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    1. These analyses establish a relationship among sex, confi-dence, and accuracy. However, they do not discriminate betweenalternative models of mediation.
    2. As estab-lished above, sex negatively predicted both confidence ratings,b = -.38, and mental rotation scores, b = -.29, whereas con-fidence positively predicted mental rotation scores, b = ?.56.
    3. Stated differently, when the effect ofconfidence was taken into account, the sex difference in mentalrotation scores was eliminated. That confidence reduced thepredictive validity of the sex factor to nearly zero (i.e., b =-.09) indicates not only that confidence mediated the sex dif-ference in mental rotation performance, but indeed that thismediation was nearly complete.
    4. Thus, mental rotation performance did notmediate the sex difference in confidence, but rather confidencestrongly mediated the sex difference in mental rotation per-formance.
    5. So, together, Figs. 2 and 3 reveal thatmales and females were similarly successful at calibrating theirconfidence to their accuracy (Fig. 3), though males tendedtoward the upper part of the distribution on both confidence andaccuracy (Fig. 2).
    6. That is, as one’s confidence increased, so did one’saccuracy (see Fig. 3).
    7. Figure 2 illustrates the relationship of confidence and accu-racy across participants; individuals who were highly confidentalso tended to be highly accurate.
    8. This suggests thatconfidence may contribute not only to the sex difference inmental rotation performance, but also to individual differenceswithin each sex (see also Cooke-Simpson & Voyer, 2007).
    9. As shown in Table 1, males were also significantly moreaccurate than females, t(65) = 2.44, p\.05, and the effect size(d = .58) was comparable to that observed in other studies (d =.66, Voyer et al., 1995).
    10. As expected, an independent samples t-test revealed that males(M = 5.61, SD = 1.02) were more confident than females (M =4.62, SD = 1.41), d = .74, t(65) = 3.26, p\.01.
    11. Specifically, if confidence medi-ates mental rotation, then (1) confidence should predict mentalrotation scores not only between sexes, but also within sexes, (2)rendering confidence irrelevant to the task should attenuate thesex difference, and (3) manipulating participants’ confidenceshould affect their mental rotation performance.
    12. .

      Women provide fewer responses to the MRT than men, which means that they deliberately abstain from responding to some MRT questions. This could indicate that women are less confident of their MRT responses than men are.

    13. Because confidence appears tobe an important component of the MRT, it stands as a plausiblemediator of performance.
    14. The most common measure of mental rotation performanceis the Mental Rotations Test (MRT; Vandenberg & Kuse, 1978),which is based on the 3-dimensional block figures introduced byShepard and Metzler (1971) and updated by Peters et al. (1995).
    15. .

      Evidence from previous research indicates that confidence mediates performance on cognitive tasks, but the relationship between confidence and spatial ability is under studied and not well understood.

    16. Preliminary evidence suggests that confidence might indeedunderlie the sex difference in mental rotation.
    17. .

      Multiple studies have found that stereotype threat (especially for sex stereotypes) can affect performance on cognitive tasks by influencing confidence.

    18. We therefore tested whether confidence mediatedmental rotation performance.
    19. basic cognitive skills, such as attention, memory, and judgment(e.g., Schmader et al., 2008), which ultimately would affectperformance.
    20. The beliefthat one (or one’s social group) is skilled or poor at a given taskmay well affect one’s confidence when approaching that taskand this effect on confidence may have cascading effects on
    21. Much of the research on gender role and sex stereotype effectsassumes confidence as a potential cognitive mechanism bywhich those social factors exert their effect.
    22. So, in summary, beliefs about and aware-ness of sex stereotypes are both related to the sex difference inmental rotation performance. But how exactly might sex ste-reotypes affect performance?
    23. Mental rotation performance may also be affected by mereawareness of, rather than belief in, the stereotype that men aresuperior to women on spatial tasks.
    24. .

      Research has suggested that women who hold the stereotypical belief that men are better than women at spatial tasks might perform worse on these spatial tasks as a result of this belief.

    25. Performance on spatialtasks thus is clearly related to gender role beliefs and traits.
    26. Gender role beliefs and traits may partially explain the sex dif-ference in mental rotation performance.
    27. Here, we examined whether one suchsociocognitive factor, namely participants’ confidence, contrib-uted to this sex difference in mental rotation performance.Although this presumed relation between confidence and men-tal rotation performance has received little empirical attention,related research on gender roles, sex stereotypes, and stereotypethreat provides a rich source of supportive evidence.
    28. .

