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. 2022 Aug;29(8):203–215. doi: 10.1101/lm.053599.122

Assessing the importance of sex in a hippocampus-dependent behavioral test battery in C57BL/6NTac mice

Korey D Stevanovic 1,3, Sydney A Fry 1,3, Jemma MS DeFilipp 1, Nicholas Wu 2, Briana J Bernstein 1, Jesse D Cushman 1
PMCID: PMC9374270  PMID: 35882502

Abstract

Inclusion of male and female subjects in behavioral neuroscience research requires a concerted effort to characterize sex differences in standardized behavioral assays. Sex differences in hippocampus-dependent assays have been widely reported but are still poorly characterized. In the present study, we conducted a parametric analysis of spontaneous alternation, object recognition, and fear conditioning in a commonly used control strain, C57BL/6NTac. Our findings show largely similar performance between males and females across the majority of behavioral end points. However, we identified an important difference in nonassociative fear sensitization, whereby females showed an enhanced fear response to the 75-dB tone that is used as the conditional stimulus. In addition, we observed an impairment in object location performance in females that was ameliorated by more extensive habituation to handling. Together, these findings argue that sex differences in nonassociative fear responses to both novel auditory cues and novel objects need to be considered when designing and interpreting cognitive assays in C57BL/6 mice. Furthermore, this elevated fear sensitization could serve as a novel approach to model the increased incidence of anxiety disorders in women.

Conducting sex-balanced studies in neurobehavioral research requires a concerted effort to reverse long-standing andronormativity, in part by characterizing baseline performance in male and female control subjects (Brown and Bolivar 2018; Shansky and Murphy 2021). Despite known differences in sex hormones, biological stress systems, and genetics, male models are more conventionally used. This bias is most commonly attributed to a desire to avoid variability from the estrous cycle in females, despite no evidence that females are more variable than males, and underserves the entire population via potentially undetected avenues for clinical treatment (Meziane et al. 2007; Clayton and Collins 2014; Prendergast et al. 2014). Researchers need to understand which assays produce sex differences in controls to design appropriately powered experiments and interpret the results befittingly. This is critical to resolving both the reproducibility crisis and ensuring translational relevance (Pigott 2003; Clayton and Collins 2014; Li and Graham 2017; Shansky and Murphy 2021). There are widespread sex differences in the incidence of behavioral disorders, such as anxiety, depression, and substance use disorders (Altemus et al. 2014; Agabio et al. 2016). The present study aims to characterize the performance of male and female C57BL/6NTac mice in a standardized behavioral test battery of hippocampal function. The hippocampus is critical for spatial, temporal, and contextual learning and memory (Howard and Eichenbaum 2015) and plays an important role in a wide range of neurodevelopmental, neurodegenerative, and neuropsychiatric disorders (Hillerer et al. 2019). The present study focused on three widely used assays: spontaneous alternation, object recognition, and fear conditioning. The goal was to subject these assays to a careful parametric analysis to (1) confirm that they are indeed measuring the type of learning and memory they were designed for (O'Leary and Brown 2012) and (2) determine whether this is consistent across males and females. The C57BL/6NTac substrain was selected for this analysis, as it is a commonly used control strain and has been shown to express more robust fear conditioning (Radulovic et al. 1998). In order to properly design sex-balanced studies, it is critical to establish whether there are sex differences in both baseline performance and the nature of the primary learning process being assessed.

Spontaneous alternation is a simple and high-throughput spatial working memory assay (Lalonde 2002; Kraeuter et al. 2019), particularly for animal models of Alzheimer's disease (Davis et al. 2017). It involves assessing an animal's innate tendency to explore a novel environment in a nonrandom and efficient pattern such that it is more likely to explore a maze arm that is more novel relative to a more recently traversed arm. In a three-arm Y-maze, the animal tends to alternate visits to each of the three arms in succession rather than a purely random pattern (Hughes 2004). Sex differences in spontaneous alternation have been reported but have not been consistently characterized (Conrad et al. 2003; Ulloa et al. 2004; Agrati et al. 2005; Carreira et al. 2017). This task is thought to be spatially mediated in that the mice form a spatial representation of the environment using distal visual cues. The task also requires working memory, as the animal must maintain a memory of the arm it most recently visited (Kraeuter et al. 2019). Sex differences have been reported in spatial learning both in rodents and humans; however, the differences are often quite small, not consistently observed, and domain-specific (Monfort et al. 2015; Voyer et al. 2017; Yagi and Galea 2019). This is likely influenced by differences in task parameters, such as the richness of distal visual cues and the relative reliance on spatial versus nonspatial strategies. In order to assess whether this task depends on distal visual cues equally in males and females, we used three different distal cue conditions: stimulus-rich distal visual cues, stimulus-poor distal visual cues, and total darkness (Lennartz 2008; O'Leary and Brown 2012).

Object recognition assays rely on the innate tendency of rodents to investigate novel objects more than familiar ones. In the most common procedure, the subjects are familiarized with two identical objects. After a delay period, the animals are re-exposed to one novel and one familiar object. Intact learning and memory are inferred by increased investigation of the novel object. This task has been shown to be hippocampus-independent under some conditions, relying primarily on cortical structures such as the perirhinal cortex and medial prefrontal cortex (Barker et al. 2007; Winters et al. 2008; Warburton and Brown 2015). However, recent evidence suggests that long retention intervals in mice render the task hippocampus-dependent (Hammond 2004; Cohen and Stackman 2015). Another common approach is to displace one of the objects for the second exposure, commonly referred to as the object location task (Ennaceur et al. 1997; Assini et al. 2009). This task has been shown to be hippocampus-dependent, presumably due to a spatial learning and memory component (Assini et al. 2009). Sex differences have been reported in both object recognition and object location assays, but the results are inconsistent (Sutcliffe et al. 2007; Koss and Frick 2017; Mccarthy et al. 2018). One report suggests that females may be better able to detect more subtle differences in the features of the object (Bettis and Jacobs 2012). To address this, we used two object pairs: distinctly different objects and similar objects. In addition, sex differences in object location may be influenced by the displacement distance, so we used two conditions: large displacement and small displacement.

Fear conditioning involves pairing mild aversive footshocks with contextual and discrete conditional stimuli (Curzon et al. 2009; Cushman and Fanselow 2010). The hippocampus forms an integrated, multisensory representation of the contextual stimuli that can then be associated with the shock. Delay tone conditioning protocols, where the shock coterminates or immediately follows the tone presentation, produces a hippocampus-independent tone–shock association (Oh and Han 2020). Extending the interval between the tone and the shock to 15–20 sec can render the tone–shock association hippocampus-dependent and is referred to as trace conditioning (Chowdhury et al. 2005; Wanisch et al. 2005; Cushman and Fanselow 2010; Gilmartin et al. 2014). The hippocampus is thought to maintain a “trace” of the tone presentation over time, allowing the tone–shock association to form, although the exact mechanisms are still unclear (Knight 2004; Gilmartin et al. 2014). Re-exposure to the training context drives the expression of the species-specific defensive reaction of freezing, which is expressed in proportion to the strength of the context–shock association. Re-exposure to the tone—typically in a neutral, novel context—drives freezing in proportion to the tone–shock association. However, an often overlooked but important confounder of these assays is that the tone–shock association is not the only contributor to the expression of freezing. Nonassociative factors can also drive freezing. Prior shock exposure can sensitize the animal to subsequently respond more fearfully to otherwise neutral stimuli. While nonassociative controls were once commonplace (Rescorla 1967; Mackintosh 1974), they are very infrequently run, and nonassociative contribution to freezing is often not considered (although see Siegmund and Wotjak 2007a,b; Hassien et al. 2020).

Prior studies have reported sex differences in tone freezing; however, the extent to which these differences are driven by associative versus nonassociative factors is unknown (Moore et al. 2010; Ter Horst et al. 2012; Day et al. 2020; Hassien et al. 2020). To characterize sex differences in associative versus nonassociative fear learning and memory, we used five different fear conditioning protocols: two associative protocols (Trace and Delay) and three nonassociative protocols (Sensitization, Explicitly Unpaired, and No Shock). The Sensitization control involves context-only shock presentations with no tone presented during training. In the Explicitly Unpaired protocol, the shock and tone are separated by as long as possible (90 sec). In the No Shock protocol, only the tone was presented during the “training” session. We also sought to characterize potential sex differences in context conditioning, as differences have been reported (Maren et al. 1994; Barker and Galea 2010) and there is also some evidence to suggest that context fear is modulated by the estrous cycle (Cushman et al. 2014; Trask et al. 2020).

