown in Supplementary Figure 4; complete results for these as well as additional linear regression analyses available in Supplementary Tables 4 and 5). Taken together, these results support associations between Oxtr genotype and differences in correlated functions of the VTA, PLC, NAcC, and PVN during mating encounters.

DISCUSSION

Understanding how individual variation in neuropeptide systems influences neural and behavioral functions during social contexts is an important knowledge gap in basic and translational neuroscience. In this study, we used the prairie vole model to test whether an Oxtr gene polymorphism influences the function of OXTR-expressing brain regions and behavior during brief mating encounters. While this polymorphism was not associated with marked differences in mating behaviors or levels of FOS expression within the analyzed regions, it was strongly associated with distinct patterns of FOS expression covariance across these regions. At the level of individual brain regions, we found the most consistent evidence for genotype-associated differences in correlated FOS expression among the PVN, VTA, NAcC, and PLC, regions in which OXTRs have been previously shown to regulate social behaviors (Dölen and Malenka, 2014; Hung et al., 2017; Smith and Wang, 2014; Young et al., 2001). Taken together, our findings suggest that individual genetic variation in Oxtr is associated with distinct patterns of correlated FOS expression among OXTR-expressing brain regions during a milestone social encounter in male prairie voles. More broadly, our work supports previously proposed models that variation in neuropeptide receptor expression across limbic and mesolimbic dopaminergic regions is a key contributor to diversity in neural responses to social stimuli (Goodson and Kabelik, 2009; Newman, 1999).

Individual prairie voles vary in the formation of selective social attachments, or pair bonds, with mating partners in the laboratory and in naturalistic field enclosures (King et al., 2016; Madrid et al., 2020; Okhovat et al., 2015; Streatfeild et al., 2011). We previously showed that the C allele at NT213739, which is associated with greater OXTR expression in the striatum in our colony (and more modestly with greater OXTR expression in some other regions) (Inoue et al., 2022; King et al., 2016), is associated with accelerated (<6 hours) partner preference formation in males (King et al., 2016), consistent with findings that socially monogamous behavioral phenotypes are associated with greater striatal OXTR expression in semi-natural field enclosures (Ophir et al., 2012). Based on these studies, we hypothesized that behavioral differences associated with the C allele at NT213739 may be evident early on during initial mating encounters, long before the formation of pair bonds. We did not find evidence for an association between Oxtr genotype and mating behaviors, consistent with our previous studies in which OXTR blockade did not alter mating behaviors in the same paradigm (Johnson et al., 2017, 2016). However, in these studies we analyzed relatively coarse-grained measures of mating behavior across the 30-minute period, and it is possible that subtle Oxtr-associated behavioral differences exist that will be uncovered by more sophisticated (Warren et al., 2025) and/or higher-dimensional behavioral analyses (Berman, 2018). Taken together, our results suggest that the C allele at NT213739 is not associated with major differences in male mating behaviors during initial mating encounters with a female.

Individual variation in Oxtr and region-specific OXTR expression has been linked to social phenotypes in multiple species (Calcagnoli et al., 2014; Dumais et al., 2013; Freeman et al., 2018; Jiménez et al., 2015; Mooney et al., 2015; Olazábal and Sandberg, 2020; Ophir et al., 2012). Although the role of OXTR in neuronal and circuit functions has been extensively studied in several brain regions (Marlin et al., 2015; Mitre et al., 2016; Nakajima et al., 2014; Owen et al., 2013; Xiao et al., 2018), it remains largely unclear how natural variation in Oxtr and region-specific OXTR expression influence these functions. We found that the C allele at NT213739 was not strongly associated with levels of FOS expression within OXTR-expressing brain regions, but was strongly associated with patterns of FOS expression covariance among these regions, consistent with previous studies in male prairie voles and other rodents (Faykoo-Martinez et al., 2018; Johnson et al., 2017, 2016). This result is consistent with two previous studies in which central and region-specific blockade of OXTRs during mating did not alter FOS expression levels within regions but altered how FOS expression was related among regions (Johnson et al., 2017, 2016).

We previously showed that brain-wide OXTR blockade during mating weakens FOS covariance among OXTR-expressing regions, and similarly that targeted NAc OXTR blockade weakens the association between FOS expression in the NAc and FOS expression in other regions (Johnson et al., 2016, 2017). Notably, during these two studies, the T allele was highly prevalent in our colony (~50% T/T, ~40% C/T, ~10% C/C), and thus mated animals with intact OXTR signaling and positive FOS covariance may have been predominantly T/T individuals. Nonetheless, based on our observations of weaker FOS expression covariance following OXTR blockade, we hypothesized that the C allele at NT213739 (associated with greater region-specific OXTR expression) would be associated with more positive FOS covariance. Opposite to this prediction, the C allele at NT213739 was associated with weaker and less positive FOS covariance across regions. Weaker FOS expression covariance associated with 1) OXTR blockade and 2) greater region-specific OXTR expression may be explained by an inverted U-relationship, and would be consistent with studies in naked mole rats in which both exogenous OT delivery and OXTR antagonism weakened FOS expression covariance among regions in multiple social contexts (Faykoo-Martinez et al., 2018). Importantly, although changes in correlated FOS expression may reflect changes in function, the direction of change should not be interpreted as improved, optimal, or adaptive. For example, human neuroimaging studies have demonstrated increased functional connectivity between brain regions in association with a variety of neuropsychiatric dysfunctions (Bas-Hoogendam et al., 2021; Cao et al., 2018; Jie et al., 2016; Supekar et al., 2013; Wang et al., 2020).

