In rodents, the first weeks of postnatal life feature remarkable changes in fear memory acquisition, retention, extinction, and discrimination. Early development is also marked by profound changes in brain circuits underlying fear memory processing, with heightened sensitivity to environmental influences and stress, providing a powerful model to study the intersection between brain structure, function, and the impacts of stress. Nevertheless, difficulties related to breeding and housing young rodents, preweaning manipulations, and potential increased variability within that population pose considerable challenges to developmental fear research. Here we discuss several factors that may promote variability in studies examining fear conditioning in young rodents and provide recommendations to increase replicability. We focus primarily on experimental conditions, design, and analysis of rodent fear data, with an emphasis on mouse studies. The convergence of anatomical, synaptic, physiological, and behavioral changes during early life may increase variability, but careful practice and transparency in reporting may improve rigor and consensus in the field. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC.

Fear memory processing is crucial for threat response and survival. In rodents, fear memories are often studied using Pavlovian fear conditioning, whereby a conditioned stimulus (CS, e.g., a neutral tone) is paired with an unconditioned stimulus (US, e.g., foot shock) to generate a CS-US association. The CS-US association is later assessed by presentation of the CS alone, which triggers the innate fear response of freezing, defined as the absence of all movement except for breathing (Blanchard & Blanchard, 1969; Fanselow, 1980). Given the importance of fear learning to survival, it is not surprising that rodents can form fear associations from a very early age. Despite its early onset, multiple aspects of fear processing continue to change across early postnatal development in mice and rats, including the ability to form, refine, inhibit, and retain fear memories (Akers et al., 2012, 2014; Alberini & Travaglia, 2017; Baker & Richardson, 2015; Bath et al., 2016; Campbell & Ampuero, 1985; Campbell & Campbell, 1962; Campbell & Spear, 1972; Ganella & Kim, 2014; Gogolla et al., 2009; Guskjolen et al., 2018; Josselyn & Frankland, 2012; Kim et al., 2006, 2009; Kim & Richardson, 2007a,b, 2008; Kucharski & Spear, 1984; Moriceau & Sullivan, 2006; Park et al., 2017b; Park, Ganella, Perry et al., 2020; Pattwell et al., 2012, 2016; Revillo et al., 2015; Rudy & Morledge, 1994; Samifanni et al., 2021; Sullivan et al., 2000; Tallot et al., 2016). Importantly, these changes occur against a backdrop of other developmental milestones, including (1) leaving the nest, increasing both exploration and exposure to threats, (2) anatomical and synaptic changes in the brain, and (3) heightened sensitivity to environmental influences and stress (Bell, 2018; Brenhouse & Andersen, 2011; Brust et al., 2015; Knudsen, 2004; Livia Terranova & Laviola, 1995; Sachser et al., 2020). The confluence of these factors imposes serious challenges and potentially confounds the study of fear processing during early life. Here we provide a brief overview of developmental differences in fear processing in rodents, followed by a discussion of some potential underlying factors, providing recommendations aimed at minimizing experimental variability, with a focus on mouse studies (also see the exemplary overview by Cowan & Richardson, 2018).

NOTE : All protocols involving live animals must be reviewed and approved by an Institutional Animal Care and Use Committee (IACUC) and must conform to government regulations for the care and use of laboratory animals.

Infancy and Juvenility

Decades of prior research suggest that fear processing is developmentally regulated (Akers et al., 2012, 2014; Alberini & Travaglia, 2017; Campbell & Campbell, 1962; Campbell & Spear, 1972; Ganella & Kim, 2014; Guskjolen et al., 2018; Herry et al., 2010; Josselyn & Frankland, 2012; Kim et al., 2006, 2009; Kim & Richardson, 2008; Li et al., 2012; Li et al., 2018; Moriceau & Sullivan, 2006; Park et al., 2017b; Park, Ganella, Perry et al., 2020; Pattwell et al., 2012; Revillo et al., 2015; Rudy & Morledge, 1994; Samifanni et al., 2021; Sullivan et al., 2000; Tallot et al., 2016). Freezing behavior is first expressed during infancy in rats (by postnatal day [P] 10; Takahashi, 1994), a time in which they begin to venture outside of the nest and show increased exploration (Bolles & Woods, 1964). Seminal work in infant rats has shown that rats up to P10 will approach an odor that was previously paired with an aversive foot shock, but from P10 onwards they begin to avoid the odor and demonstrate aversion learning (Moriceau & Sullivan, 2004, 2006; Sullivan et al., 2000; Sullivan & Wilson, 1994; Tallot et al., 2016), exemplifying the nonlinear changes that shape the emergence of fear learning in rodents.