Results

Spontaneous alternation

We observed no sex differences in percent alternations across all three cue conditions (cued: n = 51 male, 51 female; uncued: n = 20 male, 20 female; and red light: n = 24 male, 24 female; effect of sex: F(1, 184) = 1.689, P = 0.195) (Fig. 1B). Cued and uncued conditions showed similar levels of alternation; however, alternations were reduced under the red light condition (effect of cued condition: F(2, 184) = 35.330, P < 0.001, P < 0.001 for red light relative to both cued and uncued). In addition, percent alternation was above chance in both the cued and uncued conditions (P < 0.001) but was not above chance in the red light condition (P = 0.523). This indicates that under the red light condition, where no distal visual cues are available, percentage alternation is at chance levels. Explicitly placing cues on the walls did not provide any additional benefit to percent alternation relative to the cues already available in the testing arena. This indicates that the spatial cues available in the testing room are sufficient to support alternation. Finally, we observed no sex differences in spontaneous alternation.

Figure 1.

Figure 1.

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Sex difference characterization in spontaneous alternation. (A) Diagram of the spontaneous alternation task. Mice were allowed to freely explore the Y-maze for 8 min, and the sequence of arm entries was recorded. An alternation was defined as consecutively visiting each of the three arms in succession (left), whereas a nonalternation occurred when the mouse revisited one of the three arms (right). (B) Diagram of the three cue conditions. Cued: Large shapes were placed around the maze to provide rich visual cues. Uncued: No explicit visual cues were provided other than those naturally present in the circular curtained testing area. Red light: Testing was conducted under red light, so no visual input was available to the animal. (C) No sex differences were observed in spontaneous alternation performance. Cued versus uncued showed similar levels of above-chance performance, whereas performance was at chance under red light. (D) Females showed an overall increase in distance traveled driven primarily in the cued and uncued conditions. Both males and females showed a reduction in distance traveled in red light relative to cued and uncued conditions. (*) P < 0.05.

We also analyzed the total distance traveled during the 8-min spontaneous alternation assay (Fig. 1C) using an ANOVA with cue condition and sex as factors. For this measure, there was an overall effect of sex (F(1, 184) = 14.297, P < 0.001) and cue condition (F(2, 184) = 7.606, P = 0.001) but no interaction effect. The sex difference was driven by increased distance traveled in the females, primarily in the cued (P = 0.004) and uncued (P = 0.010) conditions. The red light condition showed reduced distance moved relative to cued and uncued (P < 0.01). This indicates greater exploratory locomotion in females relative to males and an overall reduction in locomotion in the total darkness conditions of the red light condition.

Novel/spatial object recognition

For the novel object recognition experiments, we observed a similar significant preference for the novel object in both males (F(1, 19) = 5.124, P = 0.036, n = 20) and females (F(1, 19) = 4.670, P = 0.044, n = 20) (Fig. 2D). We also failed to observe any effect of the two different object pairs that were intended to create two different difficulty levels (effect of object difficulty: F(1, 36) = 0.529, P = 0.472; sex by difficulty interaction: F(1, 36) = 0.0007, P = 0.931) (Supplemental Fig. S1C) and therefore pooled the results across these object pairs. These results indicate no sex difference in novel object recognition with a 24-h delay between familiarization and testing. Furthermore, the lack of an impact of the similar versus distinct object pairs indicates that both pairs were equally discriminable by both male and female mice.

Figure 2.

Figure 2.

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Sex difference characterization in novel and spatial object recognition. (A) Diagram for the tasks. (B) Under conditions of minimal handling prior to the experiment, males showed significantly increased investigation of the displaced object, whereas females did not. (C) When given more extensive handling, both males and females showed a significant preference for the displaced object. (D) Object recognition performance was similar between males and females. (*) P < 0.05.

For the spatial object recognition assay, we observed that only the male mice showed a significant preference for the displaced object (F(1, 9) = 6.437, P = 0.032; n = 10 male, large displacement; n = 10 male, small displacement; n = 9 female, large displacement; n = 10 female, small displacement) (Fig. 2B). This indicates a sex difference in that male mice were able to show successful spatial object recognition performance, whereas females did not. We next tested whether more extensive handling procedures could improve performance in the task and the extent to which this might impact the sex difference that we observed. With more extensive handling, both male and female mice showed a significant preference for the displaced object under large displacement conditions (P = 0.001 and P = 0.037, respectively; n = 14 male, large displacement; n = 14 male, small displacement; n = 12 female, large displacement; n = 11 female, small displacement) (Fig. 2C). Neither sex showed a significant preference under the small displacement condition (Supplemental Fig. S1A,B). Further examination of the total amount of object investigation between minimal and extensive handling showed that investigation was greatly increased in both sexes on the familiarization (Supplemental Fig. S2A) and test (Supplemental Fig. S2B) days. These findings indicate that under more extensive handling conditions, female mice can show successful spatial object recognition. More extensive handling increases object investigation in both sexes; however, this seems to specifically impact task performance in females.

Context test

As seen in Figure 4A (below), there was no effect of fear conditioning type (FC type; F(3, 95) = 0.783, P = 0.507), sex (F(1, 95) = 0.211, P = 0.647), or interaction (F(3, 95) = 1.538, P = 0.210; n = 12 males and n = 12 females for Delay, Trace, Explicitly Unpaired, and Sensitization; n = 16 males and n = 16 females for No Shock) (see Fig. 3 for description of tone fear parameters). The No Shock group had substantially lower freezing levels than all other groups (P < 0.001, 5.94% ± 2.47% SEM), as expected, and was not included in the minute-by-minute analysis of the shock groups. We analyzed the minute-by-minute freezing kinetics to determine whether sex or fear conditioning protocol made an impact. There was an overall effect of minutes (F(7, 609) = 12.398, P < 0.001) driven by the typical pattern of reduced freezing in the first minute as well as an interaction of minute × sex (F(7, 609) = 3.256, P = 0.002). Closer inspection of sex differences within each FC type showed elevated freezing in females for Explicitly Unpaired at minutes 6 and 7 (P = 0.021 and P = 0.046, respectively) (Fig. 4E) and a reduction in freezing in females for Trace at minute 1 (P = 0.009) (Fig. 4D). Closer inspection of freezing in the first minute showed a significant effect of FC type for females (F(4, 47) = 3.277, P < 0.03) (Fig. 4B) but not for males (F(3, 48) = 0.242, P = 0.866). Within females, the Trace conditioned group showed significantly less freezing than Delay (P = 0.009) or Explicitly Unpaired (P = 0.012). Overall, these findings show that average freezing across an 8-min test is not significantly impacted by sex or fear conditioning protocol; however, there are significant sex differences in the minute-by-minute kinetics, particularly within the first minute.

Figure 4.

Figure 4.

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Characterization of sex differences for context freezing. (A) There were no overall differences in context freezing average across 8 min. (B) Freezing during the first minute of the context test interacted with sex and conditioning protocol. Males showed similar levels regardless of protocol, whereas females showed a reduction in Trace relative to Delay or Explicitly Unpaired. (C–F) Minute-by-minute kinetics of context freezing for the different protocols. (*) P < 0.05.

Figure 3.

Figure 3.

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Diagram of fear conditioning protocols. (A) Training and testing took place over 3 d: day 1—training, day 2—context test, and day 3—tone test. (B) For each protocol, the shock was presented relative to the tone as follows: Delay: Shock immediately followed the tone. Trace: Shock occurred 20 sec after the tone. Explicitly Unpaired: The shock was separated as much as possible from the tone (90 sec). Sensitization: The tone was not presented; five shocks were presented in the absence of the tone. No Shock: Only the tone was presented. (C) For both training and testing, the tone was presented five times over the 21.5-min session. P < 0.05.

Tone test

We first analyzed tone and posttone freezing averaged across the five tone presentations. Prior work has shown the posttone interval to provide unique information (Quinn et al. 2008) that is distinct from freezing during the tone interval, specifically that posttone freezing is hippocampus-dependent even for delay conditioning. Baseline freezing prior to the first tone presentation did not differ as a function of sex (F(1, 127) = 0.040, P = 0.842), but did differ as a function of fear conditioning protocol (F(4, 127) = 10.57, P < 0.001), with the No Shock group showing lower freezing relative to all other groups (P < 0.001), as expected (Fig. 5G). Tone freezing was significantly impacted by fear conditioning protocol, as expected (F(4, 127) = 100.291, P < 0.001), with the No Shock group significantly below all other groups (P < 0.001) and Delay above all other groups (P < 0.001) (Fig. 5A). Explicitly Unpaired and Sensitization were above No Shock, but below Trace and Delay (P < 0.001) (Fig. 5A). Trace was intermediate between Delay and the three nonassociative control groups (P < 0.001) (Fig. 5A). Posttone freezing (Fig. 5B) showed a similar overall effect of FC type (F(4, 127) = 78.652, P < 0.001). Differences between protocols in posttone freezing largely followed a pattern similar to that of tone freezing, but with the notable exception that the Sensitization protocol was overall higher than Explicitly Unpaired (P = 0.049). There was an overall effect of sex (F(1, 127) = 5.911, P = 0.017), driven by an increase in females in the Sensitization protocol (F(1, 24) = 7.928, P = 0.010). This analysis indicates that averaged tone freezing follows the expected pattern whereby Delay produces the strongest associative learning followed by Trace. Both associative groups were above the nonassociative controls. However, there is a clear sex difference in the Sensitization protocol whereby females show elevated posttone freezing.