We observed the strongest and most consistent evidence for Oxtr genotype-associated differences in correlated FOS expression between VTA and PLC, NAcC and VTA, NAcC and PVN, and NAcC and PLC. All of these regions express OXTRs and are highly interconnected, with the PLC, NAc, and VTA representing key nodes in the well-studied mesolimbic reward network. Previous tracing and functional manipulation studies have shown how oxytocin-synthesizing neurons in the PVN interact with these mesolimbic regions. In rodents, oxytocin-synthesizing neurons in the PVN project to the NAc (Ross et al., 2009), PLC (Gimpl and Fahrenholz, 2001), and VTA (Beier et al., 2015). The VTA is reciprocally interconnected with the PLC (Beckstead et al., 1979; Souza et al., 2022) and NAcC (Beckstead et al., 1979; Heimer et al., 1991), and OXTRs are expressed on dopaminergic and glutamatergic neurons in the VTA that project to the NAc and PLC in mice (Peris et al., 2017). Stimulation of oxytocinergic PVN projections to the VTA facilitate social reward in male mice (Hung et al., 2017), oxytocin gates excitatory inputs from the PLC to the VTA (Xiao et al., 2018), and exogenous oxytocin injections into the VTA increase penile erections and increase dopamine release into the NAc and PVN in rats (Melis et al., 2007). It is intriguing to speculate that the C allele at NT213739 is associated with differences in how social information is encoded into the mesolimbic reward system during initial mating encounters.

There are several limitations to these experiments, some of which we described previously (Johnson et al., 2016; Walum et al., 2016). Notably, FOS expression represents a molecular snapshot at a single timepoint, precluding inferences about real-time information flow across brain regions that can be gained using methods like calcium imaging or electrophysiological recording. Additionally, in these experiments, we studied how Oxtr genotype is associated with FOS expression and behavior in adults, and therefore the effects of variable OXTR expression through development cannot be separated from immediate differences in central OXTR signaling during sociosexual interaction. Future investigations using viral and/or transgenic approaches allowing temporally-controlled central and region-specific gene editing (e.g. CRISPR, transiently regulated Cre-recombination, etc.) can resolve these factors. Importantly, sample sizes in these experiments were relatively small. Studies with larger sample sizes are important for replication, and increased statistical power may reveal behavioral and neural effects associated with Oxtr genotype that were not detected in this study (Walum et al., 2016). Additionally, while this SNP is associated with brain region-specific Oxtr expression in our colony, this association may not generalize to other colonies, as the SNP is likely part of a larger haplotype containing multiple SNPs, only one of which may be causal. It is also important to note that although we analyzed the effect of Oxtr genotype on FOS expression, we did not directly measure Oxtr expression in these subjects. Finally, anatomical resolution of OXTR (and V1aR) expression has advanced slowly due to limitations in development of specific antibodies, hindering interpretations of these and other data at the cellular level. More finely resolved clues will continue to emerge from single cell sequencing (Boender et al., 2023b; Johnson et al., 2023; Moffitt et al., 2018), calcium imaging (Scribner et al., 2020; Yukinaga et al., 2022), double in situ hybridization (Inoue et al., 2022), and gene-editing experiments (Berendzen et al., 2023; Boender et al., 2023a; Horie et al., 2020, 2019) that will collectively provide a deeper and more nuanced understanding of OXTR function.

Despite these limitations, these experiments are to our knowledge the first to link a genetic variant associated with region-specific OXTR expression in the brain to patterns of neuronal activation during social contexts. Our results complement human neuroimaging evidence that genetic variation in OXTR influences functional connectivity among brain regions at rest and in response to social stimuli in healthy (Seeley et al., 2018; Tost et al., 2011, 2010; Wang et al., 2013; Zimmermann et al., 2018) and neuropsychiatric conditions (Hernandez et al., 2020, 2017; Johnson and Young, 2017; Watanabe et al., 2017). Future studies are needed to molecularly define the cell populations and circuits underlying these effects and to understand their functional roles in social learning and behavior.

Supplementary Material

1
2
3
4
5
6

HIGHLIGHTS.

