1. Introduction: Sex and Gender in Space
This two-paper project was conceptualized during the fourth general meeting of the NeuroGenderings Network, held in New York in March 2016. This international, transdisciplinary network aims to develop innovative and critical theoretical and methodological approaches toward the neuroscience and neuroculture of sex/gender and sexuality (see www.neurogenderings.wordpress.com). Grounded in feminist, gender, and queer theory, work associated with the network has critiqued the “difference-oriented method in brain research” (Schmitz and Höppner 2014a) that parses sex and gender into separate domains and constructs sex as a universal, fixed, dimorphic essence. Such work also questions the very division between “women” and “men” that is so often presupposed in (and reproduced by) empirical neuroscientific work. NeuroGenderings Network scholars use the term “sex/gender” to emphasize the inseparable interactions of biological, social, and cultural dynamics (Kaiser et al. 2009) and seek to develop research methods for empirical neuroscience that takes into account overlap, contingency, entanglement, interindividual variation, and “mosaicism” (as described, e.g., in Joel et al. 2015; Rippon et al. 2014).
Rippon et al. (2014) visualize the difference between essentialist and social context models of neuroscientific research on sex/gender (figure 1). Where the essentialist model (shaded) relies on simple comparisons of female and male subjects at a single point in time and traces any resulting group differences directly back to fixed biological causes, a more complex social context model (unshaded) considers many additional causes. These include influences on subjects before the experiment commences (e.g., personal histories of gendered activities), as well as the design of the study itself (e.g., operationalization of variables). The social context model acknowledges the dynamic and reciprocal influences that gendered social and cultural factors have on behavioral variables.
Here, we aim to apply the social context model to research investigations of “spatial stuff,” a term we adopted to avoid a priori specification. We felt this was the ideal forum to demonstrate alternatives to a standard essentialist approach and to critically highlight the biases of neuro-psycho-scientific knowledge production. Differences in spatial ability are commonly invoked as the most robust and binary sex differences, and also commonly associated with innate, fixed neural substrates. The idea that brains are male or female by natural design, and that men are naturally superior to women in spatial cognition as a result, has been mobilized to naturalize and justify gender inequalities in STEM (science, technology, engineering, mathematics) fields (Liben 2015; Reilly and Neumann 2013). Research on sex/gender and spatial cognition therefore motivates discussions about the social impact of scientific practices as well as scientific rigor.
We aim to use feminist and queer informed neuroscience perspectives (e.g., Bluhm, Maibom, and Jacobson 2012; Dussauge and Kaiser 2012; Fine 2010; Jordan-Young 2010; Schmitz and Höppner 2014b) first to debate possible approaches to spatial cognition that account for the multifaceted dimensions and interactions that shape brain structures, functions, and behaviors in relation to sex/gender, and second to discuss research questions and methods that will move the field beyond biological determinism and sex essentialism. Such a debate also uncovers a range of difficulties and dissensus, which we present as valuable in addressing the issues associated with developing such an approach.
Our initial thought space, produced at the NG4 meeting, represents our thinking about approaching spatial cognition in figure 2. In this conceptual space, we mapped some of the concerns that come into play when we think critically about spatial research in relation to sex/gender. It represents the interlinkage of the personal and professional perspectives of those involved in spatial cognition, experimental issues, and discursive or ethical aspects – all situated in a larger sociocultural context which shapes and is shaped by these interwoven phenomena.
Once we mapped the multitudinous issues associated with defining and investigating spatial cognition, we decided to adopt the nonspecific term “spatial stuff” as a deliberate space holder. We wish to avoid prescriptive advance specification of what could be included and how it might be defined, aware that such early specifications can invoke certain assumptions, associations, and biases. Additionally, we wish to acknowledge the multifaceted and wide-ranging nature of this (and indeed any) research sphere our mapping identified.
Our aim is to develop an approach for a study that explores spatial stuff from a critical sex/gender perspective and might take into account the complex and dynamic interplay of all the factors enfolded therein. Our strategy is two-fold and is represented in the two parts of this paper.
In part 1, we aim to assess the current state of the field and review evidence that points to the biosocial nature of spatial stuff to support our claim that the development of spatial stuff cannot be understood with an essentialist model. We do not intend to provide an exhaustive overview of the current knowledge on sex/gender differences in spatial stuff. Rather, we provide insight into how spatial cognition has been studied in terms of sex/gender differences and highlight those questions and concerns that need to be addressed in order to advance our understanding in this area.
In part 2, we illustrate the dissensus-based discourse associated with the development of a spatial stuff research protocol specifically designed to address the issues identified. Our discussion is based on the steps preceding the production of a preregistration model, following a concept widely used in medical research, where each step of a specific research design, from hypotheses through to data analyses, is subject to peer review in advance of the research. We felt that the need to elucidate each step in this way could provide an ideal forum for the application of a critical gender lens to a spatial stuff research journey.
The purpose of this framework, and of the possible research protocols that we can extract from it, is to foster more empirically adequate and insightful research practices by encouraging researchers to adopt a more critical approach to spatial stuff (e.g., by questioning common-sense definitions of sex and gender, or by considering the dynamic interaction of biological and experiential factors that lie beneath individual or group-based differences in spatial cognition).
We are particularly cautious of the reification of boundaries and binaries and the risk of creating a paradigm that simply repackages deterministic beliefs in seemingly progressive words. As authors, we bring different discursive concerns, such as social power relations, ethics of intervention, feminist philosophy of science, and acknowledging but not overselling plasticity findings. We conclude by discussing these issues at the end of the second part of this paper.
2. Investigating the Multifaceted Dimensions that Shape Spatial Stuff
Analyses of spatial stuff comprise a wide range of tasks. For example, spatial cognition tasks, such as mental rotation, measure the ability to mentally manipulate an object by rotating it, often assessed by asking participants to determine whether different figures represent the same geometrical object seen from different angles (Shepard and Metzler 1971). Environmental cognition tasks measure navigation skills and the development of mental maps with particular spatial cues such as landmarks or directions (Golledge 1987). These include the ability to find one’s own position or the positions of objects and their relations in space, to navigate in space, to show directions to a goal, to find routes, or to recall landmarks from the environment.
Here, we present an overview of research on the many dimensions and intersections that shape spatial and environmental competencies and strategies, with a focus on biosocial interactions in their development and on sex/gender aspects.
2.1. Competencies: What Differences Do We Aim to Investigate?
Since the 1990s, the view that men, on average, outperform women on spatial cognition has changed to a view that men and women have evolved to specialize in different skills (e.g., Sherry and Hampson 1997; Silverman, Choi, and Peters 2007). This has resulted in an idea of “male” and “female” brains, designed to differ in ways that ensure “behavioral complementarity” between the sexes (Ingalhalikar et al. 2014). Biologically framed positions assume that the sex of the brain is hardwired before birth, primarily because testosterone, secreted by the fetus once its gonads have developed, “masculinizes” it (Bao and Swaab 2011). Socialization may impact brain development at a later point in time, such thinking argues, but brain sex itself is decidedly precultural: “From the start the environment is acting on differently wired brains in boys and girls” (Kimura 1992, 118). Albeit extremely contentious, this concept of hard-wired differences is habitually invoked in research and even more in popular science to this day (Grossi 2017).