      Research has reliably demonstrated that men perform better at the MRT than women do. It is unlikely that there is a purely biological explanation for this sex difference, and sociocognitive factors probably play a role in the sex difference.

    29. Given the complexity of the taskand the magnitude of the sex difference, it likely has multi-ple causes or mediators.
    30. Of all cognitive sex differences, the mental rotation of abstractfigures in 3-dimensional space is the most robust (Halpern, 2000;Hines, 2004; Linn & Petersen, 1985; Maccoby & Jacklin, 1974).
    31. Thus, confidence medi-ates the sex difference in mental rotation performance and hencethe sex difference appears to be a difference of performancerather than ability. Results are discussed in relation to otherpotential mediators and mechanisms, such as gender roles,sex stereotypes, spatial experience, rotation strategies, work-ing memory, and spatial attention.
    32. On tasks that require the mental rotation of 3-dimensional figures, males typically exhibit higher accuracythan females. Using the most common measure of mental rota-tion (i.e., the Mental Rotations Test), we investigated whetherindividual variability in confidence mediates this sex differ-ence in mental rotation performance.
  2. Jun 2022
    1. .

      Lots of research has investigated the cause of sex differences in MRT performance. One proposed explanation is that men and women emphasize different instructional aspects under timed conditions. For this reason, men are able to complete more items than women do when taking the MRT.

    2. Gender differences in favor of men in spatial abilities are one of the most commonly replicated finding inpsychology research (Hedges & Nowell, 1995; Linn & Petersen, 1985; Voyer, Voyer, & Bryden, 1995). Among thetasks that produce such differences, the Mental Rotations Test (MRT), developed by Vandenberg and Kuse (1978),produces the largest effects (Linn & Petersen, 1985; Peters, 2005).
    3. Eighty undergraduate students (40 males, 40 females) completed the MRT while ratingtheir confidence in the accuracy of their answers for each item. As expected, gender differences in favor of men were obtained.Results also indicated a positive correlation between confidence ratings and scores on the MRT, as well as negative correlationsbetween confidence ratings and MRT outcomes presumed to reflect propensity to guess. More elaborate analyses using a measureof accuracy of predictions (the Brier score) indicated that men have a more accurate perception of their performance on the MRTthan women do.



    1. Further support for a constant anduniform biological explanation comes from studies that findsimilar effect sizes for gender across cultures (Silverman,Phillips, & Silverman, 1996).
    2. The distinct hormonal environments of men and womenmay play a role.
    3. .

      Hormones having an activational effect on cognitive functioning in adulthood could also cause sex differences in the MRT. Research has suggested that greater exposure to androgens/estrogens in adulthood can affect cognitive functioning.

    4. .

      Organizational effects during prenatal development could also play a role in MRT sex differences, since these effects could cause the brain to develop differently based on androgen or estradiol exposure. They could also occur as a result of hemispheric specialization. Right hemisphere specialization favors spatial tasks, and left hemisphere specialization favors verbal tasks, and male brains are more lateralized to the right while female brains are more bilateral. For this reason, men may have an advantage in spatial processing that causes them to be better at the MRT. .

    5. When brain imaging studies are done on subjects per-forming mental rotation tasks, there is some evidence ofactivation in motor areas of the brain.
    6. .

      Neuroimaging studies have shown that mental rotation involves parietal region activation. Specifically, males activate the left inferior parietal region and the right head of the caudate nucleus while completing MRTs and females activate the parietal lobe in general while completing MRTs.

    7. Biological factors have also been discussed as potentialcauses for this difference. Biological theories stress theimportance of genetics, hormonal influence, brain organi-zation, and maturational factors.
    8. There is,however, no consensus as to the role of task complexity ongender differences in mental rotation.
    9. Task difficulty is one potential performance factor thathas been explored (Bryden, George, & Inch, 1990; Collins& Kimura, 1997).
    10. .

      Differences in performance on the mental rotation task could be due to cultural norms subconsciously influencing performance or due to task variables that inflate male performance advantage (such as task difficulty, previous task exposure, time limits, and weighted scoring systems).