  • Male prairie voles show correlated FOS increases across brain areas during mating

  • Oxtr genotype does not predict major differences in mating behavior or FOS levels

  • Oxtr genotype is associated with neural activity patterns during mating contexts

  • Oxtr genotype is associated with correlated FOS among mesolimbic dopamine regions

ACKNOWLEDGEMENTS

We thank Dr. Larry J. Young for his support, guidance, and mentorship during our time in his laboratory and beyond. We additionally thank Lorra Julian, Kathy Martinez, Dr. Jamie LaPrairie, and Dr. Denyse Levesque for their supportive work surrounding the project and more broadly the Emory National Primate Research Center prairie vole colony. This research was supported in part by NIH grants R35GM155357 to ZVJ; R01MH096983, R01MH112788, and P50MH100023 to LJY; and OD P51OD011132 to Emory National Primate Research Center (ZVJ and LJY).

Footnotes

CRediT authorship contribution statement

Lanikea B. King: Conceptualization, Project administration, Investigation, Writing – original draft, Writing – review & editing; Hasse Walum: Software, Data curation, Methodology, Formal analysis, Visualization, Writing – original draft, Writing – review & editing; Mike Xiao: Investigation, Software, Data curation; Asha Y. Caslin: Investigation, Data curation; Fuad C. Haddad: Investigation; Larry J. Young: Conceptualization, Funding acquisition, Resources, Supervision; Zachary V. Johnson: Conceptualization, Methodology, Funding acquisition, Resources, Supervision, Project administration, Investigation, Data curation, Formal analysis, Visualization, Writing – original draft, Writing – review & editing

Declaration of interests

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Zachary Johnson reports financial support was provided by NIH National Institute of General Medical Sciences. Zachary Johnson reports financial support was provided by National Institute of Mental Health. Larry Young reports financial support was provided by National Institute of Mental Health. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

DATA AVAILABILITY

To facilitate replication, data for this project are available from Zenodo: 10.5281/zenodo.14630590.