Figure 5.

Figure 5.

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Characterization of sex differences in tone freezing. (A) Averaging freezing across all five tone presentations shows similar performance for males and females. (B) Averaging freezing during the 20 sec immediately following the tone shows elevated freezing in the females for the Sensitization group. (C–G) Average tone and posttone freezing relative to baseline for each protocol. Note small but significant elevation in tone freezing in the No Shock group. (H) Analysis of freezing to the first tone for Trace (left) and Sensitization (right). Freezing to the first tone was reduced in females for Trace. Tone and posttone freezing was elevated in females for Sensitization. (*) P < 0.05.

We additionally analyzed whether tone and/or posttone freezing was elevated above baseline across the FC types. As expected, in the Delay and Trace groups, tone freezing was significantly elevated (P < 0.001), and this was not impacted by sex (Fig. 5C,D). Within the nonassociative groups, the Explicitly Unpaired group showed a similar, sex-independent elevation (P < 0.001) (Fig. 5E,F). The No Shock group showed a subtle but significant increase in freezing (F(2, 60) = 4.052, P = 0.022) (Fig. 5G) that was driven predominantly by females (within females, P = 0.045; within males, P = 0.309). Within the Sensitization group, freezing was also increased (P < 0.001) (Fig. 5F), and this was strongly influenced by sex (sex interaction: F(2, 44) = 5.266, P = 0.009), driven predominantly by increased posttone freezing (as described above). This analysis shows that while the level of tone freezing in the associative groups (Delay and Trace) is above the freezing of the nonassociative groups, there is still substantial nonassociative freezing. In the No Shock group, this nonassociative freezing is higher in females relative to males.

We next analyzed freezing behavior on a tone-by-tone basis to understand the precise kinetics better. Both tone and posttone intervals were analyzed as a repeated measures ANOVA with five within-subject levels (each tone presentation) and two between-subject factors (sex and fear conditioning protocol). Baseline freezing was used as a covariate to account for the difference in baseline freezing for the No Shock group (as well as reduce variance) (see (Jacobs et al. 2010). For both tone and posttone freezing, there was a significant interval × FC type × sex interaction (F(16, 464) = 1.801, P = 0.028; F(16, 464) = 1.888, P = 0.020), indicating that there are sex differences in the detailed kinetics of freezing. Analysis of the sex by FC type interaction within each tone presentation indicated that the sex interaction is driven specifically during the first tone presentation (tone: F(4, 127) = 2.664, P = 0.036; posttone: F(4, 127) = 4.035, P = 0.004). We therefore focused subsequent analysis on the first tone presentation. For the Trace group, tone freezing was significantly reduced in females (F(1, 24) = 4.561, P = 0.044) (Fig. 5H), whereas posttone did not differ (P = 0.289). Females in the Sensitization group showed elevated posttone freezing (F(1, 24) = 11.087, P = 0.003) (Fig. 5H) and a trend for elevated tone freezing (F(1, 24) = 3.411, P = 0.078). These findings show response patterns distinctly different from the first tone presentation in males versus females.

We analyzed the data from the acquisition day in order to determine whether freezing was higher in females during the initial tone presentations (Supplemental Fig. S3). We did not observe elevated freezing to the first tone presentation in females, which argues that the increased nonassociative freezing in females is not evident when initially placed in the fear conditioning chamber in the absence of prior shock presentation. However, freezing to the second tone presentation was elevated in females particularly in the Explicitly Unpaired group (Supplemental Fig. S3D). In this training protocol, the tone is separated from the shock by ∼90 sec. The elevated freezing in the females is thus consistent with a rapid sensitization-like effect that mirrors the findings from the increased nonassociative freezing in the Sensitization group during the tone test: During Explicitly Unpaired training, the first shock sensitizes the females such that their freezing is elevated to the subsequent tone presentation.

To account for the estrous cycle's effect on nonassociative fear learning, we tracked the cycle of female mice run through the Sensitization protocol and then analyzed the freezing behavior (Supplemental Fig. S4A). This was done based on prior evidence of estrous cycle-dependent changes in contextual fear conditioning, which was hypothesized to be due to changes in contextual processing (Cushman et al. 2014). We found increased nonassociative freezing in both estrus and late diestrus (Supplemental Fig. S4B) and confirmed that nonshocked females show elevated freezing to the novel tone presentation (Supplemental Fig. S4C). In addition, a separate cohort of mice was trained and tested with the Sensitization protocol at a different institution to determine whether this nonassociative freezing is a robust, repeatable effect. As shown in Supplemental Figure S5C, this group showed a similar increase in nonassociative freezing to a novel tone in females, which was strongest during the first tone presentation. Overall, these findings indicate that increased nonassociative freezing in females relative to males is robust and particularly evident in initial tone presentations and after a sensitizing experience, such as prior shock presentation.

Discussion

Overall, this parametric analysis found largely similar performance between male and female C57BL/6NTac mice across the majority of behavioral end points; however, it identified an important difference in nonassociative sensitization. This has implications for the design and interpretation of sex-balanced behavioral assays, most importantly for fear conditioning studies, but also for studies that may be differentially impacted by handling stress in males and females. Females showed an enhanced nonassociative fear response to the 75-dB tone that is used as the “neutral” conditional stimulus for fear conditioning experiments. Under some conditions, females also showed a small increase in freezing to the tone even in the absence of prior shock experience; however, prior context–shock pairings substantially increase this sex difference. This draws into question the underlying assumption of the tone as an initially neutral stimulus for females, though further work will be required to fully test this hypothesis. Furthermore, our finding that a relative impairment in object location performance in females could be ameliorated by more extensive handling argues that handling-induced stress may differentially impact cognitive performance, possibly through similar stress sensitization mechanisms. These findings have profound implications for the design and interpretation of sex-balanced behavioral studies and provide novel avenues to investigate the underlying mechanisms of this sex difference with possible translational implications.

We observed no sex differences in spontaneous alternation performance and confirmed that alternation does depend on distal visual cues in both sexes. However, the addition of discrete distal visual cues does not provide an additional benefit beyond the spatial cues that are inherent to the experimental setup. We found no sex differences in novel object recognition performance and no impact on the degree of object similarity. We found females’ object location discrimination less accurate than males, but this apparent deficit was ameliorated by an extensive handling protocol for all mice prior to the task. There is evidence of this phenomenon when using C57BL/6 mice, as females were found to be less anxious with more handling (Sensini et al. 2020). This argues that a more extensive handling regimen is important when conducting sex-balanced studies. The fear conditioning results showed no major sex differences in context freezing; however, there were subtle differences in minute-by-minute kinetics. While associative tone fear was largely similar, we consistently saw increased nonassociative freezing in females, which was found to be estrous cycle-independent.

These findings have immediate practical implications for the design and interpretation of sex-balanced neurobehavioral studies. In several assays, such as spontaneous alternation, novel object recognition, tone, and contextual fear conditioning, we did not observe any major sex differences. This indicates that sex does not need to be considered as a factor in designing basic experiments using these assays. However, similar performance does not necessarily mean that the same underlying strategies or neural pathways are used. Confirming that above-chance spontaneous alternation performance requires visual cues in both sexes suggests that males and females perform this task similarly. Similar object recognition performance and lack of dependence on object discriminability argues that males and females show an equivalent ability to encode and retrieve object features. It is certainly possible that the object pairs that we used were both sufficiently distinct, given that we failed to reproduce the effect of object similarity observed by others (Bettis and Jacobs 2012), so future, more detailed parametric work remains to resolve this discrepancy (Inayat et al. 2021; Spry et al. 2021).

Relatively reduced success in object location assays in females is consistent with prior reports of a relative impairment in spatial performance in females compared with males (Beck and Luine 2002; Frick and Gresack 2003; Jonasson 2005; Sutcliffe et al. 2007; van Goethem et al. 2012). Some of these sex-based differences are conserved in humans (Hyde 2016; Piber et al. 2018). A meta-analysis of sex differences in visual–spatial working memory in humans found a slight male advantage that emerged at 13–17 yr of age; however, location memory tasks highlight a slight female advantage (Voyer et al. 2017). A great deal of work remains to be done to fully determine the extent to which sex differences are present in spatial processing and the specific conditions that may give rise to such differences. The present findings argue for caution in interpretating differences in performance in spatial tasks as a pure measure of differences in spatial learning and memory, as nonassociative factors may differentially impact males and females.