During juvenility (often noted as ∼P18-29; Bell, 2018; Cowan & Richardson, 2018), mice and rats venture out of the nest more frequently, thereby increasing encounters with threatening stimuli (Bell, 2018; Brust et al., 2015). As a result, this is a crucial time for fear-related systems to come online and ensure survival. Accordingly, juvenility marks the onset of the acquisition and retention of life-long or persistent fear memories (Akers et al., 2012, 2014; Alberini & Travaglia, 2017; Campbell & Ampuero, 1985; Campbell & Campbell, 1962; Guskjolen et al., 2018; Josselyn & Frankland, 2012; Nieves et al., 2020; Revillo et al., 2015; Samifanni et al., 2021). Juvenility also features a transition in the way rodents extinguish fear memories (Callaghan & Richardson, 2013; Gogolla et al., 2009; Kim & Richardson, 2007a,b; Park et al., 2017b; Park, Ganella, Perry et al., 2020; Yap & Richardson, 2007). Specifically, when infant rodents undergo fear extinction there is a permanent suppression of the fear response (immature-type extinction; Gogolla et al., 2009; Kim & Richardson, 2007a,b; Li et al., 2018; Park et al., 2017b; Park, Ganella, Perry et al., 2020; Yap & Richardson, 2007); however, starting from juvenility, extinction ceases to be so permanent and animals start to display a return of the fear memory over time, even spontaneously (adult-type extinction; Bouton & Bolles, 1979a,b; Corcoran & Maren, 2004; Herry et al., 2010; Myers & Davis, 2007; Pape & Pare, 2010; Quirk & Mueller, 2008; Rescorla & Heth, 1975). This transition between immature and adult extinction profiles occurs sometime between P16 and P23 in mice (Gogolla et al., 2009) and between P17 and P18 in rats (Kim & Richardson, 2007a,b; Park et al., 2017b; Park, Ganella, Perry et al., 2020; Revillo et al., 2016; Revillo, Paglini, & Arias, 2014). Juvenility is also marked by an increase in the precision of contextual fear memories, which reach adult levels of contextual discrimination at P24 in mice (Ramsaran et al., 2018, 2023).

Puberty, Adolescence, and Sex Differences

Even though juvenility encompasses key transitions in fear processing systems that coincide with ethological changes in threat exposure, adolescence (P30-55; Cowan & Richardson, 2018) has been the prime focus of rodent developmental fear studies. The transition between juvenility and adolescence is accompanied by several physiological and behavioral changes, including endocrine changes marking the onset of puberty and sexual maturity as well as increased risk-taking behaviors (Schneider, 2013; Spear, 2000; Vetter-O'Hagen & Spear, 2012; Walker et al., 2017). Although the first surge of gonadal hormones occurs during the perinatal period (1 week before and after birth), a second surge occurs during puberty (McCarthy et al., 2017), which often overlaps with adolescence (Vetter-O'Hagen & Spear, 2012). Importantly, as circulating hormones in early development alter and shape neural networks, the onset of puberty may bring further sex-specific changes in anatomy, circuitry, and behavior. This is particularly relevant to fear processing because pubertal hormones can influence the formation, extinction, and generalization of fear memories (Colón et al., 2023; Crestani et al., 2022; McDermott et al., 2012; Perry et al., 2020). Notably, the onset of puberty is known to vary by sex, which may increase variability in developmental fear research. In general, female rodents have an earlier onset of puberty compared to males, similar to humans (Schneider, 2013). Female mice show external signs of puberty around P26-29 and female rats by P30-39 (Piekarski et al., 2017; Schneider, 2013; Vetter-O'Hagen & Spear, 2012). In contrast, male mice first show pubertal markers around P30 and male rats around P40-45 (Koss et al., 2015; Schneider, 2013; Vetter-O'Hagen & Spear, 2012). Given that females have an earlier puberty onset, it is likely that gonadal hormones may contribute to transient and/or long-lasting sex differences in systems encompassing fear processing around adolescence. Indeed, several lines of evidence suggest that specific neural correlates of fear processing mature earlier in female rodents (for review, see Premachandran et al., 2020). As one example, female rats display an earlier transition to the adult-type extinction system compared to males (Park et al., 2017b), but this timeline has not been assessed in female mice.

Sex differences are also found in fear extinction in early life. While many studies report a deficit in extinction learning and/or retrieval in adolescent males (Baker & Richardson, 2015; Baker-Andresen et al., 2013; Callaghan & Richardson, 2012b; Ganella et al., 2017; McCallum et al., 2010; Pattwell et al., 2012, 2016; but also see Experimental Design section), adolescent female rats show improved extinction compared to their adult counterparts (McCormick et al., 2013), suggesting a potential sex difference in extinction learning during adolescence. Importantly, Perry et al. (2020) reported that adolescent female rats in proestrus or metestrus/diestrus display impaired extinction compared to adolescent males (and females in estrus), pointing to a role for the estrous cycle in regulating extinction during adolescence. Together, these studies emphasize a need to expand research on sex differences in adolescent fear extinction and highlight the importance of monitoring estrous cycle in developmental fear experiments.