REFERENCES

  1. Anacker AM, Beery AK, 2013. Life in groups: the roles of oxytocin in mammalian sociality. Front Behav Neurosci 7, 185. 10.3389/fnbeh.2013.00185 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bas-Hoogendam JM, Steenbergen H. van, Kadosh KC, Westenberg PM, Wee N.J.A. van der, 2021. Intrinsic functional connectivity in families genetically enriched for social anxiety disorder – an endophenotype study. eBioMedicine 69. 10.1016/j.ebiom.2021.103445 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Beckstead RM, Domesick VB, Nauta WJ, 1979. Efferent connections of the substantia nigra and ventral tegmental area in the rat. Brain Res 175, 191–217. 10.1016/0006-8993(79)91001-1 [DOI] [PubMed] [Google Scholar]
  4. Beier KT, Steinberg EE, DeLoach KE, Xie S, Miyamichi K, Schwarz L, Gao XJ, Kremer EJ, Malenka RC, Luo L, 2015. Circuit Architecture of VTA Dopamine Neurons Revealed by Systematic Input-Output Mapping. Cell 162, 622–634. 10.1016/j.cell.2015.07.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Ben-Ami Bartal I, Breton JM, Sheng H, Long KL, Chen S, Halliday A, Kenney JW, Wheeler AL, Frankland P, Shilyansky C, Deisseroth K, Keltner D, Kaufer D, 2021. Neural correlates of ingroup bias for prosociality in rats. eLife 10, e65582. 10.7554/eLife.65582 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Berendzen KM, Sharma R, Mandujano MA, Wei Y, Rogers FD, Simmons TC, Seelke AMH, Bond JM, Larios R, Goodwin NL, Sherman M, Parthasarthy S, Espineda I, Knoedler JR, Beery A, Bales KL, Shah NM, Manoli DS, 2023. Oxytocin receptor is not required for social attachment in prairie voles. Neuron 111, 787–796.e4. 10.1016/j.neuron.2022.12.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Berman Gordon J. 2018. “Measuring Behavior across Scales.” BMC Biology 16 (1): 23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Boender AJ, Boon M, Albers HE, Eck SR, Fricker BA, Kelly AM, LeDoux JE, Motta SC, Shrestha P, Taylor JH, Trainor BC, Triana-Del Rio R, Young LJ, 2023a. An AAV-CRISPR/Cas9 strategy for gene editing across divergent rodent species: Targeting neural oxytocin receptors as a proof of concept. Science Advances 9, eadf4950. 10.1126/sciadv.adf4950 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Boender AJ, Johnson ZV, Gruenhagen GW, Horie K, Hegarty BE, Streelman JT, Walum H, Young LJ, 2023b. Natural variation in oxytocin receptor signaling causes widespread changes in brain transcription: a link to the natural killer gene complex. 10.1101/2023.10.26.564214 [DOI] [Google Scholar]
  10. Borland JM, Aiani LM, Norvelle A, Grantham KN, O’Laughlin K, Terranova JI, Frantz KJ, Albers HE, 2019. Sex-dependent regulation of social reward by oxytocin receptors in the ventral tegmental area. Neuropsychopharmacol 44, 785–792. 10.1038/s41386-018-0262-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Calcagnoli F, de Boer SF, Beiderbeck DI, Althaus M, Koolhaas JM, Neumann ID, 2014. Local oxytocin expression and oxytocin receptor binding in the male rat brain is associated with aggressiveness. Behavioural Brain Research 261, 315–322. 10.1016/j.bbr.2013.12.050 [DOI] [PubMed] [Google Scholar]
  12. Cao H, Chén OY, Chung Y, Forsyth JK, McEwen SC, Gee DG, Bearden CE, Addington J, Goodyear B, Cadenhead KS, Mirzakhanian H, Cornblatt BA, Carrión RE, Mathalon DH, McGlashan TH, Perkins DO, Belger A, Seidman LJ, Thermenos H, Tsuang MT, van Erp TGM, Walker EF, Hamann S, Anticevic A, Woods SW, Cannon TD, 2018. Cerebello-thalamo-cortical hyperconnectivity as a state-independent functional neural signature for psychosis prediction and characterization. Nat Commun 9, 3836. 10.1038/s41467-018-06350-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Dölen G, Malenka RC, 2014. The Emerging Role of Nucleus Accumbens Oxytocin in Social Cognition. Biological Psychiatry 76, 354–355. 10.1016/j.biopsych.2014.06.009 [DOI] [PubMed] [Google Scholar]
  14. Donaldson ZR, Young LJ, 2008. Oxytocin, vasopressin, and the neurogenetics of sociality. Science 322, 900–4. 10.1126/science.1158668 [DOI] [PubMed] [Google Scholar]
  15. Dumais KM, Bredewold R, Mayer TE, Veenema AH, 2013. Sex differences in oxytocin receptor binding in forebrain regions: Correlations with social interest in brain region- and sex-specific ways. Hormones and Behavior 64, 693–701. 10.1016/j.yhbeh.2013.08.012 [DOI] [PubMed] [Google Scholar]
  16. Faykoo-Martinez M, Mooney SJ, Holmes MM, 2018. Oxytocin Manipulation Alters Neural Activity in Response to Social Stimuli in Eusocial Naked Mole-Rats. Frontiers in Behavioral Neuroscience 12. 10.3389/fnbeh.2018.00272 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Freeman SM, Palumbo MC, Lawrence RH, Smith AL, Goodman MM, Bales KL, 2018. Effect of age and autism spectrum disorder on oxytocin receptor density in the human basal forebrain and midbrain. Transl Psychiatry 8, 1–11. 10.1038/s41398-018-0315-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Garrison JL, Macosko EZ, Bernstein S, Pokala N, Albrecht DR, Bargmann CI, 2012. Oxytocin/vasopressin-related peptides have an ancient role in reproductive behavior. Science 338, 540–3. 10.1126/science.1226201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Gimpl G, Fahrenholz F, 2001. The oxytocin receptor system: structure, function, and regulation. Physiol Rev 81, 629–683. 10.1152/physrev.2001.81.2.629 [DOI] [PubMed] [Google Scholar]
