Unlike women, when the possibility of an illicit relationship exists, men are quicker to assume that

This review discusses alcohol/other drug addiction as both a sociocultural and biological phenomenon. Sex differences and gender are not solely determined by biology, nor are they entirely sociocultural. The interactions among biological, environmental, sociocultural and developmental influences result in phenotypes that may be more masculine or more feminine. These gender-related sex differences in the brain can influence the responses to drugs of abuse, progressive changes in the brain after exposure to drugs of abuse and whether addiction results from drug-taking experiences. The basic laboratory evidence for sex differences in addiction is discussed within the context of four types of sex/gender differences.

Keywords: Addiction, Animal Models, Sociocultural Influences, Gender, Sex Differences

The theme of this special issue is sex differences in the brain. This article will discuss the topic of gender and sex differences in drug addiction, our field of study, but there are similar gender and sex differences in compulsive behaviors such as gambling (Potenza et al. 2001; Blanco et al. 2006). We define addiction as the chronic, compulsive use of a substance or engagement in a behavior, regardless of negative consequences. We use sex to refer to the characterization of an individual as female or male from biological and morphological features. As discussed below, there are similar sex differences in humans and rodents in addiction or addiction-like behaviors (respectively). This suggests that there are some basic biological differences between females and males that influence how each responds to drugs of abuse and engage in addictive behaviors (Becker et al. 2012; Perry et al. 2013b; Carroll and Anker 2010; Lynch 2006; Kerstetter et al. 2012; Becker and Hu 2008).

Gender is defined as a system of social organization with a set of behavioral prescriptions that are believed to follow from biological sex characteristics. These perceptions of gender are socially constructed and shaped by sociocultural structures and processes over time (Fausto-Sterling 2012). Researchers in the social and natural sciences have demonstrated that addictions and consequences of addictions differ by biological sex and also by gender (Becker et al. 2016). A thesis of this article is that gender and sex differences in addiction are a complicated interaction between sociocultural factors and neurobiological sex differences.

Unfortunately, reports of “sex differences in the brain” means to many people who are not neuroscientists that male and female brains are “hard-wired” to be different from each other. In addition, the conceptualization of addiction as a “brain disease” contributes to the belief that some people’s brains make it almost inevitable that they will become addicts (Meurk et al. 2016; Hall et al. 2015; Johnson et al. 2015). When a scientist describes findings of sex differences that result in women becoming addicted more rapidly than men (Anglin et al. 1987), for example, many non-scientists assume that there is nothing anyone can do to change this. While it is likely that some individuals are more vulnerable for addiction, as will be discussed below, it is not an inevitable outcome that a vulnerable person will necessarily become an addict. Additionally, for many people the label of ‘brain disease’ strips them of their agency, so they fail to take responsibility for their addiction (Wiens and Walker 2015). Neuroscientists understand that the human brain is not “hardwired”, but it is rare that the nuances are conveyed to the public by the popular press. It is important to do so. Scientific findings need to be presented in a way that does not attribute sex differences in addiction entirely to the brain, and this message conveyed to the media as well. This idea will be revisited at the conclusion of this article.

A third goal for this article is to address a conclusion of an article by Vidal et al (2012), that “The challenge is not to deny that there are brain differences between the sexes, but to find out their origin and to assess their significance in real-life situations” (p. 301). This article discusses reports of “brain, sex and gender” by scientists and the subsequent popular reports. Both scientists and the lay audience may not dissociate the differences between mechanisms mediating biological sex differences (the meaning here is the hormone/genetic-driven differences between males and females) vs. cognitive sex differences (differences between males and females in fMRI images while performing cognitive tasks) (Vidal 2012). These two types of sex differences differ in the extent to which they may be modified by environmental and sociocultural factors, with cognitive sex differences being affected to a greater extent by learning.

First, some evidence for sex differences in addiction, in both animals and humans will be briefly reviewed. This has been the topic of a number of detailed reviews recently (Becker and Koob 2016; Carroll and Lynch 2016; Perry et al. 2016), the reader is referred to these articles for additional details. We describe four ways to understand patterns related to sex/gender, and then discuss how findings can be framed in terms of gender influences and sex differences in the brain. The article ends with thoughts about how to discuss results with scientific and lay audiences in ways that stress the complex interrelationships among biological and environmental factors and challenge assumptions about biological determinism‥

This section provides a brief overview of the state of current knowledge regarding gender, and sex differences in addiction. It is important to note that unexamined assumptions about how women “should” behave have influenced research agendas (Campbell 2000; Campbell and Ettore 2011). As a result, findings remain incomplete and sometimes contradictory, particularly when the LGBT community is considered (Hughes et al. 2016). Nevertheless, humans, monkeys and rodents exhibit similar sex differences in addiction-like behavior (Carroll et al. 2005; Carroll et al. 2016; Becker et al. 2012) and biological sex differences can affect addiction-like behavior differently for males and females (Becker et al. 2012; Perry et al. 2013a). Effects of the environment and positive or negative experience can also affect the brain and influence vulnerability to addiction differently in males and females (Bowman et al. 2004; Thomas et al. 2009; Carroll et al. 2009).

For centuries it has been known that the phenomenon we now call addiction is a progressive condition. Today, we conceptualize addiction as having a series of stages: initiation/acquisition, escalation, maintenance, abstinence or withdrawal, and relapse or reinstatement of use (Table 1). The initial stage involves engagement with the drug, when the person or animal experiences its rewarding aspects after sampling the drug. It is important to note that some individuals never progress past this point, indefinitely using the drug occasionally or even stopping use. During acquisition the individual is not addicted, but for some individuals engagement and drug taking escalates and addiction follows, while others maintain moderate intake indefinitely or even stop using altogether (Deroche-Gamonet et al. 2004; Belin et al. 2008).

Sex Differences in Stages of Addiction

Using drugs can be related to social roles; for most of American history, men were much more likely than women to drink alcohol and use illicit drugs recreationally, while women were more likely to be prescribed drugs as medicine (McClellan 2011; Kandall 1999; McClellan 2017). Today, however, in adolescents equal numbers of boys and girls ages 12–17 use illegal drugs (Substance Abuse and Mental Health Services Administration 2014).

Within the general population, individuals differ in their risk for addiction due to a range of factors including genetic and personality traits (Heinrich et al. 2016), experience of trauma or abuse (Boschloo et al. 2011; Stevens et al. 2003; Kachadourian et al. 2014; Lieberman et al. 2016), and sociocultural influences (Felitti et al. 1998; Macleod et al. 2013). Physicians, psychiatrists and social workers have believed since early in the 20th century that women escalate alcohol use rapidly once they start (McClellan 2011; McClellan 2017; Kandall 1999). Still, we do not know what makes some individuals at greater risk for addiction. For those women and men who are vulnerable to addiction (i.e., escalate use after initial drug use and continue to use despite adverse consequences), women tend to progress more rapidly than men from initial experience to addiction (Bobzean et al. 2014; Brady and Randall 1999; Anglin et al. 1987). In contrast, a recent analysis of data from two U.S. national surveys found no evidence that in the general population women exhibit a shorter period of time from first use to alcohol dependence (Keyes et al. 2010). The contradiction may be explained by the fact that the “telescoping” phenomenon was reported for alcoholism in women who were in a treatment program already (Piazza et al. 1989). More rapid escalation after initiation of drug use in women compared with men has been replicated for other drugs of abuse (Richmond-Rakerd et al. 2016; Brady and Randall 1999; Moran-Santa Maria et al. 2014). In the general population only 15–20% are at risk for addiction (Kandel et al. 1997), therefore, it is possible that these differences occur within those individuals who make up the 15–20% of the population most at-risk, and this effect is obscured when the general population is studied. Thus, we are defining vulnerable as those who show rapid escalation of drug taking. Among this vilunerable group, females exhibit a greater rate of escalation of drug use than males‥