Given the considerable influence of gonadal hormones in fear behavior during adolescence and adulthood (Chang et al., 2009; Colón et al., 2023; Crestani et al., 2022; Gupta et al., 2001; Jasnow et al., 2006; Lebron-Milad & Milad, 2012; McDermott et al., 2012; Milad et al., 2009; Perry et al., 2020), it is expected that the onset of puberty between late juvenility and early adolescence will contribute to variability in fear processing. Importantly, this timing can also be influenced by strain in both mice and rats (Bell, 2018; Keeley et al., 2015; Nelson et al., 1990). Strain and substrain differences in fear behavior have been reported in both adolescent and adult rodents (Balogh & Wehner, 2003; Camp et al., 2012; Cazares et al., 2019; Eltokhi et al., 2020; Hefner et al., 2008; MacPherson et al., 2013; Owen et al., 1997). For example, C57 substrains C57BL/6J (Jackson Laboratories), C57BL/6NCrl (Charles River Laboratories), and C57BL/6NHsd (Harlan Sprague-Dawley) show notable differences in fear behavior in adulthood, especially in contextual freezing levels (Bryant et al., 2008; Radulovic et al., 1998; Siegmund et al., 2005; Siegmund & Wotjak, 2007; Stiedl et al., 1999). Due to the interplay between strain differences and pubertal onset, strain differences in fear processing may be potentiated during adolescence.

Maturation of Neural Correlates of Fear

The aforementioned developmental changes in fear behavior coincide with the maturation of the brain circuits that support them. The first four postnatal weeks are marked by dramatic anatomical and synaptic changes in rodent brain regions that mediate fear processing, such as the amygdala, hippocampus (HPC), and medial prefrontal cortex (mPFC) (Arruda-Carvalho et al., 2017; Baker et al., 2017; Bessières et al., 2019; Blair et al., 2013; Bosch & Ehrlich, 2015; Caballero et al., 2016; Caballero & Tseng, 2016; Donato et al., 2021; Gerhard et al., 2021; Hartley & Lee, 2015; Jia et al., 2018; Kalemaki et al., 2022; King et al., 2014; Klune et al., 2021; Kolb et al., 2012; Koss et al., 2014; Kroon et al., 2019; Premachandran et al., 2020; Ramsaran et al., 2023; Rubinow & Juraska, 2009; Swann et al., 1989; Travaglia, Bisaz, Cruz et al., 2016; Travaglia, Bisaz, Sweet et al., 2016; Zimmermann et al., 2019). Interestingly, these brain regions support different aspects of fear processing and also mature at different rates. The amygdala is crucial for learning the association between CS and US (Cousens & Otto, 1998; Ehrlich et al., 2009; Maren, 2003; Maren et al., 1996; Muller et al., 1997; Orsini & Maren, 2012; Phelps & LeDoux, 2005) and is one of the first to mature, showing activity during fear behaviors from infancy in rats (Moriceau & Sullivan, 2004, 2006; Sullivan et al., 2000; Tallot et al., 2016). The HPC is essential for contextual fear associations (Debiec et al., 2002; Fanselow, 2000; Matus-Amat et al., 2004; Phelps & LeDoux, 2005; Phillips & LeDoux, 1992; Rudy et al., 2002; Sanders et al., 2003; Xu et al., 2016) and is recruited during juvenility to support contextual fear learning (Campbell & Campbell, 1962; Raineki et al., 2010; Rudy & Morledge, 1994; Schiffino et al., 2011). The mPFC plays an important role in fear expression and extinction (Arruda-Carvalho & Clem, 2015; Burgos-Robles et al., 2009; Corcoran & Quirk, 2007; Herry et al., 2008, 2010; Ledoux, 2000; Milad & Quirk, 2002; Miller & Cohen, 2001; Mukherjee & Caroni, 2018; Rozeske et al., 2015; Sierra-Mercado et al., 2006; Vidal-Gonzalez et al., 2006) and is relatively late to mature (Casey et al., 2013; Klune et al., 2021; van Eden & Uylings, 1985; Zimmermann et al., 2023), reaching adult levels of activity around adolescence (Arruda-Carvalho et al., 2017; Kalemaki et al., 2022), which coincides with the onset of its involvement in auditory fear retrieval (Li et al., 2012).