  20. Goodson JL, Kabelik D, 2009. Dynamic Limbic Networks and Social Diversity in Vertebrates: From Neural Context to Neuromodulatory Patterning. Front Neuroendocrinol 30, 429–441. 10.1016/j.yfrne.2009.05.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Goodson JL, Schrock SE, Klatt JD, Kabelik D, Kingsbury MA, 2009. Mesotocin and nonapeptide receptors promote estrildid flocking behavior. Science 325, 862–6. 10.1126/science.1174929 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Gossman KR, Dykstra B, García BH, Swopes AP, Kimbrough A, Smith AS, 2021. Pair Bond-Induced Affiliation and Aggression in Male Prairie Voles Elicit Distinct Functional Connectivity in the Social Decision-Making Network. Front. Neurosci. 15. 10.3389/fnins.2021.748431 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Gustison ML, Muñoz-Castañeda R, Osten P, Phelps SM, 2024. Sexual coordination in a whole-brain map of prairie vole pair bonding. Elife 12, RP87029. 10.7554/eLife.87029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Guzowski JF, Timlin JA, Roysam B, McNaughton BL, Worley PF, Barnes CA, 2005. Mapping behaviorally relevant neural circuits with immediate-early gene expression. Current Opinion in Neurobiology, Neuronal and glial cell biology / New technologies 15, 599–606. 10.1016/j.conb.2005.08.018 [DOI] [PubMed] [Google Scholar]
  25. Heimer L, Zahm DS, Churchill L, Kalivas PW, Wohltmann C, 1991. Specificity in the projection patterns of accumbal core and shell in the rat. Neuroscience 41, 89–125. 10.1016/0306-4522(91)90202-Y [DOI] [PubMed] [Google Scholar]
  26. Hernandez L, Lawrence KE, Padgaonkar N, Inada M, Hoekstra J, Lowe J, Eilbott JA, Jack A, Aylward E, Gaab N, Horn JVV, Bernier R, McPartland J, Webb S, Pelphrey K, Green S, Geschwind D, Bookheimer S, Dapretto M, 2020. Imaging-genetics of sex differences in ASD: distinct effects of OXTR variants on brain connectivity. Translational Psychiatry 10. 10.1038/s41398-020-0750-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Hernandez LM, Krasileva K, Green SA, Sherman LE, Ponting C, McCarron R, Lowe JK, Geschwind DH, Bookheimer SY, Dapretto M, 2017. Additive effects of oxytocin receptor gene polymorphisms on reward circuitry in youth with autism. Mol Psychiatry 22, 1134– 1139. 10.1038/mp.2016.209 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Horie K, Inoue K, Nishimori K, Young LJ, 2020. Investigation of Oxtr-expressing Neurons Projecting to Nucleus Accumbens using Oxtr-ires-Cre Knock-in prairie Voles (Microtus ochrogaster). Neuroscience 448, 312–324. 10.1016/j.neuroscience.2020.08.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Horie K, Inoue K, Suzuki S, Adachi S, Yada S, Hirayama T, Hidema S, Young LJ, Nishimori K, 2019. Oxytocin receptor knockout prairie voles generated by CRISPR/Cas9 editing show reduced preference for social novelty and exaggerated repetitive behaviors. Hormones and Behavior, SBN/ICN Meeting 2018 111, 60–69. 10.1016/j.yhbeh.2018.10.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Hung LW, Neuner S, Polepalli JS, Beier KT, Wright M, Walsh JJ, Lewis EM, Luo L, Deisseroth K, Dölen G, Malenka RC, 2017. Gating of social reward by oxytocin in the ventral tegmental area. Science 357, 1406–1411. 10.1126/science.aan4994 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Inoue K, Ford CL, Horie K, Young LJ, 2022. Oxytocin receptors are widely distributed in the prairie vole (Microtus ochrogaster) brain: Relation to social behavior, genetic polymorphisms, and the dopamine system. J Comp Neurol 530, 2881–2900. 10.1002/cne.25382 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Jie B, Wee C-Y, Shen D, Zhang D, 2016. Hyper-connectivity of functional networks for brain disease diagnosis. Medical Image Analysis 32, 84–100. 10.1016/j.media.2016.03.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Jiménez A, Young LJ, Río RT-D, LaPrairie JL, González-Mariscal G, 2015. Neuroanatomical distribution of oxytocin receptor binding in the female rabbit forebrain: Variations across the reproductive cycle. Brain Research 1629, 329–339. 10.1016/j.brainres.2015.10.043 [DOI] [PubMed] [Google Scholar]
  34. Johnson WE, Li C, Rabinovic A, 2007. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127. 10.1093/biostatistics/kxj037 [DOI] [PubMed] [Google Scholar]