In the present study, the amelioration of the female-specific deficit in object location by more extensive handling suggests that handling protocols are an important procedural factor deserving careful consideration. This also implies that differences in stress responsiveness rather than differences in spatial processing could underlie apparent sex differences reported previously. Our finding of increased nonassociative tone freezing in females, which is present at low levels even in animals that have not been shocked, suggests that females may respond more fearfully to novel, discrete stimuli. The extent to which a stimulus produces a fear response in females more so than in males may impair performance, either by directly competing with proper object investigation or by stress-induced impairments in cognition and/or synaptic plasticity (Shors et al. 2001; Wood et al. 2001; Kajantie and Phillips 2006; Zitman and Richter-Levin 2013). Two previous studies have reported evidence consistent with an increase in nonassociative fear in female rodents, suggesting this is a robust effect worthy of more direct investigation (Ter Horst et al. 2012; Hassien et al. 2020). Hippocampal-specific deletion of the mineralocorticoid receptor produced deficits in fear extinction in female but not male mice, suggesting an important role for the stress response in mediating sex differences in fear expression (Ter Horst et al. 2012). Prior studies have shown that acute stress often improves performance in males, whereas it impairs performance in females, with chronic stress often showing the opposite effect (Beck and Luine 2002; Bowman et al. 2003; Conrad et al. 2003; Luine et al. 2017).

Future work will be required to investigate the underlying mechanisms of the sex differences observed here and the extent to which these differences may be species-specific (mice vs. rats), substrain-specific, and/or age-specific (Bothe et al. 2005; Stover and Brown 2012). A likely candidate mechanism may be differences in locus coeruleus signaling between males and females (Bangasser et al. 2018). Enhanced norepinephrine release in females in response to novel and/or threatening stimuli would be predicted to produce nonassociative sensitization and greater sensitivity to handling stress. Females may have higher baseline norepinephrine signaling and may be more sensitive to long-term increases in firing rate induced by stressful experiences within both locus coeruleus neurons and downstream targets (Pavcovich and Ramirez 1991; Mana and Grace 1997; Giustino et al. 2020). From an evolutionary perspective, this could be the result of differential selection pressures in females whereby failure to return to the nest to care for pups is more strongly selected against (Jacobson and Roche 2018). In addition, the stress response in females may be differentially enhanced due to being tested in socially isolated conditions (Taylor et al. 2000).

Establishing that spontaneous alternation performance does indeed depend on visual cues in mice is an important finding, as this has not yet been demonstrated in mice to our knowledge. Spontaneous alternation has become a widely used spatial working memory assay (Lalonde 2002; Davis et al. 2017; Kraeuter et al. 2019); therefore, validating the assumption that it does indeed depend on distal visual cues is important to demonstrate that it is measuring spatial process (Brown and Bolivar 2018). Earlier work on this assay in rats demonstrated this to some extent (Lennartz 2008); however, it was entirely possible that local, intramaze cues and/or olfactory trails left by the mouse could support alternation without a need to rely on spatial cues. It is important to note that the C57BL/6NTac substrain carries a mutation for retinal degeneration that can impair vision (Mehalow 2003; Pritchett-Corning et al. 2012). However, in our present study, both males and females showed above-chance spontaneous alternation performance under normal lighting conditions, but in complete darkness, their performance was at chance. This pattern would not be observed if they had visual impairments that prevented them from seeing the extramaze cues. The observation that females did show an overall greater level of locomotion is consistent with other findings and may be driven by the increased exploratory activity associated with the proestrus phase of the estrous cycle (Marcondes et al. 2001; Bishnoi et al. 2021).

The results of associative fear conditioning groups (Delay and Trace) confirm that associative learning is the primary driver of freezing in both males and females because their average tone freezing was higher than the nonassociative groups. This is in contrast to prior criticisms that nonassociative processes may dominate tone freezing in mice (Kamprath 2004), though this could be due to the use of a lower tone intensity in the present study (Wotjak 2019). It should be noted, however, that the Explicitly Unpaired group did show increased tone freezing relative to baseline in both males and females. This argues that despite separating the CS and US by 90 sec, some level of trace or backward conditioning does occur. Also, this clearly indicates that the CS does not acquire a CS–“no US” association, which is often used as a criticism of using the Explicitly Unpaired protocol as a nonassociative control (Rescorla 1967).

Precise response kinetics, broken down by tone presentation, showed some interesting differences. During the first tone presentation, females in the Trace conditioning group showed reduced freezing at a level equivalent to the Sensitization group, though this was not reflected in the overall averaged freezing across the five tone presentations. This reduction in the hippocampus-dependent associative group combined with an increase in the nonassociative sensitization group suggests a complex interplay between associative and nonassociative factors in females, which warrants further study. The differences in nonassociative tone responses also suggest researchers should take caution when interpreting changes in freezing in females when only an associative conditioning assay is used. A manipulation could differentially impact nonassociative learning in males versus females, which could profoundly complicate proper interpretation of the results (Kamprath 2004; Wotjak 2019).

We found the increase in nonassociative tone freezing in females consistent across two separate research laboratories and that it is independent of the estrous cycle. This effect was most pronounced during the first tone presentation. The lack of an effect of the estrous cycle is in contrast to prior results showing estrous cycle-dependent changes in context fear (Cushman et al. 2014) and supports the conclusions in this prior study that such differences are driven by changes in hippocampal contextual processing rather than nonassociative changes in the expression of freezing. We also observed that nonshocked females show a small but consistent increase in freezing to the tone. This finding argues that the 75-dB tone used for these experiments is not, in fact, an entirely neutral conditional stimulus, as is generally assumed. As seen in the Sensitization groups, prior shock presentation greatly increases the fear response to the novel tone in females. However, it is notable that a fear response is present at a low level in the No Shock groups.

This nonassociative difference in females also holds a great deal of translational significance. Women suffer from anxiety disorders at much greater rates than men (Tolin and Foa 2006; Bangasser et al. 2018). To our knowledge, there are no animal models of anxiety currently in use that replicate this, likely because most early work in anxiety modeling focused almost exclusively on males (Kokras and Dalla 2014). In addition, traditional anxiety assays like the elevated plus maze often show reduced anxiety-like behaviors in females, at least in rats (Johnston and File 1991; Knight et al. 2021). Using nonassociative tone freezing as a model for developing therapies and treatments may therefore prove to be an important and novel avenue of research (e.g., see Siegmund and Wotjak 2007b). Further research into the underlying mechanisms of this sex difference can also provide insight into the neural circuits that underlie stress, anxiety, and defensive behavior (Kajantie and Phillips 2006).

We observed no overall differences in context freezing when averaged across the 8-min context test. This is consistent with several studies that failed to see sex differences in context fear in mice (Dachtler et al. 2011) and rats (Kosten et al. 2006). These data are inconsistent with several other studies that found elevated context fear in male mice (Mizuno et al. 2012) and rats (Maren et al. 1994). Analysis of minute- by-minute kinetics demonstrated that freezing in the first minute is influenced by conditioning protocol in females but not males, and the Trace group showed less learned fear than the Delay group. This is consistent with a prior finding of a sex interaction with Trace versus Delay conditioning (Moore et al. 2010), suggesting that it may be a more general finding. One possible explanation is that the mechanism by which tone and context compete for association with the shock differs between males and females, though future work would be required to test this hypothesis directly.

In conclusion, these findings show that sex differences in standard hippocampal assays need to be considered when designing sex-balanced experiments. Future work to determine parameters that minimize these differences is needed to simplify experimental designs and reduce the number of groups and animals required. One clear example from this study is that more extensive handling may help eliminate sex differences in object location performance. Furthermore, the finding of increased nonassociative freezing in females warrants further focus and could potentially serve as a novel model of the increased incidence of anxiety disorders in women.

Materials and Methods

Animals

The studies were conducted using C57BL/6 Taconic mice ordered at 8 wk of age. For the studies at the National Institute of Environmental Health Sciences (NIEHS), a total of 224 mice was used over six cohorts. All procedures were approved by the NIEHS Animal Care and Use Committee. The animals went through object recognition, spontaneous alternation, and fear conditioning procedures for each cohort as described below, with one task performed per week. The primary experiment consisted of 96 mice split into three cohorts that went through both object recognition and object location tasks as described in Supplemental Table S1. (see Supplemental Data S1 for all of the raw data). This was designed as a test battery to assess multiple domains of hippocampus-dependent learning and memory in the same animals while also exploring multiple task parameters. This was carefully designed and counterbalanced so that any differences in behavioral experience were minimized and did not systematically influence the results of subsequent behavioral assays. Parameters that were counterbalanced during novel object recognition were as follows: distinct versus similar object pairs, and object location: large (easy) versus small (hard) displacement. Additionally, both 24- and 2-h retention intervals between familiarization and testing were assessed; the 2-h retention interval did not produce reliable object preferences, and these data are not presented. Parameters counterbalanced during spontaneous alternation were as follows: distinct visual cues on the walls of the testing room versus no distinct visual cues. Parameters counterbalanced for fear conditioning were as follows: Delay, Trace, Explicitly Unpaired, and Sensitization protocols.

