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Eukaryon

Investigating the Effects of Social Isolation on Fear and Anxiety in Male Rats: Potential Involvement of the Oxytocin Receptor

Michael Janeček
Lake Forest College
Lake Forest, Illinois 60045

 

 

LAKE FOREST COLLEGE

 

Senior Thesis

 

Investigating the Effects of Social Isolation on Fear and Anxiety in Male Rats:
Potential Involvement of the Oxytocin Receptor

 

by

 

Michael Janeček

 

April 20, 2018 

 

The report of the investigation undertaken as a

Senior Thesis, to carry two courses of credit in

the Neuroscience Program

 

__________________________

Michael T. Orr

Krebs Provost and Dean of the Faculty

 

__________________________

Matthew R. Kelley, Chairperson

 

__________________________

Joanna Dabrowska

Rosalind Franklin University of
Medicine and Science

 

__________________________ 

Benjamin Zeller

 



Abstract

 

Human studies suggest that social isolation induces anxiety and prolongs recovery from psychological trauma (Cacioppo et al., 2014). Conversely, having strong social support enhances stress-coping strategies and reduces the risk of developing anxiety and PTSD (Hansen et al., 2017). Here, we measured fear-potentiated startle (FPS) to determine the effects of social isolation on fear and anxiety-like behavior in male rats. We found that social isolation did not affect fear memory acquisition or expression. However, when retested, socially-isolated rats displayed greater cued fear compared to socially-housed rats, suggestive of impaired fear extinction. Further, we investigated the role of oxytocin (OT) on the social facilitation of fear extinction by blocking OT receptors (OTR). Our results showed that the OTR is not involved in the modulation of fear recall and subsequent extinction in socially-housed or isolated rats. These results highlight the critical role of social environment in the modulation of fear memory.

Keywords: fear-potentiated startle, fear conditioning, continuous social isolation, oxytocin receptor antagonist, L-368,899 

 

















In loving memory of my dad

 

and

 

for the strongest and most brilliant mom I could imagine.



 

Acknowledgments

 

This adventurous project owes much to the combined support and influence of everyone who has touched my life, especially my mom and dad who supported me as much as they could for as long as they could, my dear brother who served me as a role model of intellectual curiosity, and my dear sister who believed in me when it mattered.

I am grateful that everywhere I have gone in my life, I have met people who believed in my potential to learn and grow. Otherwise I would have never learned English, discovered my independence at my old boarding school, or traveled to Hong Kong to step out of my comfort zone. If it was not for these steps, I would not have ended up at Lake Forest College. It was here that Dr. Anna Jones sparked my interest in social history and academic writing, and it was here that Dr. Shubhik DebBurman introduced me to the mysteries of neuroscience. I had the pleasure of conducting research with Dr. Ben Zeller who then served on my thesis committee and shaped my critical understanding of knowledge creation. Dr. Matt Kelley helped me identify graduate school as my next destination, helped me arrive there, and when serving on my thesis committee helped clarify my love for teaching, embodied in this document. Dr. Jean-Marie Maddux made me connect abstract brain stuff to behavior and my interests to visible outcomes. Dr. Holly Swyers challenged my understanding of the world, and Dr. Naomi Wentworth advised me wonderfully in life and in academics. But I also wish to make visible the amazing humanity and understanding that my friends and colleagues unconditionally opened to me, helping me get through difficult moments.  

Above all, I cannot thank Dr. Joanna Dabrowska enough. She has taught me what I know about doing science and helped me in every step along the way. Joanna is a model scientist, impossibly amazing to replicate but amazingly inspiring and worthy of following—thank you for inviting me to your lab, where I worked alongside extraordinary people, and thank you for enabling me to conduct this research, which will hopefully benefit all.

List of Abbreviations

 

ASR Acoustic startle response 

AVP Arginine vasopressin

BLA Basolateral nucleus of the amygdala 

BNST Bed nucleus of the stria terminalis

CeA Central nucleus of the amygdala 

CeM Centromedial nucleus of the amygdala

CRF Corticotropin-releasing factor 

CS Conditioned stimulus

CS+ Signaled conditioned stimulus

CS- Unsignaled conditioned stimulus 

DV Dependent variable

EPM Elevated plus maze 

FPS Fear-potentiated startle 

FST Forced swim test 

GAD Generalized anxiety disorder 

HPA Hypothalamic-pituitary-adrenal 

ITI Inter-trial interval

ITC Intercalated cell masses of the amygdala 

IV Independent variable 

LA Lateral amygdala 

LTP Long-term potentiation 

OT Oxytocin

OTA Oxytocin antagonist 

OTKO Oxytocin knock-out

OTR Oxytocin receptor

OTRKO Oxytocin receptor knock-out

PAG Periaqueductal grey

PND Post-natal day

PPI Pre-pulse inhibition

PTSD Post-traumatic stress disorder 

PVN Paraventricular nucleus of the hypothalamus 

RF Reticular formation

SAM Sympathetic adrenomedullary

SON Supraoptic nucleus of the hypothalamus 

US Unconditioned stimulus

WNB White noise burst 

 

Table of Contents

Abstract i

Dedication ii

Acknowledgments iii

List of Abbreviations iv

List of Figures viii

Global Epidemic of Loneliness 1

Loneliness versus Social Isolation 3

Manipulating Social Isolation in Animal Models 4

Social Isolation, Fear, and Anxiety in Rodents 9

Neurocircuitry of Stress, Fear, and Anxiety 13

Fear-Potentiated Startle and Social Isolation 19

Experiment 1 23

Methods 23

Animals 23

Acoustic Startle Response (ASR) Apparatus 24

Timeline 25

Procedures 26

Social Isolation 26

Fear-potentiated Startle (FPS) Testing 27

Fear Retraining 28

Data Analysis 29

Experiment 2 30

Methods 30

Contextual Fear Testing 31

Results 32

First FPS Test 33

FPS Extinction 36

FPS Retraining 40

Experiment 3 43

Methods 44

Experiment 4 46

Methods 46

First FPS Test 48

FPS Extinction 50

FPS Extinction 2 55

Discussion 58

Effect of Social Isolation on FPS 58

Role of the Oxytocin Receptor in Fear Extinction 61

Limitations 65

Future Studies 67

References 71

 

List of Figures

 

Figures

Figure 1.0 Schematic diagram of visual fear conditioning inputs and outputs, effectors, and behavioral outcomes. 16

Figure 1.1 Acoustic startle response chamber apparatus. 24

Figure 1.2. Social isolation timeline in Experiment 1. 26

Figure 1.3. Schematic of social isolation onset and fear conditioning sequence. 28

Figure 1.4. Schematic of FPS testing and retraining sequence. 29

Figure 1.5. Social isolation timeline in Experiment 2. 31

Figure 2.1. Combined shock reactivity did not differ following 24-hour isolation. 33

Figure 2.2. All rats were fear conditioned in the 1st FPS test session. 34

Figure 2.3. Cued fear did not differ between the groups in the 1st FPS test session. 36

Figure 2.4. Non-cued fear did not differ between the groups in the 1st FPS test session.    36

Figure 3.1. During the 2nd FPS test session, only isolated rats remained fear conditioned.  37

Figure 3.2. Isolated rats displayed significantly elevated cued fear in the 2nd FPS test session. 39

Figure 3.3. Non-cued fear did not differ between groups in the 2nd FPS test session. 39

Figure 3.4. Discrimination index (DI) scores were not affected by housing condition in either FPS test session. 40

Figure 3.5. Shock reactivity during retraining did not differ between the conditions. 41

Figure 3.6. Retraining using 2x CS-US pairings did not fear condition rats irrespective of housing condition. 41

Figure 3.7. Post-retraining cued fear did not differ between the conditions. 43

Figure 3.8. Post-retraining non-cued fear did not differ between the conditions. 43

Figure 5.1. Shock reactivity did not differ between the groups. 47

Figure 5.2. In the 1st FPS test session, rats were surprisingly not fear-conditioned. 48

Figure 5.3. In the 1st FPS test session, all rats startled more in noise-only trials compared to pre-shock trials. 49

Figure 5.4. Cued fear in the 1st FPS test session did not differ between conditions or treatments. 50

Figure 5.5. Non- fear in the 1st FPS test session did not differ between conditions or treatments. 50

Figure 5.6. In the 2nd FPS test session, there was no evidence of fear conditioning. 51

Figure 5.7. In the 2nd FPS test session, noise-only startle was no longer potentiated compared to pre-shock baseline. 52

Figure 5.8. Despite OTA and vehicle treatment, isolated rats displayed enhanced cued fear suggestive of cued fear extinction learning impairment.  53

Figure 5.9. Non-cued fear did not differ between the conditions or treatments.  53

Figure 6.0. Isolation enhanced cued fear on a trial-to-trial basis, but did not change over time within the 2nd FPS test session. 54

Figure 6.1. Condition or treatment did not affect rats’ DI score in the 2nd FPS test. 54

Figure 6.2. Rats did not exhibit cued fear in the 3rd FPS test session. 55

Figure 6.3. Rats extinguished non-cued fear potentiation of startle in the 3rd FPS test session. 56

Figure 6.4. Cued fear did not differ as an effect of condition or treatment in the 3rd FPS test. 57

Figure 6.5. Non-cued fear did not differ as an effect of condition or treatment in the 3rd FPS test. 57








 









 

 

          






Investigating the Effects of Social Isolation on Fear and Anxiety

 

Global Epidemic of Loneliness

 

Imagine, for a moment, the experience of a commuter in a twenty-first century metropolis such as Hong Kong. A brimming elevator descends from the smoggy twenty-second floor and spills its contents into a typhoon-proof tunnel. One-way traffic picks up the pace in the neon light of ads. The subway station conveniently doubles as a loud shopping mall; commuting and shopping blend together. Traditional and simplified Mandarin characters occasionally give way to Romanized syllables. At the platform, government banners advise against taking ketamine, while reflex vests with gloves decide where this man and that woman ought to stand. It takes two, sometimes three packed trains to finally get on board. The image of a lone salmon swimming upstream comes to mind. Once seated, faces light up in digital blue; social life and digital life blend together. Conveniently, your school or workplace is an extension of another MTR station in another shopping mall at the end of another neon-lit tunnel with another claustrophobic elevator ride. Everyone moves together but exists alone.

A fundamental issue at the core of this scenario is the challenge of fulfilling social needs in an urban landscape. Consider how having a support group of close friends may impact the experience of living and working in Hong Kong and contrast this with the wellbeing of someone who lacks family support or a circle of close friends. Hong Kong emerges as a case study of loneliness with studies finding high emotional and social loneliness in young adults (Yue, Wong, & Hiranandani, 2014), decreased sense of meaning in life (To, 2016), high levels of self-defeating humor (Yue et al., 2014), and a one-in-seven incidence of mood disorders (Lam et al., 2015). Indeed, governmental and volunteer organizations acknowledge and address the above issues and overburdened psychiatric services (Blundy, 2017) in a variety of ways (see Gonzales, 2017). However, it would be a mistake to conclude that Hong Kong represents a unique case in terms of disorder incidence, increased emotionality, and decreased social wellbeing—all associated with social isolation.

The epidemic of loneliness and its public health implications are salient in a number of urbanized societies, including the United States. For instance, Robert Putnam in his seminal work Bowling Alone: The Collapse and Revival of American Community (2000) established that, at the turn of the millennium, more U.S. dwellers than ever before felt lonely and less engaged in their communities despite population growth and unprecedented technological progress:

“Of baby boomers interviewed in 1987 … [f]ully 77 percent said the nation was worse off because of “less involvement in community activities.” In 1992 three-quarters of the U.S. workforce said that “the breakdown of community” and “selfishness” were

“serious” or “very serious” problems in America.” (p. 24)

In the U.S., a landmark American Association of Retired Persons report indicates that 35% of respondents aged 45 or more feel lonely (AARP, 2017, p. i). Similarly, in the United Kingdom, a 2017 report indicates that more than 9 million U.K. dwellers “often” or “always” feel lonely (Jo Cox Commission on Loneliness, p. 10) in post-Brexit U.K. To respond to growing concerns of a loneliness epidemic in the UK, the government appointed a minister for loneliness (Yeginsu, 2018). Rising average life expectancy may exacerbate the issue as higher age is associated with social isolation: U.S. Census Bureau projects that in the next 15 years, the proportion of elderly people in the U.S. will grow by 60% (He, Goodkind, & Kowal, 2016). Japan currently has one of the most rapidly ageing populations, which has resulted in the phenomenon of “lonely deaths” with up to 4,000 elderly people dying alone in their apartments every week (Onishi, 2017). In the light of people feeling lonelier and less trusting alongside the dim prospects for spontaneous improvement of the loneliness epidemic, more investigation into social isolation should take place. 

Most studies of social isolation in humans have emphasized its connection to health. A pivotal review by House, Landis, and Umberson (1988) implicates social isolation as a key risk factor for mortality—comparable in effect size to chronic smoking—and a range of other morbidities, such as alcoholism, cardiovascular damage, and suicide (Cacioppo, Hughes, Waite, Hawkley, & Thisted, 2006). These dramatic effects of social isolation, highlighted by the controversial punitive use of solitary confinement (Browne, Cambier, & Agha, 2011), stem from isolation being a potent environmental and social stressor. And just as environmental stressors have been found to alter neuronal activity (Kolb & Whishaw, 1998), social isolation also can exert long-term structural changes in the brain (Cacioppo, Hawkley, Norman, & Berntson, 2011). Despite the trend of rising loneliness and social isolation across the globe, the causes and effects of social isolation remain poorly understood. To elucidate the effects of social isolation, this study aims to experimentally describe the effects of continuous social isolation on fear learning and anxiety.   