Remarkably, these brain regions are also highly sensitive to stress (Akirav & Maroun, 2007; Arnsten, 2009; Cohen et al., 2013; Ferrara et al., 2021; Honeycutt et al., 2020; Johnson et al., 2018; Liu et al., 2017; McEwen et al., 2016; McEwen & Morrison, 2013; Roozendaal et al., 2009). Stress experienced in early life exerts greater impact than that experienced in adulthood (Cotella et al., 2019; Jankord et al., 2011; Romeo, 2010; Romeo & McEwen, 2006; Yohn & Blendy, 2017), including impacts on emotional learning trajectories. For instance, injection of corticosterone leads to early recruitment of the amygdala in the acquisition of odor aversion learning (Moriceau & Sullivan, 2004, 2006). Additionally, early life stress accelerates HPC maturation and the emergence of fear behaviors dependent on the HPC (e.g., earlier onset of contextual fear suppression; Bath et al., 2016), mPFC, and amygdala (e.g., earlier onset of adult-type extinction; Callaghan et al., 2014; Callaghan & Richardson, 2011, 2012b, 2013, 2014; Callaghan & Tottenham, 2016; Cowan et al., 2013).

Overall, these studies show that early development is marked by a convergence of anatomical, synaptic, physiological, and behavioral changes, as well as heightened stress sensitivity within fear circuits and associated behavior. While these changes may add variability and impose unique challenges to the study of emotional learning during early life, they also provide a unique and valuable prism for the study of brain-behavior dynamics and the consequences of external influences. Below we highlight a few of the specific factors contributing to variability in rodent developmental fear studies, focusing on breeding and housing conditions, experimental design, and analysis of fear behavioral data in mice. While others have made important contributions to this topic (Bisby et al., 2021; Cowan & Richardson, 2018) and our list is by no means exhaustive, we provide some recommendations aimed at fostering consensus, reducing variability, and increasing replicability when running Pavlovian fear conditioning experiments with young mice.

The conditions under which rodents enter and are kept in an animal facility—including how they are bred, housed (bedding, nesting, number of cagemates, among others), and manipulated—have a profound impact on many experimental outcomes, and fear behavior is no exception (Fig. 1). Furthermore, given that early life spans some of the most significant changes in housing conditions (e.g., birth, separation from the dam at weaning), it is conceivable that the impact of housing conditions will be greater in studies sampling early postnatal ages compared to those conducted in adulthood. Below we discuss a few potential sources of variability related to the way animals arrive at the facility, how they are housed, and how/when they are separated from the dam (weaning).

In-house Breeding Versus Animal Shipping

As many developmental fear experiments span ages close to weaning, they predominantly use in-house breeding, i.e., the animals are bred in the same animal facility in which experiments are conducted (Hampshire & Davis, 2005). In-house breeding minimizes transportation stress and facilitates access to early developmental stages. Despite these advantages, the time needed for each breeding cycle and other intrinsic challenges of colony management may reduce the rate at which experimental animals become available, delaying research progress. When working with juvenile or adolescent rodents, an alternative is to purchase animals directly from vendors and allow them to acclimate to the facility before testing (e.g., Ferrara et al., 2020; Hefner & Holmes, 2007; Selleck et al., 2018). It is important to note that, since this strategy requires that pups be weaned at the vendor facility prior to shipping, this approach may add variability in terms of handling and weaning. Additionally, when the animal arrival date coincides with weaning age, the stress of weaning may be conflated with that of shipping. Given the stress of shipping (Laroche et al., 2009), and that early life stress can increase fear and anxiety responses in adulthood (Malter Cohen et al., 2013; Moriceau et al., 2009; Oomen et al., 2010), the timing of shipping (e.g., juvenility versus adulthood) may be a consideration. Allowing animals to acclimate for a few days prior to behavior assessment is highly recommended to mitigate the acute effects of shipping stress. Critically, control animals must undergo the same shipping procedures as the experimental group to minimize the effects of breeding method on between-group comparisons. Nevertheless, these differences in early life experiences should be taken into account when comparing studies that use different breeding methods.

Bedding

Regardless of source, all rodents in the animal facility are placed in a cage with bedding. Although often overlooked as a variable, bedding type varies significantly between animal facilities and can have an effect on fear behavior. For example, in female (but not male) adult mice, bedding type influences freezing during contextual fear training and extinction, with small wood bedding resulting in lower freezing compared to large paper bedding (Matsuda, 2023). This may be especially relevant during development, as the smaller paws of young mice could lead them to experience bedding coarseness differently than adults. Moreover, bedding type affects the mechanical withdrawal reflex in mice, with coarse bedding reducing sensitivity (Moehring et al., 2016), which could affect pain sensitivity during foot shock. Bedding type also affects the development of mechanical hyperalgesia and chemical hypersensitivity in rats, with coarse bedding reducing pain sensitivity compared to fine sawdust (Robinson et al., 2004). Therefore, differences in bedding type could be a major contributor to low replicability of fear studies across animal facilities, even with the same species/strain and experimental design. Furthermore, some labs use aspen (Park, Ganella, Perry et al., 2020), wood chip (Ganella et al., 2016, 2017; Park et al., 2017b; Perry et al., 2020) or corncob (Bisby, Richardson et al., 2020) bedding as part of the context in the fear chamber itself (Kim et al., 2011; Kim & Richardson, 2007a,b; Yap & Richardson, 2007). Although not standard practice, including information on bedding type and size might help inform inconsistencies and increase replicability in the field.