    11. .

      The mental rotations test (MRT) was created by Vandenberg and Kuse (1978). It uses line drawing of block stimuli and consists of two 10-item sections in which the subject is required to match two of four choices to a target figure.

    12. A number of explanations have been advanced for theexistence of the gender difference in mental rotation.
    13. Voyer, Voyer, & Bryden’s (1995) meta-analysis of sexdifferences in spatial abilities, found that the average differ-ence (using Cohen’s d = (M1 − M2)/σ) between men andwomen on the (MRT; Vandenberg & Kuse, 1978), was 0.94(this represents a very large effect), indicating that men per-form nearly one standard deviation above the average per-formance of women.
    14. The ability to mentally rotate an object has been foundto produce one of the largest sex differences in the cogni-tive literature (Linn & Petersen, 1985).
    15. The visuospatial ability referred to as mental rotation has been shown to produce one of the largest and most consistent sex differences,in favor of males, in the cognitive literature.
    16. Sex differences were also seen in the patterns of correlations between rotation tasks and other neuropsycho-logical measures. Current results suggest men may rely more on left hemisphere processing than women when engaged in rotational tasks.© 2003 Elsevier Ltd. All rights reserved.



    1. .

      If men have a visuospatial advantage and global bias, and if women have a local advantage, then men should be better at classifying line orientation than women, and men should exhibit a global advantage and women should exhibit a local advantage regardless of relevant classification property. It could also be that men would be faster than women in global classification and women would be faster than men in local classification regardless of relevant classification property, Likewise, if gender differences in global-local processing are only related to visuospatial performance, then global bias for men and local bias for women would only be observed for line orientation classification but not for closure classification.

    2. .

      Global-local processing is typically tested using hierarchical stimuli (larger figures are composed of smaller figures). Generally speaking, people usually display a global advantage (faster responses to larger figures than smaller figures) in processing the hierarchical stimuli. Also, they typically display global-to-local interference (conflicting information between the larger figures and the smaller figures interferes with responses to the smaller figures but not the larger ones). Global advantage can be confounded by factors like visual angle, exposure duration, retinal position, density of elements, number and relative size of elements, and the nature of the stimuli at the global and local level.

    3. .

      Men and women were shown hierarchical stimuli that differed in closure (open/closed shape) and line orientation (oblique/horizontal or vertical line) at the global or local level. They had to classify the stimuli on the basis global variation or local variation.

    4. Pre-vious results with similar stimuli and mixed groups of participants(Han, Humphreys, & Chen, 1999; Kimchi, 1994) showed the globaladvantage that is typically observed with hierarchical stimuli (e.g.Kimchi, 1992; Navon, 1977), as well as faster classification by clo-sure than by line orientation. In addition, the global advantage wasmore pronounced when local classification was based on line ori-entation than on closure (Han et al., 1999; Kimchi, 1994).
    5. Thus, in this study, we examined gender differences in global–local processing with a visuospatial judgment task (line orienta-tion) and a shape judgment task (open vs. closed shape).
    6. .

      The stimuli used in this study were specifically designed to evoke the typical global advantage. The study also included both spatial and non-spatial task contexts to see if sex differences in global-local perception only happened in spatial task contexts.

    7. The investigation of gender differences in global–localprocessing in the context of a spatial and a non-spatial task will al-low us to examine whether these differences, if they exist, charac-terize visual perception of women and men in general, or whetherthey are related only to visuospatial performance.
    8. The main purpose of the present study was to systematicallyexamine gender differences in global–local processing.
    9. The inconsistencies in the results of these studies are mostprobably due to the differences in stimulus and task variables,which are known to affect global–local performance, as discussedearlier.
    10. Direct examinations of gender differences in global–local pro-cessing are sparse, and the results are equivocal.
    11. .

      Gender differences in global-local bias could be the result of hemispheric specialization differences in men and women. Women are better at cognitive tasks that use the left hemisphere, which is more implicated in local processing, and men are better at cognitive tasks that use the right hemisphere, which is more implicated in global processing.

    12. .

      Research suggests that men use more "global" reference points (such as the position of the sun in the sky) when navigating, while women use more "local" reference points (such as landmarks) when navigating.