Loneliness versus Social Isolation

Loneliness experienced by humans is a negative affective state stemming from a lack of social contact, which in turn promotes the seeking out of social interaction. Critically, the quality rather than the quantity of social interaction underlies perception of loneliness (Cacioppo & Hawkley, 2009). Further, self-awareness of feeling lonely is central to the experience of loneliness. Due to its subjectivity, the experience of loneliness varies between individuals. The most widely used method for measuring loneliness is the UCLA Loneliness Scale (Russell, Peplau, & Ferguson, 1978), which asks participants to rate their level of agreement with a variety of statements, such as: “My interests and ideas are not shared by those around me” or “I feel isolated from others.” Evident here, the UCLA Loneliness Scale’s 20 questions conflate loneliness and social isolation while relying on participants’ honesty, thus muddying attempts at quantifying loneliness specifically. If difficult to observe in a reliable and valid manner in humans, loneliness becomes even more challenging to measure or manipulate experimentally in animals.

Social isolation, defined as a lack of physical or other contact with members of one’s species or conspecifics, represents an objective construct that can be manipulated experimentally (e.g., McPherson, Smith-Lovin, & Brashears, 2006). The most common way of socially isolating otherwise socially active individuals is through single housing, which prevents any physical contact with conspecifics, but it may also involve restricting visual and olfactory interactions.  The social, but also the physical dimensions of an environment, such as the complexity of environment and thermoregulation, can be controlled to study the stress-eliciting and other effects of social isolation (Cacioppo, Cacioppo, Capitanio, & Cole, 2015). In the next section, social rodents will emerge as a useful model with important implications for understanding social isolation in humans. 

In brief summary, loneliness represents a subjective experience that describes an affective state in humans caused by a lack of social engagement. Social isolation is then both objectively descriptive of absent social engagement (i.e., serves as a risk factor predictive of morbidity and mortality) while also representing an important variable (e.g., length of single housing) that can be manipulated in animal models. 

Manipulating Social Isolation in Animal Models 

Social isolation as a behavioral manipulation can be administered in multiple ways and importantly can vary in length and frequency. Here, acute and chronic social isolation models are discussed. Acute social isolation lasts from minutes to hours and can be administered once or repeated daily or over longer periods of time. Acute social isolation has been found to modify the synaptic activity of dopamine-containing neurons involved in motivated action (Matthews et al., 2016), impair short-term social recognition memory (Shahar-Gold & Wagner, 2013) as well as long-term social recognition memory (Leser & Wagner, 2015), and alter the immune response (Cunnick, Kojic, & Hughes, 1994). 

Relevant to defining acute isolation, Maisonnette, Morato, and Brandao (1993) studied the minimal length of social isolation necessary to induce anxiety-like behaviors in male rats. They found that two- and 24-hour isolation reduced the number of entries into and the time spent in the unprotected, wall-less “open arm” of the elevated plus maze (EPM), a standard assay for rodent anxiety-like behavior (Da Silva, Ferreira, Carobrez, & Morato, 1996). The EPM is designed to conflict the exploratory drive of a rodent against its fear of open and brightly lit spaces, since rodents are predominantly nocturnal animals. In the EPM, less anxious-like rats tend to explore and enter the exposed open arm more often, which was the case of male rats isolated only for one hour. The results of Maisonnette et al. suggest that a two-hour isolation is sufficient to produce an observable anxiety-like behavior in male rats, illustrating the fast-acting mechanism responsible for this alteration.

Critically, social isolation acutely promotes self-preservation (Cacioppo et al., 2015). Increased anxiety-like behavior evidenced above results in increased vigilance for social threats, increased hostility and fatigue, and social withdrawal, but also increased vascular resistance and gene expression alteration, to note just a few responses. Enhanced sensitivity to social threats in particular is thought to be adaptive (Cacioppo et al., 2015). In Hans Selye’s words, exposure to unavoidable aversive situations dysregulates the hypothalamic pituitary adrenal (HPA) axis (discussed in the next section in greater detail). Selye labeled the isolation-induced buffering response as the “stress syndrome,” which in the long-term sustains the stress syndrome to the organism’s long-term detriment (Engelmann, Landgraf, & Wotjak, 2005).

To understand the adaptive and maladaptive responses to stressors, stressors need to be defined. Holmes and Rahe (1967) designed the pioneering Social Readjustment Rating Scale, a checklist of major life events within a window of 6-12 months that predicts mental health outcomes, morbidity, and mortality (Cohen & Williamson, 1991). While distinctions of stressors as life events, chronic strains, and daily hassles are often made in humans, stressor broadly “refers to any environmental, social, or internal demand which requires the individual to readjust his/her usual behavioral patterns” (Thoits, 1995, p. 54). In this sense, stress coping refers to one’s ability to address and resolve stressors, which can otherwise overtax psychological resources and result in emotional and other disturbance (Brown & Harris, 1978). 

Similar to acute isolation, chronic social isolation activates the sympathetic system and increases anxiety-like behavior. However, the long-term nature of isolation results in more severe psychological and health symptoms, such as hypervigilance to threats and cardiovascular dysfunction. For example, in addition to entering the EPM open arms less, male rats isolated for six weeks displayed disturbed locomotion (Jankowska, Pucilowski, & Kostowski, 1991). Further, female prairie voles isolated for four weeks showed increased heart rate at rest and reduced heart rate variability, which during a psychosocial resident-intruder challenge translated into an exaggerated cardiac response that took three times as long (compared to pair-housed voles) to return to pre-stress baseline (Grippo, Lamb, Carter, & Porges, 2007a). Interestingly, isolated females exhibited this enhanced sympathetic activation both in the stressogenic open and comforting closed arms of the EPM, although they explored and entered the open arm less than socially-housed females. In comparison, pair-housed voles did not show increased heart rate when tested in the EPM open arm, and their heart rate decreased when tested in the non-threatening EPM closed arm, which is protected by walls. Taken together, the above results suggest that pair-housed females are able to distinguish and respond appropriately between threatening (open arm) and safe (closed arm) environments, whereas chronically isolated female voles displayed elevated sympathetic activation regardless of how safe or dangerous the environment was (Grippo et al., 2007a). Inability to recognize threat from safety, or hypervigilance, therefore highlights a key maladaptive consequence of long-term social isolation stress. 

Also relevant is the finding that female prairie voles respond more severely than males to psychosocial stress, such as chronic social isolation. This sex-mediated vulnerability to isolation may be relevant to understanding why women are more likely in their lifetime and almost twice as likely as men in a timeframe of 12 months to develop a psychiatric disorder (Alonso, Angermeyer, Bernert, Bruffaerts, … & Vollebergh, 2004). Female, but not male voles, display elevated plasma oxytocin and corticotropin-releasing factor (CRF) levels, indicative of neuroendocrine activation in response to stress, following four weeks of chronic social isolation (Grippo, Gerena, Huang, Kumar, … & Carter, 2007b). Yet, both chronically isolated male and female prairie voles exhibit decreased pleasure-seeking, evidenced by lowered sucrose intake (Grippo et al., 2007b). Unlike the noted reduction in pleasure-seeking (anhedonia), ethanol intake and development of addictive behaviors are both enhanced by chronic social isolation (Kim & Kirkpatrick, 1996). Together, these findings associate chronic social isolation with anxiety- and depression-like behavior, such as anhedonia, addictive behavior, hypervigilance, and stress-related neuroendocrine changes in oxytocin and CRF.

Therefore, rather than accounting for all aspects of a single disorder, social isolation has been exploited to understand various risk factors, neurobiological mechanisms, and treatment responses. Specifically, aspects of alcoholism (Roske, Baeger, Frenzel, & Oehme, 1994), schizophrenia (Geyer, Wilkinson, Humby, & Robbins, 1993), and depressive disorders (Jaffe, De Frias, & Ibarra, 1993) can be examined through social isolation. A key finding lending validity to social isolation in understanding depressive behavior is that antidepressant drugs reverse learned helplessness and anhedonia produced by social isolation, arguing for social isolation’s relevance in studying depressive aspects of psychiatric conditions (Harlow, 1971; McKinney, 1984; McKinney, Suomi, & Harlow, 1971; Seaman, Lewis, DeLizio, & McKinney, 1978). Similarly, single housing in juvenile rodents reliably induces anxiety-like behavior (Parker & Morinan, 1986).

Another critical factor in social isolation is the age at which an animal is separated from maternal, monogamous partner, or sibling influence. Evidence suggests that the kind of bond that is disrupted by single housing has a distinct impact apart from physical isolation (Cacioppo et al., 2015). For instance, in their pioneering studies, Suomi, Harlow, and Kimball (1971) demonstrated that species-specific social, aggressive, and maternal behaviors fail to develop appropriately in rhesus monkeys isolated at birth. Rhesus monkeys completely isolated from mothers engage in non-nutritional eating, compulsive rocking and self-clutching, and other stereotypic behaviors, such as eye-poking and pacing (Lutz, 2014). When newborn rhesus monkeys do not grow up in complete isolation but are assigned to peer rearing by older siblings, their acoustic startle response, indicative of emotionality and defensiveness, shows exaggerated threat processing and increased aspartame intake indicates enhanced reward seeking (Nelson, Herman, Barrett, Noble, …, & Pine, 2009). In male rats raised in social isolation (i.e., isolation rearing), forced swim test challenge yields decreased motivation to escape from the aversive water environment and more “learned helplessness,” supporting the conclusion that early life adversity in the form of isolation produces a severely maladaptive phenotype across mammals in part due to the disruption of maternal bond (Brenes, Rodriguez, & Fornaguera, 2008). However, comparatively little is known about the impact of social isolation in adulthood, which, unlike the more vulnerable period of adolescence, should correspond to better stress-coping skills and lower psychosocial stress interference with cognitive maturation. In this vein, maternal bond disruption plays a less important role than sibling or partner bond disruption, which is thus more relevant to understanding social isolation in adult humans (Bosch, Nair, Ahern, Neumann, & Young, 2009).

Rodents, such as rats and prairie voles, which exhibit socially rich interactions (e.g., play-fighting and complex social learning) (Vanderschuren & Trezza, 2013), are typically used for social isolation manipulations (Neumann, Wegener, Homberg, Cohen, & Mathé, 2011). Rats’ genome is more complex and thus more relevant to extrapolation to the human genome than that of mice, and rat brains are structurally and functionally similar to human brains (Semple, Blomgren, Gimlin, Ferriero, & Noble-Haeusslein, 2013). Rodents also have shorter and more manageable life spans than primates, and their size allows for easier and more effective transportation, control of living space, environmental complexity (e.g., enrichment or deprivation), and thermoregulation, in turn lending better understanding of social isolation (Cacioppo et al., 2015). Further, Pavlovian fear conditioning and EPM allow for the standardization of fear and anxiety-like behavior, respectively, across studies. In terms of animal welfare and the “three Rs” principle of replacement of animals for non-animals, reduction of the number of animals, and refinement of procedure to minimize pain and distress (Fenwick, Griffin, & Gauthier, 2009), rodents represent an advanced enough model that satisfies the cost-benefit analysis compared to higher order animals (e.g., dogs or monkeys) yet possesses the cognitive and social complexity relevant to studying social isolation, fear, and anxiety. For these practical and translational reasons, social isolation will be mostly discussed in terms of rodent studies.   

Social Isolation, Fear, and Anxiety in Rodents

If short-term and especially long-term social isolation induce hypervigilance as shown above, then behavioral responses to fearful stimuli should reflect animal’s increased threat sensitivity. Thus, the relationship between social isolation and fear memory can help elucidate the mechanism of social isolation. Pavlovian fear conditioning (also known as classical conditioning) serves as a robust paradigm to measure learned fear, whereby a non-noxious, neutral stimulus, such as a light or a tone, can be temporally associated with a naturally aversive stimulus, such as a foot shock or a tail shock. If the neutral and aversive stimuli co-terminate, an animal learns that the light or tone cue predicts the shock (unconditioned stimulus, US) and thus attains aversive value (conditioned stimulus, CS). The more distant in time the neutral and aversive stimuli presentations occur, the less effective the fear conditioning becomes (for conceptual review see Raybuck & Lattal, 2014). The fear memory of CS-US pairings in rodents can then be retrieved and measured by presenting the CS without the US and observing, for example, time spent “freezing” in anticipation of a shock, or whole-body startle reflex potentiation in the presence of the CS. Potentiation here refers to the enhancement of the startle amplitude when first presented with the CS (but in the absence of US), which evokes a fearful state corresponding to increased threat responsiveness. 