Findings on spatial or environmental cognition show many inconsistencies in the framing of a general sex/gender difference (for an overview, see Schmitz 1999). Research from the 1980s to the 1990s contrasted males’ outperformance in route learning and processing directions from an unknown map to females’ better competence in remembering and positioning landmarks (for review, see Kimura 1992). Contradictory results, however, have been reported when it comes to the accuracy of assessing direction and distance to unseen targets in a familiar environment. Some studies report a male advantage (Galea and Kimura 1993; Holding and Holding 1989; Lawton 1994; Lawton, Charleston, and Zieles 1996; Miller and Santoni 1986), whereas others do not find gender differences in environmental competencies (Golledge, Dougherty, and Bell 1995; Kirasic, Allen, and Siegel 1984; Montello and Pick 1993; Sadalla and Montello 1989). Some of these contradictory results could be discussed in relation to different sample sizes, arguing that the results of studies with higher sample sizes are more reliable than those with fewer participants. However, except the study by Lawton (1994) with 228 women and 138 men, most studies examined only medium or small numbers of participants. For example, among studies reporting sex/gender differences, Galea and Kimura (1993) studied forty-eight women and forty-eight men; Lawton, Charleston, and Zieles (1996) studied fifty-five women and twenty men; Miller and Santoni (1986) studied twenty girls and twenty boys (age eleven), twenty girls and twenty boys (age nineteen), and twenty-eight women and thirty-one men (adults); and Holding and Holding (1989) studied only twelve women and twelve men. The same holds for those studies that reveal no differences in environmental skills (null findings): Golledge, Dougherty, and Bell (1995) studied twenty women and twenty men; Kirasic, Allen, and Siegel (1995) studied twenty-four women and twenty-four men; Montello and Pick studied eleven women and thirteen men; and Sadalla and Montello (1989) studied twenty-five women and twenty-one men. In consequence, the argument of a general sex difference in environmental cognition remains controversial due to the low statistical power from these small samples, in addition to participants who differ in age and environmental experience.
Moreover, Cohen’s d, a statistical measure to assess the strength of difference between group results, turned out to be only small to moderate for sex/gender differences in a meta-analysis of general spatial and environmental cognition (d=0.11–0.35) (Hyde 2005). It shows a robust difference between female and male participants in only one task category, the mental rotation tasks (d=0.56 in Linn and Peterson 1985; d=0.73 in Voyer, Voyer, and Bryden 1995). The task requires participants to rotate an object in their mind’s eye in order to judge whether or not other drawn images represent the same geometrical object seen from different angles. Several studies suggest, however, that this difference is diminished or even eliminated when more realistic stimuli are used – for example, when the task involves 3D instead of 2D stimuli or mounted models instead of drawings (Fisher, Meredith, and Gray 2018; McWilliams, Hamilton, and Muncer 1997; Neubauer, Bergner, and Schatz 2010).
Thus, there are many spatial competencies, but mental rotation has dominated research on spatial stuff and has played a crucial role in entangling sex/gender with spatial cognition. This set of subtasks, although it does not represent spatial competencies comprehensively and does not necessarily explain complex real-world environmental cognition, remains prominent in the research of sex/gender aspects in spatial skills. This narrow focus on mental rotation, combined with the biological framework in which research outcomes are typically interpreted, suggests that research is primarily motivated by confirming that sex is a fundamental division that gives rise to precultural and pre-experiential differences in spatial skills. As a result, developmental and social aspects of sex/gender variation in mental rotation (as well as other spatial competencies) remain underexamined.
2.2. Development and Social Experience with Spatial Stuff
To start with the most prominent sub-test for measuring spatial competencies, there is a broad debate on what factors are responsible for sex/gender differences in mental rotation skills (Coluccia and Louse 2004). A frequently cited string of argumentation for biological inheritance, i.e., of a sex difference, is that infant girls show higher interest in a familiar stimulus that has been rotated compared to infant boys. Based on the assumption that gaze duration indicates looking preference, and that looking preference is guided by stimulus novelty, these results have been taken to indicate that girls do not recognize a rotated stimulus as easily as boys do (e.g., Quinn and Liben 2008). Since these studies are conducted on very young subjects, supposedly before gendered socialization can take effect, such results are taken to support the notion of a hardwired sex difference in mental rotation. However, as Levine et al. (2016) point out, not all infant studies of mental rotation find the same differences. In particular, it seems that studies that use the most rich and realistic 3D stimuli tend to yield null findings (see also Frick and Möhring 2013). Moreover, Levine et al. discuss alternative explanations for the purported novelty effect: boys may have an advantage in recognizing orientation-independent relations between parts of an object rather than in mental rotation ability; or girls may be more interested in location novelty than in object novelty. What all these interpretations share is that they propose some inherent sex difference in spatial cognition that would help to explain differences found in older subjects. However, the available evidence fails to clarify the exact nature of this difference, as well as the precise developmental processes through which such differences may emerge and persist or expand with age.
At any rate, it is unlikely that a relationship between differences in infants and differences in older children and adults can be explained with reference to biology alone. Indeed, observational studies that take into account prior experiences or experimental studies in which spatial cognition is trained strongly suggest that spatial competence can be acquired with practice. In their meta-analysis of 217 training studies, Uttal et al. (2013) found an average effect size for trained groups versus control groups of 0.47 (Hedge’s g, a statistical measure similar to Cohen’s d). Training effects differed by task categories. The smallest average effect size was found for intrinsic-static tasks, which involve manipulation of the internal spatial relations of a stationary object (g=0.32), and the largest average effect size was found for extrinsic-static tasks, which concern the spatial relationships between multiple stationary objects (g=0.69). Dynamic tasks, in which objects are moved, yielded intermediate training effects (g=0.44 for intrinsic dynamic tasks, which include a mental rotation task, and g=0.49 for extrinsic dynamic tasks). Uttal et al. (2013) also tested whether sex/gender moderated training effects. Despite the fact that individual differences in initial skill predicted training effectiveness (with those who scored the lowest at pretesting demonstrating the highest gains), training effects were equally substantial for men and women, so that an initial gender gap that favored men was maintained. This confirmed a similar finding in an earlier review (Baenninger and Newcombe 1989).
Nevertheless, some studies have found training to diminish or even close a sex/gender gap. For example, in a sample of forty-eight undergraduate students, Feng, Spence, and Pratt (2007) found that a sex/gender difference in spatial attention – which supports higher-order spatial cognition – was effectively closed after ten hours of video game play. In addition, the training also reduced an initial difference in mental rotation. It is of particular interest here that the training task and the criterion task were quite dissimilar, which demonstrates transfer of training experience from one particular task to another (Lawton 2010). Tzuriel and Egozi (2010) used a training task of visuospatial processing in 116 children aged seven to eight. After eight weekly forty-five-minute sessions, an initial gender gap that favored boys disappeared in the trained groups, with trained girls outperforming untrained boys at post-testing. Other studies have also shown that video game practice increases spatial task scores (Cherney 2008; Cherney and Neff 2004; Terlecki, Newcombe, and Littel 2008), and that such practice can lead to similar environmental cognition scores for men and women after training on or prompting participants on the specific skill, e.g., for targeting directions, assessing distances or recalling landmarks, or even for navigating in an unfamiliar environment (Galea and Kimura 1993; Kirasic, Allen, and Siegel 1984; McGuinness and Sparks 1983; Ward, Newcombe, and Overton 1986).
On what conditions training can close an existing gender gap in spatial cognition warrants further investigation. However, research on the malleability of spatial cognition leaves little doubt that sex/gender differences in spatial skills can be shaped by differential prior experiences. In further support of this notion, Jirout and Newcombe (2015), using a US sample of 847 children aged four to seven, found that boys play more with spatial toys than girls, and that this difference in play frequency partially accounts for an observed advantage of boys on a block design task. Similarly, Terlecki and Newcombe (2005), in a sample of 1,300 undergraduate students, found that male students played significantly more video games than female students, and that this difference in experience mediated gender differences on a mental rotation task. Quaiser-Pohl, Geiser, and Lehmann (2006) studied 861 German children aged ten to twenty and found that boys not only play more video games than girls, but also tend to play different kinds of games. Whereas girls preferred logic and skill-training games, boys preferred action and simulation games. Since simulation games, especially those that involve aiming at targets, could develop mental rotation in a way that other forms of video game play do not, this difference may partially explain men’s advantage on a mental rotation task. Practice or training of particular skills, following recent studies, can diminish or even close a sex/gender gap, maybe with differing dynamics according to the participants’ age (Levine et al. 2016). However, it should be stated that in the last years the number of girls who play first-person shooters is at least as high as that of boys of a similar age (Hahn 2017). The impacts of these developments, and on the valence of characters and game content (e.g., whether the characters are portrayed with specific physiological and psychological gender attributes), may be an interesting topic for future research.