Weaning

Weaning, a time when the litter is separated from the mother and placed in a new cage, is a significant period in an animal's life and plays an important role in physiology, behavior, and neurological development (Berry et al., 2012; Kanari et al., 2005; Ladd et al., 1996; Terranova & Laviola, 2001). The standard age of weaning in most rodent facilities is P21 (Bechard & Mason, 2010), and is therefore an important variable to consider when conducting developmental studies that sample adjacent ages. It is important to remark that weaning is an artificial procedure, since maternal care in the wild continues well beyond P21, with nursing in both rats and mice extending to P27-28 (König & Markl, 1987; Mendl & Paul, 1990; Oštádalová & Babický, 2012) and young mice dispersing from the mother around P40 (Berdoy & Drickamer, 2007). Even in a laboratory setting, if juvenile mice are provided with an alternative cage but still have access to the dam, pups continue to visit and receive maternal care up until P35 (Bechard & Mason, 2010). This is in stark contrast to the abrupt and permanent nature of weaning in an animal facility.

Several studies show that the timing of weaning, either before (early weaning) or after (late weaning) P21, affects a number of behaviors and physiological processes. Early weaning (typically between P14 and P16) is considered a form of early-life stress and robustly affects aggression, feeding behavior, anxiety, and social interaction (dos Santos Oliveira et al., 2011; Ishikawa et al., 2015; Ito et al., 2006; Kikusui et al., 2004, 2006, 2009; Kodama et al., 2008; Nakamura et al., 2003; Ono et al., 2008; Shimozuru et al., 2007; Takita & Kikusui, 2016). Early weaning can also lead to increased stereotypy, believed to represent an effort to return to the mother (Latham & Mason, 2008; Würbel & Stauffacher, 1997). Notably, some studies suggest that the effects of early weaning may be sex-specific, with early weaning males (but not females) showing increased glucocorticoid receptor expression and higher basal corticosterone levels even in adulthood (Kikusui et al., 2006). Further, female mice that are weaned early proceed to wean their own pups earlier (Curley et al., 2009), emphasizing the long-term effects of this manipulation. Interestingly, some of the endocrine and behavioral effects of early weaning have also been reported in animals with low body weight, with higher weaning weight being positively associated with adult reproductive success, especially in males (Krackow, 1993; Krackow & Hoeck, 1989). These data emphasize weaning weight as a potentially influential metric that should be recorded and correlated with future behavioral performance.

When it comes to fear processing, early weaning increases freezing during auditory fear retrieval (Kreiker et al., 2021), extinction training, and extinction retrieval (Mogi et al., 2016). Interestingly, early weaning also led to lower paired-pulse facilitation in the mPFC-amygdala pathway (Takita & Kikusui, 2016), which is strongly implicated in fear memory processing (Arruda-Carvalho & Clem, 2014; Bukalo et al., 2015; Cho et al., 2013; Do-Monte et al., 2015; Duvarci & Pare, 2014; Gunduz-Cinar et al., 2023; Herry et al., 2008; Hübner et al., 2014; Marek et al., 2013; Quirk & Mueller, 2008; Sotres-Bayon & Quirk, 2010; Stafford et al., 2013). In contrast, late weaning (usually P25 or later) leads to higher levels of social behavior (Curley et al., 2009), increased exploration, and reduced anxiety-like behavior (Richter et al., 2016). Nevertheless, the effects of late weaning on fear processing remain under-investigated. Despite an absence of these data, the broad effects of either early or late weaning described above make it clear that weaning is an important variable in the experimental design of developmental fear studies, particularly when sampling ages close to P21. If using a range of weaning ages (e.g., P21 ± 1), keeping the interval between weaning and behavior constant will likely help decrease variability in behavioral outcomes. As a general rule, limiting the age range within a sampled experimental group to ±1 or 2 days would further reduce variability associated with individual and sex differences in development, including those related to the onset of puberty.

One way to avoid the potential impacts of weaning is to postpone it until after the experimental timeline is complete. Juvenile (P25) rats that were not weaned show higher overall contextual freezing than those weaned at P21 (Park et al., 2017a). Interestingly, age-dependent differences in fear extinction are observed even in the absence of weaning (Gogolla et al., 2009; Kim & Richardson, 2007b; Yap & Richardson, 2007), but whether or not weaning alters their timing is unclear. While these studies point to eliminating weaning as an appealing strategy to minimize stress and variability, its application is restricted in age range, as most animal facilities will not allow late weaning past adolescence.