The concept of Pavlovian learning acknowledges that memory is dynamic and that its substrate undergoes stable and labile phases (Rescorla, 1988; Tonegawa, Pignatelli, Roy, & Ryan, 2015). As a result, many time points of learning can be examined and manipulated. These time points correspond (but are not limited to) processes of fear memory acquisition, consolidation, recall, extinction, and reinstatement. These memory processes stem from the recognized theory (for reviews see Schafe, Nader, Blair, & LeDoux, 2001; and Alberini & LeDoux, 2013) that memories, when first learned (acquired), are initially labile and without interference become stable (consolidate) over time, but their retrieval (recall) activates them and modifies them, upon which they need to be stabilized (reconsolidated) again. Further, the learned association of CS-US pairings, if retrieved and expressed enough times without the presence of the original US, can be dissociated (extinguished). Yet, extinction learning needs to be better understood because it has been found to be disrupted in patients suffering from the post-traumatic stress disorder (PTSD) (see Jovanovic and Ressler, 2010), whereby fear response to a traumatic event generalizes onto safe, non-threatening contexts, increasing the likelihood of fear recall (Rothbaum and Davis, 2003). In non-pathological circumstances, CS extinction can be successfully learnt—since extinction is an active learning process in contrast to forgetting or memory decay—but the original CS memory can sometimes still be retrieved (reinstated) by presenting the original US only in the original conditioning context. Considering psychosocial stress influence on memory, measuring fear memory in isolated rats can help us understand how social isolation affects memory dynamics.  

Helpfully, fear can be quantified in several ways, and time spent freezing in rodents is but one such measure. Freezing, though at first counterintuitive in the face of danger, represents an adaptive response in scenarios where escape is not possible. However, while freezing time is most commonly used to study Pavlovian fear conditioning in rodents, freezing does not allow precise quantification of all fear components. Specifically, so-called non-cued fear, which refers to a generalized fear response in the absence of a discrete cue (and is therefore sometimes termed “background anxiety”), is often overlooked in studies that only look at freezing behavior (Ayers, Agostini, Schulkin, & Rosen, 2016; Missig, Ayers, Schulkin, & Rosen, 2010). This is because CS-elicited freezing tends to last longer than the CS presentation itself, making it challenging to measure post-CS freezing during inter-trial intervals (ITIs). Although some studies do quantify time spent freezing in ITIs, most studies that utilize freezing as a dependent measure use pre-shock freezing as a baseline, omitting non-cued fear altogether. 

Another way of quantifying defensiveness and stress reactivity is the acoustic startle response (ASR) elicited by a noise that results in a whole-body startle reflex in stressed and naïve rats. ASR has good translatability from rodents and primates to humans and can quantify components of fear more precisely than time spent freezing (Davis, Walker, Miles, & Grillon, 2010), which is why ASR serves as a reliable and valid measure of vigilance and emotional defensiveness, two indicators of an anxiety-like state. However, rodent ASR by itself cannot tell us much about fear memory. 

One way to examine fear-learning using the ASR is through the fear-potentiated startle (FPS) paradigm, which exploits the enhancement of ASR by a simultaneous CS presentation in fear-conditioned animals. In the presence of a CS+ (e.g., a signaled light cue), an auditory stimulus startles naïve rats 50-60% more compared to the auditory stimulus-evoked startle alone (Davis et al., 2010). This CS+ potentiation of startle is caused by its association with a foot shock, whereby the CS+ onset begins before but co-terminates with the foot shock and therefore in the animal’s mind comes to predict the foot shock. The paradigm is called “fear potentiation” because it contains a learned component that is specific to a cue (i.e., cued fear), although fear generalization onto the immediate environment (i.e., contextual fear) and non-cued fear still occur and can be tested separately. Unlike in the freezing paradigm, FPS can be measured in the absence of a CS and hence can differentiate non-cued fear (or background anxiety) from cued fear in fear-conditioned rats. Having described viable ways of assessing both fear and anxiety-related emotionality, let us now turn to how fear and anxiety differ. 

Anxiety manifests as a state of apprehension or worry and, like loneliness, depends on self-perception, such that it is specific to humans (Epstein, 1985; Fathi-Ashtiani, Ejei, Khodapanahi, & Tarkhorani, 2007). That is why, without being able to know how animals feel, animal behavior is characterized as anxiety-like. If left unresolved or amplified, anxiety grows into a sustained maladaptive trait characterized by hypervigilance and excessive emotional processing with psychological and somatic consequences (DSM-V, 2013). Unlike fear, anxiety is diffuse, future-oriented (e.g., worrying or anticipation), and elicited by more distant, less specific, and less predictable threats (Davis et al., 2010). Anxiety can thus be operationalized as sustained negative affect in the absence of a discrete threat stimulus or in anticipation of a threat. Put differently, anxiety does not require classical or associative learning. In sum, anxiety-like behavior in animals can be measured as exploratory behavior in the exposed, wall-less open arm of the elevated plus maze (EPM), as acoustic startle response (ASR), as approach-avoidance behavior, and importantly as non-cued fear in the FPS together with ASR, indicative of stress reactivity (Neumann et al., 2011).

Fear, on the other hand, is elicited by the presence of a threatening conditioned stimulus (CS), dissipates rapidly upon the removal of the treat, and critically represents a learned response (Davis et al., 2010). Phasic fear, which is short-lasting and specific, prepares the organism for defensive behavior (e.g., freezing, jump attack, startle, or escape) in the face of imminent danger. Elevated cued fear reactivity is for example present in patients suffering from phobias, characterized by a vigorous defensive behavior in the presence of a CS, such as a spider (Straube, Mentzel, & Miltner, 2007). While phobias also involve anticipatory and anxiety-like components, and their sustenance is complex, the mechanism of phobic fear acquisition highlights the distinction between learned responses (Pavlovian fear conditioning) and, in simplified terms, unlearned affective states (anxiety) as well as their clinical relevance—more than 10 million adults in the US suffer from phobias (Winerman, 2005). Ironically, phobias also stress the commonly muddied distinction between fear and anxiety because anxiety contains fear-like components. As the name suggests, generalized anxiety disorder (GAD) together with PTSD, described above, stems from the over-generalization of a fear response onto an otherwise neutral and safe context (for review see Dunsmoor & Paz, 2015). 

To summarize, FPS can reveal reflexive responses of a rat or a human to both non-cued and cued stimuli, quantifying precisely both background anxiety and phasic fear. Having good inter-species translatability, FPS improves on the dependent variable of freezing and enables the differentiation and observation of distinct fear and anxiety-like components. Ultimately, FPS proves invaluable for its ability to explore the effects of social isolation on fear memory.

Neurocircuitry of Fear-learning and Anxiety

To bring back Selye, psychosocial stress caused by social isolation has so far been discussed in terms of the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic adrenomedullary (SAM) axis, which together drive the classical endocrine stress response (Lukkes, Summers, Scholl, Renner, & Forster, 2009; van Honk, Bos, Terburg, Heany, & Stein, 2015). While the HPA and SAM are understood to regulate the “fight-or-flight” response to facilitate survival by redistributing organism’s key somatic resources, such as blood, oxygen, and glucose into skeletal muscles involved in voluntary movement, this tells us little about fear learning and anxiety. The HPA and SAM axes do tell us how a fearful stimulus engages through downstream brain signaling the sympathetic branch of the autonomic nervous system, which controls respiration, reflexes, cardiac function, and blood vessel constriction and dilation to regulate blood flow (Cacioppo et al., 2015; Rodrigues, LeDoux, & Sapolsky, 2009). 

The neurocircuitry of Pavlovian fear conditioning (and FPS) clarifies how other components of fear and anxiety are learned and how they manifest. The amygdala, a structure that integrates emotions, emotional behavior, and motivation, is at the forefront of fear learning and fear memory in both primates and rodents. That is because the lateral amygdala (LA), shown in Figure 1.0, serves as the main point of entry of sensory inputs from the auditory and visual thalamus nuclei. The somatosensory thalamus on the other hand projects to the central nucleus of the amygdala (CeA), which together with the LA project to the centromedial nucleus of amygdala (CeM). CeM is one of the critical amygdalar output structures and as such modulates a variety of behaviors relevant to fear and anxiety, from corticosteroid (stress hormone) release in the blood to trigeminal nerve muscle contractions that produce the facial expression of fear (Davis, Rainnie, & Cassell, 1994).

During fear conditioning, an auditory or a visual cue serves as a conditioned stimulus (CS), whereas somatosensory information is usually delivered as a foot shock (unconditioned stimulus, US). When CS and US stimuli are temporally associated, such as through paired CS-US presentations that co-terminate together, learning can take place. This is because concurrent LA and CeA activation of CeM causes at the neuronal level so-called long-term potentiation (LTP), whereby memory formation is presumed to happen (Clugnet & LeDoux, 1990; Kim, DeCola, Landeira-Fernandez, & Fanselow, 1991). The plastic LTP process of stimuli association takes place at the Hebbian synapse, which connects individual neurons and represents the essential site of electrochemical information transfer and modification at the molecular level (Brown, Kairiss, & Keenan, 1990). For example, if the registration of a visual CS via the visual thalamus weakly activates a specific CeM neuron, and a concurrent, strong signal conveying somatosensory information about foot shock reaches and activates the same CeM neuron, the weaker visual signal will become potentiated. If repeated several times through CS-US pairing, LTP takes place by the means of post-synaptic strengthening and receptor increase, such that in the future only one of the stimuli (CS or US) is required to elicit their association. Consolidation and reconsolidation, mentioned above, refer to the synaptic modification process, which is not immediate. While the retrieval of consolidated associations at will is not always available, reinstatement demonstrates that even previously-associated stimuli can be made relevant again given the appropriate stimulus exposure.

CeM is the main output structure of the amygdala and the main source of projections to brainstem structures that represent fear effectors. From these, periaqueductal grey (PAG) mediates freezing behavior while the pontine reticular formation (RF) mediates the startle response. Although the CeM projects to key effectors, it is the CeA that has been shown to be critical for fear memory acquisition, consolidation, and , while the basolateral amygdala (BLA) serves as the main site of long-term fear memory storage (Gale, Anagnostaras, Godsil, Mitchell, & Fanselow, 2004). Also note that the reflexive startle response mediated by the RF is not processed by the amygdala if no CeA-dependent learning of emotional processing takes place—indeed, the startle-eliciting WNB is too quick and potentially life-or-death determining to be registered by the auditory thalamus. 

Traditionally, the CeA has been thought to underlie phasic fear responses to short, discrete stimuli. The bed nucleus of stria terminalis (BNST), a part of the extended amygdala, on the other hand, has been through lesion studies (Hitchcock and Davis, 1991; Gewirtz, NcNish, & Davis, 1998) shown to mediate long-duration, anxiety-like (e.g., contextual, anticipatory, and unpredictable fear) responses (Davis et al., 2010). Recently, this straightforward distinction has been complicated by the reciprocity and overlap of BNST and CeA projections, illustrated in Figure 1.0 (Shackman & Fox, 2016). The BNST appears to be involved in the ability to discriminate between threat and safety

 

stimuli and to respond to them appropriately (Goode and Maren, 2017; Gungor and Paré, 2016). For these reasons, the BNST is emerging as a pivotal structure underlying individual stress reactivity differences (Duvarci, Bauer, & Paré, 2009) and hence being of incredible importance to dissecting stress-related disorder etiology (Lebow & Chen, 2016). 

An array of stress- and fear-related endogenous (produced by the body) signaling chemicals, such as arginine vasopressin (AVP) and oxytocin (OT), is engaged in modulating the fear-learning process described above. In the paraventricular nucleus of hypothalamus (PVN), synthesis and release of stress hormones (e.g., CRF, but also OT) into the hypophysial portal blood system that connects to the anterior pituitary gland takes place (Engelmann et al., 2005). Both forced swim test (FST) and social defeat result in AVP release, but OT is released only during FST. Notably, the relative plasma concentration change is statistically significant for OT during the FST only, while central AVP release during either stressor is not reflected in blood plasma. When FST is repeated over three days, local AVP release in the PVN becomes significantly elevated on each consecutive day. However, the opposite trend is observed for AVP release in the supraoptic nucleus of hypothalamus (SON), where FST sessions on Day 2 and Day 3 induce attenuated AVP release in comparison to Day 1 (Engelmann et al., 2005). These intricacies of stressor-specific AVP and OT release underscore, first, the need for behavioral measures as well as endogenous stress hormone measures to dissociate the consequences of stressors, and second, the involvement of endogenous AVP and OT in response to psychosocial and physical threats. 

While the roles of CRF and cortisol (humans) or corticosterone (rodents) are relatively well understood, the involvement of OT and AVP within fear modulation remains elusive in comparison. Within the scope of the present study, we will focus on the action of OT rather than AVP despite their cross-binding reactivity, which suggests that OT binds OTR with only 10 times the affinity of AVP (Baribeau & Anagnostou, 2015). Even though OT has been shown to have numerous anxiety-attenuating, or anxiolytic, properties in mice (Ring, Malberg, Potestio, Ping … & Rosenzweig-Lipson, 2006), rats (Bale, Davis, Auger, Dorsa, & McCarthy, 2001), and humans (Ellenbogen, Linnen, Cardoso, & Joober, 2014), OT also modulates fear in a variety of ways depending on the age, brain site, sex, and mode of administration. Therefore, OT administration into the basolateral (BLA) or central nuclei (CeA) of amygdala produces opposite effects (Lahoud & Maroun, 2013), while OT can also interfere with fear learning in a phase-dependent manner (Toth, Neumann, & Slattery, 2012a) and interfere with extinction and enhance fear in the BLA and CeA (Kritman, Lahoud, & Maroun, 2017). However, most of the above findings pointing to OT’s involvement in fear modulation come from exogenous OT not produced in the body and therefore do not persuasively attest to the role of endogenous OT that is synthesized and released within the body, for example in response to FST in male rats.  