2.2.1. Spatial Stuff Strategies and Competences
Social development and learning experience play an important role in the development of spatial and environmental behavior (Kimura 1992). At this point, a differentiation between strategy and competence studies is necessary. Gender differences in environmental knowledge may be related to different environmental strategies rather than to different competencies. Environmental strategies, according to a definition by Lawton (1994), comprise, for example, a wayfinding strategy that depends on route directions (left/right) versus on particular landmarks. A configurational strategy would take Euclidian markers as metric distances and cardinal directions as reference points for macro-spatial orientation. In turn, environmental competencies result from differing preferences for one or the other strategy (Lawton 2010; Schmitz 1997, 1999). For example, a male advantage in route knowledge and route recalling compared to a female advantage in landmark recalling turned out to correlate with a higher percentage of women preferring a more landmark-based strategy and men preferring a more configurational strategy to navigate in space (Galea and Kimura 1993). These assumptions have been underpinned by studies from Lawton, who found that men report a higher use of the configurational strategy and women report a higher use of landmarks and route directions (Lawton 1994; Lawton, Charleston, and Zieles 1996). The individual development of mental maps through successful learning strategies could explain this manifestation of preferences in environmental strategies. The question, then, is how to discuss the construction of differences in strategies in individual development.
In general, the individual variability in spatial and environmental strategies is often higher than differences between the female and male subjects. In other words, there are more differences among men or among women in skill and strategies with spatial navigation than there are differences between women and men. Successful strategies for navigation by using route directions, configurational cues, and landmarks are learned in childhood and youth, and to a certain extent girls and boys in Western societies still gain different experiences in outdoor navigation. Boys are allowed to discover their environment on their own more than girls, and in line with these experiences, feelings of security and insecurity conjoin that influence the choices individuals later make about their strategies (Schmitz 1999). Anxiety, prior experience in childhood and adolescent outdoor navigation, and even professional practice shape strategic preferences that, in consequence, correlate with measurement of competencies (Lawton 1994; Lawton and Kallaij 2002; Schmitz 1999). Independent home range exploration (e.g., self-directed and unaccompanied) is an important factor to improve children’s pointing accuracy even in unfamiliar environments (Neidthardt and Popp 2010). Furthermore, children of about seven years showed better results in pointing to unseen objects in real environments compared to in a virtual simulation experiment (Neidthardt and Popp 2012). Influences of real movement in contrast to virtually simulated movement have to be taken into account in researching environmental cognition (Neidthardt and Schmitz 2001).
As with mental rotation, training turns out to shape navigation strategies. A regression analysis in a study by Livingston-Lee et al. (2014), in which participants were trained to navigate a maze with or without cue objects, found that wayfinding strategies are better explained by training (combined with environmental awareness) than by gender. Likewise, a navigation study in a three-dimensional maze with children and adolescents between seven and sixteen years showed that prior experience, scores of motivation, self-confidence, and anxiety in wayfinding all better explained the use of landmarks or directions in navigation strategy than did gender (Schmitz 1997). Lawton (1994) has presented similar results for adults.
Some research on spatial stuff has considered intersections of gender with sociocultural factors. Berry (1966), for example, found no gender differences in spatial skills among Inuit people. This finding is representative for societies that are built on a less gendered division of labor (in which girls and boys hunt) and stands in contrast to sex/gender differences in the West African Temne, who do show greater gendered division of labor. In addition, Neidthardt and Popp (2012) found better competencies of pointing accuracy in Namibian kindergarten children, who could develop spatial experience by exploring extended home ranges, compared to German children growing up in rural areas. In addition, there were no gender differences among the five-year-old Namibian children. In a US sample of school children, Levine et al. (2005) found that boys outperformed girls on two different spatial cognition tasks (including a mental rotation task) among children of high and middle socioeconomic status, but not among those of low status – indicating that gender disparities in spatial skills cannot be accounted for by biological factors alone.
On a more general level, studies that research sociocultural impacts on cognitive skills open up the view to the embeddedness and mutual interactions between individual behavior and powerful gendered culture with its dimensions of segregation, and its inclusions and exclusions of experiences and practices. Hyde (2014) for example, in a large study on mathematic skills of adolescents, found that scores on social gender equity measures in a society – for example, women’s degree of inclusion in the political sphere, labor market segregation, or gender pay gap – predict gender effects in math skills.
In summary, all of the findings on the role of social experiences, type of training, strategies, and competencies in many aspects of spatial stuff demonstrate the misconception of a purely essentialist approach to research in this area. Additionally, it appears that between-sex differences in brain structure, cognition, or behavior are typically reported as the most informative and consequential aspect of a given data set, even though these are small or modest, whereas between-group similarities and within-group variation are typically ignored (Hyde 2005). In contrast to such approaches, we suggest that methods for studying the development of spatial stuff should be designed to highlight patterns of variation and change beyond simple group comparisons, including individual variation and changes over time. Moreover, we question whether the category of sex/gender is actually useful for explaining inter-individual differences in spatial strategies and competencies. Consequently, this point leads to questioning the conceptualization of independent variables in studies of spatial stuff and touches the question of how to categorize research participants (see part 2 of this paper).
2.2.2. Stereotype Threat
In close relationship with the experience-strategy dimension, more recent research has outlined the so-called stereotype threat effect, which potentially shapes observed group differences when aspects of social group membership, such as race or gender, are made salient (Fine 2010; Steele and Aronson 1995). Stereotype threat refers to the fear that one will confirm a negative stereotype about a category to which one belongs. A stereotype threat effect occurs when this fear interferes with the performance of the stigmatized group. One way to make this fear more salient in tasks is by informing research participants that one group (e.g., male participants) commonly outperforms another group (e.g., female participants) on the task they are about to complete.
Stereotype threat has been shown to affect girls’ and women’s performance on tasks related to math, science, and spatial skills, including the mental rotation tasks (Estes and Felker 2012). For example, Moè and Pazzaglia (2006) found that men’s and women’s accuracy on a mental rotation task increased after participants were told that their gender is typically superior but decreased after they are told that the other gender is typically superior. Similarly, Ortner and Sieverding (2008) found that priming with a “typical male” stereotype did not yield sex/gender differences in task performance, whereas priming with a “typical female” stereotype was related to lowered mental rotation scores in women. In a sample of 216 fourth graders, Neuburger et al. (2012) found that an initial advantage for boys on a mental rotation task disappeared after the children were instructed that there was usually no gender difference on the task, or that girls typically performed better. However, an earlier study with a similar sample and design did not find any stereotype threat effect (Titze, Jansen, and Heil 2010). A recent study by Sanchis-Segura et al. (2018) found effects of stereotype threat in a 3D mental rotation task. Stereotypic gender-science associations correlate with task performance in females and males, but gender differences only appeared under stereotype re-activating conditions and diminished with higher level of self-confidence. Moreover, the gender differences could only be affirmed for humanities students but not for STEM students.
Stereotype threat effects have also been examined by presenting a task in various ways. For example, Sharps, Welton, and Price (1993) observed a gender difference in spatial memory by using a paper map and a model of wooden blocks and suggesting that the map condition negatively impacted women’s performance. Some research suggests that even merely asking participants about their gender prior to testing can affect task performance, as the priming of one’s identity activates gender stereotypes with which one has become familiar through earlier socialization (e.g., McGlone and Aronson 2006; but see Stricker and Ward 2004 for different findings).
Recently, however, the stereotype threat effect has been questioned by critics who argue that the literature on this topic suffers from publication bias and p-hacking (Flore and Wicherts 2015; Stoet and Geary 2012). Thus, it is likely that the significance of the stereotype threat effect has been overstated. Until the issue of publication bias has been fully resolved, however, it would be appropriately cautious to address the potential effect of explicit or implicit stereotyping biases in researching spatial stuff. A pertinent question, then, is whether stereotype threat should be operationalized and explicitly included in the experimental design, or whether researchers should try to avoid triggering stereotypes.