In follow-up experiments, 96 mice went through an extensive handling procedure prior to spontaneous alternation, which was followed by object location the week after. During spontaneous alternation in the follow-up experiments, the red light condition as described below was added. No Shock controls (16 male and 16 female) were added in an additional cohort (see Supplemental Table S1). For the studies conducted at University of California at Los Angeles (UCLA), a separate group of 32 mice performed object recognition, spontaneous alternation, and fear conditioning using the Sensitization protocol (see Supplemental Fig. S5 for this confirmatory data). For the estrous cycle study, a separate group of 31 mice was used to investigate the effects of estrous stage on baseline freezing during fear conditioning (see Supplemental Fig. S4). All procedures were approved by the UCLA Animal Care and Use Committee.

Spontaneous alternation

The Y-maze (Med Associates), used to assess spontaneous alternation, includes three identical arms (15 in W × 15 in L × 7.8 in H) in the shape of a Y, labeled A, B, and C. It was placed in the center of a 72-in × 72-in black, sound-attenuating curtained enclosure. Before starting the experiment, the equipment was cleaned thoroughly with Accel. Mice were run under three conditions: stimulus-rich (cued), stimulus-poor (uncued), and total darkness (red light) (Fig. 1B). The cued condition was conducted under dim white light (5 lux) and included large white spatial cues equidistant apart around the Y-maze and attached to the black curtains. The cues were a triangle, circle, vertical line, and square. The uncued condition was conducted under dim white light but did not have any explicit spatial cues attached to the curtains. The red light condition was used to mimic total darkness for the mice so that no distal visual cues were available.

During each trial, the mouse was placed at the end of the designated start arm and allowed to explore the maze freely for 8 min. Video tracking was conducted via EthoVision XT and was used to calculate percent alternation and distance traveled. An entry was defined as the mouse completely crossing into one arm of the maze. An alternation was defined as entering all three arms within a series of the three arm choices (Fig. 1A). The percent alternation score was calculated by dividing the number of alternations by possible alternations [percent alternation = number of alternations/(number of entries − 2) × 100)]. Between each trial, the equipment was cleaned thoroughly with Windex.

Extensive/minimal handling

The minimal handling protocol took place over 3 d. The experimenter placed a hand on the bedding in each rodent cage for 5 min on the first day. On the second day, the experimenter placed a hand in the rodent cage for 3 min and held each mouse for 30 sec (the mice were held by their tails and allowed to walk freely on the hand/arm of the experimenter). The mice were tail-marked for identification on the second day. Day 3 handling included 2 min of the experimenter's hand in the rodent cage, and each mouse was held for 30 sec. The experimenter changed gloves between sexes on each day of handling.

The extensive handling protocol took place over 10 d. The first 3 d of handling were identical to the minimal handling protocol. On the fourth day, the mice were brought into the experiment room and each mouse was transferred to a clean, empty cage for 30 sec. The experimenter placed a hand into the cage after 15 sec, and the mouse was allowed to explore freely. On the fifth day, the mice were brought into the experiment room. Mice were allowed to walk across the experimenter's hand for 30 sec (as the experimenter lightly grasped their tail) before being placed in an empty cage for 30 sec. Day 6 was the same protocol as day five, but the mice were held for 15 sec and placed in the box for 15 sec. Days 7–10, the mice were also brought into the experiment room. They were lifted from their home cage to the empty cage, allowed to traverse the empty cage freely for 5 sec, and then returned to their home cage. This was repeated for a total of 30 sec. Whenever mice were lifted by their tail, they were also allowed to have at least two limbs touching the other hand of the experimenter for support.

Novel/spatial object recognition

Object recognition tasks took place during three phases: habituation, familiarization, and test phase. Each phase took place in the same dimly lit (5 lux) arena (NOR box: 12 in × 12 in; SOR box: 18 in × 18 in), with a camera positioned directly in the middle at the top of the box, surrounded by lights such that it did not cast a shadow. During the habituation phase, the animal was allowed to explore the open-field arena for 10 min on two consecutive days. On the third day, the familiarization phase took place. For both the novel object recognition and the object location tasks, two matching objects were set up in the arena and placed directly in opposite corners of the arena. Two object pairs were used during the novel object recognition experiments: similar (easy) object pair and distinct (hard) object pair. The similar object pair was a small clear vial with a black lid filled with water and a 25-mL Erlenmeyer flask with a black marble covering the opening on top of the flask. The distinct object pair was the small clear vial filled with water and the Erlenmeyer flask with purple construction paper on the inside to add a color difference. The object pair used for the object location tasks was two 250-mL Erlenmeyer flasks filled with sand and covered with a metal lid. The object locations were counterbalanced across arenas to account for side preference. The animal was allowed to explore the arena and objects for 10 min.

After a 24-h retention interval, the test phase took place. For the novel object recognition task, while both objects remained in the same locations, one object remained the same and the other was replaced with a novel object (Fig. 2A). Within the box, the positions of novel and familiar objects were counterbalanced across animals. For the large displacement object location task condition, one of the two objects was moved to the back corner of the arena (Fig. 2A). For the small displacement object location task condition, one of the two objects was moved halfway between the corners of the arena against the wall. The animal was allowed to explore the arena and the altered objects for 10 min. The cumulative time each mouse spent investigating objects was tracked using EthoVision XT. Investigation was defined as orienting toward and investigating the object within a 2-cm circumference around the object; climbing was not scored as investigation. The efficacy of the automated scoring was validated against manual scoring. Our automated method showed a high correlation with manual scoring (Pearson correlation coefficient: 0.801). The arena and objects were cleaned with 75% ethanol between animals and allowed to dry.

Fear conditioning

The fear conditioning task took place during three phases: fear acquisition day, context day, and test day (Fig. 3A). The task was run in the fear conditioning chambers (Med Associates). Chamber dimensions were 29 in × 25 in × 23.5 in, and arena dimensions were 10 in × 12 in × 9.5 in. During the fear acquisition day, the animal was placed in context A (standard grid floor, white walls, and fans on) and, after a 3-min baseline, introduced to five tone (75 dB)/shock (0.5 mA) pairings with 3 min between each of the five pairings. The animal was exposed to one of five protocols: Delay, Trace, Explicitly Unpaired, Sensitization, and No Shock. During the Delay protocol, a 2-sec shock was administered directly after the 20-sec tone. During the Trace protocol, a 2-sec shock was administered 20 sec after the 20-sec tone. During the Explicitly Unpaired protocol, a 2-sec shock was administered 90 sec after the 20-sec tone. During the Sensitization protocol, a 2-sec shock was administered with no tone presentation. During the No Shock protocol, the shock was omitted, but mice were exposed to the training context and tone for the same length of time (Fig. 5B). Freezing behavior was recorded through the Video Freeze program. The fear conditioning chambers were cleaned with 75% isopropyl alcohol, and five sprays of Simple Green cleaning solution were put into the pan for scent. On the context test day, the animal was introduced to the context A environment for 8 min. Video Freeze recorded freezing behavior, and the chambers were cleaned the same as the fear acquisition day.

On the test day, the animal was exposed to context B (white plastic floor, black plastic A frame, and fans off) and exposed to a five-tone (75-dB) protocol (Fig. 3C). The fear conditioning chambers were cleaned with 75% ethanol, and five sprays of Windex cleaning solution were put into the pan for scent. Freezing behavior was recorded.

Based on prior evidence that the estrous cycle can impact fear conditioning, particularly contextual fear conditioning and posttone freezing (Cushman and Fanselow 2010), we next assessed whether the elevated nonassociative freezing was estrous cycle-dependent. We trained mice with the Sensitization protocol (five 0.5-mA shocks and no tone) during either estrus or diestrus phases. They were tested (five 75-dB tone presentations) the next time they cycled to the phase in which they were trained. We also followed a protocol designed to reduce baseline freezing (Jacobs et al. 2010). After being trained in the Sensitization protocol, the mice were exposed to the test context for 15 min for up to 3 d. The mice were then pre-exposed to the tone test context for 15 min per day for up to 3 d or until they returned to the estrous phase they were trained in. The freezing levels remained high, so statistical comparisons were made by covarying by baseline (see the Results), and data were plotted as (percent tone freezing − baseline percent freezing).

Estrous cycle monitoring

Estrous cycle stages were determined by bioelectrical impedance through vaginal probing (Muromachi Impedance Monitor) based on a prior protocol (Cushman et al. 2014). A cohort of 31 mice was handled with an intermediate handling protocol (the first 4 d of the extensive handling protocol). Mice were probed at approximately 10 a.m. each morning, and their cycles were recorded daily. To facilitate cycling, a handful of male bedding was added to each cage every day. The estrus stage was defined as the day after the proestrus peak of vaginal impedance. This was accompanied by large numbers of cornified epithelial cells. The diestrus stage was defined as the second low day of vaginal impedance after estrus and characterized by very few cells, mucous streaks, and occasional nucleated parabasal cells. Only mice that went through two consistent normal estrous cycles were included in the subsequent behavioral procedures. Any mice that failed to show normal estrous cycles were used as No Shock controls. Vaginal probing continued until completion of the behavioral protocol or until the last day of the experiment for the noncycling mice.