During attempts to quit drug use (abstinence), women exhibit greater unpleasant symptoms than men do (Hogle and Curtin 2006; Becker and Koob 2016). When trying to quit smoking, women also go through more severe withdrawal than men (Hogle and Curtin 2006). Women report greater effects on mood and anxiety as well as a greater stress response, compared to men (Hogle and Curtin 2006). On the other hand, males exhibit greater withdrawal symptoms when quitting alcohol consumption than females do (Devaud et al. 2003)

Most data suggest that women and men have similar outcomes after treatment for substance use disorders (Greenfield et al. 2007) once women have navigated all the barriers to treatment and engagement that they encounter. What has been reported to differ between women and men are the factors related to relapse, which is reported to be more sporadic (occurring without apparent trigger or intent) and related to negative affect as well as previous physical and sexual abuse among women (Greenfield et al. 2007; Walitzer and Dearing 2006; Hyman et al. 2008). This propensity to relapse associated with negative affect could be related to the greater withdrawal responses that women exhibit for some drugs (Hudson and Stamp 2011; Sinha et al. 2006). Alternatively, women might experience greater sensitivity to stress or the cues associated with the drug, as relapse can be triggered by these variables (Hudson and Stamp 2011). Greater stress or cue-induced reinstatement of drug taking by females after abstinence is seen in animal models of drug self-administration (Feltenstein et al. 2011; Anker and Carroll 2010). All of these factors have been reported to be related to relapse in studies of men and women who are addicted and are trying to quit (Becker and Koob 2016). There are also issues related to social support for maintaining abstinence, with men tending to receive more social support at home and on the job and women tending to be more isolated or not supported by their partners in their decision to be abstinent (Gallop et al. 2007; Schuckit et al. 1998; Campbell and Ettore 2011). Additionally, women who are addicted experience greater stigma than do men; this combined with less social support means more isolation and greater risk for relapse for women than men (Becker et al. 2016).

Sex and gender differences in addiction and relapse can be seen in humans and in animal models. Among the vulnerable populations, females escalate drug use more rapidly than males and relapse is more likely to be triggered by stressful events or drug-related cues. But these differences are not solely determined by biology: sociocultural influences also differentially affect men and women and how they respond to drugs of abuse. In humans, stigma, on-going interpersonal violence, many more barriers to treatment-seeking and engagement, lack of social support for recovery among girls and women. The animal models as well as the clinical research need to take into consideration how contextual and social factors may influence the processes of addiction and relapse differentially in males and females.

For this very brief discussion of the neurobiology of sex differences in addiction we will focus on the nucleus accumbens and the dorsal striatum, but other areas of the brain are also involved in the neurobiology of addiction and the reader is referred to recent reviews for more details (Becker and Koob, 2016; (Becker et al. 2012; Perry et al. 2016). One current model for the development of addiction is that the nucleus accumbens is important for engaging in behaviors that are initially rewarding, while the dorsal striatum is involved in escalated drug taking and compulsive behaviors (Clark et al. 2013; Willuhn et al. 2012). When an individual experiences something new and exciting or consumes a new substance, dopamine in the nucleus accumbens and dorsal striatum are important for the development of craving or ‘wanting’ to experience it again, the endorphins in the nucleus accumbens are important for the pleasure or ‘liking’ for the new experience (Berridge 2009). In this model of addiction, when dopamine activation of the dorsal striatum becomes greater than the response to the drug in the nucleus accumbens, there is a loss of pleasure associated with drug taking even though drug taking increases (DiFeliceantonio and Berridge 2016; Castro and Berridge 2014).

The dorsal striatum is important for well-learned patterns of behavior that can operate in the background without intentional control, which is usually exerted by the prefrontal cortex. For some habits such as learning to drive a car with manual transmission, this is an advantage for being able to shift gears when needed without conscious thought. The pattern of behavior, once learned, can be executed without thinking about it and it transfers from one car to another even when the gearshift is in a different position. This flexible pattern of automatic behavior also characterizes addiction. When intake progresses from being a casual pleasure to avid and compulsive intake, the pattern of activation in the brain has also shifted from dopamine activation in the nucleus accumbens to dopamine activation in dorsolateral striatum (Willuhn et al. 2012; Clark et al. 2013; DiFeliceantonio and Berridge 2016).

Among female rats and humans that become compulsive drug takers, there is the tendency to experience the shift in loss of voluntary control of drug intake to compulsive drug intake more rapidly than for males (Becker et al. 2012; Perry et al. 2016; Perry et al. 2013b). There is a reduction in nucleus accumbens dopamine release that is thought to be what allows the dorsal striatum to assume control of the addict’s behavior, thereby transforming the drug taking into a compulsive behavior or what we consider addiction (Perry et al. 2015; Volkow et al. 2006; Clark et al. 2013; Willuhn et al. 2012). Female rats tend to exhibit a smaller response in the nucleus accumbens to drug stimulation initially, compared with males, and have a relatively greater and more rapid initial response in the dorsal striatum to drugs, coupled with a decrease in the accumbens response after cocaine taking is well established (Cummings et al. 2014; Cosgrove et al. 2014; Perry et al. 2016). This brain pattern may underlie the sex difference in escalation of drug taking that leads to addiction. Supporting this notion, women who are smokers exhibit a lower response in the ventral striatum than in the dorsal striatum to nicotine stimulation compared with male smokers (Cosgrove et al. 2014)

Investigators have considered whether the long-term changes in the brain induced by exposure to the drug of abuse are what cause an individual to become addicted to that drug. Even though all individuals, both human and animal, will exhibit changes in the brain after receiving a drug of abuse (Leyton 2007; Wegener and Koch 2009; Willuhn et al. 2010; Andersen et al. 2012), as discussed above, only about 15–20% of the population of men become addicted to drugs or alcohol among humans (Brady and Randall 1999). In the laboratory, all rodents will eventually learn to self-administer cocaine or heroin if they are isolated in a self-administration chamber for many hours with a lever to push or a nose poke hole that delivers drug intravenously, but only about 10–16% of male rats will develop drug taking behaviors that are similar to the characteristics of addiction in humans (Belin and Everitt 2008; Deroche-Gamonet et al. 2004; Belin et al. 2008). In these studies animals are considered to exhibit addiction-like behavior if they continue to take a drug when receiving an aversive mild shock, exhibit high levels of responding on a progressive ratio schedule and continue to respond for the drug under conditions when drug is not available. A few studies have examined the proportion of female rats that develop addiction-like behavior in the laboratory; in these studies where males and females are allowed to choose cocaine or a food reward, more females than males choose cocaine and females exhibit higher responding for cocaine than do males (Perry et al. 2013b; Kerstetter et al. 2012; Kerstetter and Kippin 2011).