2.3. Brain-Behavior Relationships and Brain Plasticity in Spatial Stuff Research
2.3.1. Brain and Behavior
The alleged robustness of the finding that men outperform women on tests of spatial cognition has contributed to the essentialist view that hardwired brain differences determine key cognitive skills. Indeed, there are prime examples of neurosexism (Fine 2013) in this research canon, where findings of differences in the brain have been interpreted in terms of stereotyped male superiority in spatial cognition tasks, even when cognitive skill was not measured in the scanner (Ingalhalikar et al. 2014) or at all (Tomasi and Volkow 2012), thus contributing to continued belief in sex stereotypes and their biological origins. As Rippon et al. (2014) argue, reverse inference is a questionable practice, and drawing on gender stereotypes rather than on empirical data to inform such inferences is clearly problematic (see also Bluhm 2013a, 2013b). A key aspect of this ongoing debate is the paucity of attention to issues of neuroplasticity in understanding brain-behavior relationships (Fine et al. 2013).
The concept of neuroplasticity describes how the environment and experience form the neuronal network and its activity pattern. Having already been researched for more than forty years, starting with Rosenzweig et al. (1962), it finally received more and more attention moving to the center of brain research by the time the “decade of the brain” was proposed in the 1990s. The plasticity perspective has led to a reconsideration of the bio-social brain on material, behavioral, and identity levels. It disrupts the reductionistic biological determinism whereby seemingly natural brain differences are seen to cause and so to legitimize gendered (and intersected) societal orders and norms (Pitts-Taylor 2010; Schmitz 2010).
Although the idea that experience changes brain structures and their functionality from prenatal stages throughout the whole lifespan is now a common concept in neuroscience, most studies of sex/gender differences in the brain still apply a snapshot approach (Schmitz 2010) and interpret brain activity or structure at a single point in time based on an imaginary notion of a stable – and sexed – individual brain. As Fine (2013) argues, this approach cannot yield any information about possible experiences that have contributed to observed neuronal individual or group differences. Because of this void, an outdated understanding of development as the unfolding of a preprogrammed plan – which environmental factors can only either facilitate or thwart – continues to dominate the discourse on sex/gender and the brain (Fine et al. 2013). Despite substantive evidence that gendered cognition and behavior differ across time, place, and context, “brain sex” is thus often kept firmly behind a “neurobiological line of defence” (Rubin 2009, 417) that separates what is plastic, unstable, and context-dependent from what is natural, timeless, and fixed (Kleinherenbrink 2014). Scholars from inside neuroscience have therefore called for a critical neuroscience, and particularly neurofeminist, stance to account for the dynamic interaction of biological and environmental factors, and to consider context and change, as well as the variation between and within individual brains, when formulating hypotheses, specifying a study design, and interpreting data (e.g., Choudhury and Slaby 2011; Joel and Yankelevitch-Yahav 2014; Rippon et al. 2014).
The misconception of the essentialist view is evident from scrutiny of the effects of social context on spatial performance and its neural correlates. Findings regarding the malleability of spatial performance, as training-based behavioral changes demonstrate, are complemented by evidence of neural changes during spatial skills training. For example, Haier et al. (2009) trained adolescent girls’ visual-spatial problem-solving skills for three months with Tetris and observed both structural and functional changes in frontal brain areas, which may indicate a shift towards a more effective strategy. Similarly, Jaušovec and Jaušovec (2012) reported that eighteen hours of origami training significantly improved women’s performance on a mental rotation task, accompanied by decreased frontal brain activity and increased activity in parietal areas. Whereas these studies only included women in their training paradigms, Neubauer, Bergner, and Schatz (2010) assessed adolescent boys and girls (N=77) before and after training, and found a complex interaction among sex, training, and dimensionality. Before training commenced, boys scored higher than girls on a 2D mental rotation task but not on a 3D task. As already mentioned, this effect of stimulus design has been found in several studies. After training, the gender difference on the 2D task was diminished, indicating that girls benefited from training more than boys. Surprisingly, however, training decreased brain activation during the task (again, suggesting more efficiency) for women in the 3D condition only (and for men in both the 3D and the 2D condition), warranting further clarification of the relationship between behavioral and neural measurements.
Brain researchers have also analyzed the processing of navigational and landmark cues during orientation behavior with the help of brain imaging technologies, such as functional Magnetic Resonance Imaging (fMRI). Maguire et al. (2000) found correlations between increases in posterior areas of the hippocampus (a structure in the inner part of the brain that is strongly associated with the processing of orientation information) and timelines of extended navigation experience in London taxi drivers. Her recent studies confirmed plastic changes in the right hippocampus and the right parietal cortex (both responsible for the recognition of navigational cues) and in the parahippocampus (responsible for object localization) due to spatial navigation experience (Maguire, Woollett, and Spiers 2006; Woollett and Maguire 2011). Thus, these findings provide strong evidence that changes in the brain are not only possible but can be linked to the impact of actual spatial experience.
Furthermore, studies on the neural correlates of stereotype threat effects have suggested that social pressures related to gender can affect brain activation patterns – although we must keep in mind the aforementioned discussion surrounding stereotype threat when considering these findings. Wraga et al. (2007) found that women in a negative stereotype condition showed increased activity in areas associated with emotional load, whereas women in a positive stereotype condition showed increased activation in visual processing areas and no increased emotional load. The researchers then used these activation patterns to successfully predict performance on a mental rotation task. Krendl et al. (2008) replicated a negative stereotype threat effect on women’s math processing, with decreased brain activity in cortical areas accompanied by increased activity in areas associated with self-monitoring and emotional processing. However, in a study with thirty-two boys and thirty-one girls aged fifteen to eighteen, Dunst et al. (2013) failed to replicate a stereotype threat effect on the performance on a mental rotation task. Behavioral data showed no differences between girls and boys in either the neutral or the stereotype threat condition, despite an increase of cortical arousal in girls in response to a negative stereotype. However, the authors did find that the relationship between IQ and brain activation was modulated by sex and stereotype exposure condition. A higher IQ was associated with more neural efficiency (indicated by lower brain activation) for boys in the neutral condition, but not for boys in the stereotype threat condition or for girls in either condition. The authors argue that this is possibly because boys in the neutral condition experienced the lowest amount of pressure to perform.
Overall, studies that assess how prior experiences and experimental conditions affect brain structure and function, and to what extent these effects can explain behavioral differences, suggest that brain plasticity is involved in the emergence of sex/gender differences in spatial stuff. However, these relationships are complex – for example, behavioral differences or similarities are not always congruent with neurological differences or similarities (as in Neubauer et al. 2010). This might be due to interactions with other differences, such as brain size, the ratio of white and grey matter, or hormones, all of which correlate with sex/gender, whereby one difference can compensate for another (Dunst et al. 2013; Neubauer et al. 2010, see also De Vries 2004). Such discrepancies pose a serious challenge for researchers who seek to explain stereotypical differences in behavior in neurological terms, since they easily allow for biased interpretations. That is, since the relationship between behavioral differences and neural differences is not straightforward, it is easy to interpret any brain difference as underlying an overt behavioral difference.
For example, Grön et al. (2000) investigated the brain activation of twelve women and twelve men as they navigated a virtual maze. They set out to focus on differences between women and men, and crafted hypotheses that matched prior patterns of sex/gender difference with current understandings of the brain areas that are associated with specific skills and tasks. Accordingly, they hypothesized that men’s right hippocampus would be more activated because men prefer directional cues in way finding, and women’s parahippocampus would be more activated because women prefer landmarks in way finding. The results were quite astonishing, but the authors’ interpretation was even more so. In the study, men showed, on average, a more intense activation in the left hippocampus, which the authors interpreted to represent their use of complex geometrical tools for spatial navigation. However, navigation processing, according to Maguire, Frackowiak, and Frith (1997), is attributed to the right hippocampus. Women, on average, used the right parietal cortex and the right frontal cortex more intensively. Even though this activation occurred in a different location than the one the authors proposed in their hypotheses, they interpreted their finding as proof for women’s preferred landmark processing, without taking into account alternative explanations, e.g., that frontal cortex activity may potentially represent processes of consciously assessing the task situation. In spite of these severe inconsistencies, compounded by problems with the statistical analysis (see Blanch et al. 2004) and the small number of participants (twelve men and twelve women), this study has been cited prominently as proof for biologically determined differences between women’s and men’s brains and their performance in spatial orientation. Furthermore, other studies (e.g., Blanch et al. 2004) point to a substantial inter-individual variability in the activation of the discussed brain structures that is unrelated to gender and lend no support to the notion that brain activation, spatial strategies, and performance outcomes, in general, differ between groups of women and men. Activity pattern and brain structures are interrelated, and a meta-analysis by Tan et al. (2016) also worked out that the degree of individual variability in hippocampal structures was higher than sex/gender differences. Thus, the state of research on spatial and environmental cognitive processing according to the preference for landmarks (assumed as female specialization) in contrast to the acquisition of directional cues (hypothesized as male priority) present substantial discrepancies. The same is true for the inadequate note on sex/gender differences in the activation of certain areas of the brain during these processes. Instead, the variability within gender groups in most studies is greater than the assumed differences.