The involvement of endogenous OT is best demonstrated using genetic “knock-out” (KO) rodent models that are deficient in OT production. OTKO female mice tested in the EPM enter and explore its open arm less than wildtype females, asserting that OT deficiency produces an anxiety-like phenotype in female mice (Mantella, Vollmer, & Amico, 2003). Contrastingly, OTKO male mice tested in the EPM explore and enter the open arm more, implying a decreased anxiety-like behavior (Mantella et al., 2003). Additionally, female mice with their oxytocin receptor (OTR) knocked out (OTRKO) show, in disagreement with OTKO females, less anxiety-like behavior by exploring and entering the EPM open arm more than wildtype females (Wood, Knoll, & Levitt, 2015). These results suggest that endogenous OT and its specific receptor, the OTR, play a critical role in modulating anxiety-like states in both male and female rodents. 

If the role of OT in fear modulation is somewhat elusive, fear memory outcomes of antagonizing the OTR systemically or specifically are even less well understood. Moaddab and Dabrowska (2017) have previously shown that oxytocin receptor antagonist (OTA) injected into the BNST prior to fear conditioning impairs cued fear acquisition. However, OT administered into the cerebrospinal fluid before fear recall impaired fear extinction (Toth et al., 2012a). Endogenous OT release following optogenetic stimulation suppressed freezing in fear-conditioned rats (Knobloch, Charlet, Hoffmann, Eliava, & Grinevich, 2012). Moreover, OT analog infused into the CeA before fear acquisition later suppressed contextual fear recall (Lahoud and Maroun, 2013). Further, in male rats fear-conditioned to a context, OT infusion into the BLA prior to testing suppressed the expression of contextual fear, and this OT-induced suppression was blocked by a co-administration of OT and OTA (Campbell-Smith, Holmes, Lingawi, Panayi, & Westbrook, 2015). Together, these studies provide evidence for the involvement of OTR in cued fear acquisition and contextual fear expression, providing a backdrop against which to understand the role of OT outside of its social behavior modulation. 

Fear-Potentiated Startle (FPS) and Social Isolation 

 

Few papers have directly examined the effects of social isolation in terms of FPS. One study housed male Wistar rats aged 40 days (adolescence) in groups of five or in isolation for 10 days; a third group of rats isolated for 10 days was then re-socialized in groups of five (Rosa, Nobre, Oliveira, & Brandao, 2005). The social isolation manipulation still enabled rats to see, hear, and smell the other animals. The purpose of this study was to understand the effects of isolation on fear responses to aversive stimuli, novelty, and sensorimotor gating, which refers to the brain’s ability to filter out environmental stimuli, direct attention, and execute movement. Sensorimotor gating can be measured using pre-pulse inhibition (PPI), which is a phenomenon referring to the reduction of whole-body startle reflex as a consequence of exposure to a mild, non-startling stimulus (i.e., pre-pulse) shortly before the startle-eliciting stimulus presentation.  

Rosa et al. (2005) found that rats isolated for 10 days, when exposed to novelty, vocalize significantly less and for shorter duration than group-housed rats. Lack of vocalization suggests a deficit in defensive behavior, which was not reversed by re-socialization. More relevantly, isolated, group-housed, and group-housed and re-socialized rats displayed significant CS+ potentiation of startle amplitude, signifying successful fear conditioning in all groups. 

However, both isolated and re-socialized rats showed potentiated noise-only startle amplitude, suggesting that isolation may enhance defensive behavior (i.e., startle) to non-signaled threats. As a proof of concept, pre-pulse by itself did not elicit a startle reflex, but in isolated and re-socialized rats, PPI was significantly enhanced, inhibiting about 60% of the acoustic startle response. These findings suggest that 10-day isolation in adolescent male rats activates unconditioned fear mechanisms involved in defensive behaviors, evidenced by isolation-enhanced noise-only (but not light-noise) startle, increased sensorimotor gating, and decreased vocalization when challenged with novelty. 

Another study examined the effects of adolescent social isolation on anxiety, fear extinction learning, and ethanol intake in adulthood (Skelly, Chappell, & Weiner, 2015). Male Long Evans rats aged 28 days (early adolescence) were housed singly or in groups of four for six weeks. Isolated rats in the elevated plus-maze explored the open arms less and made fewer entries into the open arms, indicating increased anxiety-like behavior in comparison to group-housed rats. Yet, this difference may have been contaminated by non-specific locomotor activity, which was significantly increased in isolated rats, such that they entered the protected closed arms more than group-housed rats. Isolation-induced locomotor enhancement was robustly replicated using the open field test, which represented a novel, aversively lit environment. This finding elaborates on the isolation-induced behavioral changes in the face of novelty.

All animals were fear conditioned two weeks after the end of social isolation housing, and all animals 24 hours later showed significant potentiation of startle amplitude in light-noise trials. Additionally, startle amplitude was increased in all noise-only trials, but in contrast to Rosa et al. (2005), there was no effect of housing condition in noise-only trials. Hence, these results indicate that six-week isolation prior to fear conditioning does not affect the acquisition or expression of cued or non-cued potentiation of the startle amplitude.  

Notably, when tested again over three consecutive days—each test session consisting of 30 trials with a CS+ presentation—housing condition significantly affected light-noise potentiation of the startle amplitude. While socially-housed rats did not show a potentiation of startle amplitude in CS+ trials, essentially showing no difference between noise-only and light-noise trials, previously isolated rats continued to exhibit the light-noise potentiation of startle. This effect was specific to CS+ startle amplitude as housing condition did not affect noise-only startle amplitude, and initial shock reactivity did not differ between the groups. This finding suggests that six-week social isolation interferes with fear memory extinction learning when male rats are fear conditioned and tested two weeks later. 

Moreover, even though no differences in ethanol or water intake were detected on the first testing day, formerly isolated rats consumed more ethanol in the second testing session than socially-housed rats. This increased ethanol intake persisted throughout the following 22 days. Similarly, isolated rats consistently preferred ethanol over water on all testing days except for the first testing session.

In a rhesus monkey model foreshadowed above, FPS and aspartame preference were used to assess the consequences of peer (PR) or mother rearing (MR) (Nelson et al., 2009). Male monkeys assigned to PR were at birth separated from their mother, cared for by humans for several weeks, and then re-housed with peers until eight months old. Two daily sessions of FPS were run, each consisting of 40 trials with mixed intensities (95 dB, 105 dB, and 115 dB). Half of the FPS trials were presented in the presence of a light (CS+) and half in dark. During the first, last, and two randomly determined trials, a light co-terminated with the delivery of a 0.5 s air puff to the face. On the second testing day, PR monkeys relative to MR monkeys displayed greater startle responses in the presence of CS+ during the 105 and 115 dB trials. Acoustic startle response to 105 and 115 dB intensities was enhanced in the PR group on both days, but light did not potentiate startle amplitude during the first test session, suggesting that PR does not affect cued fear acquisition. These results imply that contrary to the rodent studies above, higher volume auditory stimuli in monkeys separated from their mothers result in non-specific startle enhancement. CS+ potentiation of the startle response was observed on the second testing day, when monkeys were better fear conditioned (fear conditioning was interspersed throughout each testing session). In line with Rosa et al. (2005), these results show that isolated or MR animals are more responsive to non-specific startle-eliciting noise presentations, indicative of threat hypervigilance. 

Taken together, the above three studies suggest some conflicting implications for social isolation in terms of FPS. Since they represent the entirety of research done in “fear-potentiated startle” and “isolation” when these terms are searched on PubMed, modeling short-term, continuous social isolation remains a challenge.

The present study was designed to disambiguate the effects of continuous social isolation as measured by the FPS in adult male rats. First, we asked whether social isolation potentiates FPS. We hypothesized that continuous social isolation would increase vigilance and therefore potentiate the ASR regardless of cue presentation. Second, we asked whether continuous social isolation affects fear extinction, as Rosa et al. (2005) suggested, and we hypothesized that isolation would affect extinction learning. Third, we asked if social isolation affects rats’ ability to discriminate between signaled CS+ and unsignaled, noise-only trials (CS-). We hypothesized that isolation-induced hypervigilance should exaggerate responses to both safe and threatening cues, erasing the distinction between them. Fourth, we asked if oxytocin receptors (OTRs) are involved in fear extinction, and we hypothesized that OTRs contribute to social facilitation of fear extinction. 

Note that while experiments were conducted separately and that their designs are reported separately, Experiments 1 and 2 and Experiments 3 and 4 are analyzed together at the end of each relevant methods section.

Experiment 1

Experiment 1 served to model the effects of social isolation in adult male rats. Due to the lack of studies examining social isolation in terms of FPS in non-adolescent male rats, we sought to observe the effects of social isolation in our laboratory conditions and validate them using FPS, assuming that FPS is sensitive enough to measure relevant behavioral outcomes. Our preliminary hypothesis was that social isolation will lead to potentiated FPS compared to the FPS of socially-housed animals, which served as our experimental control group.

Methods

The design of the study employs one independent variable (IV) of housing condition with two levels (IV: social housing vs. social isolation) and a dependent variable (DV) of startle amplitude, which in millivolts (mV) measures the rats’ whole-body acoustic startle reflex (ASR). The IV of housing manipulation was entirely between-subjects, such that half of the rats were assigned to social isolation and half were assigned to social housing in pairs or trios. 

Animals

Male Sprague-Dawley rats aged 44-48 post-natal days (PND) and weighing 175-199 g were purchased from ENVIGO, IL. Prior to experimentation, all rats were housed in pairs or trios on a 12:12 light-dark cycle starting at 7 a.m. and ending at 7 p.m. with free access to food and water. For one week since arrival, rats adapted to the new environment, such that they were adult, or about 60 PNDs old by experimental Day 0. A total of 76 animals were used in Experiments 1-4. All experimental procedures were approved by the Institutional Animal Care and Use Committees at Rosalind Franklin University of Medicine and Science and were performed in accordance with the US National Institutes of Health guidelines.

Acoustic Startle Response (ASR) Apparatus 

All experiments were conducted in eight identical SR-LAB chambers (see Figure 1.1) with cylindrical plexiglass enclosures to hold rats during training and testing sessions (San Diego Instruments, San Diego, CA). Cylindrical enclosures enabled rats to turn around, so they did not present physical restraint stress. A high frequency loudspeaker was mounted 24 cm above the center of the enclosure, providing background noise as well as the startle-eliciting white-noise bursts (WNB; during all trial types). During fear potentiated startle (FPS) sessions, a single ceiling LED bulb administered visual conditioned stimulus (CS+). During fear conditioning, contextual fear testing, and retraining sessions, a stainless-steel grid floor was placed into the cylinders to deliver foot shocks as the unconditioned stimulus (US), which was paired with the light cue (CS-US). The sequence and presentation of all stimuli as well as startle response recording were automatically controlled by the SR-LAB software (San Diego Instruments) using a Windows 10 laptop.

 

Timeline

Before the first phase of Experiment 1 (see Figure 1.2), male rats (n=12) were ordered from ENVIGO, IL, and allowed to acclimate in the Biological Research Facility (BRF) housing for one week. All rats were housed socially, in pairs or trios, during this acclimation period. When acclimation ended, on Day 0, all rats were handled by a researcher, habituated for 45-60 minutes in a quiet room with dim lighting, and placed into plexiglass enclosures inside the sound-attenuated startle chambers (SR-LAB, San Diego) for 20-25 minutes without any stimulation. This way, rats were acquainted with the 45-60-minute habituation procedure repeated before every training or testing session as well as with the startle-measuring apparatus, reducing the stress of undergoing the first testing session. On Day 1, pre-shock acoustic startle baseline of all rats was recorded and averaged over 30 trials. On the same day, rats were split equally into two groups, social isolation and social housing, balanced around the groups’ mean pre-shock startle amplitude. About 24 hours later, on Day 2 of social isolation, all rats were fear conditioned using 10 presentations of a light cue co-terminating with an aversive foot shock. This way, the light cue attained negative valence as a threat predictor. 

In the second phase of Experiment 1, starting on Day 3, cued fear recall of all rats was tested exactly 24 hours following visual fear conditioning. Since memory consolidation is known to be time- and sleep-dependent, the 24-hour period represents a wide-enough window for consolidation to take place (Kindt & Soeter, 2018). Testing CS responses 24 hours after fear conditioning is known as “delayed extinction” of the fear as opposed to “immediate extinction” that takes place minutes after fear conditioning and has been found less effective than more spaced out extinction sessions due to the consolidation time window (Fitzgerald, Seemann, & Maren, 2014; Maren & Chang, 2006). On Day 3, all rats were habituated for 45-60 minutes in dim light and underwent an FPS test session, which consisted of 10 post-shock trials used to habituate the rats’ ASR (not included in the present analysis). In the remainder of each FPS test session, 20 trials containing CS+ (i.e., light-noise trials) and CS- (i.e., noise-only trials), mixed in a pseudorandom order followed. All rats underwent additional cued fear testing sessions on Days 6, 8, and 10, until they exhibited no enhancement of their startle amplitude in the presence of the light cue. 