Not many studies have examined the neural mechanisms for sex differences in drug-taking behavior, and more research is clearly needed. In the studies that have investigated sex differences in addiction-like behavior in the laboratory, female rats tend to exhibit similar patterns of drug taking behavior to those seen for women. For example, female rats acquire drug self-administration more readily than males (Carroll et al. 2002; Lynch and Carroll 1999; Jackson et al. 2006). This is true for all classes of drugs studied and for both rats and monkeys (Carroll et al. 2005; Carroll et al. 2002; Perry et al. 2007). Female rats also escalate their drug use more rapidly than males, take more drug when they get to maintenance dose and females will work harder to get a dose than male rats will (Roth and Carroll 2004; Westenbroek et al. 2013; Reichel et al. 2012; Anker and Carroll 2011).

There are changes in the brain of all individuals who get a drug, but the changes in the brains of individuals who become addicted are different from those who do not. This is assumed because the behavior of an addict is different from the behavior of a non-addict – if the behavior is different the brains are different. Why the changes in the brain are not the same between addicts and non-addicts is not yet completely known. Individual differences in genetics, personality traits, extent of social support, experiences or trauma during development, and in whether one is male or female are all thought to contribute to how someone responds to drugs of abuse and whether one develops compulsive behaviors associated with an addiction (Cummings et al. 2011; Perry et al. 2013b; Buisman-Pijlman et al. 2014; Becker et al. 2012; Thomas et al. 2009; Perry et al. 2005; Morgan et al. 2005; Carroll et al. 2002). This means that even though individuals can be categorized as male or female, or brought up in an impoverished vs. enriched environment, or other characteristics, these variables all interact within an individual to influence whether or not an individual will be susceptible to addiction.

Studies of rodents show that females exhibit enhanced drug-, cue-, and stress-induced reinstatement in alcohol, cocaine and morphine seeking, compared to males (Feltenstein et al. 2011; Anker and Carroll 2010; Becker and Koob 2016). The laboratory evidence supports the idea that there are biological components to the sex differences. But this does not mean that all women are going to be addicts or that women cannot quit once they have started. In fact, studies document many barriers for women in traditional treatment programs, and that treatment programs tailored for women tend to be more successful (Campbell and Ettore 2011).

For females, the phase of the menstrual/estrous cycle, and the reproductive hormones release that is associated with the cycle, may also affect drug taking and quitting behavior, because the ovarian hormones, estradiol and progesterone, have full access to the brain. The hormone condition of a woman needs to be considered when thinking about sex differences in addiction. The human menstrual cycle consists of follicular, periovulatory, and luteal phases. During the 10–12 day follicular phase, the hormone estradiol is secreted from the ovary as the follicle develops, with concentrations of estradiol increasing daily. Next, during the 2–4 day peri-ovulatory phase, a rapid increase in estradiol triggers the release of luteinizing hormone from the pituitary that induces ovulation. This is followed by the luteal phase that lasts 10–12 days and is characterized by the release of relatively high concentrations of both estradiol and progesterone from the remnant of the follicle that is retained by the ovary (the corpus luteum). Menstruation occurs at the end of the luteal phase, unless pregnancy occurs. During menstruation hormone levels are at their lowest point, indicating the beginning of the next follicular phase (Becker et al. 2005). Rats and mice have a four or five day estrous cycle that consists of a 2–3 day follicular phase called diestrus and a peri-ovulatory phase that is called ‘proestrus’ during the day of estradiol and progesterone surges and ‘estrus’ the day following the surges when the female rodent ovulates and is behaviorally receptive. Rats and mice do not have a spontaneous luteal phase (Becker et al. 2005).

The acute subjective effects of drugs of abuse can vary over the menstrual cycle in humans. For example, in women the subjective effects of cocaine and amphetamine tend to be more intense during the follicular phase when estradiol is elevated, relative to the luteal phase of the menstrual cycle when both estradiol and progesterone increase (Justice and de Wit 1999; Justice and De Wit 2000; Evans et al. 2002). It is not clear, however, that these subjective effects of estradiol and progesterone moderate intake in the cocaine-addicted woman, as exogenous progesterone did not decrease the self-administration of cocaine in this population of women (Reed et al. 2011). On the other hand, women tend to drink more alcohol during the premenstrual phase of the menstrual cycle and women with premenstrual dysphoric disorder have higher levels of alcohol use/abuse (see Becker and Koob 2016 for a complete discussion).

Most of the research on how ovarian hormones influence drug taking behavior in females has been done in rats and mice. In ovariectomized (OVX) female rats, estradiol administration affects behaviors that are induced by cocaine, amphetamine or methamphetamine, including drug self-administration. For example, OVX decreases cocaine-taking behavior. If an OVX rat is given estradiol, the rat will take more cocaine and work harder to get cocaine, just as an intact rat during estrus will work harder for cocaine (Becker and Hu 2008; Roberts et al. 1989).

On the other hand, in males neither testicular hormones nor estradiol affects cocaine-taking (Jackson et al. 2006). This sex difference is attributable to sexual differentiation of the brain during early life (Perry et al. 2013a). Estradiol also enhances the acquisition of opioid self-administration in OVX rats, and intact females acquire morphine and heroin self-administration faster and will work harder to get cocaine, morphine and heroin than will males (Jackson et al. 2006; Carroll et al. 2002; Lynch 2008).

Most laboratory studies are conducted with rats isolated in the testing chamber for hours. The chamber contains a lever or nose poke hole. The rat may receive an intravenous injection of a drug, such as cocaine, by pressing the lever or poking its nose into the hole. The rats learn to lever press or nose poke and start receiving drug. Most rats self-administer the drug, but not all rats will be highly motivated to get the drug under these conditions as determined by a progressive ratio schedule (where the number of responses increases exponentially to get a single dose). When criteria are applied that are analogous to the DSM-IV criteria (responding for drug in the presence of adverse consequences; exhibiting high rates of responding for the drug on a progressive ratio schedule; responding for drug even when not available; and loss of motivation for previously valued rewards such as highly palatable food), only a small percentage of male rats exhibit characteristics of addiction (Perry et al. 2013b; Deroche-Gamonet et al. 2004; Belin and Everitt 2008; Belin et al. 2008). These authors argue that these behavioral paradigms are better models of addiction than simply whether the rodent will self-administer a drug, as they identify a specific phenotype of animal that is more susceptible for addiction.

In a choice paradigm a rat can choose whether to receive a banana-flavored sucrose pellet or an injection of cocaine, but only a subpopulation of rats choose cocaine. The initial preference for all of the rats is the sucrose pellets. Over a period of four to eight weeks, some rats choose the cocaine over the pellets, and once a rat makes that shift to cocaine it persists. In this paradigm about 50% of females choose the cocaine (compared with 15–20% of males). The females that choose cocaine also do this sooner than the males that ultimately choose cocaine (Perry et al. 2013b). Other investigators have also shown that more females choose cocaine over a food reinforce compared with males (Kerstetter et al. 2012; Kerstetter and Kippin 2011).

Estradiol plays a role in the acquisition of cocaine-taking behavior (Hu and Becker 2008; Anker and Carroll 2011; Hu et al. 2004). Once the female is avidly self-administering cocaine, however, the ovarian hormones are no longer modulating the motivation for cocaine and cocaine intake does not vary with the estrous cycle in the choice paradigm (Cummings et al. 2011; Perry et al. 2015; Perry et al. 2013b). These results suggest that estradiol is important for the initiation of drug taking, but once the behavior is well established, it is no longer under ovarian hormone regulation.

To summarize, hormones of the menstrual or estrous cycle may enhance the initial reinforcing effect that a female gets from a drug of abuse. But once the addictive behavior is established, the hormones do not continue to play as important a role in rats or humans. Thus, the menstrual cycle may contribute to the more rapid escalation of drug taking seen in women anf females rats compared with males, by increasing the positive effects of drugs of abuse during the initial stages of acquisition. This phenomenon is most likely greater in the sub-population of women who are more vulnerable for addiction.