    13. The gender differences in navigation and way-finding also ap-pear to suggest a global bias for men versus a local bias for women.
    14. .

      Gender differences in mental rotation tasks could be accounted for by men and women using different strategies to mentally rotate an object. Research suggests that men use a more holistic or "global" approach when mentally rotating objects, while women use a more segmented or "local" approach when when mentally rotating objects.

    15. .

      Men outperform women on a variety of spatial tasks, from mental rotation tasks to maze navigation tasks.

    16. Gender differences in spatial abilities have been reported in anumber of studies over the years (see Voyer, Voyer, & Bryden,1995, for a review).
    17. Direct examinations of gender differences in global–local processing are sparse, and the results are incon-sistent. We examined this issue with a visuospatial judgment task and with a shape judgment task.Women and men were presented with hierarchical stimuli that varied in closure (open or closed shape)or in line orientation (oblique or horizontal/vertical) at the global or local level. The task was to classifythe stimuli on the basis of the variation at the global level (global classification) or at the local level (localclassification).
    18. This finding suggests that women aremore distracted than men by misleading global oriented context when performing local orientation judg-ments, perhaps because women and men differ in their ability to use cognitive schemes to compensatefor the distracting effects of the global context. Our findings further suggest that whether or not genderdifferences arise depends not only on the nature of the visual task but also on the visual context.



    1. .

      This study found that there are significant sex differences in number line estimation task performance and in confidence judgments about performance. Women/girls are significantly less precise on their number line estimation task performance than men are, and are significantly less confident about performance than men are.

    2. Nevertheless, we conducted linear mixedmodels to statistically test for developmental effects to assess whether the magnitude of genderdifferences in confidence increases (or decreases) with grade and found no evidence ofdevelopmental effects in gender differences in confidence (Appendix 4).
    3. Finally, our analyses included data from participants ranging from early childhood toadulthood, but we chose not to focus on developmental trends in our outcomes of interest.
    4. .

      This study couldn't evaluate sex differences in degree of overconfidence on number-line estimates because judgments must be made on the same scale as performance, and this was not the case for many of the experiments talked about here.

    5. .

      Measures of number line estimation performance were not detailed enough to be able to calculate absolute accuracy (degree of overconfidence) on them, so sex differences in absolute accuracy were not able to be determined.

    6. Across allparticipants, we found the mean values of gamma were positive for both genders (boys/men: n =309, M = .18, SD = .31; girls/women: n = 400, M = .20, SD = .28), which suggests that participantshave some ability to monitor the accuracy of their estimates. However, no reliable gender differencewas observed for relative accuracy (forest plot and analyses are displayed in Appendix 3). Takentogether, the present outcomes suggest that although girls/women (as compared to boys/men) areless confident in their task performance, they are equally able to discriminate between estimates thatare more versus less precise.
    7. Although we cannot calculate measures of absolute metacognitive accuracy, we were able toassess whether gender differences exist for relative accuracy, or the degree to which participants candiscriminate between number-line estimates that are more (vs. less) precise.
    8. Because of these issues, assessing the degree of over- or under-confidence for the number-line estimation task will require future advances in measurement ofjudgments and performance (so they can be made on comparable scales) for this task.
    9. In the current study, we found gender differences in confidence, even when controlling forperformance. We also found that the magnitude of the gender differences observed forconfidence were smaller than those for performance (g = .30 versus .52).
    10. .

      The experiments detailed in this meta-analysis could have their methods slightly adjusted in order to test whether girls/women having lower confidence scores on number line estimation tasks than boys/men is because of lower self-efficacy on math tasks or because of lower perceived familiarity with the numbers.

    11. .

      Boys/men may be higher in their trial-by-trial confidence judgments than girls/women because girls/women tend to have lower self-efficacy when performing math tasks than men. It could also be that girls/women being less familiar with specific numbers than boys/men lowers their number-line estimation confidence.