In the third phase of Experiment 1, on Day 15, a new startle amplitude baseline was measured across 30 noise-alone trials. On Day 16, all rats were re-trained by 2 presentations of a foot shock paired with the light cue from phase one. On Day 17, exactly 24 hours following re-training, cued fear recall was tested across 30 trials same as in phase two. On Day 20, animals were sacrificed using carbon dioxide and decapitation. 

 

Procedures

Social isolation. Following a baseline pre-shock baseline measurement on Day 1, all rats in this study were assigned to social isolation or social housing condition, such that both groups were counterbalanced and had similar average pre-shock startle values. It was ensured that rats were fear-conditioned and tested in the same chambers where their pre-shock startle was measured to minimize measurement differences between different chambers. Rats assigned to social isolation were housed one rat per cage with filter covers preventing external olfactory stimulation. The control animals were assigned to social housing, such that two or three animals were housed per one cage with no social or olfactory restriction. Cages were changed twice per week on Tuesday and Friday but only after testing or training sessions were completed, so that cage changes did not alter the rats’ stress levels. Apart from cage changes, isolated rats had no other human or conspecific contact; socially social housed rats had no human contact but free contact with conspecifics. Starting on Day 1, continuous isolation lasted for up to 20 days, during which different testing and training trials assessed the effect of housing condition on fear memory. 

Fear potentiated startle (FPS) testing.  FPS refers to the potentiation of acoustic startle response (ASR) following Pavlovian fear conditioning, where the rat associates a visual light cue (conditioned stimulus; CS) with a noxious foot shock (unconditioned stimulus; US). The US-CS pairing results in cued fear and non-cued fear potentiation of the whole-body startle reflex, triggered by a 95 dB acoustic stimulus. ASR thus measures reactivity indicative of fear, and FPS exploits the potentiation of this reactivity.

As described in the experimental timeline section, following a week of acclimation to the housing facility, each rat was handled for five minutes per day and habituated for one hour in a dimly lit room prior to any testing or training sessions. Baseline ASR was determined by a pre-shock startle session consisting of 30 noise-only trials (Day 1). Using the ASR values, rats were split equally into groups with as similar ASR means and standard deviations as possible. The treatment group of rats was socially isolated about 24 hours prior to fear-conditioning, which took place one day from the pre-shock (Day 2). During fear conditioning, each plexiglass enclosure in SR-LAB chambers contained a metallic grid floor to deliver foot shocks. After five-minute acclimation in the chambers, rats received 10 presentations of a 3.7 s cue light (CS), each co-terminating with a 0.5 s foot shock (US) of 0.5 mA. The CS-US presentations were administered unpredictably, with inter-trial intervals ranging between 60 and 180 s. Background noise was absent during the conditioning session and a non-ethanol disinfectant was used to clean the chambers to differentiate this training context from the earlier testing context.  

Twenty-four hours later (Day 3), rats were tested for recall of cued fear using the ASR apparatus (see Figure 1.3). Each rat was habituated for one hour and acclimated for five minutes in the cylindrical enclosure, this time without the shocker grid. During the cued fear testing session, rats were exposed to 30 or 50 startle-eliciting 95 dB white noise bursts (WNB, noise-only). A background noise of 70 dB was continuously played during the entire session to attenuate extraneous noises. Specifically, the FPS testing session consisted of 10 post-shock 95 dB trials, which served to habituate the rats’ ASR, followed by 20 or 40 trials, half presented with the cue light on (CS+, light-noise) and half with the cue light off (unsignaled, noise-only). 

Fear retraining. After all rats learned to extinguish their cued fear response (see Figure 1.4) as indicated by the lack of a trial type effect when comparing noise-only vs. light-noise trials, all rats underwent cued fear retraining. The retraining consisted of 2 light-shock (CS-US) pairings in the training context. The retraining session was run by the person associated with the training context, and all parameters were kept identical to the initial fear conditioning session. An FPS test session was run 24 hours later to measure cued fear recall following the retraining session. The purpose of examining fear retraining is to understand if social isolation affects the rats’ ability to re-acquire previously extinguished fear memory. In this sense, fear retraining is similar to fear reinstatement. 

Data Analysis 

Startle amplitude, defined as the maximum peak voltage, was measured within the first 200 ms after the onset of WNB. Shock reactivity amplitude was recorded during the fear-conditioning session and was defined as the maximum peak voltage, measured during the 0.5 s foot shock administration. Cued and non-cued fear were calculated as percent change scores of startle amplitude; cued fear = [(light-noise trials – noise-alone trials)/noise-alone

trials] × 100; non-cued fear = [(noise-alone trials – pre-shock trials)/pre-shock trials] × 100. Discrimination scores were calculated as cued fear proportion [light-noise trials/noise-only trials] over non-cued fear proportion [noise-only trials/pre-shock trials]. Scores < 1 signified higher response to non-cued fear, indicative of poor discrimination ability, whereas scores > 1 signified higher response to cued fear, indicative of good discrimination ability. 

All data are presented as mean ± standard error of the mean (SEM). Independent-samples t-tests and mixed-factor analyses of variance (ANOVAs) were used throughout the paper.  When appropriate, all pairwise post hoc comparisons were made using the Bonferroni correction. Statistical analyses were completed using GraphPad Prism version 7 (GraphPad Software Inc., San Diego, CA) and p-values of 0.05 or lower were considered statistically significant. 

 

Experiment 2

Since Experiment 1 only used a sample of 12 rats (6 per condition), Experiment 2 aimed to conceptually replicate the pilot study using a similar design. Our rationale was that a sample size of 12 does not offer enough statistical power to allow making meaningful conclusions. To this end, Experiment 2 abided by nearly identical timing and FPS test session spacing. However, to better understand within-session fear extinction, 50-trial instead of 30-trial FPS test sessions were used in Experiment 2. Additionally, contextual fear was measured in a 50-trial noise-only test session a day after each FPS test to understand the effects of isolation on contextual fear recall. 

 

Methods

In phase one of Experiment 2 (see Figure 1.5), after a week-long acclimation, animals (n=16) were handled for several minutes on two separate days to reduce handling-associated stress. Instead of a 20-minute chamber habituation, all rats underwent two acoustic startle pre-shock sessions on Day 0 and Day 1, where the first pre-shock served to habituate animals to the acoustic startle and was not analyzed, while the second pre-shock from Day 1 represented rats’ baseline response. Rats were split equally into two housing conditions balanced around mean startle amplitude from the second pre-shock, but the housing manipulation took place on Day 4 due to different scheduling. 

In phase two of Experiment 2, on Day 5, all rats were fear conditioned by 10 pairings of a light cue co-terminating with a foot shock 24 hours after social isolation onset. Exactly 24 hours later, on Day 6, all rats’ cued fear recall was tested across 50 trials. On Day 7, all rats were placed in the fear-conditioning context, and their contextual fear was measured by presenting 50 noise-alone trials without any foot shock or light cue trials. Another cued fear testing session took place on Day 10, followed by another contextual fear testing session on Day 11. 

In phase three of Experiment 2, a new acoustic startle pre-shock baseline was measured on Day 19 of social isolation. On Day 20, fear re-training took place by presenting all animals with two pairings of a light cue that co-terminated with a foot shock. Cued fear response was measured on Day 21 across 50 mixed trials, and contextual fear was measured on Day 22 across 50 noise-alone trials. All animals were sacrificed following the last testing session. 

Contextual fear testing

In addition to following the design of Experiment 1 closely, we wanted to understand if social isolation affects contextual fear expression and extinction. Thus, isolated and socially-housed rats were tested for contextual fear on Day 7, Day 11, and on Day 22, at least 24 hours after each cued fear testing session. Like other FPS testing sessions, after one-hour habituation, rats were loaded into ASR chambers. However, to successfully evoke memory of the training environment, we modified three parameters. First, the plexiglass compartments contained shocker grids, which were previously used to deliver foot shocks. Second, the chambers and the shockers were rigorously cleaned with a non-ethanol disinfectant, which was previously used during fear conditioning. Third, the experimenter who previously ran the fear conditioning session also loaded the rats into chambers and ran the session during contextual fear testing.

Unlike during fear conditioning, shocker grids were not active and no light cue was presented, such that the rest of the session was similar to FPS testing sessions. Following a five-minute acclimation period in the chambers, 10 post-shock 95 dB trials that were not analyzed and 40 noise-only trials were presented within 30-second inter-trial intervals to examine the potentiation of the baseline startle in response to the fear conditioning context.  

 

Results

Because Experiment 1 and Experiment 2 abided by a similar design and timing with the exception of 50-trial testing sessions and additional contextual fear testing sessions in Experiment 2, we combined data from both experiments and analyzed them together. This way, we expected to gain statistical power by increasing our sample (n=28). Still, one rat was excluded from all analyses due to flickering light during fear conditioning session, making the total sample size smaller (n=27). Our main hypothesis was that isolated rats would display potentiated FPS (noise-only and light-noise).

Note that only the first 10 light-noise and the first 10 noise-only trials from Experiment 2 were used in this combined analysis to ensure equal testing session length, and that contextual fear could not be analyzed from combined data because Experiment 1 did not include contextual fear testing. 





First FPS Test 

First, we needed to determine whether there were any initial differences in foot shock responsiveness between the socially-housed and isolated rats. Given that the rats were assigned to these conditions in a balanced manner, we did not expect that there would be any differences and, indeed, an independent-samples t-test confirmed that there was no difference in initial foot shock reactivity, t(26) = 0.860, p = 0.398. This finding, displayed in Figure 2.1, provides evidence that 24-hour isolation did not affect shock reactivity, and that our two groups were comparable at the outset. 

Next, we asked whether fear conditioning was successful, anticipating a potentiation of the acoustic startle response in the presence of the light cue (conditioned stimulus, CS+), which has been previously paired with 10 foot shocks (unconditioned stimulus, US). A two-way, mixed-factor analysis of variance (ANOVA) with the independent factor of housing condition (social vs. isolation) and repeated measure of trial type (noise-only vs. light-noise) confirmed that all animals startled significantly more in the light-noise trials compared to the noise-only trials, F(1, 25) = 12.52, p < 0.001, as shown in Figure 2.2.

Knowing that fear conditioning was successful across all animals, we expected the housing condition to affect the potentiation of startle in light-noise trials, but two-way, mixed factor ANOVA with the independent factor of housing condition (social vs. isolation) and repeated measure of trial type (noise-only vs. light-noise) did not detect an effect of condition, F(1, 25) = 0.199, p = 0.660. Similarly, housing condition did not interact with trial type (noise-only vs. light-noise), F(1, 25) = 1.539, p = 0.226. Thus, 48-hour isolation did not affect the potentiation of startle in light-noise trials.

Further, we asked if Pavlovian fear conditioning increased the rats’ responsiveness to the noise stimulus alone (CS-). Indeed, all animals tested in the first FPS session displayed potentiated noise-only startle as evidenced by a two-way, mixed factor ANOVA with independent factor of housing condition (social vs. isolation) and repeated measure of trial type (pre-shock vs. noise-only), F(1, 25) = 11.01, p = 0.003. Together, the above findings provide persuasive evidence for the presence of cued and non-cued fear potentiation of the startle amplitude 24 hours after fear conditioning and 48 hours after isolation onset (see Figure 2.2). 

Since all animals exhibited startle potentiation in noise-only trials, we did not anticipate housing condition to influence this potentiation. A two-way, mixed factor ANOVA with independent factor of housing condition and repeated measure of trial type (pre-shock vs. noise-only) confirmed that no effect of condition was present, F(1, 25) < 0.001, p = 0.985. Similarly, housing condition did not interact with trial type (pre-shock vs. noise-only), F(1, 25) = 0.050, p = 0.825. Thus, 24-hour isolation did not affect the typical FPS potentiation of startle in noise-only trials. 

To determine the effect of housing condition on the recall of noise-only versus light-noise startle, we calculated the percentage of cued fear as noted above. Visible in Figure 2.3, no differences in cued fear between the conditions were detected in the first FPS test session using an independent-samples t-test, t(25) = 0.206, p = 0.839. Similarly, an independent-samples t-test detected no differences between conditions in the percentage of non-cued fear recall, t(25) = 0.098, p = 0.923, illustrated in Figure 2.4. Therefore, in line with the raw data analysis above, 24-hour isolation did not affect the acquisition or recall of cued or non-cued fear during the first FPS test session.

FPS Extinction 

Next, we wanted to know if startle potentiation in light-noise trials persisted in the second FPS test session (extinction). To this end, a two-way, mixed factor ANOVA with independent factor of housing condition and repeated measure of trial type (noise-only vs. light-noise) detected a significant potentiation of startle in light-noise trials, F(1, 25) = 4.756, p = 0.039. This finding, evidenced in Figure 3.1, suggests that all animals remained fear conditioned during the second FPS test session. 

In line with our main hypothesis, FPS was potentiated in the second FPS test. A two-way, mixed factor ANOVA with independent factor of housing condition and repeated measure of trial type (noise-only vs. light-noise) detected a significant interaction of housing condition and trial type was detected, F(1, 25) = 6.919, p = 0.014, but not a main effect of housing condition alone, F(1, 25) = 0.1254, p = 0.726. These results summarized in Figure 3.1 indicate that housing condition affected startle in noise-only and light-noise trials in different ways. To untangle in which direction housing condition affected trial type, we ran a Bonferroni multiple comparisons test across each condition. We found socially-housed animals did not show a difference in startle amplitude between light-noise (M = 291.938, SEM = 49.291) and noise-only (M = 299.915, SEM = 55.021) trials, t(10) = 0.312, p > 0.999. However, isolated animals startled significantly more in light-noise trials (M = 315.936, SEM = 44.418) compared to noise-only trials (M = 230.579, SEM = 39.004), t(10) = 3.467, p = 0.004. This intriguing finding suggests that while social environment may facilitate cued fear extinction over a span of five days—during which rats were presented with a total of 20 noise-only and 20 light-noise trials—continuous isolation over the same period impairs cued fear extinction learning. 