The brains of males and females can differ from each other in more then one way (Becker et al. 2016; McCarthy et al. 2012). Not all sex differences in the brain develop in the same way and they are expressed in different ways. Males and females are sometimes referred to as “opposites,” or it is implied that there is a bimodal distribution of traits that typify “males” and “females”, but for most differences between males and females this is not true. There are four types of sex differences (Becker and Koob 2016; McCarthy et al. 2012) and more than one of these types of sex difference may be involved when we see variation on a given trait between males and females (Table 2). The most obvious sex differences relate to reproduction, for example women ovulate and have babies while men produce sperm and don’t get pregnant. These types of sex differences are called qualitative sex differences. Then there are more subtle sex differences, here the average or mean is different for males and females but the neural mechanisms are the same (quantitative sex difference). We see this is the psychomotor activation induced by amphetamine, where females exhibit a greater initial response to the same dose of the drug and greater behavioral sensitization (Hu and Becker 2003; Camp and Robinson 1988; Camp et al. 1986).

There are also sex differences where males and females exhibit the same response, but the mechanism underlying the trait is different (convergent sex difference). In this case there is convergence of function while the mechanisms mediating the trait are different for males and females. We think that some aspects of addiction are mediated by convergent sex differences as discussed above. For example, both males and females progress to compulsive drug taking and addiction, but in females estradiol is hypothesized to facilitate this transition by enhancing dopamine in dorsal striatum (see discussion above).

Finally, there can be sex differences where the proportion of males and females that exhibit a trait is different (population sex differences). The difference in the rate of escalation of drug taking is likely a population sex difference. Prenatal stress causes male rats to escalate drug taking so they resemble females (Thomas et al 2009). Experience interacts with the developing brain, in this example, to shift the proportion of male rats that show rapid escalation of drug taking to be comparable to females. In one retrospective study, family violence in childhood, especially directed against the child, was associated with increased risk of injection drug use for both men and women (Macleod et al. 2013). So the population of individuals with drug abuse problems may be increased by childhood abuse or trauma. In a prospective study, abused and neglected girls were more likely than boys from comparable backgrounds to abuse illegal drugs as adults (Wilson and Widom 2009). As this example shows, the number of men and women with drug abuse problems depends on the developmental experiences of both boys and girls and the outcome measure. In some cases a population sex difference may appear to bemquantitative sex difference if only the means of the dependent variable for males and females are considered – rather than looking for variation within males and females.

Each type of sex difference contributes to the overall phenotype of an individual; while all four types of sex differences are acting within each person, and individual types of sex differences may shape the phenotype of an individual in different ways. This makes the continuum of masculine-feminine traits even richer in terms of the variety that can be produced.

Research on the differences between females and males can be controversial, especially in societies like ours where gender roles are in flux, and because assumptions about immutable biological differences have been used to justify unequal opportunities for women compared to men. That is exactly why the issue must be approached with rigorous scientific methods, and scientists must be aware of the political and social contexts surrounding their work. The bodies of men and women have many elements that look and function essentially in the same way (e.g., we all have arms and legs, lungs and a liver, etc.), yet we tend to be defined by our different sexual organs. The first question we ask a new parent is: Is it a boy or a girl? We ascribe essential differences to individuals based on whether they are male or female, without knowing if a particular trait is present in a particular individual (Fausto-Sterling 2012).

When scientists say that the brains of men and women are different, the intent is to convey that our brains have some regions that look and function the same in men and women and others that look and function differently (Cahill et al. 2001; Cahill 2014; Cahill 2006). There is variation in masculine and feminine traits due to variations in genes expressed, the hormones secreted during development, the intra-uterine environment, as well as influences of maternal nutritional status, stress and the hormones of puberty (McCarthy and Arnold 2011; Sisk and Zehr 2005; Bale and Epperson 2015). These biological processes are further modified by individual experience and sociocultural factors that can differentially affect females and males (Figure 1).

The sexual differentiation of the bi-potential brain is not bimodal – ending up either all male or all female. Instead the adult brain exists on a continuum that can be influenced by events during embryonic development and postnatal life. Events prior to puberty will tend to have a greater effect on the adult brain than events after puberty.

A. Sexual differentiation of the brain is a result of testosterone produced by the developing testes in the male acting on the bi-potential brain to induce sexual differentiation of target brain regions. At puberty hormones from the testes and ovaries induce additional developmental events throughout the brain that further enhance or diminish sex differences in the brain. In the figure the bipotential brain is depicted in lavender that becomes more blue (masculine) or red (feminine) during development. The red arrows depict the female typical path and the blue arrows the male-typical path. Prior to puberty the brains are not fully formed and the hormones at puberty influence development further to result in the final phenotype. The bar at the bottom indicated that the sexual differentiation of the brain exists along a continuum from feminine to masculine.

B. Experiences during prenatal development Influence sex differences in the brain (large green ‘Experience’ arrows). Events and experience during development can have the same or different effects on males and females. The direction of the effect depends on what type of event it is and when it happens during development. In the example here, prenatal experience, such as maternal stress can make both male and female fetuses less masculinized. Resulting in offspring that are both shifted in the same direction along the continuum. Other developmental events could have different effects.

C. Experiences during post-natal development prior to puberty, such as playing with trucks by boys (blue ‘Experience’ arrow) vs. dolls by the girls (red ‘Experience’ arrow), can lead to greater sex differences in the brains of adults than would be there without these variations in experience. If boys and girls have the same experiences, both would potentially be affected by the experience, but the direction of the effect would depend on the brain at the time the experience occurs.

For example, if a mother rat undergoes restraint stress during the last week of gestation, the period when the fetal testes are normally masculinizing the brain, there are permanent effects on brain and behavior (Kerchner and Ward 1992; de Souza et al. 2013). Both male and female offspring will show the effects of their mother’s stress, but in different ways. The males in the litter will be less aggressive, more prone to addiction and will have learning deficits as adults (Thomas et al. 2009; Bowman et al. 2004). On the other hand, the females will exhibit greater anxiety and depressive-like symptoms as adults (Thomas et al. 2009; Bowman et al. 2004; Van den Hove et al. 2013; Ward and Stehm 1991).

Other types of activities or events can also affect development of the brain in different ways for males and females. Events and experience during development can have the same or different effects on males and females (Juraska 1984; Juraska 1998). The direction of the effect depends on what type of event it is (e.g., good vs. bad nutrition would have different types of influences than enriched environments). Furthermore, even though gendered experiences during development (e.g., playing trucks or hitting a ball vs. playing with dolls or jumping rope) may be influenced by prenatal hormones, these experiences also contribute to greater sex differences in the brains of adults than would be there without these variations in experience (Hines 2011).

For many sex differences in the brain, male-typical and female-typical traits could be considered to be represented along a continuum, rather than a bimodal distribution (Figure 1). Each human’s brain is the result of an intricate interplay between biology and environment across the life span. This means that not all areas of a given brain are “masculine” (displaying characteristics more likely to be seen in males) in all men or “feminine” (with features more strongly associated with females) in all women. In fact, it is suggested that the human brain tends to be a mosaic of sexually differentiated brain regions, some of which tend to be more “masculine”, and others more “feminine”(Cahill 2006). The brains of women and men develop through complex interactions among the biology (the brain developing in response to genetic and hormonal signals), the physical environment, and sociocultural experiences of an individual, all of which shape the development of the brain throughout life (Hines 2011; Wallen 1996). As a result, customs and practices contribute to sex differences in the brain.