  35. Johnson ZV, Hegarty BE, Gruenhagen GW, Lancaster TJ, McGrath PT, Streelman JT, 2023. Cellular profiling of a recently-evolved social behavior in cichlid fishes. Nat Commun 14, 4891. 10.1038/s41467-023-40331-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Johnson ZV, Walum H, Jamal YA, Xiao Y, Keebaugh AC, Inoue K, Young LJ, 2016. Central oxytocin receptors mediate mating-induced partner preferences and enhance correlated activation across forebrain nuclei in male prairie voles. Hormones and Behavior 79, 8–17. 10.1016/j.yhbeh.2015.11.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Johnson ZV, Walum H, Xiao Y, Riefkohl PC, Young LJ, 2017. Oxytocin receptors modulate a social salience neural network in male prairie voles. Hormones and Behavior 87, 16–24. 10.1016/j.yhbeh.2016.10.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Johnson ZV, Young LJ, 2018. Evolutionary diversity as a catalyst for biological discovery. Integr Zool 13, 616–633. 10.1111/1749-4877.12339 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Johnson ZV, Young LJ, 2017. Oxytocin and vasopressin neural networks: Implications for social behavioral diversity and translational neuroscience. Neuroscience & Biobehavioral Reviews 76, 87–98. 10.1016/j.neubiorev.2017.01.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Jurek B, Neumann ID, 2018. The Oxytocin Receptor: From Intracellular Signaling to Behavior. Physiol Rev 98, 1805–1908. 10.1152/physrev.00031.2017 [DOI] [PubMed] [Google Scholar]
  41. Kimbrough A, Lurie DJ, Collazo A, Kreifeldt M, Sidhu H, Macedo GC, D’Esposito M, Contet C, George O, 2020. Brain-wide functional architecture remodeling by alcohol dependence and abstinence. Proceedings of the National Academy of Sciences 117, 2149– 2159. 10.1073/pnas.1909915117 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. King LB, Walum H, Inoue K, Eyrich NW, Young LJ, 2016. Variation in the Oxytocin Receptor Gene Predicts Brain Region–Specific Expression and Social Attachment. Biological Psychiatry 80, 160–169. 10.1016/j.biopsych.2015.12.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Knobloch HS, Grinevich V, 2014. Evolution of oxytocin pathways in the brain of vertebrates. Front Behav Neurosci 8, 31. 10.3389/fnbeh.2014.00031 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Leal Santos S, Stackmann M, Muñoz Zamora A, Mastrodonato A, De Landri AV, Vaughan N, Chen BK, Lanio M, Denny CA, 2021. Propranolol Decreases Fear Expression by Modulating Fear Memory Traces. Biological Psychiatry, Mechanisms of Stress and Fear 89, 1150–1161. 10.1016/j.biopsych.2021.01.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Lee HJ, Macbeth AH, Pagani JH, Young WS, 2009. Oxytocin: the great facilitator of life. Prog Neurobiol 88, 127–51. 10.1016/j.pneurobio.2009.04.001S0301-0082(09)00046-X [pii] [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Lyons MR, West AE, 2011. Mechanisms of specificity in neuronal activity-regulated gene transcription. Prog Neurobiol 94, 259–295. 10.1016/j.pneurobio.2011.05.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Madrid JE, Parker KJ, Ophir AG, 2020. Chapter Five - Variation, plasticity, and alternative mating tactics: Revisiting what we know about the socially monogamous prairie vole, in: Naguib M, Barrett L, Healy SD, Podos J, Simmons LW, Zuk M (Eds.), Advances in the Study of Behavior. Academic Press, pp. 203–242. 10.1016/bs.asb.2020.02.001 [DOI] [Google Scholar]
  48. Marlin BJ, Mitre M, D’amour JA, Chao MV, Froemke RC, 2015. Oxytocin enables maternal behaviour by balancing cortical inhibition. Nature 520, 499–504. 10.1038/nature14402 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Melis MR, Melis T, Cocco C, Succu S, Sanna F, Pillolla G, Boi A, Ferri G-L, Argiolas A, 2007. Oxytocin injected into the ventral tegmental area induces penile erection and increases extracellular dopamine in the nucleus accumbens and paraventricular nucleus of the hypothalamus of male rats. Eur J Neurosci 26, 1026–1035. 10.1111/j.1460-9568.2007.05721.x [DOI] [PubMed] [Google Scholar]
  50. Mitre M, Marlin BJ, Schiavo JK, Morina E, Norden SE, Hackett TA, Aoki CJ, Chao MV, Froemke RC, 2016. A Distributed Network for Social Cognition Enriched for Oxytocin Receptors. J. Neurosci. 36, 2517–2535. 10.1523/JNEUROSCI.2409-15.2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Moffitt JR, Bambah-Mukku D, Eichhorn SW, Vaughn E, Shekhar K, Perez JD, Rubinstein ND, Hao J, Regev A, Dulac C, Zhuang X, 2018. Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region. Science 362. 10.1126/science.aau5324 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Mooney SJ, Coen CW, Holmes MM, Beery AK, 2015. Region-specific associations between sex, social status, and oxytocin receptor density in the brains of eusocial rodents. Neuroscience 303, 261–269. 10.1016/j.neuroscience.2015.06.043 [DOI] [PubMed] [Google Scholar]
  53. Nagasawa M, Mitsui S, En S, Ohtani N, Ohta M, Sakuma Y, Onaka T, Mogi K, Kikusui T, 2015. Social evolution. Oxytocin-gaze positive loop and the coevolution of human-dog bonds. Science 348, 333–6. 10.1126/science.1261022 348/6232/333 [pii] [DOI] [PubMed] [Google Scholar]
  54. Nakajima M, Görlich A, Heintz N, 2014. Oxytocin Modulates Female Sociosexual Behavior through a Specific Class of Prefrontal Cortical Interneurons. Cell 159, 295–305. 10.1016/j.cell.2014.09.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Newman SW, 1999. The medial extended amygdala in male reproductive behavior. A node in the mammalian social behavior network. Ann N Y Acad Sci 877, 242–257. 10.1111/j.1749-6632.1999.tb09271.x [DOI] [PubMed] [Google Scholar]