In terms of non-cued startle potentiation, a two-way, mixed factor ANOVA with independent factor of housing condition and repeated measure of trial type (pre-shock vs. noise-only) detected a significant trial type effect, F(1, 25) = 12.790, p = 0.002. Yet, no effect of condition, F(1, 25) = 0.758, p = 0.392, or interaction of condition and trial type, F(1, 25) = 0.918, p = 0.347, was detected. These findings imply that startle potentiation in noise-only trials persisted in the second FPS test session, but that isolation had no impact on noise-only startle amplitude. 

In support of these conclusions, an independent-samples t-test detected a significant difference between the housing groups in their percentage of cued fear, t(25) = 2.156, p = 0.041, demonstrated in Figure 3.2, whereby isolated rats displayed more cued fear (M = 57.76, SEM = 18.49) than socially-housed rats (M = 10.46, SEM = 11.01). However, no difference between groups was observed in terms of their percentage of non-cued fear, t(25) = 0.950, p = 0.351. These findings imply that only cued fear persists in isolated but not socially-housed rats during the second FPS test session, while non-cued fear remains unaffected by housing condition. 

 

Due to the pronounced difference in cued fear extinction learning, we suspected that the rats’ ability to discriminate between the signaled threat cue (CS+) and the unsignaled safety cue (CS-) may differ as a function of housing condition. To this end, we calculated, and in Figure 3.4 graphed, a discrimination index (DI) as described prior. However, an independent-samples t-test did not detect a difference in discriminatory ability between the two conditions, t(25) = 0.913, p = 0.370. In fact, both isolated (M = 2.640, SEM = 0.353) and socially-housed rats (M = 2.139, SEM = 0.425) showed appropriately (DI score above 1.0) enhanced responses to threat versus no cue. This result indicates that both cued and non-cued fear need to be affected in opposite directions in order to influence the rats’ discriminatory ability. Here, all rats discriminated appropriately between the presence of threat and its absence. 

FPS retraining 

After all rats successfully extinguished their cued fear, evidenced by the lack of a trial type (noise-only vs. light-noise) effect, we wanted to know if only two presentations of CS-US pairings (see Figure 3.5) would be sufficient to fear condition rats again. An independent-samples t-test determined that rats did not differ in their shock reactivity during the CS-US pairings, t(25) = 0.239, p = 0.813. In other words, previous fear conditioning and continuous social isolation did not affect rats’ responsiveness to foot shocks. 



We anticipated that two CS-US presentations would be sufficient to re-condition previously-conditioned rats. However, a two-way, mixed factor ANOVA with the factor of housing condition and trial type (noise-only vs. light-noise) did not yield a significant effect of trial type, F(1, 25) = 1.995, p = 0.170, visualized in Figure 3.6. We asked whether the lack of a trial type effect was due to an interaction of trial type and housing condition, but a two-way, mixed factor ANOVA with the factor of housing condition and trial type (noise-only vs. light-noise) did not support this possibility, F(1, 25) = 0.651, p = 0.427. Similarly, no effect of condition was detected, F(1, 25) = 0.146, p = 0.705. These results mean that fear retraining did not work as intended, and that its lack of a trial type effect was not due to the housing condition or due to an interaction of housing condition and trial type. 

We were also curious if non-cued fear potentiation of startle in noise-only trials was affected by fear retraining. To this end, a two-way, mixed factor ANOVA with the factor of housing condition and trial type (pre-shock vs. noise-only) detected a significant effect of trial type, F(1, 25) = 17.92, p < 0.001, reflected in Figure 3.6. However, no effect of condition, F(1, 25) = 0.912, p = 0.349, or interaction of trial type and condition, F(1, 25) = 0.385, p = 0.540, was detected. These findings suggest that non-cued fear startle potentiation may persist for a long time or be affected by retraining; this distinction remains unclear because animals never extinguished their non-cued fear.

In line with the raw data analysis, cued fear percentage did not differ between the groups (see Figure 3.7), as evidenced by an independent-samples t-test, t(25) = 0.235, p = 0.816. Similarly, non-cued fear percentage (see Figure 3.8) did not differ between the groups, t(25) = 0.971, p = 0.341. In this regard, no differences between conditions were observed in terms of cued or non-cued fear, implying that retraining using two CS-US presentations is insufficient to induce either despite the large standard error of the mean variation 

 

Experiment 3

Experiment 3 used a social isolation model like Experiment 1 and Experiment 2, but it sought to understand the contribution of the oxytocin receptor to fear extinction learning. Our hypothesis was that social housing facilitates fear extinction and that oxytocin, a hormone and a neuromodulator underlying social behavior, modulates this phenomenon via oxytocin receptor transmission. To this end, we attempted to acutely block cued fear extinction learning during the first FPS test using a systemic oxytocin antagonist (OTA) drug, L-368-899 (Tocris Bioscience, IL), which crosses the blood-brain barrier.

Studies have previously shown that intraperitoneal administration of L-368,899 (hence referred to as OTA) at 5 mg/kg dose to male rats blocks oxytocin-mediated hippocampal plasticity (Lee, Park, Chung, Kim, … & Han, 2015), induces cannabinoid-withdrawal syndrome (Cui, Bowen, Gu, Hannesson, … & Zhang, 2001), decreases social initiation behavior (Boulet, Cloutier, Ossenkopp, & Kavaliers, 2016), and returns to baseline oxytocin-induced locomotor increase (Klenerová, Krejčí, Šída, Hliňák, & Hynie, 2009), suggesting that 5 mg/kg is a behaviorally potent dose in male rats. Similarly, the studies above demonstrate that behavioral changes can be consistently observed 30-60 minutes post injection.

Notably, Experiment 3 employed a between-subjects 2x2 design of two IVs, each with two levels (IV1: social housing vs. social isolation; IV2: vehicle vs. oxytocin antagonist). Again, the DV of startle amplitude was used to measure the effect of condition and treatment on FPS. As in the first two experiments described above and analyzed together, two experiments involving systemic OTA injections were conducted. The combined data from Experiment 3 and Experiment 4 are analyzed below to increase statistical power needed to detect meaningful differences. 

Methods

In phase one of Experiment 3, rats (n=24) arrived and were allowed to acclimatize to the housing facility for one week (see Figure 4.1). All rats were housed in trios at this time. On the next day, all rats were handled for several minutes using a dummy syringe (that lacked a needle) to accustom them to receiving intraperitoneal (IP) injections. This procedure was repeated on the following day, except all 24 rats were administered saline using a syringe with a needle (0.2 ml, IP). On Day 0, a mock simulation of drug administration took place, whereby all rats were injected with saline (0.2 ml, IP) in a time-sensitive manner, habituated for 60 minutes, and loaded into SR-LAB chambers for a 20-minute habituation without any stimulation or recording. On Day 1 of social isolation, rats’ pre-shock startle baseline was measured and animals were split equally into 4 groups of 6 rats, balanced around their mean startle amplitude: 1) social housing + vehicle; 2) social housing + OTA; 3) social isolation + vehicle; 4) social isolation + OTA. On Day 2, all rats were fear conditioned by 10 pairings of a light cue (CS) co-terminating with a foot shock (US). 

In phase two of Experiment 3, at least 24 hours after fear conditioning, rats were brought to the habituation room, where they were previously handled, and they were weighted and administered IP either sterile double-deionized water (ddH2O) or OTA (dissolved in ddH2O at concentration of 5 mg/kg/ml). Next, all rats were left to habituate for 60 minutes, at the end of which they were tested for FPS during a 30-trial session on Day 3. Next, on Day 5 and Day 8, cued fear recall was tested again.

 

Experiment 4

Experiment 4 used a similar design as Experiment 3 to allow for their data to be combined and analyzed together. The drug administration procedure and testing parameters were kept identical Experiment 3 with the exception of a longer interval between the 2nd and 3rd FPS test sessions in Experiment 4. Our main hypothesis was that an acute oxytocin receptor blockade would impair cued fear extinction learning in socially-housed rats. 

Methods

A replication of Experiment 3 using 24 male rats was conducted in the same manner as described above. The OTA injection took place at least 24 hours after fear conditioning, and all animals were tested for FPS 60 minutes post injection. However, the second FPS test took place on Day 7 (instead of Day 5) and the third FPS test took place on Day 15 (instead of Day 8) due to logistical issues. 

Results

Using data combined from Experiment 3 and Experiment 4, shock reactivity was determined to be comparable between social rats in the vehicle condition (SOC-VEH, n=12), social rats in the OTA condition (SOC-OTA, n=12), isolated rats in the vehicle condition (ISO-VEH, n=12), and isolated rats in the OTA condition (ISO-OTA, n=12) as seen in Figure 5.1. A two-way, mixed factor ANOVA with the independent factors of treatment and condition determined that there was no difference between the groups in terms of condition, F(1, 44) = 1.476, p = 0.231). Similarly, no effect of treatment was found, F(1, 44) = 0.772, p = 0.384, because no treatment was administered. Therefore, all groups of rats displayed comparable shock reactivity at the outset of the experiment despite the 24-hour isolation. 







First FPS Test  

To check if all groups of rats have been fear conditioned (see Figure 5.2), and if the OTA drug acutely affected fear recall, a three-way, mixed factor ANOVA with the independent factors of treatment (vehicle vs. OTA) and housing condition (social vs. isolation) and repeated measure of trial type (noise-only vs. light-noise) was run. A trend toward significance was detected in terms of trial type between noise-only and light-noise trials, F(1, 88) = 3.404, p = 0.068, and no effect of treatment was detected, F(1, 88) = 0.114, p = 0.736. Unexpectedly, rats were not fear conditioned during the first FPS test session, and, as anticipated, OTA did not acutely affect light-noise startle, F(1, 88) < 0.001, p = 0.995.

 

To see if housing condition or OTA acutely affected noise-only startle potentiation, a three-way, mixed factor ANOVA with the independent factors of treatment (vehicle vs. OTA) and housing condition (social vs. isolation) and repeated measure of trial type (pre-shock vs. noise-only) only detected (see Figure 5.3) a significant effect of trial type, F(1, 88) = 8.497, p = 0.005. As anticipated, OTA did not affect noise-only startle, F(1, 88) < 0.001, p = 0.999.

Based on the raw data analysis above, we did not expect cued fear percentage to be affected by either housing condition or treatment at this time point, and a two-way ANOVA with the independent factors of treatment and condition did not detect an effect of condition, F(1, 44) = 0.188, p = 0.667, and it did not detect and effect of treatment, F(1, 44) = 0.137, p = 0.713. Even though raw data analysis evidences that rats startled more in noise-only trials, non-cued fear percentage was not affected by condition, F(1, 44) = 0.044, p = 0.835, or by the treatment, F(1, 44) = 1.571, p = 0.135. These results in Figures 5.4 and 5.5 further suggest that neither 24-hour isolation nor 5 mg/kg OTA administered systemically 60 minutes prior to fear recall affected FPS. 




FPS Extinction 

Since not all rats were fear conditioned when their fear memory was the strongest (24 hours after fear conditioning), we did not expect in Figure 5.6 to detect a trial type effect in light-noise trials relative to noise-only trials. Indeed, a three-way, mixed factor ANOVA with the independent factors of treatment (vehicle vs. OTA) and housing condition (social vs. isolation) and repeated measure of trial type (noise-only vs. light-noise) did not find an effect a trial type, F(1, 88) = 0.599, p = 0.441. 

Notably, no main effects of condition, treatment, or interaction were detected despite previous evidence of impaired cued fear extinction in isolated rats specifically at this time point. Still, we highlight the results of these analyses. The lack of previously observed interaction between trial type and housing condition at this time point surprised us, F(1, 88) = 2.032, p = 0.158. We therefore considered if an effect of treatment underlies the lack of interaction. Because we attempted to manipulate the outcome of the oxytocin receptor in cued fear extinction learning, which started with the first FPS test session, we expected to find an effect of treatment in the second FPS test session. Contrary to our expectations, a three-way, mixed factor ANOVA with the independent factors of treatment (vehicle vs. OTA) and housing condition (social vs. isolation) and repeated measure of trial type (noise-only vs. light-noise) did not detect a main effect of the OTA drug, F(1, 88) = 0.079, p = 0.780, or of any interactions. 

Interestingly, although we have previously shown the persistence of non-cued FPS, a three-way, mixed factor ANOVA with the independent factors of treatment (vehicle vs. OTA) and housing condition (social vs. isolation) and repeated measure of trial type (pre-shock vs. noise-only) did not detect a trial type effect in noise-only trials, F(1, 88) = 2.788, p = 0.099, or an effect of interaction. Together, these results highlighted in Figure 5.7 suggest that all rats have by the end of the 2nd FPS test session extinguished both light-noise and noise-only startle potentiation, and that OTR blockade during the first recall of fear does not affect subsequent fear extinction. 