It is important to remember that even for laboratory animals there are behavioral and experiential effects interacting with the biology to differentially affect females and males. Not only is there variation among females and males, as discussed above, but also different types of sex (and gender) differences emerge from these various processes. In this time of individualized medicine, sex differences are important, but not as a bimodal characteristic of an individual, or discussed separately from environmental influences, and scientists have a responsibility to convey these nuances to the general public. Sex differences are important as a biological factor that interacts with genetics, epigenetics and environmental conditions to mediate developmental pathways for expression of specific traits.

​

Significance

Alcohol/other drug addiction is a major public health concern; understanding the basic mechanisms mediating the path to addiction in both women and men is important for improving prevention and enhancing treatment. In rodents, estradiol in female rats enhances acquisition and escalation of drug taking, motivation for drugs of abuse, and relapse-like behaviors. Nevertheless, even in rats, not all variation between the sexes is due to the biological processes involved, but result from an interaction among genetics, epigenetics, sociocultural factors and environmental conditions that mediate expression of specific traits such as risk and protective factors for addiction.

Authorship:

JBB, MM, and BGR were all involved in the conception of this manuscript. JBB drafted the original manuscript. All provided critical revisions of the manuscript for important intellectual content. All authors critically reviewed content and approved final version for publication.

The authors confirm they have no conflict of interest.