2.3.2. Hormones and Behavior
Research into the role of hormonal factors in the prenatal organization and the postnatal activation of brain areas associated with key cognitive skills has often focused on visuo-spatial abilities (Schoning et al. 2007). However, the evidence for a connection between mental rotation and androgens (either “prenatal” or circulating) is inconsistent, with some studies finding a significant relationship and others finding none (e.g., Auyeung et al. 2012; Grossi and Fine 2012; Hines 2006; Puts et al. 2010). As with brain imaging research, there have been many critiques of the methodology and interpretation of findings in this area (Fine 2017; Jordan-Young 2010).
Again, the omission of contextual factors is key to the scrutiny of such studies. Any potential relationship between prenatal hormone exposure and postnatal spatial competence is likely to be moderated by a range of experiences, e.g., how many video games a child plays. Likewise, the impact of socialization depends on biological and other social factors as well. As mentioned above, in a number of studies girls or women gained more from spatial cognition training than did boys or men. This might be due to a ceiling effect in boys and men or to biological, psychological, or contextual confounders that co-vary with sex/gender (e.g., hormones, body esteem, motivation, gender beliefs, parental support, stress, diet, etc.). In other words, two children who play the same video game do not necessarily share the same experience. Gameplay experience may thus be understood as an interaction between at least three dimensions: the gamer’s prior experiences and traits, situational aspects (e.g., stereotype threat), and the game’s characteristics. With respect to the latter, for example, the genders of a game’s protagonists or whether its objectives or overall atmosphere invoke associations with masculinity or femininity may affect how a child experiences the game (cf. findings that gendered associations affect task performance, discussed above).
A similar level of complexity appears when we consider the impact of postnatal hormone levels on gendered behavior. Previous research has demonstrated, for example, that testosterone levels change in response to experiences related to competition and dominance (e.g., competing or wielding power), sexuality, partnering, or parenting (reviewed in van Anders 2013; van Anders and Watson 2006). In addition, such effects are not straightforward but appear to be modulated by contextual, psychological, and physiological conditions. For example, the effect of competing or winning on testosterone levels can depend on the location of the competition (Carré 2009), the nature of the competition (Zilioli, Mehta, and Watson 2014), cognitive appraisal (Oliveira and Oliveira 2014), drive for power (Schultheiss and Rohde 2002), and interactions with and base levels of other hormones (Mehta and Josephs 2010). Such moderators may help to explain why hormonal responses to competition or victory have been observed more clearly for men than for women (Jiménez, Aguilar, and Alvero-Cruz 2012). Van Anders and her colleagues recently proposed a “gender-testosterone pathway” to highlight this change in cause-effect thinking – suggesting that, as men are encouraged to engage in testosterone-boosting activities whereas women are not, a “lifetime of gender socialization could contribute to ‘sex differences’ in testosterone” (van Anders, Steiger, and Goldey 2015, 13805).
In addition, there are generally more psychophysiological studies on testosterone for men than there are for women. Studies that investigate relationships between testosterone, psychological correlates, and social situations have generally focused on biological males rather than other groups of people because many researchers operate based on the social construction of testosterone as a “male” and therefore “masculine” hormone. This construction includes the notion that testosterone is of primary relevance to behaviors that are construed as masculine and should therefore primarily be relevant to and exhibited by men. Rather than maintaining this perspective of using the social construction of hormones as masculine or feminine, a social context approach would use as a starting point the specific context-related functionality of a specific hormone in addition to the moderators mentioned above (see, e.g., van Anders 2013).
Taking potential moderators into account, as well as conceptualizing the causal relationship between hormones and behavior as at least bidirectional if not inseparably entangled, may help to elucidate the connections between hormones and spatial stuff, which have so far yielded inconsistent results. Interestingly, in a longitudinal study, Courvoisier et al. (2013) found an association between circulating testosterone and mental rotation performance that was U-shaped for women but inversely U-shaped for men, yet this association disappeared after training. So, as one factor is manipulated, the predictive weight of another shifts – making it impossible to universalize the relationship between a single predictor and the outcome variable of interest.
Studying the development of spatial stuff thus requires paying attention to the dynamic nature of interactions between sex/gender, skill, hormones, practice, and other factors. It turns out to be a misconception that genes and prenatal hormone exposure would preprogram the brain to develop in a masculine or a feminine direction, and that socialization would steer the individual development in a way that either agrees with or diverts from the original design. Instead, we propose, taking up the notion of a gendered testosterone pathway following van Anders et al. (2015) to base studies on spatial stuff on a conception that accounts for the mutual interactions of social and cultural impacts and hormone levels at every stage of brain development and behavior.
3. Designing Studies to Address the Multifaceted Dimensions of Spatial Stuff
In psychological and neurobiological research on sex/gender differences, nature-nurture dualism remains persistent (Eagly and Wood 2013). Yet the inconsistencies evident in the findings from essentialist studies that take the binary dichotomization of sex as the primary (or only) independent variable, and ignore contextual issues such as experience and expectations, indicate the insufficiency and inaccuracy of this approach. Instead, the investigation of spatial stuff requires the consideration of multifaceted dimensions (see figure 3).
Taking the above literature into consideration, we developed a schema that starts to integrate all those factors, their interactions and variations, and the biological dynamics and experiences that could affect spatial stuff. This schema takes seriously the point that critical gender theorists have stressed, namely that nurture and nature are deeply entangled in an enduring network of reciprocal exchange (Fausto-Sterling 2000). Consequently, research methods that address the development of behavioral strategies or skills, and their related brain structures and activity patterns, should be grounded in a theoretical perspective that truly integrates the interaction of biological and material and social/experiential factors – one that does not simply focus on social construction as an alternative to biological processes.
Bibliography
Auyeung, Bonnie, Rebecca Knickmeyer, Emma Ashwin, Kevin Taylor, Gerald Hackett, and Simon Baron-Cohen. 2012. “Effects of Fetal Testosterone on Visuospatial Ability.” Archives of Sexual Behavior 41, no. 3: 571–81.
Baenninger, Maryann, and Nora Newcombe. 1989. “The Role of Experience in Spatial Test Performance: A Meta-Analysis.” Sex Roles 20, no. 5: 327–44.
Bao, Ai-Min, and Dick F. Swaab. 2011. “Sexual Differentiation of the Human Brain: Relation to Gender Identity, Sexual Orientation and Neuropsychiatric Disorders.” Frontiers in Neuroendocrinology 32, no. 2: 214–26.
Berry, John W. 1966. “Temne and Eskimo Perceptual Skills.” International Journal of Psychology 1, no. 3: 207–29.
Blanch, Richard J., David Brennan, Barrie Condon, Celestine Santosh, and Donald Hadley. 2004. “Are There Gender-Specific Neural Substrates of Route Learning from Different Perspectives?” Cerebral Cortex 14, no. 11: 1207–13.
Bluhm, Robyn, Anne Jaap Jacobson, and Heidi Lene Maibom. 2012. Neurofeminism: Issues at the Intersection of Feminist Theory and Cognitive Science. Hampshire, UK: Palgrave MacMillan.
Bluhm, Robyn. 2013a. “Self‐Fulfilling Prophecies: The Influence of Gender Stereotypes on Functional Neuroimaging Research on Emotion.” Hypatia 28, no. 4: 870–86.
Bluhm, Robyn. 2013b. “New Research, Old Problems: Methodological and Ethical Issues in fMRI Research Examining Sex/Gender Differences in Emotion Processing.” Neuroethics 6, no. 2: 319–30.