  56. O’Connell LA, Hofmann HA, 2011. The vertebrate mesolimbic reward system and social behavior network: a comparative synthesis. Journal of Comparative Neurology 519, 3599–639. 10.1002/cne.22735 [DOI] [PubMed] [Google Scholar]
  57. Okabe S, Yoshida M, Takayanagi Y, Onaka T, 2015. Activation of hypothalamic oxytocin neurons following tactile stimuli in rats. Neurosci Lett 600, 22–27. S0304-3940(15)00422-X [pii] 10.1016/j.neulet.2015.05.055 [DOI] [PubMed] [Google Scholar]
  58. Okhovat M, Berrio A, Wallace G, Ophir AG, Phelps SM, 2015. Sexual fidelity trade-offs promote regulatory variation in the prairie vole brain. Science 350, 1371–1374. 10.1126/science.aac5791 [DOI] [PubMed] [Google Scholar]
  59. Olazábal DE, Sandberg NY, 2020. Variation in the density of oxytocin receptors in the brain as mechanism of adaptation to specific social and reproductive strategies. Gen Comp Endocrinol 286, 113337. 10.1016/j.ygcen.2019.113337 [DOI] [PubMed] [Google Scholar]
  60. Olazábal DE, Young LJ, 2006a. Oxytocin receptors in the nucleus accumbens facilitate “spontaneous” maternal behavior in adult female prairie voles. Neuroscience 141, 559–568. 10.1016/j.neuroscience.2006.04.017 [DOI] [PubMed] [Google Scholar]
  61. Olazábal DE, Young LJ, 2006b. Species and individual differences in juvenile female alloparental care are associated with oxytocin receptor density in the striatum and the lateral septum. Hormones and Behavior 49, 681–687. 10.1016/j.yhbeh.2005.12.010 [DOI] [PubMed] [Google Scholar]
  62. Ophir AG, Gessel A, Zheng D-J, Phelps SM, 2012. Oxytocin receptor density is associated with male mating tactics and social monogamy. Hormones and Behavior, Oxytocin, Vasopressin and Social Behavior 61, 445–453. 10.1016/j.yhbeh.2012.01.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Owen SF, Tuncdemir SN, Bader PL, Tirko NN, Fishell G, Tsien RW, 2013. Oxytocin enhances hippocampal spike transmission by modulating fast-spiking interneurons. Nature 500, 458–462. 10.1038/nature12330 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Peris J, MacFadyen K, Smith JA, de Kloet AD, Wang L, Krause EG, 2017. Oxytocin receptors are expressed on dopamine and glutamate neurons in the mouse ventral tegmental area that project to nucleus accumbens and other mesolimbic targets. Journal of Comparative Neurology 525, 1094–1108. 10.1002/cne.24116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Rogers-Carter MM, Varela JA, Gribbons KB, Pierce AF, McGoey MT, Ritchey M, Christianson JP, 2018. Insular cortex mediates approach and avoidance responses to social affective stimuli. Nat Neurosci 21, 404–414. 10.1038/s41593-018-0071-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Ross HE, Cole CD, Smith Y, Neumann ID, Landgraf R, Murphy AZ, Young LJ, 2009. Characterization of the oxytocin system regulating affiliative behavior in female prairie voles. Neuroscience 162, 892–903. 10.1016/j.neuroscience.2009.05.055 [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Sabihi S, Dong SM, Durosko NE, Leuner B, 2014. Oxytocin in the medial prefrontal cortex regulates maternal care, maternal aggression and anxiety during the postpartum period. Front. Behav. Neurosci. 8. 10.3389/fnbeh.2014.00258 [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Scribner JL, Vance EA, Protter DSW, Sheeran WM, Saslow E, Cameron RT, Klein EM, Jimenez JC, Kheirbek MA, Donaldson ZR, 2020. A neuronal signature for monogamous reunion. Proceedings of the National Academy of Sciences 117, 11076–11084. 10.1073/pnas.1917287117 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Seeley SH, Chou Y, O’Connor M-F, 2018. Intranasal oxytocin and OXTR genotype effects on resting state functional connectivity: A systematic review. Neuroscience & Biobehavioral Reviews 95, 17–32. 10.1016/j.neubiorev.2018.09.011 [DOI] [PubMed] [Google Scholar]
  70. Seltzer LJ, Ziegler TE, Pollak SD, 2010. Social vocalizations can release oxytocin in humans. Proceedings. Biological sciences / The Royal Society 277, 2661–6. 10.1098/rspb.2010.0567 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Smith AS, Wang Z, 2014. Hypothalamic Oxytocin Mediates Social Buffering of the Stress Response. Biological Psychiatry, Neurobiological Moderators of Stress Response 76, 281–288. 10.1016/j.biopsych.2013.09.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Souza R, Bueno D, Lima LB, Muchon MJ, Gonçalves L, Donato J, Shammah-Lagnado SJ, Metzger M, 2022. Top-down projections of the prefrontal cortex to the ventral tegmental area, laterodorsal tegmental nucleus, and median raphe nucleus. Brain Struct Funct 227, 2465– 2487. 10.1007/s00429-022-02538-2 [DOI] [PubMed] [Google Scholar]
  73. Streatfeild CA, Mabry KE, Keane B, Crist TO, Solomon NG, 2011. Intraspecific variability in the social and genetic mating systems of prairie voles, Microtus ochrogaster. Animal Behaviour 82, 1387–1398. 10.1016/j.anbehav.2011.09.023 [DOI] [Google Scholar]