Statistical analysis

All statistical analysis was performed using SPSS (IBM, Inc., build 1.0.0.1058) and graphed using Graphpad Prism (Dotmatics, Inc., version 9.1.2). The statistical approach was to start with analysis of variance (ANOVA) to limit the number of subsequent post-hoc comparisons to those justified by the ANOVA. Comparisons justified by significant main effects or interaction terms used Fisher's least significant difference (LSD) post-hoc comparisons when more than two groups were compared (e.g., different fear conditioning protocols or cue conditions). This ANOVA-guided approach restricts the number of comparisons so that type I error is constrained. The specific ANOVA approach is described in each section of the Results, and the P-values for the LSD post-hocs are described.

Supplementary Material

Supplemental Material
supp_29_8_203__DC1.html (1.2KB, html)

Acknowledgments

This research was supported in part by the Intramural Research Program of the National Institutes of Health, the National Institute of Environmental Health Sciences (NIEHS). We thank the students in the 2016 Summer University of California at Los Angeles Psychology 111 class for assistance in data collection for the fear conditioning data set: Chandni Patel, Tiffany Luu, Anita Sarkar, Nancy Cao, Alexandro Guerrero, Arthi Naini, Jessica Lin, Xioye Zuo, and Karampreet Singh. In addition, we thank Johnny Scher and Aki Min for their assistance in data collection at the NIEHS.

Footnotes

[Supplemental material is available for this article.]