Considering the findings above, there is significant evidence that weaning affects fear conditioning and retrieval, and may differentially impact males and females. Differences in weaning procedures (and its proximity to the ages tested) across labs likely adds variability to developmental fear studies. Research directly comparing the effects of the timing of weaning on fear behavior conducted within the same facility and with identical experimental conditions would increase insight into the degree of its influence on fear memory outputs. At a minimum, recognition of weaning as a major variable and transparency in reporting of weaning procedures would improve replicability.

Animals Per Cage

The stress of weaning is predominantly attributed to separation from the dam, but it is also accompanied by another major change: reduction of the total number of animals that occupy the cage. Infant and juvenile rodents are initially kept with the dam in large groups of up to 14 pups, at an average of 6-8 in a lab setting (Jalali et al., 2016). Some studies cull litters to a certain size shortly after parturition—e.g., 8-10 pups (Brasser & Spear, 2004; Kreiker et al., 2021), 9 pups (Carew & Rudy, 1991), or 10 pups (Revillo, Castello, et al., 2014)—in order to better control for litter effects (for a recommendation to standardize litter sizes as early as possible, see Cowan & Richardson, 2018). Following weaning, the standard procedure in animal facilities is to house same-sex littermates together in groups of 3-5 (with considerable variation, see below).

Several studies point to the number of animals per cage as having a significant impact on behavior, including fear. Solo-housing for extended periods of time can lead to enhanced contextual fear responses and impaired fear extinction (Pibiri et al., 2008). On the other hand, overcrowding is considered a form of chronic social stress that increases anxiety-like behaviors in mice (Lin et al., 2015; Reiss et al., 2007). Interestingly, stress (including overcrowding) biases the sex-ratio of the progeny of stressed dams toward more females (Trivers & Willard, 1973), a parameter that should be monitored when conducting in-house breeding.

In Canada, animal care guidelines (CCAC, 2022) state a standard group size for mice as 4-5 per cage, with cages harboring at least 100 cm² (15.5 in²) floor space per mouse, with studies emphasizing the importance of sufficient space requirements for mouse welfare (Bailoo et al., 2018; Makowska et al., 2019). In mouse developmental fear studies, cage allotment tends to cluster around 2-5 mice (Gerhard & Meyer, 2021; Lanjewar et al., 2023; Samifanni et al., 2021), though some limit the maximum to 4 animals per cage (Hefner & Holmes, 2007). Rat developmental studies feature greater variability in the number of animals per cage, with some reaching significantly higher numbers than most mouse studies. Ranges include a maximum of 3 (Ferrara et al., 2020) or 4 (Chocyk et al., 2014) animals per cage to groups of 5-6 (Perry et al., 2020) or 6 (Ganella et al., 2017). Some studies use up to 4-8 (McCallum et al., 2010; Yap & Richardson, 2007; Zimmermann et al., 2023) and combine litters (Kim et al., 2011). While keeping a larger number of animals post-weaning (or preserving the whole litter together; Kim et al., 2011; McCallum et al., 2010; Yap & Richardson, 2007; Zimmermann et al., 2023) would maintain consistency with pre-weaning conditions to minimize the stress of weaning, this may not be sustainable at older ages given the size of the animals and local animal care guidelines.

Given the developmental constraints delineated above, it seems likely that differences in experimental design, a known source of variability, may disproportionally affect developmental fear studies. A major concern when conducting fear studies across development is the possibility that animals of different ages may experience pain and respond to foot shocks differently, thereby influencing their fear responses. To account for that possibility, some labs vary their fear conditioning protocols according to animal age to obtain equivalent freezing levels at fear retrieval across groups, most often by increasing CS-US pairings for younger mice (Gogolla et al., 2009; Samifanni et al., 2021) and rats (Brown et al., 2021; Ganella et al., 2016; Kim et al., 2009; Kim & Richardson, 2007a, 2008). While this addresses one important variable, titrating the experimental design to normalize freezing output may overlook impacts of fear conditioning outside of freezing. Conversely, the use of a single training protocol across ages (Akers et al., 2012; Koppensteiner et al., 2019; Li et al., 2018; Park et al., 2017a; Park, Ganella, & Kim, 2020; Pattwell et al., 2012; Raineki et al., 2010; Samifanni et al., 2021) might discount age-specific impacts of stress and pain that could affect other aspects of emotional learning beyond the standard metrics analyzed in fear experiments. As is the norm for developmental studies (and beyond), any experimental design choice comes with intrinsic limitations that should be taken into account when interpreting results. Measuring a broader range of behavioral output metrics, including grooming, darting, jumping, and rearing, may help with validation of the choice of experimental design, especially given reports of sex differences in some of these metrics (Borkar et al., 2020; Colom-Lapetina et al., 2019; Gruene et al., 2015; Mitchell et al., 2022; Seemiller et al., 2021; Shansky, 2018).