    12. That is, as compared toboys/men, girls/women may generally have less task-specific efficacy for number-line esti-mation (either because of its math component, spatial component, or both) and may also haveless perceived familiarity with the numbers. In fact, lower self-efficacy may push some girls/women away from engaging in math tasks, which in turn could reduce their actual familiaritywith those numbers.
    13. As mentioned in the Introduction, confidence judgments can be influ-enced by multiple theory- and experience-based factors (e.g., Undorf et al. 2018). The observedgender gap in confidence could be explained by differences in judgment cue use by girls/womenand boys/men.
    14. Although considerable debate exists over the causes of such gender differences when they areobserved (e.g., Hyde 2014), we imagine that psychological (e.g., differences in math attitudes;Sidney et al. 2019), social (e.g., differences in early spatial experiences, such as exposure to spatiallanguage, media, and toys; Caldera et al. 1989; Doyle et al. 2012; Pruden and Levine 2017; orgendered stereotypes about math and spatial ability, McGlone and Aronson 2006; Moè andPazzaglia 2006), and possibly even biological factors (e.g., sexual dimorphism in the parietalcortex; Goldstein et al. 2001) could contribute to the gender differences observed in the number-line estimation task (as is the case for performance; e.g., Tosto et al. 2018).
    15. .

      The meta-analysis revealed that boys/men are generally more precise and more confident (even when controlling for estimation precision) than girls/women in their number-line estimates.

    16. However, gender remained astatistically significant predictor of confidence: Even when controlling for trial-level estimationprecision, girls/women were .038 points less confident in their estimates than were boys/men.
    17. Thus, it appears that the average girl/woman was about 7%less confident than the average boy/man (.048 / .688 = .0697; Model A).
    18. Using the fixed-effects estimates, girl’s/women’s confidence wasestimated to be .048 points lower than boy’s/men’s (p = .001; Model A).
    19. Using linearmixed-effects models to predict confidence, we again found that girls/women were slightlyless confident than boys/men (replicating the findings from the Hedges’ g meta-analysis).We also found that these gender differences remained when estimation precision wasaccounted for.
    20. To summarize the main outcomes, we again found thatgirls/women were less precise in their number-line estimates than were boys/men (replicatingthe findings from the Hedges’ g meta-analysis).
    21. The fixed-effects model resulted in a similar overall mean effect size,g = .26, 95% CI [.10, .41], p = .002.
    22. A gender difference occurred in confidence favoringboys/men (Fig. 2). The overall weighted effect size was g = .30, 95% CI [.12, .47], p = .002.No significant heterogeneity was observed among the effect sizes, Q(17) = 19.03, p = .33.
    23. This indexrevealed a small, non-significant amount of heterogeneity among the effect sizes; I2 = 10.69%.
    24. Our analyses revealed medium gender differences innumber-line estimation performance favoring boys/men (g = .52; Appendix 2).
    25. .

      Confidence judgments refer to an individual's self-assessment about how they performed on a specific task. Confidence judgments are how confidence on specific task performance is measured.

    26. Thus, any gender differences in confidence couldarise from (somewhat) accurate monitoring of performance or from gender biases in makingconfidence judgments. Thus, if gender differences occur in confidence, will they remain whengender differences in performance is statistically controlled?
    27. Thus,whether gender differences will occur in confidence for this task remains an open question. Asimportant, we also investigated whether gender differences occur in confidence when taskperformance (i.e., estimation precision) is controlled. This analysis is critical because whengender differences occur in performance and in confidence, then the former differences inperformance could (appropriately) be producing the gender differences in confidence.
    28. To date, few investigations are available about gender differences in trial-by-trial confidencejudgments for math tasks, and that evidence is mixed.
    29. .

      Sex differences in experience-based inferences might also be the reason why there are sex differences in confidence judgments about number line estimation tasks (i.e., responding quicker produces more confidence, and vice versa), assuming that sex differences do occur in such experiences.

    30. .

      Sex differences in self-efficacy might be the reason why there are sex differences in confidence judgments about number line estimation tasks. Studies have presented competing evidence about sex differences in self efficacy related to mathematics. As such, it is unclear whether men or women would be favored in relation to self-efficacy about number line estimation tasks.