References

  1. Agabio R, Campesi I, Pisanu C, Gessa GL, Franconi F. 2016. Sex differences in substance use disorders: focus on side effects. Addict Biol 21: 1030–1042. 10.1111/adb.12395 [DOI] [PubMed] [Google Scholar]
  2. Agrati D, Fernández-Guasti A, Zuluaga MJ, Uriarte N, Pereira M, Ferreira A. 2005. Compulsive-like behaviour according to the sex and the reproductive stage of female rats. Behav Brain Res 161: 313–319. 10.1016/j.bbr.2005.02.017 [DOI] [PubMed] [Google Scholar]
  3. Altemus M, Sarvaiya N, Neill Epperson C. 2014. Sex differences in anxiety and depression clinical perspectives. Front Neuroendocrinol 35: 320–330. 10.1016/j.yfrne.2014.05.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Assini FL, Duzzioni M, Takahashi RN. 2009. Object location memory in mice: pharmacological validation and further evidence of hippocampal CA1 participation. Behav Brain Res 204: 206–211. 10.1016/j.bbr.2009.06.005 [DOI] [PubMed] [Google Scholar]
  5. Bangasser DA, Eck SR, Telenson AM, Salvatore M. 2018. Sex differences in stress regulation of arousal and cognition. Physiol Behav 187: 42–50. 10.1016/j.physbeh.2017.09.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Barker JM, Galea LAM. 2010. Males show stronger contextual fear conditioning than females after context pre-exposure. Physiol Behav 99: 82–90. 10.1016/j.physbeh.2009.10.014 [DOI] [PubMed] [Google Scholar]
  7. Barker GRI, Bird F, Alexander V, Warburton EC. 2007. Recognition memory for objects, place, and temporal order: a disconnection analysis of the role of the medial prefrontal cortex and perirhinal cortex. J Neurosci 27: 2948–2957. 10.1523/JNEUROSCI.5289-06.2007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Beck KD, Luine VN. 2002. Sex differences in behavioral and neurochemical profiles after chronic stress: role of housing conditions. Physiol Behav 75: 661–673. 10.1016/S0031-9384(02)00670-4 [DOI] [PubMed] [Google Scholar]
  9. Bettis T, Jacobs LF. 2012. Sex differences in object recognition are modulated by object similarity. Behav Brain Res 233: 288–292. 10.1016/j.bbr.2012.04.028 [DOI] [PubMed] [Google Scholar]
  10. Bishnoi IR, Ossenkopp KP, Kavaliers M. 2021. Sex and age differences in locomotor and anxiety-like behaviors in rats: from adolescence to adulthood. Dev Psychobiol 63: 496–511. 10.1002/dev.22037 [DOI] [PubMed] [Google Scholar]
  11. Bothe GWM, Bolivar VJ, Vedder MJ, Geistfeld JG. 2005. Behavioral differences among fourteen inbred mouse strains commonly used as disease models. Comp Med 55: 326–334. [PubMed] [Google Scholar]
  12. Bowman RE, Beck KD, Luine VN. 2003. Chronic stress effects on memory: sex differences in performance and monoaminergic activity. Horm Behav 43: 48–59. 10.1016/S0018-506X(02)00022-3 [DOI] [PubMed] [Google Scholar]
  13. Brown RE, Bolivar S. 2018. The importance of behavioural bioassays in neuroscience. J Neurosci Methods 300: 68–76. 10.1016/j.jneumeth.2017.05.022 [DOI] [PubMed] [Google Scholar]
  14. Carreira MB, Cossio R, Britton GB. 2017. Individual and sex differences in high and low responder phenotypes. Behav Process 136: 20–27. 10.1016/j.beproc.2017.01.006 [DOI] [PubMed] [Google Scholar]
  15. Chowdhury N, Quinn JJ, Fanselow MS. 2005. Dorsal hippocampus involvement in trace fear conditioning with long, but not short, trace intervals in mice. Behav Neurosci 119: 1396–1402. 10.1037/0735-7044.119.5.1396 [DOI] [PubMed] [Google Scholar]
  16. Clayton J, Collins FS. 2014. Policy: NIH to balance sex in cell and animal studies. Nature 509: 282–283. 10.1038/509282a [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Cohen SJ, Stackman RW. 2015. Assessing rodent hippocampal involvement in the novel object recognition task. A review. Behav Brain Res 285: 105–117. 10.1016/j.bbr.2014.08.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Conrad CD, Grote KA, Hobbs RJ, Ferayorni A. 2003. Sex differences in spatial and non-spatial Y-maze performance after chronic stress. Neurobiol Learn Mem 79: 32–40. 10.1016/S1074-7427(02)00018-7 [DOI] [PubMed] [Google Scholar]
  19. Curzon P, Rustay NR, Browman KE. 2009. Cued and contextual fear conditioning for rodents. In Methods behavior analysis in neuroscience (ed. Buccafusco JJ), Chapter 2. CRC Press/Taylor & Francis, Boca Raton, FL. 10.1201/NOE1420052343.ch2 [DOI] [PubMed] [Google Scholar]
  20. Cushman JD, Fanselow MS. 2010. Fear conditioning. In Encyclopedia of behavioral neuroscience (ed. Koob GF, et al. ), pp. 524–531. Elsevier, Amsterdam, the Netherlands. [Google Scholar]
  21. Cushman JD, Moore MD, Olsen RW, Fanselow MS. 2014. The role of the δ GABA(A) receptor in ovarian cycle-linked changes in hippocampus-dependent learning and memory. Neurochem Res 39: 1140–1146. 10.1007/s11064-014-1282-6 [DOI] [PubMed] [Google Scholar]
  22. Dachtler J, Fox KD, Good MA. 2011. Gender specific requirement of GluR1 receptors in contextual conditioning but not spatial learning. Neurobiol Learn Mem 96: 461–467. 10.1016/j.nlm.2011.07.001 [DOI] [PubMed] [Google Scholar]
  23. Davis KE, Burnett K, Gigg J. 2017. Water and T-maze protocols are equally efficient methods to assess spatial memory in 3xTg Alzheimer's disease mice. Behav Brain Res 331: 54–66. 10.1016/j.bbr.2017.05.005 [DOI] [PubMed] [Google Scholar]
  24. Day HLL, Suwansawang S, Halliday DM, Stevenson CW. 2020. Sex differences in auditory fear discrimination are associated with altered medial prefrontal cortex function. Sci Rep 10: 6300. 10.1038/s41598-020-63405-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Ennaceur A, Neave N, Aggleton JP. 1997. Spontaneous object recognition and object location memory in rats: the effects of lesions in the cingulate cortices, the medial prefrontal cortex, the cingulum bundle and the fornix. Exp Brain Res 113: 509–519. 10.1007/PL00005603 [DOI] [PubMed] [Google Scholar]
  26. Frick KM, Gresack JE. 2003. Sex differences in the behavioral response to spatial and object novelty in adult C57BL/6 mice. Behav Neurosci 117: 8. 10.1037/0735-7044.117.6.1283 [DOI] [PubMed] [Google Scholar]
  27. Gilmartin MR, Balderston NL, Helmstetter FJ. 2014. Prefrontal cortical regulation of fear learning. Trends Neurosci 37: 455–464. 10.1016/j.tins.2014.05.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Giustino TF, Ramanathan KR, Totty MS, Miles OW, Maren S. 2020. Locus coeruleus norepinephrine drives stress-induced increases in basolateral amygdala firing and impairs extinction learning. J Neurosci 40: 907–916. 10.1523/JNEUROSCI.1092-19.2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Hammond R. 2004. On the delay-dependent involvement of the hippocampus in object recognition memory. Neurobiol Learn Mem 82: 26–34. 10.1016/j.nlm.2004.03.005 [DOI] [PubMed] [Google Scholar]
  30. Hassien AM, Shue F, Bernier BE, Drew MR. 2020. A mouse model of stress-enhanced fear learning demonstrates extinction-sensitive and extinction-resistant effects of footshock stress. Behav Brain Res 379: 112391. 10.1016/j.bbr.2019.112391 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Hillerer KM, Slattery DA, Pletzer B. 2019. Neurobiological mechanisms underlying sex-related differences in stress-related disorders: effects of neuroactive steroids on the hippocampus. Front Neuroendocrinol 55: 100796. 10.1016/j.yfrne.2019.100796 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Howard MW, Eichenbaum H. 2015. Time and space in the hippocampus. Brain Res 1621: 345–354. 10.1016/j.brainres.2014.10.069 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Hughes RN. 2004. The value of spontaneous alternation behavior (SAB) as a test of retention in pharmacological investigations of memory. Neurosci Biobehav Rev 28: 8. 10.1016/j.neubiorev.2004.06.006 [DOI] [PubMed] [Google Scholar]
  34. Hyde JS. 2016. Sex and cognition: gender and cognitive functions. Curr Opin Neurobiol 38: 53–56. 10.1016/j.conb.2016.02.007 [DOI] [PubMed] [Google Scholar]
  35. Inayat M, Cruz-Sanchez A, Thorpe HHA, Frie JA, Richards BA, Khokhar JY, Arruda-Carvalho M. 2021. Promoting and optimizing the use of 3D-printed objects in spontaneous recognition memory tasks in rodents: a method for improving rigor and reproducibility. eNeuro 8: ENEURO.0319-0321. 10.1523/ENEURO.0319-21.2021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Jacobs NS, Cushman JD, Fanselow MS. 2010. The accurate measurement of fear memory in Pavlovian conditioning: resolving the baseline issue. J Neurosci Methods 190: 235–239. 10.1016/j.jneumeth.2010.04.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Jacobson NC, Roche MJ. 2018. Current evolutionary adaptiveness of anxiety: extreme phenotypes of anxiety predict increased fertility across multiple generations. J Psychiatr Res 106: 82–90. 10.1016/j.jpsychires.2018.10.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Johnston AL, File SE. 1991. Sex differences in animal tests of anxiety. Physiol Behav 49: 245–250. 10.1016/0031-9384(91)90039-Q [DOI] [PubMed] [Google Scholar]
  39. Jonasson Z. 2005. Meta-analysis of sex differences in rodent models of learning and memory: a review of behavioral and biological data. Neurosci Biobehav Rev 28: 811–825. 10.1016/j.neubiorev.2004.10.006 [DOI] [PubMed] [Google Scholar]
  40. Kajantie E, Phillips D. 2006. The effects of sex and hormonal status on the physiological response to acute psychosocial stress. Psychoneuroendocrinology 31: 151–178. 10.1016/j.psyneuen.2005.07.002 [DOI] [PubMed] [Google Scholar]
  41. Kamprath K. 2004. Nonassociative learning processes determine expression and extinction of conditioned fear in mice. Learn Mem 11: 770–786. 10.1101/lm.86104 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Knight DC. 2004. Neural substrates mediating human delay and trace fear conditioning. J Neurosci 24: 218–228. 10.1523/JNEUROSCI.0433-03.2004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Knight P, Chellian R, Wilson R, Behnood-Rod A, Panunzio S, Bruijnzeel AW. 2021. Sex differences in the elevated plus-maze test and large open field test in adult Wistar rats. Pharmacol Biochem Behav 204: 173168. 10.1016/j.pbb.2021.173168 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Kokras N, Dalla C. 2014. Sex differences in animal models of psychiatric disorders. Br J Pharmacol 171: 4595–4619. 10.1111/bph.12710 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Koss WA, Frick KM. 2017. Sex differences in hippocampal function. J Neurosci Res 95: 539–562. 10.1002/jnr.23864 [DOI] [PubMed] [Google Scholar]
  46. Kosten TA, Lee HJ, Kim JJ. 2006. Early life stress impairs fear conditioning in adult male and female rats. Brain Res 1087: 142–150. 10.1016/j.brainres.2006.03.009 [DOI] [PubMed] [Google Scholar]
  47. Kraeuter A-K, Guest PC, Sarnyai Z. 2019. The Y-maze for assessment of spatial working and reference memory in mice. Methods Mol Biol 1916: 105–111. 10.1007/978-1-4939-8994-2_10 [DOI] [PubMed] [Google Scholar]