Carré, Justin M. 2009. “No Place Like Home: Testosterone Responses to Victory Depend on Game Location.” American Journal of Human Biology 21, no. 3: 392–4.
Cherney, Isabelle D. 2008. “Mom, Let Me Play More Computer Games: They Improve My Mental Rotation Skills.” Sex Roles 59, no. 11–12: 776–86.
Cherney, Isabelle D., and Nicole L. Neff. 2004. “Role of Strategies and Prior Exposure in Mental Rotation.” Perceptual and Motor Skills 98, no. 3 suppl: 1269–82.
Choudhury, Suparna, and Jan Slaby, eds. 2011. Critical Neuroscience: A Handbook of the Social and Cultural Contexts of Neuroscience. West Sussex, UK: Wiley Blackwell.
Coluccia, Emanuele, and Giorgia Louse. 2004. “Gender Differences in Spatial Orientation: A Review.” Journal of Environmental Psychology 24, no. 3: 329–40.
Courvoisier, Delphine S., Olivier Renaud, Christian Geiser, Kerstin Paschke, Kevin Gaudy, and Kirsten Jordan. 2013. “Sex Hormones and Mental Rotation: An intensive Longitudinal Investigation.” Hormones and Behavior 63, no. 2: 345–51.
De Vries, Geert J. 2004. “Minireview: Sex Differences in Adult and Developing Brains: Compensation, Compensation, Compensation.” Endocrinology 145, no. 3: 1063–8.
Dunst, Beate, Mathias Benedek, Sabine Bergner, Ursula Athenstaedt, and Aljoscha C. Neubauer. 2013. “Sex Differences in Neural Efficiency: Are They Due to the Stereotype Threat Effect?” Personality and Individual Differences 55, no. 7: 744–9.
Dussauge, Isabelle, and Anelis Kaiser. 2012. “Neuroscience and Sex/Gender. Special Issue.” Neuroethics 5, no. 3: 211–15.
Eagly, Alice H., and Wendy Wood. 2013. “The Nature-Nurture Debates: 25 Years of Challenges in Understanding the Psychology of Gender.” Perspectives on Psychological Science 8, no. 3: 340–57.
Estes, Zachary, and Sydney Felker. 2012. “Confidence Mediates the Sex Difference in Mental Rotation Performance.” Archives of Sexual Behavior 41, no. 3: 557–70.
Fausto-Sterling, Anne. 2000. “Dueling Dualisms.” In Sexing the Body: Gender Politics and the Construction of Sexuality, 1–29. New York: Basic Books.
Feng, Jing, Ian Spence, and Jay Pratt. 2007. “Playing an Action Video Game Reduces Gender Differences in Spatial Cognition.” Psychological Science 18, no. 10: 850–5.
Fine, Cordelia. 2010. Delusions of Gender: How Our Minds, Society, and Neurosexism Create Difference. New York: W.W. Norton & Company, Inc.
–. 2013. “Is There Neurosexism in Functional Neuroimaging Investigations of Sex Differences?” Neuroethics 6, no. 2: 369–409.
–. 2017. Testosterone Rex: Myths of Sex, Science, and Society. New York: W.W. Norton & Company.
Fine, Cordelia, Rebecca Jordan-Young, Anelis Kaiser, and Gina Rippon. 2013. “Plasticity, Plasticity, Plasticity… And the Rigid Problem of Sex.” Trends in Cognitive Sciences 17, no. 11: 550–1.
Fisher, Maryanne L., Tami Meredith, and Melissa Gray. 2018. “Sex Differences in Mental Rotation Ability Are a Consequence of Procedure and Artificiality of Stimuli.” Evolutionary Psychological Science 4, no. 2: 124–33.
Flore, Paulette C., and Jelte M. Wicherts. 2015. “Does Stereotype Threat Influence Performance of Girls in Stereotyped Domains? A Meta-Analysis.” Journal of School Psychology 53, no. 1: 25–44.
Frick A, and W. Möhring. 2013. “Mental Object Rotation and Motor Development in 8-and 10-Month-Old Infants.” J Exp Child Psychol no. 115: 708–20.
Galea, Lisa A.M., and Doreen Kimura. 1993. “Sex Differences in Route-Learning.” Personality and Individual Differences 14, no. 1: 53–65.
Golledge, R.G., V. Dougherty, and S. Bell. 1995. “Acquiring Spatial Knowledge: Survey Versus Route-Based Knowledge in Unfamiliar Environments.” Annals of the Association of American Geographers 85, no. 1: 134–58.
Golledge, R.G. 1987. “Environmental Cognition.” In Handbook of Environmental Psychology, edited by D. Stokols and I. Altman, 131–74. New York: Wiley.
Grön, Georg, Arthur P. Wunderlich, Manfred Spitzer, Reinhard Tomczak, and Matthias W. Riepe. 2000. “Brain Activation during Human Navigation: Gender-Different Neural Networks as Substrate of Performance.” Nature Neuroscience 3, no. 4: 404.
Grossi, G. 2017. “Hardwiring: Innateness in the Age of the Brain.” Biology and Philosophy 32, no. 6: 1–36.
Grossi, Giordana, and Cordelia Fine. 2012. “The Role of Fetal Testosterone in the Development of “the Essential Difference” between the Sexes: Some Essential Issues.” Neurofeminism: Issues at the Intersection of Feminist Theory and Cognitive Science, edited by R. Bluhm, A.J. Jacobson, and H.L. Maibom, 73–104. Hampshire, UK: Palgrave Macmillan.
Hahn, Sabine. 2017. Gender und Gaming. Bielefeld: transcript.
Haier, Richard J., Sherif Karama, Leonard Leyba, and Rex E. Jung. 2009. “MRI Assessment of Cortical Thickness and Functional Activity Changes in Adolescent Girls Following Three Months of Practice on a Visual-Spatial Task.” BMC Research Notes 2, no. 1: 174.
Hines, Melissa. 2006. “Prenatal Testosterone and Gender-Related Behaviour.” European Journal of Endocrinology 155, no. suppl 1: S115–21.
Holding, Carol S., and Dennis H. Holding. 1989. “Acquisition of Route Network Knowledge by Males and Females.” The Journal of General Psychology 116, no. 1: 29–41.
Hyde, Janet Shibley. 2005. “The Gender Similarities Hypothesis.” American Psychologist 60, no. 6: 581–92.
Hyde, Janet Shibley. 2014. “Gender Similarities and Differences.” Annual Review of Psychology 65: 373–98.
Ingalhalikar, Madhura, Alex Smith, Drew Parker, Theodore D. Satterthwaite, Mark A. Elliott, Kosha Ruparel, Hakon Hakonarson, Raquel E. Gur, Ruben C. Gur, and Ragini Verma. 2014. “Sex Differences in the Structural Connectome of the Human Brain.” Proceedings of the National Academy of Sciences 111, no. 2: 823–8.
Jaušovec, Norbert, and Ksenija Jaušovec. 2012. “Sex Differences in Mental Rotation and Cortical Activation Patterns: Can Training Change Them?” Intelligence 40, no. 2: 151–62.
Jiménez, Manuel, Raúl Aguilar, and José R. Alvero-Cruz. 2012. “Effects of Victory and Defeat on Testosterone and Cortisol Response to Competition: Evidence for Same Response Patterns in Men and Women.” Psychoneuroendocrinology 37, no. 9: 1577–81.
Jirout, Jamie J., and Nora S. Newcombe. 2015. “Building Blocks for Developing Spatial Skills: Evidence from a Large, Representative US Sample.” Psychological Science 26, no. 3: 302–10.
Joel, D., and R. Yankelevitch, Yahav. 2014. “Reconceptualizing Sex, Brain and Psychopathology: Interaction, Interaction, Interaction.” British Journal of Pharmacology 171, no. 20: 4620–35.
Joel, Daphna, Zohar Berman, Ido Tavor, Nadav Wexler, Olga Gaber, Yaniv Stein, and Nisan Shefi, et al. 2015. “Sex Beyond the Genitalia: The Human Brain Mosaic.” Proceedings of the National Academy of Sciences 112, no. 50: 15468–73.
Jordan-Young, Rebecca M. 2010. Brain Storm: The Flaws in the Science of Sex Differences. Cambridge, MA: Harvard University Press.