  74. Supekar K, Uddin LQ, Khouzam A, Phillips J, Gaillard WD, Kenworthy LE, Yerys BE, Vaidya CJ, Menon V, 2013. Brain Hyperconnectivity in Children with Autism and its Links to Social Deficits. Cell Reports 5, 738–747. 10.1016/j.celrep.2013.10.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Tanimizu T, Kenney JW, Okano E, Kadoma K, Frankland PW, Kida S, 2017. Functional Connectivity of Multiple Brain Regions Required for the Consolidation of Social Recognition Memory. J. Neurosci. 37, 4103–4116. 10.1523/JNEUROSCI.3451-16.2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Tost H, Kolachana B, Hakimi S, Lemaitre H, Verchinski BA, Mattay VS, Weinberger DR, Meyer–Lindenberg A, 2010. A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function. Proceedings of the National Academy of Sciences 107, 13936–13941. 10.1073/pnas.1003296107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Tost H, Kolachana B, Verchinski BA, Bilek E, Goldman AL, Mattay VS, Weinberger DR, Meyer-Lindenberg A, 2011. Neurogenetic Effects of OXTR rs2254298 in the Extended Limbic System of Healthy Caucasian Adults. Biological Psychiatry 70, e37–e39. 10.1016/j.biopsych.2011.06.034 [DOI] [PubMed] [Google Scholar]
  78. Vetere G, Kenney JW, Tran LM, Xia F, Steadman PE, Parkinson J, Josselyn SA, Frankland PW, 2017. Chemogenetic Interrogation of a Brain-wide Fear Memory Network in Mice. Neuron 94, 363–374.e4. 10.1016/j.neuron.2017.03.037 [DOI] [PubMed] [Google Scholar]
  79. Walum H, Waldman ID, Young LJ, 2016. Statistical and Methodological Considerations for the Interpretation of Intranasal Oxytocin Studies. Biological Psychiatry, Oxytocin and Psychiatry: From DNA to Social Behavior 79, 251–257. 10.1016/j.biopsych.2015.06.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Walum H, Young LJ, 2018. The neural mechanisms and circuitry of the pair bond. Nat Rev Neurosci 19, 643–654. 10.1038/s41583-018-0072-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Wang J, Qin W, Liu B, Wang D, Zhang Y, Jiang T, Yu C, 2013. Variant in OXTR gene and functional connectivity of the hypothalamus in normal subjects. NeuroImage 81, 199–204. 10.1016/j.neuroimage.2013.05.029 [DOI] [PubMed] [Google Scholar]
  82. Wang Y, Gao Y, Tang S, Lu L, Zhang L, Bu X, Li H, Hu Xiaoxiao, Hu Xinyu, Jiang P, Jia Z, Gong Q, Sweeney JA, Huang X, 2020. Large-scale network dysfunction in the acute state compared to the remitted state of bipolar disorder: A meta-analysis of resting-state functional connectivity. eBioMedicine 54. 10.1016/j.ebiom.2020.102742 [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Warren MR, Zha J, Young LJ, Liu RC, 2025. Vocal recognition of partners by female prairie voles. iScience 28, 111796. 10.1016/j.isci.2025.111796 [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Watanabe T, Otowa T, Abe O, Kuwabara H, Aoki Y, Natsubori T, Takao H, Kakiuchi C, Kondo K, Ikeda M, Iwata N, Kasai K, Sasaki T, Yamasue H, 2017. Oxytocin receptor gene variations predict neural and behavioral response to oxytocin in autism. Soc Cogn Affect Neurosci 12, 496–506. 10.1093/scan/nsw150 [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Williams AV, Duque-Wilckens N, Ramos-Maciel S, Campi KL, Bhela SK, Xu CK, Jackson K, Chini B, Pesavento PA, Trainor BC, 2020. Social approach and social vigilance are differentially regulated by oxytocin receptors in the nucleus accumbens. Neuropsychopharmacol. 45, 1423–1430. 10.1038/s41386-020-0657-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Xiao L, Priest MF, Kozorovitskiy Y, 2018. Oxytocin functions as a spatiotemporal filter for excitatory synaptic inputs to VTA dopamine neurons. eLife 7, e33892. 10.7554/eLife.33892 [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Young LJ, Lim MM, Gingrich B, Insel TR, 2001. Cellular mechanisms of social attachment. Horm Behav 40, 133–138. 10.1006/hbeh.2001.1691 [DOI] [PubMed] [Google Scholar]
  88. Yukinaga H, Hagihara M, Tsujimoto K, Chiang H-L, Kato S, Kobayashi K, Miyamichi K, 2022. Recording and manipulation of the maternal oxytocin neural activities in mice. Current Biology 32, 3821–3829.e6. 10.1016/j.cub.2022.06.083 [DOI] [PubMed] [Google Scholar]
  89. Zimmermann J, Deris N, Montag C, Reuter M, Felten A, Becker B, Weber B, Markett S, 2018. A common polymorphism on the oxytocin receptor gene (rs2268498) and resting-state functional connectivity of amygdala subregions - A genetic imaging study. NeuroImage 179, 1–10. 10.1016/j.neuroimage.2018.06.014 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS2086036-supplement-1.csv (210B, csv)
2
NIHMS2086036-supplement-2.csv (315B, csv)
3
NIHMS2086036-supplement-3.xlsx (13.9KB, xlsx)
4
NIHMS2086036-supplement-4.csv (2.9KB, csv)
5
NIHMS2086036-supplement-5.csv (5.6KB, csv)
6
NIHMS2086036-supplement-6.docx (906.2KB, docx)

Data Availability Statement

To facilitate replication, data for this project are available from Zenodo: 10.5281/zenodo.14630590.

RESOURCES