Due to the increased contextual generalization seen in infant and juvenile mice (Ramsaran et al., 2023), great consideration should be given to the elements used to distinguish between contexts at early ages, especially when analyzing auditory fear. Auditory fear training often occurs in a context that is ideally distinguishable from the fear retrieval context (where the animal is exposed to the CS only) through the use of olfactory (e.g., distinct neutral odors), visual (e.g., different color or patterned panel inserts), or tactile (e.g., metal versus plastic floors) cues. Achieving successful discrimination between contexts is important to avoid compounding freezing to the CS with any residual generalized freezing to the training context. To determine whether the degree of dissimilarity between contexts is sufficient to overcome age-dependent differences in contextual generalization in auditory fear experiments, it is important to track baseline freezing data in the fear retrieval (alternative) context prior to tone onset across the ages tested and adjust experimental parameters to achieve equivalent discrimination, if necessary. Early optimization of contextual parameters and transparent reporting of baseline freezing in auditory fear conditioning experiments using young rodents would improve rigor and data reliability.

Another way in which experimental design affects developmental fear pertains to the study of adolescent extinction. While a considerable literature reports an extinction learning and/or retention deficit in adolescence, this is not always replicated (for a more extensive discussion, see Bisby et al., 2021; for an integration of their parameters and others highlighted here, see Supporting Information Table S1). One factor that may contribute to inconsistency in the reports of adolescent extinction learning is experimental design. Extinction protocols vary by the number of CS presentations per trial and the number of extinction trials per animal (e.g., single extinction trial versus multiple trials across consecutive days; see Supporting Information Table S1). Importantly, Kim et al. (2011) and McCallum et al. (2010) found that doubling the extinction protocol rescued the adolescent extinction deficit. This is consistent with another study conducted by Gerhard and Meyer (2021) that saw no extinction deficit in adolescent mice, but used a greater number of tone presentations compared to studies that do see a deficit (i.e., 40 vs. 20). It is important to mention that differences in the design of extinction protocols also impact adult rodents (Cain et al., 2003; Gerhard & Meyer, 2021; Ledgerwood et al., 2005; MacPherson et al., 2013), which demonstrate greater extinction retention when trials are spaced across several days rather than in a single day (in mice: Cain et al., 2003; Gerhard & Meyer, 2021). Thus, it is possible that conducting extinction trials across multiple days with massed trials may facilitate extinction learning in both younger and older rodents. Taken together, the choice of extinction protocol appears to be a major determinant of whether a deficit in extinction will be detected in adolescent rodents. Importantly, while this conclusion does not preclude the existence of a higher threshold for successful fear extinction in adolescent rodents compared to adults, it might inform experimental design choices when conducting extinction experiments with adolescent animals.

Overall, several factors need to be considered when designing and interpreting developmental fear experiments. Although experimental designs vary in many other ways not covered here (e.g., intertrial intervals, pre-exposure to context, handling), it is clear that choices made when designing fear experiments may have a greater impact when studying development and should be thoroughly validated internally and carefully guided by existing literature.

Historically, rodent freezing was quantified predominantly through manual scoring (Bourtchuladze et al., 1994; Fanselow & Bolles, 1979; Paylor et al., 1994; Phillips & LeDoux, 1992). This was followed by a substantial shift toward computer-assisted systems for automated scoring (Anagnostaras et al., 2000), whose sensitivity has substantially improved in recent years. Even so, the size of infant mice poses considerable challenges for quantifying fear behavior in early life. Some features of young mice (e.g., ears and paws) are less easily distinguishable on camera due to their small size, and the animals may at times be partially or completely occluded from view. This is a serious limitation of certain fear chamber setups, whereby the protruding lip of the grid floor nearest to the camera can partially or even completely block the view of juvenile or infant mice. These developmental constraints may explain why manual scoring remains the method of choice for many developmental fear researchers.

The majority of studies analyzing rodent fear behavior in development have a blinded experimenter manually score freezing across the whole behavioral session (Carew & Rudy, 1991; Colon et al., 2018; Glavonic et al., 2023; Pattwell et al., 2012; Revillo et al., 2016; Revillo, Paglini, & Arias, et al., 2014). As this can be quite labor-intensive, a subset of studies uses a time-sampling approach, in which a binary freezing/no freezing category is assigned to a particular time interval of 3 s (Baker & Richardson, 2015; Bisby et al., 2018; Harmon-Jones & Richardson, 2021; Kim et al., 2009, 2011; Kim & Richardson, 2007a,b, 2008; McCallum et al., 2010; Yap & Richardson, 2007; Zimmermann et al., 2023), 5 s (Cain et al., 2003; Hefner & Holmes, 2007), or 10 s (Kutlu et al., 2018; Morgan & Pfaff, 2001). Although manual scoring is time-consuming and may carry the possibility of observer bias, it allows for quantification of complex behaviors that might be difficult to score automatically (such as grooming and rearing, as in Colon et al., 2018, but see below). Manual scoring also minimizes data loss in cases of partial visual occlusion of the animal, since a human observer may be still able to assess freezing in those instances. However, manual analysis does not allow for easy or consistent adjustment in the parameters for measuring freezing (e.g., minimum freezing threshold, or how long the animal must freeze in order for it to count as one freezing instance), making direct comparisons with automated metrics challenging.