    31. As with other metacognitive judgments (e.g.,judgments of learning), confidence judgments are not based on direct access to how preciselynumbers are represented in memory. Rather, theories of metacognition distinguish between twotypes of information that can be used as a basis for judgments (e.g., Koriat 1997; Koriat andAckerman 2010; Koriat and Levy-Sadot 1999). Theory-based judgments are informed bypeople’s naive beliefs about learning or their perceptions about their own abilities. In contrast,experience-based judgments are informed by on-line monitoring during task performance. In thenumber-line estimation task, both of these factors could influence confidence judgments aboutestimation performance.
    32. Second, given that gender differencesdo occur in number-line estimation performance, any gender differences in confidence couldarise because people’s confidence tracks their performance.
    33. Given such gender differences in number-line estimation performance, will gender differencesalso occur in confidence? Answering this question is important for a couple reasons. First, ifgirls/women are less confident in their estimation performance (as compared to boys/men),differences in confidence could partly be contributing to the differences in performance (for anexample in the context of the mental rotation task, see Estes and Felker 2012).
    34. To foreshadow, such gender differences in number-line estimation performance also occurred in the present research, which motivated our focuson confidence.
    35. Consistent with the above rationale, gender differences have been observed in number-lineestimation performance across development and for various numerical scales, with mediumeffect sizes on average (Bull et al. 2013; Gunderson et al. 2012; Hutchinson et al. 2019;LeFevre et al. 2010; Reinert et al. 2017; Thompson and Opfer 2008).
    36. .

      There are gender differences in the performance of various cognitive tasks: women tend to be better at verbal tasks and men tend to be better at spatial tasks.

    37. .

      Because number-line estimation is a spatial task, it is reasonable to assume that men would perform better on it than women.

    38. Thus, to motivate our interest in confidence, we begin by first considering why (and whether)gender differences occur in number-line estimation performance.
    39. To the extent that space and number are intertwined in the number-line estimation task – the focaltask in our analyses – one might anticipate gender differences due to the inherent spatial character-istics of the task.
    40. The present research evaluates the extent to which gender differences arise in confidence onnumber-line estimation, a task which taps the fundamental ability to estimate numerical magnitude(and is predictive of future math achievement; e.g., Bailey et al. 2014; Booth and Siegler 2006, 2008;Fazio et al. 2014; Fuchs et al. 2010; Geary 2011; Schneider et al. 2018; Siegler 2016; Siegler et al.2011, 2012; Siegler and Thompson 2014; Tosto et al. 2018).
    41. Does a gender gap occur in which girls are less confident than boys when they are engaged inmath tasks such as number-line estimation?
    42. Boys/men were more precise (g = .52) andmore confident (g = .30) in their estimates than were girls/women. Linear mixed modelanalyses of the trial-level data revealed that girls’/women’s estimates had about 31%more error than did boys’/men’s estimates, and even when controlling for precision, girls/women were about 7% less confident in their estimates than were boys/men.
    43. Prior research has found gender differences in spatial tasks in which men perform better,and are more confident, than women. Do gender differences also occur in people’sconfidence as they perform number-line estimation, a common spatial-numeric taskpredictive of math achievement?
    1. In summary, the current study indicates that sex differences inglobal self-assessments of performance do not always coincide with sexdifferences in moment-to-moment spatial performance monitoring.Even though female students were in most cases less confident thanmale students in their general spatial ability, their trial-by-trial meta-cognitive monitoring accuracy was not impaired in either an absoluteor relative sense. Thus, female students appear to have relatively ac-curate perceptions of their spatial performance for spatial orientationand spatial visualization tasks.
    2. .

      Research suggests that even women with high spatial reasoning ability are underconfident about that ability. This study's results showed that women generally had lower absolute accuracy than men when making global performance postdictions on spatial orientation tasks than men did.

    3. Regardless, the current results show that even female studentspursuing STEM degrees are less confident than male students in theirability to reason spatially about some STEM related content. It is un-clear if these differences reflect true underconfidence or if they are dueto actual differences in academic spatial ability.
    4. .

      This study's results differing from the findings of previous studies could also be because students in this sample are less susceptible to having their metacognitive monitoring accuracy affected by negative stereotypes than students in more typical samples. The negative stereotype of women being worse at spatial tasks would normally make it so that women have worse metacognitive monitoring accuracy, but in this case they do not because they strongly identify with spatially oriented tasks (being STEM majors).

    5. .

      This study's results differing from the findings of previous studies could be because of the sample. This sample was taken from a STEM university, so both the men and the women in the sample had above average spatial reasoning ability and spatial experience. In a sample from a less STEM-oriented university, this would not be the case. Hence, this sampling difference may have biased the results of the study so that sex differences were not as prominent as they would be in a more typical setting.