• Allen AM, Lunos S, Heishman SJ, al’Absi M, Hatsukami D, Allen SS. Subjective response to nicotine by menstrual phase. Addict Behav. 2015;43:50–53. [PMC free article] [PubMed] [Google Scholar]
• Andersen ML, Sawyer EK, Howell LL. Contributions of neuroimaging to understanding sex differences in cocaine abuse. Experimental and Clinical Psychopharmacology. 2012;20(1):2–15. [PMC free article] [PubMed] [Google Scholar]
• Anglin MD, Hser YI, McGlothlin WH. Sex differences in addict careers. 2. Becoming addicted. The American Journal of Drug and Alcohol Abuse. 1987;13(1–2):59–71. [PubMed] [Google Scholar]
• Anker JJ, Carroll ME. Females are more vulnerable to drug abuse than males: evidence from preclinical studies and the role of ovarian hormones. Current topics in behavioral neurosciences. 2011;8:73–96. [PubMed] [Google Scholar]
• Anker JJ, Carroll ME. Reinstatement of cocaine seeking induced by drugs, cues, and stress in adolescent and adult rats. Psychopharmacology. 2010;208(2):211–222. [PMC free article] [PubMed] [Google Scholar]
• Bale TL, Epperson CN. Sex differences and stress across the lifespan. Nature Neuroscience. 2015;18(10):1413–1420. [PMC free article] [PubMed] [Google Scholar]
• Becker JB, Arnold AP, Berkley KJ, Blaustein JD, Eckel LA, Hampson E, Herman JP, Marts S, Sadee W, Steiner M, Taylor J, Young E. Strategies and methods for research on sex differences in brain and behavior. Endocrinology. 2005;146(4):1650–1673. [PubMed] [Google Scholar]
• Becker JB, Hu M. Sex differences in drug abuse. Frontiers in Neuroendocrinology. 2008;29(1):36–47. [PMC free article] [PubMed] [Google Scholar]
• Becker JB, Koob GF. Sex Differences in Animal Models: Focus on Addiction. Pharmacological Reviews. 2016;68(2):242–263. [PMC free article] [PubMed] [Google Scholar]
• Becker JB, McClellan M, Reed BG. Sociocultural context for sex differences in addiction. Addiction Biology. 2016 [PMC free article] [PubMed] [Google Scholar]
• Becker JB, Perry AN, Westenbroek C. Sex differences in the neural mechanisms mediating addiction: a new synthesis and hypothesis. Biology of sex differences. 2012;3(1):14. [PMC free article] [PubMed] [Google Scholar]
• Belin D, Everitt BJ. Cocaine seeking habits depend upon dopamine-dependent serial connectivity linking the ventral with the dorsal striatum. Neuron. 2008;57(3):432–441. [PubMed] [Google Scholar]
• Belin D, Mar AC, Dalley JW, Robbins TW, Everitt BJ. High impulsivity predicts the switch to compulsive cocaine-taking. Science (New York) 2008;320(5881):1352–1355. [PMC free article] [PubMed] [Google Scholar]
• Berridge KC. “Liking” and “wanting” food rewards: brain substrates and roles in eating disorders. Physiology & Behavior. 2009;97(5):537–550. [PMC free article] [PubMed] [Google Scholar]
• Blanco C, Hasin DS, Petry N, Stinson FS, Grant BF. Sex differences in subclinical and DSM-IV pathological gambling: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Psychological Medicine. 2006;36(7):943–953. [PubMed] [Google Scholar]
• Bobzean SA, DeNobrega AK, Perrotti LI. Sex differences in the neurobiology of drug addiction. Experimental Neurology. 2014;259:64–74. [PubMed] [Google Scholar]
• Boschloo L, Vogelzangs N, Smit JH, van den Brink W, Veltman DJ, Beekman AT, Penninx BW. Comorbidity and risk indicators for alcohol use disorders among persons with anxiety and/or depressive disorders: findings from the Netherlands Study of Depression and Anxiety (NESDA) Journal of Affective Disorders. 2011;131(1–3):233–242. [PubMed] [Google Scholar]
• Bowman RE, MacLusky NJ, Sarmiento Y, Frankfurt M, Gordon M, Luine VN. Sexually dimorphic effects of prenatal stress on cognition, hormonal responses, and central neurotransmitters. Endocrinology. 2004;145(8):3778–3787. [PubMed] [Google Scholar]
• Brady KT, Randall CL. Gender differences in substance use disorders. The Psychiatric Clinics of North America. 1999;22(2):241–252. [PubMed] [Google Scholar]
• Buisman-Pijlman FT, Sumracki NM, Gordon JJ, Hull PR, Carter CS, Tops M. Individual differences underlying susceptibility to addiction: Role for the endogenous oxytocin system. Pharmacology, Biochemistry, and Behavior. 2014;119:22–38. [PubMed] [Google Scholar]
• Cahill L. Equal ≠ the same: sex differences in the human brain. Cerebrum: the Dana forum on brain science. 2014;2014:5. [PMC free article] [PubMed] [Google Scholar]
• Cahill L. Why sex matters for neuroscience. Nature Reviews. Neuroscience. 2006;7(6):477–484. [PubMed] [Google Scholar]
• Cahill L, Haier RJ, White NS, Fallon J, Kilpatrick L, Lawrence C, Potkin SG, Alkire MT. Sex-related difference in amygdala activity during emotionally influenced memory storage. Neurobiology of Learning and Memory. 2001;75(1):1–9. [PubMed] [Google Scholar]
• Camp DM, Becker JB, Robinson TE. Sex differences in the effects of gonadectomy on amphetamine-induced rotational behavior in rats. Behavioral and Neural Biology. 1986;46(3):491–495. [PubMed] [Google Scholar]
• Camp DM, Robinson TE. Susceptibility to sensitization. I. Sex differences in the enduring effects of chronic D-amphetamine treatment on locomotion, stereotyped behavior and brain monoamines. Behavioural Brain Research. 1988;30(1):55–68. [PubMed] [Google Scholar]
• Campbell N, Ettore E. Gendering Addiction: The Politics of Drug Treatment in a Neurochemical World. New York: Palgrave Macmillan; 2011. [Google Scholar]
• Campbell ND. Using Women: Gender, Drug Policy, and Social Justice. New York: Routledge; 2000. [Google Scholar]
• Carroll ME, Anker JJ. Sex differences and ovarian hormones in animal models of drug dependence. Hormones and Behavior. 2010;58(1):44–56. [PubMed] [Google Scholar]
• Carroll ME, Anker JJ, Perry JL. Modeling risk factors for nicotine and other drug abuse in the preclinical laboratory. Drug and Alcohol Dependence. 2009;(104 Suppl 1):S70–S78. [PubMed] [Google Scholar]
• Carroll ME, Batulis DK, Landry KL, Morgan AD. Sex differences in the escalation of oral phencyclidine (PCP) self-administration under FR and PR schedules in rhesus monkeys. Psychopharmacology. 2005;180(3):414–426. [PubMed] [Google Scholar]
• Carroll ME, Collins M, Kohl EA, Johnson S, Dougen B. Sex and menstrual cycle effects on chronic oral cocaine self-administration in rhesus monkeys: Effects of a nondrug alternative reward. Psychopharmacology. 2016 [PMC free article] [PubMed] [Google Scholar]
• Carroll ME, Lynch WJ. How to study sex differences in addiction using animal models. Addiction Biology. 2016 [PMC free article] [PubMed] [Google Scholar]
• Carroll ME, Morgan AD, Lynch WJ, Campbell UC, Dess NK. Intravenous cocaine and heroin self-administration in rats selectively bred for differential saccharin intake: phenotype and sex differences. Psychopharmacology. 2002;161(3):304–313. [PubMed] [Google Scholar]
• Castro DC, Berridge KC. Advances in the neurobiological bases for food “liking” versus “wanting.” Physiology & Behavior. 2014 [PMC free article] [PubMed] [Google Scholar]
• Clark JJ, Collins AL, Sanford CA, Phillips PE. Dopamine encoding of Pavlovian incentive stimuli diminishes with extended training. The Journal of Neuroscience. 2013;33(8):3526–3532. [PMC free article] [PubMed] [Google Scholar]
• Cosgrove KP, Wang S, Kim SJ, McGovern E, Nabulsi N, Gao H, Labaree D, Tagare HD, Sullivan JM, Morris ED. Sex differences in the brain’s dopamine signature of cigarette smoking. The Journal of Neuroscience. 2014;34(50):16851–16855. [PMC free article] [PubMed] [Google Scholar]
• Cummings JA, Gowl BA, Westenbroek C, Clinton SM, Akil H, Becker JB. Effects of a selectively bred novelty-seeking phenotype on the motivation to take cocaine in male and female rats. Biology of sex differences. 2011;2:3. [PMC free article] [PubMed] [Google Scholar]
• Cummings JA, Jagannathan L, Jackson LR, Becker JB. Sex differences in the effects of estradiol in the nucleus accumbens and striatum on the response to cocaine: neurochemistry and behavior. Drug and Alcohol Dependence. 2014;135:22–28. [PMC free article] [PubMed] [Google Scholar]
• Deroche-Gamonet V, Belin D, Piazza PV. Evidence for addiction-like behavior in the rat. Science (New York) 2004;305(5686):1014–1017. [PubMed] [Google Scholar]
• Devaud LL, Alele P, Ritu C. Sex differences in the central nervous system actions of ethanol. Critical Reviews in Neurobiology. 2003;15(1):41–59. [PubMed] [Google Scholar]