Kaiser, Anelis, Sven Haller, Sigrid Schmitz, and Cordula Nitsch. 2009. “On Sex/Gender Related Similarities and Differences in fMRI Language Research.” Brain Research Reviews 61, no. 2: 49–59.
Kimura, Doreen. 1992 “Sex Differences in the Brain.” Scientific American 267, no. 3: 118–25.
Kirasic, Kathleen C., Gary L. Allen, and Alexander W. Siegel. 1984. “Expression of Configurational Knowledge of Large-Scale Environments: Students’ Performance of Cognitive Tasks.” Environment and Behavior 16, no. 6: 687–712.
Kleinherenbrink, Annelies. 2014. “Mapping Plasticity: Sex/Gender and the Changing Brain.” Tijdschrift voor Genderstudies 17, no. 4: 305–26.
Krendl, Anne C., Jennifer A. Richeson, William M. Kelley, and Todd F. Heatherton. 2008. “The Negative Consequences of Threat: A Functional Magnetic Resonance Imaging Investigation of the Neural Mechanisms Underlying Women’s Underperformance in Math.” Psychological Science 19, no. 2: 168–75.
Lawton, Carol A. 1994. “Gender Differences in Way-Finding Strategies: Relationship to Spatial Ability and Spatial Anxiety.” Sex Roles 30, no. 11–12: 765–79.
Lawton, Carol A. 2010. “Gender, Spatial Abilities, and Wayfinding.” In Handbook of Gender Research in Psychology, edited by J.C. Chrisler and D.R. McCreary, 317–41. New York: Springer.
Lawton, Carol A., Stephanie I. Charleston, and Amy S. Zieles. 1996. “Individual-and Gender-Related Differences in Indoor Wayfinding.” Environment and Behavior 28, no. 2: 204–19.
Lawton, Carol A., and Janos Kallai. 2002. “Gender Differences in Wayfinding Strategies and Anxiety about Wayfinding: A Cross-Cultural Comparison.” Sex Roles 47, no. 9–10: 389–401.
Levine, Susan C., Marina Vasilyeva, Stella F. Lourenco, Nora S. Newcombe, and Janellen Huttenlocher. 2005. “Socioeconomic Status Modifies the Sex Difference in Spatial Skill.” Psychological Science 16, no. 11: 841–5.
Levine, Susan C., Alana Foley, Stella Lourenco, Stacy Ehrlich, and Kristin Ratliff. 2016. “Sex Differences in Spatial Cognition: Advancing the Conversation.” Wiley Interdisciplinary Reviews: Cognitive Science 7, no. 2: 127–55.
Liben, L.S. 2015. “The STEM Gender Gap: The Case for Spatial Interventions.” International Journal of Gender, Science and Technology 7, no. 2: 133–50.
Linn, Marcia C., and Anne C. Petersen. 1985. “Emergence and Characterization of Sex Differences in Spatial Ability: A Meta-analysis.” Child Development: 1479–98.
Livingston-Lee, Sharon A., Philipp M. Zerman, and Susan T.Gilligan. 2014. “Navigational Strategy May Be More a Matter of Environment and Experience than Gender.” Learning and Motivation 45: 30–43.
Maguire Eleanore A., Richard S.J. Frackowiak, and Chris Frith. 1997. “Recalling Routes around London: Activation of the Right Hippocampus in Taxi Drivers.” The Journal of Neuroscience 17, no. 18: 7103–10.
Maguire, Eleanore A., Katherine Woollett, and Hugo J. Spiers. 2006. “London Taxi Drivers and Bus Drivers: A Structural MRI and Neuropsychological Analysis.” Hippocampus 16: 1091–101.
Maguire, Eleanor A., David G. Gadian, Ingrid S. Johnsrude, Catriona D. Good, John Ashburner, Richard S.J. Frackowiak, and Christopher D. Frith. 2000. “Navigation-Related Structural Change in the Hippocampi of Taxi Drivers.” Proceedings of the National Academy of Sciences 97, no. 8: 4398–403.
McGlone, Matthew S., and Joshua Aronson. 2006. “Stereotype Threat, Identity Salience, and Spatial Reasoning.” Journal of Applied Developmental Psychology 27, no. 5: 486–93.
McGuiness, Diane, and Janet Sparks. 1983. “Cognitive Style and Cognitive Maps: Sex Differences in Representations of a Familiar Terrain.” Journal of Mental Imagery 7, no. 2: 91–100.
McWilliams, W., C.J. Hamilton, and S.J. Muncer. 1997. “On Mental Rotation in Three Dimensions.” Perceptual and Motor Skills 85, no. 1: 297–8.
Mehta, Pranjal H., and Robert A. Josephs. 2010. “Testosterone and Cortisol Jointly Regulate Dominance: Evidence for a Dual-Hormone Hypothesis.” Hormones and Behavior 58, no. 5: 898–906.
Miller, Leon K., and Viana Santoni. 1986. “Sex Differences in Spatial Abilities: Strategic and Experiential Correlates.” Acta Psychologica 62, no. 3: 225–35.
Moè, Angelica, and Francesca Pazzaglia. 2006. “Following the Instructions!: Effects of Gender Beliefs in Mental Rotation.” Learning and Individual Differences 16, no. 4: 369–77.
Montello, Daniel R., and Herbert L. Pick Jr. 1993. “Integrating Knowledge of Vertically Aligned Large-Scale Spaces.” Environment and Behavior 25, no. 3: 457–84.
Neidhardt, Eva, and Michael Popp. 2010. “Spatial Tests, Familiarity with the Surroundings, and Spatial Activity Experience: How Do They Contribute to Children’s Spatial Orientation in Macro Environments?” Journal of Individual Differences 31, no. 2: 59–63.
–. 2012. “Activity Effects on Path Integration Tasks for Children in Different Environments.” In Spatial Cognition, edited by C. Stachniss, K. Schill, and D. Uttal, 210–19. LNAI 7463.
Neidhardt, Eva, and Sigrid Schmitz. 2001. “Entwicklung von Strategien und Kompetenzen in der räumlichen Orientierung und in der Raumkognition: Einflüsse von Geschlecht, Alter, Erfahrung und Motivation.” Psychologie in Erziehung und Unterricht 48: 262–79.
Neubauer, Aljoscha C., Sabine Bergner, and Martina Schatz. 2010. “Two- vs. Three-Dimensional Presentation of Mental Rotation Tasks: Sex Differences and Effects of Training on Performance and Brain Activation.” Intelligence 38, no. 5: 529–39.
Neuburger, Sarah, Petra Jansen, Martin Heil, and Claudia Quaiser-Pohl. 2012. “A Threat in the Classroom.” Zeitschrift für Psychologie, no 220: 61–9.
Oliveira, Rui, and Gonçalo Oliveira. 2014. “Androgen Responsiveness to Competition in Humans: The Role of Cognitive Variables.” Neuroscience and Neuroeconomics, no. 3: 19–32.
Ortner, Tuulia M., and Monika Sieverding. 2008. “Where Are the Gender Differences? Male Priming Boosts Spatial Skills in Women.” Sex Roles 59, no. 3–4: 274–81.
Pitts-Taylor, Victoria. 2010. “The Plastic Brain: Neoliberalism and the Neuronal Self.” Health 14, no. 6: 635–52.
Puts, David A., Rodrigo A. Cárdenas, Drew H. Bailey, Robert P. Burriss, Cynthia L. Jordan, and S. Marc Breedlove. 2010. “Salivary Testosterone Does Not Predict Mental Rotation Performance in Men or Women.” Hormones and Behavior 58, no. 2: 282–9.
Quaiser-Pohl, Claudia, Christian Geiser, and Wolfgang Lehmann. 2006. “The Relationship between Computer-Game Preference, Gender, and Mental-Rotation Ability.” Personality and Individual Differences 40, no. 3: 609–19.
Quinn, Paul C., and Lynn S. Liben. 2008. “A Sex Difference in Mental Rotation in Young Infants.” Psychological Science 19, no. 11: 1067–70.
Reilly, D. and Neumann, D.L. 2013. “Gender-Role Differences in Spatial Ability: A Meta-Analytic Review.” Sex Roles 68, no. 9–10: 521–35.