However, in line with the previously observed cued fear extinction learning deficit in isolated rats, we found a difference in the percentage of cued fear (see Figure 5.8) expressed during the second FPS test session. A two-way ANOVA with the independent factors of treatment and housing condition detected a significant main effect of condition, F(1, 44) = 0.437, p = 0.049, providing additional evidence of differential cued fear extinction between isolated and socially-housed rats. Because no difference between conditions was detected in the percentage of non-cued fear (see Figure 5.9) using a two-way ANOVA with the independent factors of treatment and housing condition, F (1, 44) = 0.019, p = 0.889, the extinction learning impairment is specific to cued fear. This important finding replication indicates that the effect of housing condition on cued fear extinction can survive an acute blockade of OTR during fear the first fear recall. 

To look at cued fear dynamics over time, we split the second FPS test session into two halves (see Figure 6.0) and calculated trial-to-trial cued fear percentage change between the first five and the second five trials. A three-way, mixed factor ANOVA with the independent factors of housing condition and treatment and a repeated measure of cued fear percentage change detected a significant main effect of housing condition, F(1, 88) = 6.036, p = 0.016, but not an effect of time, F(1, 88) = 0.873, p = 0.353. This finding implies that cued fear extinction did not change throughout the second FPS test session. Rather, isolated and socially-housed rats in the second FPS test session displayed significantly different rates of cued fear. 

Due to the robust difference in cued fear between the housing conditions, we thought that the rats’ discriminatory index scores may be affected (see Figure 6.1). However, a two-way ANOVA with the independent factors of treatment and housing condition did not detect an effect of condition on the DI, F(1, 44) = 0.780, p = 0.382. A closer look at the DI illustrated that SOC-VEH (M = 1.059, SEM = 0.233), SOC-OTA (M = 1.123, SEM = 0.228), ISO-VEH (M = 1.107, SEM = 0.186), and ISO-OTA (M = 1.530, SEM = 0.352) all responded similarly (~1.0) to threat and the absence of a cue. 

FPS Extinction 2

To observe the long-term consequences of the OTA drug on cued fear (see Figure 6.2), we conducted a third FPS test session. A two-way ANOVA with the independent factors of treatment and housing condition and repeated measure of trial type (noise-only vs. light-noise) did not detect an effect of trial type, as expected, F(1, 88) = 0.027, p = 0.869. A two-way ANOVA with the independent factors of treatment and housing condition and repeated measure of trial type (pre-shock vs. noise-only) did not detect an effect of trial type either, F(1, 88) = 2.630, p = 0.108, illustrated in Figure 6.3. These results indicate that all rats extinguished cued and non-cued fear by the start of the third FPS test session.

To confirm this conclusion in terms of calculated cued fear, shown in Figure 6.4, a two-way ANOVA with the factors of housing condition and treatment did not detect an effect of condition, F(1, 44) = 0.440, p = 0.511, and it did not detect an interaction of treatment and condition, F(1, 44) = 1.637, p = 0.207. However, for non-cued fear, a two-way ANOVA with the factors of housing condition and treatment detected a weak trend toward significance in terms of treatment by condition interaction, F(1, 44) = 3.067, p = 0.087. 

This non-significant trend visible in Figure 6.5 suggests that the housing condition may differently affect treatment outcomes, such that social rats that received vehicle injection show greater non-cued fear (M = 60.015, SEM = 58.833) than social animals that received the OTA drug (M = -16.262, SEM = 8.632). On the other hand, isolated rats that received a vehicle injection exhibit diminished non-cued fear (M = -26.015, SEM = 9.908) compared to isolated rats injected with the OTA (M = 7.126, SEM = 16.429). Together, these findings suggest that an acute OTR blockade during the first fear recall may have long-term effects on non-cued fear recall and non-cued fear extinction. 

Discussion

We found that while social environment does not affect fear acquisition or fear recall, lack of social interaction impairs fear extinction. Our combined data suggested that unlike socially-housed rats, rats living alone may require twice as many extinction opportunities to learn that a conditioned stimulus (CS+) no longer predicts danger. Further, we reported that once all rats fully extinguish their fear memory, social environment does not play a role in their re-acquisition of fear to a CS+. Last, we provided persuasive evidence that the oxytocin receptor, which exclusively binds oxytocin, a hormone and neuromodulator involved in social behavior and cognition, does not affect fear recall and subsequent extinction regardless of social environment. 

Effect of Social Isolation on FPS

The purpose of Experiments 1 and 2 was to examine the effects of social isolation on fear and anxiety using FPS. In contrast to previous studies detecting behavioral, cognitive, and molecular consequences of acute (2-24 hour) social isolation in rodents (Leser & Wagner, 2015; Maisonnette et al., 1993; Matthews et al., 2016; Shahar-Gold & Wagner, 2013), 24-hour isolation did not affect FPS acquisition and 48-hour isolation did not affect FPS recall. Therefore, we did not find support for our initial hypothesis that social isolation potentiates FPS. 

Instead, Experiments 1 and 2 indicated that during the second FPS test session (extinction), isolated rats continued to display FPS while socially-housed rats extinguished their FPS over the same number of testing trials. This fascinating result suggests that social housing facilitates cued fear extinction learning, that social isolation impairs cued fear extinction learning, or both. The experimental design made it impossible to dissociate the contribution of the two potential effects, although support for both possibilities exists. It is noteworthy that rats remain socially engaged throughout their lives, and that fear extinction evolutionarily occurs within a social environment, such that it may be more salient to view the present finding in terms of isolation-induced learning impairment because our social housing condition did not enrich social environment beyond what the rats were accustomed to. 

In support of our findings, Skelly et al. (2015) isolated adolescent (PND 28) rats for 6 weeks, re-housed them, and tested them in the elevated plus maze (EPM) and in the open field test. Then, the previously-isolated rats’ acquisition and extinction of FPS were tested. Remarkably, while Skelly et al. found that previously-isolated rats acquired cued fear comparably to socially-housed rats, a sequence of three extinction sessions revealed that isolated (but not socially-housed) rats suffer from impaired cued fear extinction learning. This result contextualizes the presently observed learning deficit, indicating that both 6 weeks of prior (adolescent rat) and 5 days of parallel (adult rat) social isolation remarkably produced a similar extinction learning impairment. In the absence of a distinct social enrichment condition, Skelly et al. (2015) also argue that the observed difference in fear extinction must be isolation-induced. 

Experiments 1 and 2 also set out to test whether rats’ social environment affected their ability to reinstate (or reactivate) fear memory. Rather than reinstating fear using only the unconditioned, aversive foot shock itself, we exposed each rat to two CS-US pairings, more akin to FPS retraining than reinstatement. We found that two CS-US presentations were insufficient in retraining rats to fear the CS+, and that housing condition did not affect how rats re-acquired or recalled FPS. Clinically, the phenomenon of context-specific reinstatement represents a mechanism of symptom exacerbation in anxiety and PTSD patients caused by re-exposure to trauma-like stimuli (Cannistraro & Rauch, 2003; Lin, Tseng, Mao, Chen, & Gean, 2011; Norrholm, Jovanovic, Vervliet, Myers, & Duncan, 2006). Here, we showed that up to 17 days of social isolation did not affect cue-specific reinstatement of fear (retraining) in adult male rats. 

Similar to the null effect of social isolation on cued FPS recall, we did not detect any effects of housing condition on non-cued FPS in Experiments 1 and 2. Since non-cued fear is contingent upon prior exposure to CS+ after fear conditioning is acquired, non-cued fear may therefore represent a more diffuse, generalizable component of cued fear (Dunsmoor & Paz, 2015). Put differently, non-cued fear corresponds to hypervigilance associated with an anxiety-like state, also known as background anxiety (Missig et al., 2010). Since 2- or 24-hour isolation has been shown to acutely elevate anxiety-like behavior of adult male rats in the EPM (Maisonnette et al., 1993), the present lack of non-cued fear startle potentiation after 48-hour (or longer) isolation came as a surprise. The discrepancy between the acute consequences of social isolation on anxiety-like behavior in the EPM compared to the lack thereof in the FPS may point to a ceiling effect of the traumatic process of fear conditioning. Notably, the necessity of CS+ exposure to trigger non-cued (CS-) fear suggests that, unlike some types of anxiety, non-cued fear has an active generalization learning component. Still, rats regardless of condition never learned to extinguish their non-cued fear in Experiments 1 and 2, hinting at the persistence of non-cued fear (see this in contrast to Experiments 3 and 4, where possibly unsuccessful fear conditioning resulted in non-cued fear extinction).  

Importantly, the present lack of CS- startle potentiation in isolated, adult male rats (post-60 PND) contrasts with the findings of a similar study done by Rosa et al. (2005), although several caveats should be noted. Rosa et al. (2005) isolated young adult males (40 PND) for 10 days and fear conditioned them similarly to our paradigm, using 10 CS-US presentations. Twenty-four hours after fear conditioning, previously-isolated rats exhibited potentiated startle in noise-only trials compared to the group-housed rats’ noise-only startle. Thus, the effect of social isolation was measured between-subjects and not relative to the isolated rats’ pre-shock stress reactivity, obscuring any initial variance between the experimental groups. While Rosa et al. (2005) did not habituate the rats’ startle response at the outset of the FPS test session, they conducted a longer, 60-trial test session. Rosa et al.’s (2005) findings suggest that early adult rats previously isolated for 10 days, once fear conditioned, startle more in the absence of a CS+ than group-housed rats. However, it may be that their group-housed rats would have exhibited noise-only startle potentiation if compared to a within-subjects pre-shock baseline. 

In fact, Rosa et al. (2005) calculated differences (noise-only vs. light-noise) in startle amplitude, but found them not to differ between housing conditions, implying that rats assigned to the isolation condition may have been initially more stress reactive than socially-housed rats. In contrast to Rosa et al. (2005), the present study suggests that continuous isolation lasting up to 16 days does not affect non-cued fear relative to pre-shock baseline or compared to socially-housed rats’ non-cued fear.  

Role of the Oxytocin Receptor in Fear Extinction 

Experiments 3 and 4 together aimed to examine how the oxytocin receptor (OTR), if at all, affected cued fear extinction learning. To this end, we globally blocked OTR during fear recall and initial fear extinction learning in the first FPS test session. Still, the oxytocin antagonist (OTA) drug may have also affected the onset of extinction memory consolidation due to its absorption profile in male rats (discussed later). We expected to block oxytocin’s (OT) contribution to fear extinction learning specifically in socially-housed rats, which have previously displayed more effective fear extinction compared to isolated rats.  

We found that global OTR blockade did not acutely affect FPS in socially-housed or isolated rats as shown in the first FPS test session. This negative finding helps qualify the results of a study done by Missig et al. (2010), who systemically administered synthetic oxytocin (0.1 µg, subcutaneously) before fear recall and found that it attenuated non-cued fear but not cued fear in fear-conditioned rats. Missig et al. (2010) also found that compared to non-stressed rats, fear-conditioned rats given exogenous oxytocin (0.1 µg, subcutaneously) startled less in all trial types. Another study demonstrated the involvement of OT in fear extinction (Toth et al., 2012a) by infusing OT intracerebroventricularly (1.0 µg, ICV) into the cerebrospinal fluid before fear recall and observing impaired fear extinction in OT-infused rats. However, in line with the present study, Toth et al. (2012a) failed to detect an effect of intracerebroventricularly blocking OTR prior to fear recall. Taken together, these results indicate that acute OTR blockade in peripheral, central, or peripheral and central nervous systems has null effects on fear recall or fear extinction. On the other hand, exogenous OT administration attenuates non-cued fear and impairs fear extinction. 

The contrast between anxiety-attenuating effects of synthetic (exogenous) OT and null effects of OTR blockade suggests that OT produced in male rats (endogenous) may not be involved in fear extinction. Alternatively, intracerebroventricular and systemic modes of drug administration may, via brain-specific OTR binding, produce contrasting effects that fail to yield an overall net effect. Consider that synthetic OT infusion (0.1 µg) into the infralimbic (IL) cortex or the basolateral nucleus of amygdala (BLA) prior to fear recall both enhanced fear extinction 24 and 48 hours later, but that OT infusion into the central nucleus of amygdala (CeA) had null effects on fear extinction (Lahoud & Maroun, 2013). In contrast, OT infusion into the BLA prior to fear conditioning increased cued fear recall during testing (Lahoud & Maroun, 2013). Therefore, it is likely that global OT manipulations (such as the one in the present study) lack the specificity needed to examine brain-specific effects on fear extinction.

Returning to the present study, the absence of a trial type effect (p = 0.068) between noise-only and light-noise trials in the first FPS test session is puzzling and needs to be addressed. Fear recall is typically robust 24 hours after fear conditioning unless memory consolidation is disrupted. For instance, the first fear recall test in non-stressed rats tends to yield 50-60% cued fear potentiation of the noise-only startle response (unpublished data; Davis et al., 2010). Here, OTA-injected rats displayed sub-40% cued fear potentiation, possibly contaminating an otherwise detectable effect of fear conditioning on trial type. Notable is also the high standard error of the mean in Figure 5.4, which could be explained by the uneven distribution of poorly (18 rats) and highly (8 rats) stress-reactive rats as determined by pre-shock ASR (not shown). Relevantly, Moaddab and Dabrowska (2017) previously found that rats with low pre-shock startle ASR, when injected with OTA into the dorsolateral BNST (200 ng, (d(CH2)51, Tyr(Me)2, Thr4, Orn8, des-Gly-NH92)-vasotocin) prior to fear conditioning, displayed significantly reduced cued fear. Thus, while it may be that the memory consolidation process was in fact disrupted or that the fear conditioning session did not work as intended, there is a possibility that the treatment manipulation, though nonsignificant upon combined analysis, interfered with fear recall in socially-housed, OTA-injected rats, or that an external stimulus disrupted the FPS testing. 