  48. Lalonde R. 2002. The neurobiological basis of spontaneous alternation. Neurosci Biobehav Rev 26: 91–104. 10.1016/S0149-7634(01)00041-0 [DOI] [PubMed] [Google Scholar]
  49. Lennartz RC. 2008. The role of extramaze cues in spontaneous alternation in a plus-maze. Learn Behav 36: 138–144. 10.3758/LB.36.2.138 [DOI] [PubMed] [Google Scholar]
  50. Li SH, Graham BM. 2017. Why are women so vulnerable to anxiety, trauma-related and stress-related disorders? The potential role of sex hormones. Lancet Psychiatry 4: 73–82. 10.1016/S2215-0366(16)30358-3 [DOI] [PubMed] [Google Scholar]
  51. Luine V, Gomez J, Beck K, Bowman R. 2017. Sex differences in chronic stress effects on cognition in rodents. Pharmacol Biochem Behav 152: 6. 10.1016/j.pbb.2016.08.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Mackintosh NJ. 1974. The psychology of animal learning. Academic Press, Oxford, England. [Google Scholar]
  53. Mana MJ, Grace AA. 1997. Chronic cold stress alters the basal and evoked electrophysiological activity of rat locus coeruleus neurons. Neuroscience 81: 1055–1064. 10.1016/S0306-4522(97)00225-X [DOI] [PubMed] [Google Scholar]
  54. Marcondes FK, Miguel KJ, Melo LL, Spadari-Bratfisch RC. 2001. Estrous cycle influences the response of female rats in the elevated plus-maze test. Physiol Behav 74: 435–440. 10.1016/S0031-9384(01)00593-5 [DOI] [PubMed] [Google Scholar]
  55. Maren S, De Oca B, Fanselow MS. 1994. Sex differences in hippocampal long-term potentiation (LTP) and Pavlovian fear conditioning in rats: positive correlation between LTP and contextual learning. Brain Res 661: 25–34. 10.1016/0006-8993(94)91176-2 [DOI] [PubMed] [Google Scholar]
  56. Mccarthy M, Kusljic S, Gogos A. 2018. The role of sex and sex steroids in the novel object recognition task. In Handbook of object novelty recognition (Ennaceur A, de Souza Silva MA), pp. 499–529. Elsevier, Amsterdam, the Netherlands. [Google Scholar]
  57. Mehalow AK. 2003. CRB1 is essential for external limiting membrane integrity and photoreceptor morphogenesis in the mammalian retina. Hum Mol Genet 12: 2179–2189. 10.1093/hmg/ddg232 [DOI] [PubMed] [Google Scholar]
  58. Meziane H, Ouagazzal A-M, Aubert L, Wietrzych M, Krezel W. 2007. Estrous cycle effects on behavior of C57BL/6J and BALB/cByJ female mice: implications for phenotyping strategies. Genes Brain Behav 6: 192–200. 10.1111/j.1601-183X.2006.00249.x [DOI] [PubMed] [Google Scholar]
  59. Mizuno K, Dempster E, Mill J, Giese KP. 2012. Long-lasting regulation of hippocampal Bdnf gene transcription after contextual fear conditioning. Genes Brain Behav 11: 651–659. 10.1111/j.1601-183X.2012.00805.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Monfort P, Gomez-Gimenez B, Llansola M, Felipo V. 2015. Gender differences in spatial learning, synaptic activity, and long-term potentiation in the hippocampus in rats: molecular mechanisms. ACS Chem Neurosci 6: 1420–1427. 10.1021/acschemneuro.5b00096 [DOI] [PubMed] [Google Scholar]
  61. Moore MD, Cushman J, Chandra D, Homanics GE, Olsen RW, Fanselow MS. 2010. Trace and contextual fear conditioning is enhanced in mice lacking the α4 subunit of the GABAA receptor. Neurobiol Learn Mem 93: 383–387. 10.1016/j.nlm.2009.12.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Oh J-P, Han J-H. 2020. A critical role of hippocampus for formation of remote cued fear memory. Mol Brain 13: 112. 10.1186/s13041-020-00652-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. O'Leary TP, Brown RE. 2012. The effects of apparatus design and test procedure on learning and memory performance of C57BL/6J mice on the Barnes maze. J Neurosci Methods 203: 315–324. 10.1016/j.jneumeth.2011.09.027 [DOI] [PubMed] [Google Scholar]
  64. Pavcovich LA, Ramirez OA. 1991. Time course effects of uncontrollable stress in locus coeruleus neuronal activity. Brain Res Bull 26: 17–21. 10.1016/0361-9230(91)90186-N [DOI] [PubMed] [Google Scholar]
  65. Piber D, Nowacki J, Mueller SC, Wingenfeld K, Otte C. 2018. Sex effects on spatial learning but not on spatial memory retrieval in healthy young adults. Behav Brain Res 336: 44–50. 10.1016/j.bbr.2017.08.034 [DOI] [PubMed] [Google Scholar]
  66. Pigott TA. 2003. Anxiety disorders in women. Psychiatr Clin North Am 26: 621–672. 10.1016/S0193-953X(03)00040-6 [DOI] [PubMed] [Google Scholar]
  67. Prendergast BJ, Onishi KG, Zucker I. 2014. Female mice liberated for inclusion in neuroscience and biomedical research. Neurosci Biobehav Rev 40: 1–5. 10.1016/j.neubiorev.2014.01.001 [DOI] [PubMed] [Google Scholar]
  68. Pritchett-Corning KR, Clifford CB, Elder BJ, Vezina M. 2012. Retinal lesions and other potential confounders of ocular research in inbred mice. Invest Opthalmol Vis Sci 53: 3764. 10.1167/iovs.12-10056 [DOI] [PubMed] [Google Scholar]
  69. Quinn JJ, Ma QD, Tinsley MR, Koch C, Fanselow MS. 2008. Inverse temporal contributions of the dorsal hippocampus and medial prefrontal cortex to the expression of long-term fear memories. Learn Mem 15: 368–372. 10.1101/lm.813608 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Radulovic J, Kammermeier J, Spiess J. 1998. Generalization of fear responses in C57BL/6N mice subjected to one-trial foreground contextual fear conditioning. Behav Brain Res 95: 179–189. 10.1016/S0166-4328(98)00039-4 [DOI] [PubMed] [Google Scholar]
  71. Rescorla RA. 1967. Pavlovian conditioning and its proper control procedures. Psychol Rev 74: 71–80. 10.1037/h0024109 [DOI] [PubMed] [Google Scholar]
  72. Sensini F, Inta D, Palme R, Brandwein C, Pfeiffer N, Riva MA, Gass P, Mallien AS. 2020. The impact of handling technique and handling frequency on laboratory mouse welfare is sex-specific. Sci Rep 10: 17281. 10.1038/s41598-020-74279-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Shansky RM, Murphy AZ. 2021. Considering sex as a biological variable will require a global shift in science culture. Nat Neurosci 24: 457–464. 10.1038/s41593-021-00806-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Shors TJ, Miesegaes G, Beylin A, Zhao M, Rydel T, Gould E. 2001. Neurogenesis in the adult is involved in the formation of trace memories. Nature 410: 372–376. 10.1038/35066584 [DOI] [PubMed] [Google Scholar]
  75. Siegmund A, Wotjak CT. 2007a. Hyperarousal does not depend on trauma-related contextual memory in an animal model of posttraumatic stress disorder. Physiol Behav 90: 103–107. 10.1016/j.physbeh.2006.08.032 [DOI] [PubMed] [Google Scholar]
  76. Siegmund A, Wotjak CT. 2007b. A mouse model of posttraumatic stress disorder that distinguishes between conditioned and sensitised fear. J Psychiatr Res 41: 848–860. 10.1016/j.jpsychires.2006.07.017 [DOI] [PubMed] [Google Scholar]
  77. Spry KP, Fry SA, Defillip JMS, Drye SG, Stevanovic KD, Hunnicutt J, Bernstein BJ, Thompson EE, Cushman JD. 2021. 3D-printed capacitive sensor objects for object recognition assays. eNeuro 8: ENEURO.0310-0320. 10.1523/ENEURO.0310-20.2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Stover KR, Brown RE. 2012. Age-related changes in visual acuity, learning and memory in the APPswe/PS1dE9 mouse model of Alzheimer's disease. Behav Brain Res 231: 75–85. 10.1016/j.bbr.2012.02.044 [DOI] [PubMed] [Google Scholar]
  79. Sutcliffe JS, Marshall KM, Neill JC. 2007. Influence of gender on working and spatial memory in the novel object recognition task in the rat. Behav Brain Res 177: 117–125. 10.1016/j.bbr.2006.10.029 [DOI] [PubMed] [Google Scholar]
  80. Taylor SE, Klein LC, Lewis BP, Gruenewald TL, Gurung RAR, Updegraff JA. 2000. Biobehavioral responses to stress in females: tend-and-befriend, not fight-or-flight. Psychol Rev 107: 411–429. 10.1037/0033-295X.107.3.411 [DOI] [PubMed] [Google Scholar]
  81. Ter Horst JP, Carobrez AP, Van Der Mark MH, De Kloet ER, Oitzl MS. 2012. Sex differences in fear memory and extinction of mice with forebrain-specific disruption of the mineralocorticoid receptor. Eur J Neurosci 36: 3096–3102. 10.1111/j.1460-9568.2012.08237.x [DOI] [PubMed] [Google Scholar]
  82. Tolin DF, Foa EB. 2006. Sex differences in trauma and posttraumatic stress disorder: a quantitative review of 25 years of research. Psychol Bull 132: 959–992. 10.1037/0033-2909.132.6.959 [DOI] [PubMed] [Google Scholar]
  83. Trask S, Reis DS, Ferrara NC, Helmstetter FJ. 2020. Decreased cued fear discrimination learning in female rats as a function of estrous phase. Learn Mem 27: 254–257. 10.1101/lm.051185.119 [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Ulloa RE, Nicolini H, Fernández-Guasti A. 2004. Sex differences on spontaneous alternation in prepubertal rats: implications for an animal model of obsessive–compulsive disorder. Prog Neuropsychopharmacol Biol Psychiatry 28: 687–692. 10.1016/j.pnpbp.2004.05.005 [DOI] [PubMed] [Google Scholar]
  85. van Goethem NP, Rutten K, van der Staay FJ, Jans LA, Akkerman S, Steinbusch HW, Blokland A, van't Klooster J, Prickaerts J. 2012. Object recognition testing: rodent species, strains, housing conditions, and estrous cycle. Behav Brain Res 232: 323–334. 10.1016/j.bbr.2012.03.023 [DOI] [PubMed] [Google Scholar]
  86. Voyer D, Voyer SD, Saint-Aubin J. 2017. Sex differences in visual-spatial working memory: a meta-analysis. Psychon Bull Rev 24: 307–334. 10.3758/s13423-016-1085-7 [DOI] [PubMed] [Google Scholar]
  87. Wanisch K, Tang J, Mederer A, Wotjak CT. 2005. Trace fear conditioning depends on NMDA receptor activation and protein synthesis within the dorsal hippocampus of mice. Behav Brain Res 157: 63–69. 10.1016/j.bbr.2004.06.009 [DOI] [PubMed] [Google Scholar]
  88. Warburton EC, Brown MW. 2015. Neural circuitry for rat recognition memory. Behav Brain Res 285: 131–139. 10.1016/j.bbr.2014.09.050 [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Winters BD, Saksida LM, Bussey TJ. 2008. Object recognition memory: neurobiological mechanisms of encoding, consolidation and retrieval. Neurosci Biobehav Rev 32: 1055–1070. 10.1016/j.neubiorev.2008.04.004 [DOI] [PubMed] [Google Scholar]
  90. Wood GE, Beylin AV, Shors TJ. 2001. The contribution of adrenal and reproductive hormones to the opposing effects of stress on trace conditioning in males versus females. Behav Neurosci 115: 175–187. 10.1037/0735-7044.115.1.175 [DOI] [PubMed] [Google Scholar]
  91. Wotjak CT. 2019. Sound check, stage design and screen plot: how to increase the comparability of fear conditioning and fear extinction experiments. Psychopharmacology 236: 33–48. 10.1007/s00213-018-5111-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Yagi S, Galea LAM. 2019. Sex differences in hippocampal cognition and neurogenesis. Neuropsychopharmacology 44: 200–213. 10.1038/s41386-018-0208-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  93. Zitman FMP, Richter-Levin G. 2013. Age and sex-dependent differences in activity, plasticity and response to stress in the dentate gyrus. Neuroscience 249: 21–30. 10.1016/j.neuroscience.2013.05.030 [DOI] [PubMed] [Google Scholar]

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