Rippon, Gina, Rebecca Jordan-Young, Anelis Kaiser, and Cordelia Fine. 2014. “Recommendations for Sex/Gender Neuroimaging Research: Key Principles and Implications for Research Design, Analysis, and Interpretation.” Frontiers in Human Neuroscience 8.
Rosenzweig, Mark R., David Krech, Edward L. Bennett, and Marian C. Diamond. 1962. “Effects of Environmental Complexity and Training on Brain Chemistry and Anatomy: A Replication and Extension.” Journal of Comparative and Physiological Psychology 55, no. 4: 429–37.
Rubin, Beatrix P. 2009. “Changing Brains: The Emergence of the Field of Adult Neurogenesis.” BioSocieties 4, no. 4: 407–24.
Sadalla, Edward K., and Daniel R. Montello. 1989. “Remembering Changes in Direction.” Environment and Behavior 21, no. 3: 346–63.
Sanchis-Segura, Carla, Naiara Aguirre, Alvano J. Cruz.-Gomez, Noemi Solozano, and Cristina Forn. 2018. “Do Gender-Related Stereotypes Affect Spatial Performance? Exploring When, How and to Whom Using a Chronometric Two-Choice Mental Rotation Task.” Frontiers in Psychology 9: doi: 10.3389/fpsyg.2018.01261.
Schöning, S., A. Engelien, H. Kugel, S. Schäfer, H. Schiffbauer, P. Zwitserlood, E. Pletziger, et al. 2007. “Functional Anatomy of Visuo-spatial Working Memory During Mental Rotation Is Influenced by Sex, Menstrual Cycle, and Sex Steroid Hormones.” Neuropsychologia 45, no. 14: 3203–14.
Schmitz, Sigrid. 1997. “Gender-Related Strategies in Environmental Development: Effects of Anxiety on Wayfinding in and Representation of a Three-Dimensional Maze.” Journal of Environmental Psychology 17, no. 3: 215–28.
–. 1999. “Gender Differences in Acquisition of Environmental Knowledge Related to Wayfinding Behavior, Spatial Anxiety and Self-Estimated Environmental Competencies.” Sex Roles 41, no. 1: 71–93.
–. 2010. “Sex, Gender, and the Brain-Biological Determinism versus Socio-cultural Constructivism.” In Gender and Sex in Biomedicine: Theories, Methodologies, Results, edited by Inge Klinge and Claudia Wiesemann, 57–76. Göttingen: Göttingen University Press.
Schmitz, Sigrid, and Grit Höppner. 2014a. “Neurofeminism and Feminist Neurosciences: A Critical Review of Contemporary Brain Research.” Frontiers in Human Neuroscience 8: doi: 10.3389fnhum.2014.00546.
Schmitz, Sigrid, and Grit Höppner, eds. 2014b. Gendered Neurocultures: Feminist and Queer Perspectives on Current Brain Discourses. Vienna: Zaglossus.
Schultheiss, Oliver C., and Wolfgang Rohde. 2002. “Implicit Power Motivation Predicts Men’s Testosterone Changes and Implicit Learning in a Contest Situation.” Hormones and Behavior 41, no. 2: 195–202.
Sharps, Matthew J., Angela L. Welton, and Jana L. Price. 1993. “Gender and Task in the Determination of Spatial Cognitive Performance.” Psychology of Women Quarterly 17, no. 1: 71–82.
Shepard, Roger N., and Jacqueline Metzler. 1971. “Mental Rotation of Three-Dimensional Objects.” Science 171, no. 3972: 701–3.
Sherry, David F., and Elizabeth Hampson. 1997. “Evolution and the Hormonal Control of Sexually-Dimorphic Spatial Abilities in Humans.” Trends in Cognitive Sciences 1, no. 2: 50–6.
Silverman, Irwin, Jean Choi, and Michael Peters. 2007. “The Hunter-Gatherer Theory of Sex Differences in Spatial Abilities: Data from 40 Countries.” Archives of Sexual Behavior 36, no. 2: 261–8.
Steele, Claude M., and Joshua Aronson. 1995. “Stereotype Threat and the Intellectual Test Performance of African Americans.” Journal of Personality and Social Psychology 69, no. 5: 797.
Stoet, G., and D.C. Geary. 2012. “Can Stereotype Threat Explain the Gender Gap in Mathematics Performance and Achievement?” Review of General Psychology, no. 16: 93–102.
Stricker, Lawrence J., and William C. Ward. 2004. “Stereotype Threat, Inquiring about Test Takers’ Ethnicity and Gender, and Standardized Test Performance.” Journal of Applied Social Psychology 34, no. 4: 665–93.
Tan, Anh, Wenli Ma, Amit Vira, Dhruv Marwha, and Lise Eliot. 2016. “The Human Hippocampus Is Not Sexually-Dimorphic: Meta-analysis of Structural MRI Volumes.” Neuroimage 124: 350–66.
Terlecki, M.S., and Nora S. Newcombe. 2005. “How Important Is the Digital Divide? The Relation of Computer and Videogame Usage to Gender Differences in Mental Rotation Ability.” Sex Roles 53, no. 5: 433–41.
Terlecki, M.S., Nora S. Newcombe, and Michelle Littel. 2008. “Durable and Generalized Effects of Spatial Experience on Mental Rotation: Gender Differences in Growth Patterns.” Applied Cognitive Psychology 22: 996–1013.
Titze, Corinna, Petra Jansen, and Martin Heil. 2010. “Mental Rotation Performance in Fourth Graders: No Effects of Gender Beliefs (Yet?).” Learning and Individual Differences 20, no. 5: 459–63.
Tomasi, Dardo, and Nora D. Volkow. 2012. “Gender Differences in Brain Functional Connectivity Density.” Human Brain Mapping 33, no. 4: 849–60.
Tzuriel, David, and Gila Egozi. 2010. “Gender Differences in Spatial Ability of Young Children: The Effects of Training and Processing Strategies.” Child Development 81, no. 5: 1417–30.
Uttal, David H., Nathaniel G. Meadow, Elizabeth Tipton, Linda L. Hand, Alison R. Alden, Christopher Warren, and Nora S. Newcombe. 2013. “The Malleability of Spatial Skills: A Meta-Analysis of Training Studies.” Psychological Bulletin 139, no. 2: 352.
Van Anders, Sari M. 2013. “Beyond Masculinity: Testosterone, Gender/Sex, and Human Social Behavior in a Comparative Context.” Frontiers in Neuroendocrinology 34, no. 3: 198–210.
Van Anders, Sari M., Jeffrey Steiger, and Katherine L. Goldey. 2015. “Effects of Gendered Behavior on Testosterone in Women and Men.” Proceedings of the National Academy of Sciences 112, no. 45: 13805–10.
Van Anders, Sari M., and Neil V. Watson. 2006. “Social Neuroendocrinology.” Human Nature 17, no. 2: 212–37.
Voyer, Daniel, Susan Voyer, and M. Philip Bryden. 1995. “Magnitude of Sex Differences in Spatial Abilities: A Meta-Analysis and Consideration of Critical Variables.” Psychological Bulletin 117, no. 2: 250.
Ward, Shawn L., Nora Newcombe, and Willis F. Overton. 1986. “Turn Left at the Church, or Three Miles North: A Study of Direction Giving and Sex Differences.” Environment and Behavior 18, no. 2: 192–213.
Woollett, Katherine, and Eleanor A. Maguire. 2011. “Acquiring ‘the Knowledge’ of London’s Layout Drives Structural Brain Changes.” Current Biology 21, no. 24: 2109–14.
Wraga, Maryjane, Molly Helt, Emily Jacobs, and Kerry Sullivan. 2007. “Neural Basis of Stereotype-Induced Shifts in Women’s Mental Rotation Performance.” Social Cognitive and Affective Neuroscience 2, no. 1: 12–19.
Zilioli, Samuele, Pranjal H. Mehta, and Neil V. Watson. 2014. “Losing the Battle but Winning the War: Uncertain Outcomes Reverse the Usual Effect of Winning on Testosterone.” Biological Psychology 103: 54–62.