Similar to the first FPS test session in Experiments 3 and 4, we did not find differences in treatment, condition, or condition × treatment interaction in the second FPS test session (extinction). Briefly, we hypothesized that oxytocin underlies fear extinction facilitation in socially-housed rats and that OTR blockade during initial fear recall would impair fear extinction in socially-housed (but not isolated) rats. Instead, we found that OTA had null effects on FPS (both cued and non-cued fear) in male rats tested for fear extinction. The lack of a treatment effect argues that the net effect of fear extinction was not modulated by OTR. Convincing evidence in support of the null hypothesis also comes from a successful replication of isolation-induced cued fear extinction impairment (previously observed during the second FPS test session in Experiments 1 and 2) despite the pharmacological intervention. Interestingly, this pivotal result was detected even though all the rats extinguished both cued and non-cued fear to the extent that trial type (pre-shock vs. noise-only) no longer differed significantly. The difference in the rate of fear extinction learning between housing conditions was not reflected in the rats’ discriminatory index, although isolated rats seemingly responded more strongly to CS+ trials, as would be expected based on their persisting cued fear. In this light, there is the possibility that fear conditioning in fact worked—otherwise a difference in extinction learning could not be observed—but that something interfered with the first FPS testing session.

The lack of a treatment effect in previously-injected rats is interesting because some evidence suggests that a single dose of OT or OTA can produce long-term consequences. Specifically, one study (Klenerová, Krejčí, Šída, Hliňák, & Hynie, 2009) administered systemically a smaller dose of the same OTA (1 mg/kg, L-368,899) in non-stressed, adult male rats and found null effects of drug on acute locomotor activity in the open field test. However, when rats previously injected with OTA were re-tested 2 days later, their total movement distance significantly differed from previously saline-injected rats. This result suggests that the OTR system may be highly plastic and that globally blocking OTR can have delayed or long-lasting locomotor consequences. Furthermore, when OT (0.05 mg/kg) and OTA were injected in parallel, then OTR acutely blocked OT-induced locomotor activity increase (Klenerová et al., 2009). But, when re-tested 2 days later, rats previously given an OT and OTA cocktail saw their locomotor activity resemble that of previously OT-injected rats. These findings imply that both OT and OTA enhance locomotion, but it should be noted that FPS is a reflexive phenomenon and unlikely to be affected by general locomotion ability. Further, when OT and OTA are injected in parallel, only the OT-induced effects on locomotion persist, suggesting contrasting short-term versus long-term consequences of systemic OTA injection.

Although non-cued fear was not significantly affected by either treatment or condition in the second FPS test session, the differential housing condition × treatment trends were suggestive of an interaction (see Figure. 5.9). To better understand how non-cued fear may change as a result of treatment and condition, the second FPS test was split into first 5 and second 5 trials, which were then compared. Effect of time was absent, indicating that non-cued fear did not change significantly throughout the second FPS testing session. Yet, isolated rats displayed overall greater non-cued fear, indicative of an anxiety-like state during the second FPS test session. 

In fact, during the third FPS test session, a trend toward significance in terms of condition × treatment interaction was discerned. Socially-housed, previously OTA-injected rats showed diminished non-cued fear compared to vehicle-injected rats. On the other hand, isolated rats previously injected with OTA exhibited stronger non-cued fear compared to vehicle-treated rats. These findings, together with the lack of a difference in cued fear in the third FPS test session, propose that non-cued fear extinction learning may be under the sensitive control of OTR depending on the rats’ social environment. This line of evidence expands on the key finding that OT can acutely attenuate non-cued fear in fear-conditioned animals (Ayers, Agostini, Schulkin, & Rosen, 2016; Ayers, Missig, Schulkin, & Rosen, 2011; Missig et al., 2010). 

Limitations

Failure to detect an effect of fear conditioning in the first FPS test session in Experiments 3 and 4 raises questions about the effect of OTA on fear memory consolidation and cued fear recall and the reliability of the fear conditioning apparatus. A recalibration of all the startle response chambers was conducted between Experiment 3 and Experiment 4, upon which the analog-digital signal curve was adjusted, thereby slightly decreasing the acoustic startle stimulus volume to the regular 95 dB. Previously, chambers were producing startle-eliciting stimuli closer to 105 dB, and the small change in volume may have affected FPS recall. In other words, rats in Experiment 1 and 2 display high FPS perhaps due to individual variation but also due to being presented with a louder acoustic stimulus. We have found that the plexiglass cylinders attenuate sound volume by additional 5-10 dB, possibly explaining how such a minute difference in volume may have affected the FPS results in Experiment 4. Before a replication of fear conditioning in isolated and OTA-injected rats is done, a proper calibration should precede each experiment, such that the testing parameters are documented and kept constant across testing sessions. Last, there is always the possibility of an acute stress interference (e.g., loud noise, strong perfume) during the first FPS test session, which in theory may have impaired proper fear recall at least during some testing trials. 

Not having tested the effects of social isolation and OTR blockade in female rats limits this study’s generalizability, for we cannot make conclusions regarding the role of OT in isolated females in terms of FPS. Further, the effect of L-368,899 was not validated, complicating unresolved questions about how the dosage, timing, and method of administration could affect FPS. Validating the OTA drug is pertinent because in our case it has been accidentally stored at 4°C instead of -20°C for a period of two weeks. However, the drug was still in lyophilized (freeze-dried) powder form (i.e., not diluted and thus less reactive) when this issue was discovered, and a representative from Tocris Bioscience suggested that improper storage should not have a major impact on the drug pharmacokinetics.

In terms of smaller discrepancies, the design timelines between experiments were not always kept identical due to logistical difficulties, which may have introduced additional variation within our data. Further limitations include not measuring endogenous markers of the stress response or of the rats’ immune response (Scotti, Carlton, Demas, & Grippo, 2015), both of which have implications for hippocampal activity and memory (Slavich & Irwin, 2014; Todorović & Filipović, 2017). A possibly easy solution to measuring stress in another way would be to quantify the rats’ defecation rate, which positively correlates with acute stress (Blizard, Eldridge, & Jones, 2015). Of note is also the fact that in Experiments 1 and 2, control rats were housed in pairs and trios, whereas in Experiments 3 and 4, all control rats were in trios, possibly resulting in different degrees of social buffering and social interaction. Last, the possibility that socially-housed rats to some extent socially transmitted conditioned fear amongst each other (unlike isolated rats) cannot be excluded, since rats have been found to communicate information about threats and rewards (Masuda, Narikiyo, Someya, & Aou, 2013), such that they can acquire social anxiety-like behavior by observing another rat’s fear response (Toth, Neumann, & Slattery, 2012b). But because all rats were fear conditioned in the same manner, and no significantly enhanced fear in socially-housed controls was observed, the consequences of social transmission of fear may be negligible.

Future Studies

One way in which the question of OT’s contribution to cued fear extinction learning could be expanded upon is by administering OTA right before the second FPS test session (extinction) to examine if OTA acutely affects the isolation-induced cued fear extinction impairment. Having manipulated the OTR system both during the initial fear recall (in which fear extinction first takes place), it remains to be seen whether OTR plays a role in fear extinction in the second FPS. This manipulation may help elucidate the contribution of isolation-induced learning impairment compared to the social facilitation of fear extinction and social buffering. This question remains relevant in the light of Rosa et al. (2015) findings, particularly since social environment has been found to buffer against stress (Kiyokawa, Hiroshima, Takeuchi, & Mori, 2014) and since the presence of a conspecific facilitates fear extinction learning through cortical OT transmission (Brill-Maoz & Maroun, 2016). However, increasing the OTA dose and reducing the interval between the injection and FPS testing should be considered in order to achieve the most efficacious OTR blockade. Further, testing whether OTA produces effects in a dose-dependent manner would clarify if the present dose (5 mg/kg) is too low given its administration 60 minutes prior to loading the rats into testing chambers.

Regarding the possible interference of OTA in fear memory consolidation after the first FPS test session, it should be noted that the drug’s half-life is between 78 and 108 minutes in male rats given 2.5 and 10 mg/kg (intravenous, IV), respectively (Thompson, Vincent, Miller, Colletti, & Chiu, 1997). Thus, the drug likely affected the onset of extinction memory consolidation. Therefore, it is be pertinent to modify the time point and the drug dose to only affect fear extinction. 

Relevant to testing the dose-dependent effects of OTA is conducting a validation that the drug in fact works as intended, since no treatment effects were observed in the present study. The most elegant validation experiment would consist of administering OTA to wildtype rats and to rats that are deficient in OT due to having the OT gene knocked out. The expectation would be that no effect of drug on social interaction would be observed in the OT-deficient animals in contrast to the wildtype animals. However, the only OT knockout models currently available are mouse models (Mantella et al., 2003). 

Therefore, we instead propose to inject two groups of socially-housed rats with saline or OTA and perfuse the rats 90 minutes post injection. Then, we would run immunohistochemistry protocol to double-label OT-immunoreactive cells and a neuronal marker of transcription activity, such as c-Fos, which is sensitive to changes taking place in a 90-minute timeframe. We would expect that OTA-injected rats would show little to no colocalization of OT-immunoreactive cells with the c-Fos antibody signal, and, conversely, that saline-injected rats would show normal levels of OT neuronal activity. The underlying assumption is that OT cells express OTR even though OT cells are not the only ones that do. In this sense, the OTA could be injected in parallel with an OT agonist or synthetic OT, where the OT-induced effect should be blocked by simultaneous OTR administration, and more satisfactory results could be obtained.

Limited evidence from the present study indicates that the social facilitation of fear extinction or the isolation-induced extinction impairment may occur between FPS test sessions, judging from the lack of an effect of time when analyzing within-session cued fear extinction. Therefore, it would be relevant to isolate rats for an extended period of time (1-2 weeks) following fear conditioning without testing them during this period. Instead, assuming that the fear conditioning protocol worked sufficiently, all rats would be tested for fear recall after the cessation of isolation. The goal of this “incubation” of fear memory experiment would be to examine whether social environment-dependent facilitation or impairment of cued fear memory extinction takes place without explicit exposure to the CS+ and CS-. Additionally, this experiment would examine whether housing condition affects fear generalization prior to CS+ presentation. Our expectation would be that without the opportunity to extinguish cued fear, cued fear recall should remain strong regardless of housing environment.

Related to the suggested experiment above, it would be intriguing to examine how social environment affects specifically fear extinction learning consolidation. To this end, rats would be kept in isolation or social housing as described in the experiments above. However, immediately after the end of the first FPS testing session, rats’ housing conditions would be switched (isolation to social housing and vice versa) to understand how acute re-socialization compared to acute isolation affect fear extinction consolidation. To control for both manipulations, two groups of rats would remain in their respective (isolation or social housing) conditions throughout the consolidation period. Days later, all rats would be tested for fear extinction over several FPS test sessions, although the familiarity of pairs to be re-socialized should also be controlled. 

Last, and perhaps most essentially in terms of generalizing the present results and increasing their external validity, all of the reported procedures need to be replicated using female rats to understand why females are more prone to psychosocial stressors (Alonso et al., 2004) and if oxytocin plays a role in isolation-induced vulnerability and fear-learning. 

In conclusion, the present study attempted to explore the effects of social environment on fear memory using the fear-potentiated startle paradigm in male rats. To our knowledge, this is the first study to employ continuous social isolation in adult male rats and to measure its effect on fear memory using FPS. We found that while social isolation compared to social housing did not enhance FPS, it consistently impaired fear extinction learning in a time-dependent manner. This finding has relevant implications to the way GAD, PTSD, and phobias are treated in humans, suggesting that a social environment may facilitate, for instance, exposure therapy and learning. On the other hand, relatively short social isolation could impair attempts to extinguish fear and traumatic memories. To understand the mechanism behind the isolation-induced learning impairment, we explored how the oxytocin receptor contributes to fear extinction learning. We reported that a global blockade of the oxytocin receptor did not affect fear extinction learning even though some trends toward statistical significance suggest that oxytocin reception may in fact be involved in acute cued fear attenuation and in non-cued fear modulation, in line with literature findings. This study’s major limitations involve relying on a systemic manipulation of OTR that may not be specific enough to yield a meaningful net effect, and the inability to make generalizations about social isolation in females. To remedy these concerns, we proposed a number of future directions and identified salient research questions beyond the scope of this study.

As the global epidemic of loneliness continues to exacerbate, the present study calls for more research to be done in social isolation and learning to further elucidate how being isolated affects brain and behavior. Due to the lack of causal evidence about how precisely our repeated exposure to novel technologies (and its associated lack of face-to-face social interaction)—and given the rapid pace of technological evolution, globalization, and digitization of our lives—the specific consequences of our lifestyle changes are difficult to predict. With much yet to be known, we argue, the loneliness epidemic should not be taken lightly.

 

 

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