Video-assisted scoring of freezing behavior is a very useful tool, as it dramatically reduces the time required to score behavioral data and removes observer bias. The most common automated freezing scoring software programs used in developmental fear studies are VideoFreeze (MedAssociates) (Ferrara et al., 2020; Ganella et al., 2017, 2018; Gerhard & Meyer, 2021; Lanjewar et al., 2023; McDermott et al., 2012; Park et al., 2020; Perry et al., 2020), FreezeFrame (Actimetrics) (Akers et al., 2012; Ishii et al., 2019; Koppensteiner et al., 2019; Riddle et al., 2013), and Ethovision (Noldus, more commonly used for non-freezing behaviors) (Bailoo et al., 2020; Bath et al., 2016). See Table 1 for a comparison of freezing quantification methods within the parameters discussed here. These software tools provide control over parameters used to optimize freezing quantification, such as the motion threshold, sample rate, and minimum freeze duration. Critically, due to the factors mentioned above, the freezing parameters used to measure adult behavior may not optimally capture freezing in younger animals. Thus, when using this method in developmental studies, it is important to first optimize freezing parameters across the ages tested and to maintain consistency within and between labs.

Typically, studies vary motion thresholds to capture freezing across species and ages. As a reference, developmental fear studies in mice often use the lowest VideoFreeze motion threshold of 18 arbitrary units (au) (Gerhard & Meyer, 2021; Lanjewar et al., 2023; Samifanni et al., 2021), while studies in rats use from 50 au (Ganella et al., 2017 at P34; Handford et al., 2014 in adults; Perry et al., 2020 at P35) to 70 au (Park et al., 2017, 2020 at P18). Some studies use different VideoFreeze motion threshold values for each age within the same study (i.e., one threshold value is used for juveniles while another is used for adults) in order to best correlate with manual scoring conducted on a subset of animals (Ganella et al., 2016, 2018). Motion threshold values are rarely reported for FreezeFrame, likely because this metric is adjusted per individual animal within the software.

In addition to the motion threshold, the choice of minimum duration required to constitute a freezing episode significantly impacts behavioral output and consequent interpretation. While many studies do not publish this value, several reported the use of 1 s (Lanjewar et al., 2023; Perry et al., 2020; Samifanni et al., 2021) or 2 s (Chocyk et al., 2014). Harmonization of these metrics across labs may reduce variability and improve convergence between studies.

Finally, the increased sensitivity of recent behavioral tracking methods such as DeepLabCut (Mathis et al., 2018) may help address some of the developmental constraints in automated behavior tracking. As these methods can detect and track smaller body parts (i.e., tails and ears) of young animals, they should be tested and validated in the case of visual occlusion. Tools such as DeepLabCut are becoming standard in behavioral neuroscience and can successfully capture a wide range of behavioral parameters in young mice (Gerhard et al., 2023), carrying great potential for reliable and diverse quantification of developmental fear behavior.

Developmental studies offer unique insight into how brain circuits mature to support behavior, but also carry unique challenges and sources of variability. The aim of this overview is to identify and discuss factors that may contribute to variability across developmental fear studies in mice and offer recommendations aimed at harmonizing practices across labs. Overall, transparency in the reporting of experimental parameters—including how animals are bred, the type of bedding used, when and how animals are weaned, the experimental design, and how fear behavior is analyzed—is strongly encouraged so that these variables can be weighed into the interpretation of findings across studies. The successful adaptation of the use of viral, opto/chemogenetic, and calcium imaging tools in young rodents has significantly expanded the depth and breadth of inquiry into the neural mechanisms of developmental fear processes. Harmonization of experimental procedures across labs will facilitate consensus and increase cohesion in this fast-expanding research field.

Acknowledgments

This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada (NSERC CGS D – 569380 – 2022 to JW and RGPIN-2017-06344 to MAC), an Ontario Graduate Scholarship (OGS 2023 to HP), and grants to MAC from the Canadian Institutes of Health Research (CIHR; PJT 399790), the Human Frontier Science Program Organization (CDA00009/2018 and RGY0072/2019), and the SickKids Foundation and CIHR–Institute of Human Development, Child and Youth Health (NI19-1132R).

Author Contributions

Hanista Premachandran : Conceptualization; writing—original draft; writing—review and editing. Jennifer Wilkin : Conceptualization; writing—original draft; writing—review and editing. Maithe Arruda-Carvalho : Conceptualization; funding acquisition; supervision; writing—review and editing.

Conflict of Interest

The authors have no conflict of interest to disclose.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study

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