• DiFeliceantonio AG, Berridge KC. Dorsolateral neostriatum contribution to incentive salience: Opioid or dopamine stimulation makes one reward cue more motivationally attractive than another. The European Journal of Neuroscience. 2016 [PMC free article] [PubMed] [Google Scholar]
• Evans SM, Haney M, Foltin RW. The effects of smoked cocaine during the follicular and luteal phases of the menstrual cycle in women. Psychopharmacology. 2002;159(4):397–406. [PubMed] [Google Scholar]
• Fausto-Sterling A. Sex/Gender: Biology in a Social World. New York and London: Routledge; 2012. [Google Scholar]
• Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, Koss MP, Marks JS. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine. 1998;14(4):245–258. [PubMed] [Google Scholar]
• Feltenstein MW, Henderson AR, See RE. Enhancement of cue-induced reinstatement of cocaine-seeking in rats by yohimbine: sex differences and the role of the estrous cycle. Psychopharmacology. 2011;216(1):53–62. [PMC free article] [PubMed] [Google Scholar]
• Gallop RJ, Crits-Christoph P, Ten Have TR, Barber JP, Frank A, Griffin ML, Thase ME. Differential transitions between cocaine use and abstinence for men and women. Journal of Consulting and Clinical Psychology. 2007;75(1):95–103. [PubMed] [Google Scholar]
• Greenfield SF, Brooks AJ, Gordon SM, Green CA, Kropp F, McHugh RK, Lincoln M, Hien D, Miele GM. Substance abuse treatment entry, retention, and outcome in women: a review of the literature. Drug and Alcohol Dependence. 2007;86(1):1–21. [PMC free article] [PubMed] [Google Scholar]
• Hall W, Carter A, Forlini C. The brain disease model of addiction: is it supported by the evidence and has it delivered on its promises? The Lancet. Psychiatry. 2015;2(1):105–110. [PubMed] [Google Scholar]
• Heinrich A, Müller KU, Banaschewski T, Barker GJ, Bokde AL, Bromberg U, Büchel C, Conrod P, Fauth-Bühler M, Papadopoulos D, Gallinat J, Garavan H, Gowland P, Heinz A, Ittermann B, Mann K, Martinot JL, Paus T, Pausova Z, Smolka M, Ströhle A, Rietschel M, Flor H, Schumann G, Nees F and IMAGEN consortium. Prediction of alcohol drinking in adolescents: Personality-traits, behavior, brain responses, and genetic variations in the context of reward sensitivity. Biological Psychology. 2016;118:79–87. [PubMed] [Google Scholar]
• Hines M. Gender development and the human brain. Annual Review of Neuroscience. 2011;34:69–88. [PubMed] [Google Scholar]
• Hogle JM, Curtin JJ. Sex differences in negative affective response during nicotine withdrawal. Psychophysiology. 2006;43(4):344–356. [PubMed] [Google Scholar]
• Van den Hove DL, Kenis G, Brass A, Opstelten R, Rutten BP, Bruschettini M, Blanco CE, Lesch KP, Steinbusch HW, Prickaerts J. Vulnerability versus resilience to prenatal stress in male and female rats; implications from gene expression profiles in the hippocampus and frontal cortex. European Neuropsychopharmacology. 2013;23(10):1226–1246. [PubMed] [Google Scholar]
• Hu M, Becker JB. Acquisition of cocaine self-administration in ovariectomized female rats: effect of estradiol dose or chronic estradiol administration. Drug and Alcohol Dependence. 2008;94(1–3):56–62. [PMC free article] [PubMed] [Google Scholar]
• Hu M, Becker JB. Effects of sex and estrogen on behavioral sensitization to cocaine in rats. The Journal of Neuroscience. 2003;23(2):693–699. [PMC free article] [PubMed] [Google Scholar]
• Hu M, Crombag HS, Robinson TE, Becker JB. Biological basis of sex differences in the propensity to self-administer cocaine. Neuropsychopharmacology. 2004;29(1):81–85. [PubMed] [Google Scholar]
• Hudson A, Stamp JA. Ovarian hormones and propensity to drug relapse: a review. Neuroscience and Biobehavioral Reviews. 2011;35(3):427–436. [PubMed] [Google Scholar]
• Hughes TL, Wilsnack SC, Kantor LW. The Influence of Gender and Sexual Orientation on Alcohol Use and Alcohol-Related Problems: Toward a Global Perspective. Alcohol research : current reviews. 2016;38(1):121–132. [PMC free article] [PubMed] [Google Scholar]
• Hyman SM, Paliwal P, Chaplin TM, Mazure CM, Rounsaville BJ, Sinha R. Severity of childhood trauma is predictive of cocaine relapse outcomes in women but not men. Drug and Alcohol Dependence. 2008;92(1–3):208–216. [PMC free article] [PubMed] [Google Scholar]
• Jackson LR, Robinson TE, Becker JB. Sex differences and hormonal influences on acquisition of cocaine self-administration in rats. Neuropsychopharmacology. 2006;31(1):129–138. [PubMed] [Google Scholar]
• Johnson RA, Lukens JM, Kole JW, Sisti DA. Views about responsibility for alcohol addiction and negative evaluations of naltrexone. Substance Abuse Treatment, Prevention, and Policy. 2015;10:10. [PMC free article] [PubMed] [Google Scholar]
• Juraska JM. Neural plasticity and the development of sex differences. Annual review of sex research. 1998;9:20–38. [PubMed] [Google Scholar]
• Juraska JM. Sex differences in developmental plasticity in the visual cortex and hippocampal dentate gyrus. Progress in Brain Research. 1984;61:205–214. [PubMed] [Google Scholar]
• Justice AJ, de Wit H. Acute effects of d-amphetamine during the follicular and luteal phases of the menstrual cycle in women. Psychopharmacology. 1999;145(1):67–75. [PubMed] [Google Scholar]
• Justice AJH, De Wit H. Acute effects of d-amphetamine during the early and late follicular phases of the menstrual cycle in women. Pharmacology Biochemistry and Behavior. 2000;66:509–515. [PubMed] [Google Scholar]
• Kachadourian LK, Pilver CE, Potenza MN. Trauma, PTSD, and binge and hazardous drinking among women and men: findings from a national study. Journal of Psychiatric Research. 2014;55:35–43. [PMC free article] [PubMed] [Google Scholar]
• Kandall SR. Substance and Shadow: Women and Addiction in the United States. Cambridge, MA: Harvard University Press; 1999. [Google Scholar]
• Kandel D, Chen K, Warner LA, Kessler RC, Grant B. Prevalence and demographic correlates of symptoms of last year dependence on alcohol, nicotine, marijuana and cocaine in the U.S. population. Drug and Alcohol Dependence. 1997;44(1):11–29. [PubMed] [Google Scholar]
• Kerchner M, Ward IL. SDN-MPOA volume in male rats is decreased by prenatal stress, but is not related to ejaculatory behavior. Brain Research. 1992;581(2):244–251. [PubMed] [Google Scholar]
• Kerstetter KA, Ballis MA, Duffin-Lutgen S, Carr AE, Behrens AM, Kippin TE. Sex differences in selecting between food and cocaine reinforcement are mediated by estrogen. Neuropsychopharmacology. 2012;37(12):2605–2614. [PMC free article] [PubMed] [Google Scholar]
• Kerstetter KA, Kippin TE. Impact of Sex and Gonadal Hormones on Cocaine and Food Reinforcement Paradigms. Journal of addiction research & therapy. 2011;S4(2) [PMC free article] [PubMed] [Google Scholar]
• Keyes KM, Martins SS, Blanco C, Hasin DS. Telescoping and gender differences in alcohol dependence: new evidence from two national surveys. The American Journal of Psychiatry. 2010;167(8):969–976. [PMC free article] [PubMed] [Google Scholar]
• Leyton M. Conditioned and sensitized responses to stimulant drugs in humans. Progress in Neuro-Psychopharmacology & Biological Psychiatry. 2007;31(8):1601–1613. [PubMed] [Google Scholar]
• Lieberman R, Armeli S, Scott DM, Kranzler HR, Tennen H, Covault J. FKBP5 genotype interacts with early life trauma to predict heavy drinking in college students. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics. 2016 [PMC free article] [PubMed] [Google Scholar]
• Lynch WJ. Acquisition and maintenance of cocaine self-administration in adolescent rats: effects of sex and gonadal hormones. Psychopharmacology. 2008;197(2):237–246. [PubMed] [Google Scholar]
• Lynch WJ. Sex differences in vulnerability to drug self-administration. Experimental and Clinical Psychopharmacology. 2006;14(1):34–41. [PubMed] [Google Scholar]
• Lynch WJ, Carroll ME. Sex differences in the acquisition of intravenously self-administered cocaine and heroin in rats. Psychopharmacology. 1999;144(1):77–82. [PubMed] [Google Scholar]
• Macleod J, Hickman M, Jones HE, Copeland L, McKenzie J, De Angelis D, Kimber J, Robertson JR. Early life influences on the risk of injecting drug use: case control study based on the Edinburgh Addiction Cohort. Addiction. 2013;108(4):743–750. [PubMed] [Google Scholar]
• McCarthy MM, Arnold AP. Reframing sexual differentiation of the brain. Nature Neuroscience. 2011;14(6):677–683. [PMC free article] [PubMed] [Google Scholar]
• McCarthy MM, Arnold AP, Ball GF, Blaustein JD, De Vries GJ. Sex differences in the brain: the not so inconvenient truth. The Journal of Neuroscience. 2012;32(7):2241–2247. [PMC free article] [PubMed] [Google Scholar]
• McClellan ML. Historical Perspectives on Alcoholism Treatment for Women. Alcoholism Treatment Quarterly. 2011;29(4):332–56. [Google Scholar]
• McClellan ML. Lady Lushes: Gender, Alcoholism, and Medicine in Modern America. 1st. New York, NY: Rutgers University Press; 2017. [Google Scholar]
• Meurk C, Morphett K, Carter A, Weier M, Lucke J, Hall W. Scepticism and hope in a complex predicament: People with addictions deliberate about neuroscience. The International journal on drug policy. 2016;32:34–43. [PubMed] [Google Scholar]
• Moran-Santa Maria MM, Flanagan J, Brady K. Ovarian hormones and drug abuse. Current Psychiatry Reports. 2014;16(11):511. [PMC free article] [PubMed] [Google Scholar]
• Morgan AD, Dess NK, Carroll ME. Escalation of intravenous cocaine self-administration, progressive-ratio performance, and reinstatement in rats selectively bred for high (HiS) and low (LoS) saccharin intake. Psychopharmacology. 2005;178(1):41–51. [PubMed] [Google Scholar]
• Perry AN, Westenbroek C, Becker JB. Impact of pubertal and adult estradiol treatments on cocaine self-administration. Hormones and Behavior. 2013a;64(4):573–578. [PMC free article] [PubMed] [Google Scholar]
• Perry AN, Westenbroek C, Becker JB. Sex Differences and Addiction. In: Shansky RM, editor. Sex Differences in the Central Nervous System. New York: Academic Press; 2016. pp. 129–147. [Google Scholar]
• Perry AN, Westenbroek C, Becker JB. The development of a preference for cocaine over food identifies individual rats with addiction-like behaviors. Plos One. 2013b;8(11):e79465. [PMC free article] [PubMed] [Google Scholar]
• Perry AN, Westenbroek C, Jagannathan L, Becker JB. The Roles of Dopamine and α1-Adrenergic Receptors in Cocaine Preferences in Female and Male Rats. Neuropsychopharmacology. 2015;40(12):2696–2704. [PMC free article] [PubMed] [Google Scholar]
• Perry JL, Larson EB, German JP, Madden GJ, Carroll ME. Impulsivity (delay discounting) as a predictor of acquisition of IV cocaine self-administration in female rats. Psychopharmacology. 2005;178(2–3):193–201. [PubMed] [Google Scholar]
• Perry JL, Nelson SE, Anderson MM, Morgan AD, Carroll ME. Impulsivity (delay discounting) for food and cocaine in male and female rats selectively bred for high and low saccharin intake. Pharmacology, Biochemistry, and Behavior. 2007;86(4):822–837. [PMC free article] [PubMed] [Google Scholar]
• Piazza NJ, Vrbka JL, Yeager RD. Telescoping of alcoholism in women alcoholics. The International journal of the addictions. 1989;24(1):19–28. [PubMed] [Google Scholar]
• Potenza MN, Steinberg MA, McLaughlin SD, Wu R, Rounsaville BJ, O’Malley SS. Gender-related differences in the characteristics of problem gamblers using a gambling helpline. The American Journal of Psychiatry. 2001;158(9):1500–1505. [PubMed] [Google Scholar]
• Reed SC, Evans SM, Bedi G, Rubin E, Foltin RW. The effects of oral micronized progesterone on smoked cocaine self-administration in women. Hormones and Behavior. 2011;59(2):227–235. [PMC free article] [PubMed] [Google Scholar]
• Reichel CM, Chan CH, Ghee SM, See RE. Sex differences in escalation of methamphetamine self-administration: cognitive and motivational consequences in rats. Psychopharmacology. 2012;223(4):371–380. [PMC free article] [PubMed] [Google Scholar]
• Richmond-Rakerd LS, Fleming KA, Slutske WS. Investigating Progression in Substance Use Initiation Using a Discrete-Time Multiple Event Process Survival Mixture (MEPSUM) Approach. Clinical Psychological Science. 2016;4(2):167–182. Available at: http://cpx.sagepub.com.proxy.lib.umich.edu/content/4/2/167.full.pdf+html. [PMC free article] [PubMed] [Google Scholar]
• Roberts DC, Bennett SA, Vickers GJ. The estrous cycle affects cocaine self-administration on a progressive ratio schedule in rats. Psychopharmacology. 1989;98(3):408–411. [PubMed] [Google Scholar]
• Roth ME, Carroll ME. Sex differences in the escalation of intravenous cocaine intake following long- or short-access to cocaine self-administration. Pharmacology, Biochemistry, and Behavior. 2004;78(2):199–207. [PubMed] [Google Scholar]
• Schuckit MA, Daeppen JB, Tipp JE, Hesselbrock M, Bucholz KK. The clinical course of alcohol-related problems in alcohol dependent and nonalcohol dependent drinking women and men. Journal of Studies on Alcohol. 1998;59(5):581–590. [PubMed] [Google Scholar]
• Sinha R, Garcia M, Paliwal P, Kreek MJ, Rounsaville BJ. Stress-induced cocaine craving and hypothalamic-pituitary-adrenal responses are predictive of cocaine relapse outcomes. Archives of General Psychiatry. 2006;63(3):324–331. [PubMed] [Google Scholar]
• Sisk CL, Zehr JL. Pubertal hormones organize the adolescent brain and behavior. Frontiers in Neuroendocrinology. 2005;26(3–4):163–174. [PubMed] [Google Scholar]
• De Souza MA, Centenaro LA, Menegotto PR, Henriques TP, Bonini J, Achaval M, Lucion AB. Prenatal stress produces social behavior deficits and alters the number of oxytocin and vasopressin neurons in adult rats. Neurochemical Research. 2013;38(7):1479–1489. [PubMed] [Google Scholar]
• Stevens SJ, Murphy BS, McKnight K. Traumatic stress and gender differences in relationship to substance abuse, mental health, physical health, and HIV risk behavior in a sample of adolescents enrolled in drug treatment. Child Maltreatment. 2003;8(1):46–57. [PubMed] [Google Scholar]
• [Accessed: 21 June 2016];Substance Abuse and Mental Health Services Administration. 2014 www.samhsa.gov [Online]. Available at: http://www.samhsa.gov/data/sites/default/files/NSDUHresultsPDFWHTML2013/Web/NSDUHresults2013.htm#2.5.
• Thomas MB, Hu M, Lee TM, Bhatnagar S, Becker JB. Sex-specific susceptibility to cocaine in rats with a history of prenatal stress. Physiology & Behavior. 2009;97(2):270–277. [PubMed] [Google Scholar]
• Vidal C. The Sexed Brain: Between Science and Ideology. Neuroethics. 2012;5:295–303. [Google Scholar]
• Volkow ND, Wang GJ, Telang F, Fowler JS, Logan J, Childress AR, Jayne M, Ma Y, Wong C. Cocaine cues and dopamine in dorsal striatum: mechanism of craving in cocaine addiction. The Journal of Neuroscience. 2006;26(24):6583–6588. [PMC free article] [PubMed] [Google Scholar]
• Walitzer KS, Dearing RL. Gender differences in alcohol and substance use relapse. Clinical Psychology Review. 2006;26(2):128–148. [PubMed] [Google Scholar]
• Wallen K. Nature needs nurture: the interaction of hormonal and social influences on the development of behavioral sex differences in rhesus monkeys. Hormones and Behavior. 1996;30(4):364–378. [PubMed] [Google Scholar]
• Ward IL, Stehm KE. Prenatal stress feminizes juvenile play patterns in male rats. Physiology & Behavior. 1991;50(3):601–605. [PubMed] [Google Scholar]
• Wegener N, Koch M. Behavioural disturbances and altered Fos protein expression in adult rats after chronic pubertal cannabinoid treatment. Brain Research. 2009;1253:81–91. [PubMed] [Google Scholar]
• Westenbroek C, Perry AN, Becker JB. Pair housing differentially affects motivation to self-administer cocaine in male and female rats. Behavioural Brain Research. 2013;252:68–71. [PMC free article] [PubMed] [Google Scholar]
• Wiens TK, Walker LJ. The chronic disease concept of addiction: Helpful or harmful? Addiction research & theory. 2015;23(4):309–321. [Google Scholar]
• Willuhn I, Burgeno LM, Everitt BJ, Phillips PE. Hierarchical recruitment of phasic dopamine signaling in the striatum during the progression of cocaine use. Proceedings of the National Academy of Sciences of the United States of America. 2012;109(50):20703–20708. [PMC free article] [PubMed] [Google Scholar]
• Willuhn I, Wanat MJ, Clark JJ, Phillips PE. Dopamine signaling in the nucleus accumbens of animals self-administering drugs of abuse. Current topics in behavioral neurosciences. 2010;3:29–71. [PMC free article] [PubMed] [Google Scholar]
• Wilson HW, Widom CS. A prospective examination of the path from child abuse and neglect to illicit drug use in middle adulthood: the potential mediating role of four risk factors. Journal of youth and adolescence. 2009;38(3):340–354. [PubMed] [Google Scholar]