    6. Given that female students have lower visual-spatial working memoryspans than male students (Voyer et al., 2017), they may be more sus-ceptible to monitoring errors in dynamic spatial domains that they arenot susceptible to in static spatial tasks.
    7. Although we observed limited sex-related differences in monitoringaccuracy in the current study, more substantial sex-related differencescould be present in qualitatively different tasks that require dynamicspatial processing.
    8. The cues people attend to can also vary when monitoring is pro-spective vs. retrospective (Nelson, 1990).
    9. However, the sex differences in relativeaccuracy we observed for the PSTV:R, suggest that the quality of thecues students used to monitor their performance may have differed formen and women. It is unclear whether these differences are task-spe-cific or reflect sex differences in cue utilization during prospectivemonitoring that are less prevalent in retrospective monitoring tasks.
    10. .

      Women might be worse at the mental rotation task than men because they pay attention to less informative cues than men do when completing the task. In other words, women might have a less effective strategy of solving the mental rotation task than men, and that's why they perform worse on it.

    11. .

      Inconsistent with the results of previous studies examining the same problem, female students were more accurate in assessing their spatial performance on a mental rotation task than male students were. It might be that female students are better at monitoring their spatial performance on some mental rotation tasks than others.

    12. Furthermore, female STEMmajors had lower self-evaluations than their male counterparts of vi-suospatial abilities needed for scientific reasoning.
    13. Across multiple spatial measures, female students displayedlower confidence in their item-level monitoring and global assessmentsof performance than did male students, even when no actual differencesin spatial performance were present (e.g., Paper Folding Test andSpatial Relations Test).
    14. 3.6. Self-perceptions of everyday and academic spatial ability

      I have no idea what any of this means.

    15. bsoluteaccuracy measures for each task were significantly positively correlatedfor male students. The same pattern was present for female studentswith the exception that their absolute accuracy for the Paper Foldingtest and PSVT:R were not significantly correlated. However, Fisher r-to-z tests indicated that there were no significant differences between themagnitudes of the absolute accuracy correlations for male or femalestudents. Relative accuracy measures for the Spatial Relations test andthe Paper Folding test were also significantly positively correlated. Noother correlations between relative accuracy measures were significantand no sex differences were present for these correlations. Correlationsbetween the absolute and relative accuracy measures were not sig-nificant with the exception that female student's relative and absoluteaccuracy for the PSVT:R was significantly negatively correlated. AFisher r-to-z test indicated that this negative correlation for femalestudents was significantly different from the correlation for male stu-dents, Z = 2.31, p < .05. T
    16. Table 3 shows that both maleand female students were underconfident in their global predictionsand postdictions for their performance on the Spatial Relations Test andPSVT:R but their estimates were well calibrated for the Paper FoldingTest. There were no sex differences in the degree of underconfidencestudents displayed for either predictions or postdictions on the PSVT:Ror for predictions of performance on the Spatial Relations Test. Abso-lute accuracy for global postdictions of performance for the SpatialRelations Test were significantly lower for females than male studentswhich indicates that female students were more underconfident in theirperformance than male students after completing the Spatial RelationsTest. There were no sex differences for either global predictions orpostdictions for the Paper Folding test.
    17. no reliable effects.
    18. It shows that both female and malestudent performed consistently across each spatial measure, with po-sitive moderate to high correlations between most tests. Fisher r-to-ztests testing sex differences in the magnitude of each correlation found
    19. Fisher r-to-z tests indicated that there were no sexdifferences in the relative accuracy for global prediction of performancefor the Spatial Relations Test (Male: r = 0.22, p = .01; Female:r = 0.37, p = .001), Z = 1.2, p = .23, Paper Folding Test (Male:r = 0.40, p = .001; Female: r = 0.29, p = .01), Z = 0.91, p = .36, orPSVT:R (Male: r = 0.48, p = .001; Female: r = 0.56, p = .001),Z = 0.90, p = .37. There were also no sex differences in relative accu-racy for global postdictions of performance on the Spatial Relations Test(Male: r = 0.44, p = .001; Female: r = 0.60, p = .001), Z = 1.61,p = .11, Paper Folding Test (Male: r = 0.71, p = .001; Female:r = 0.68, p = .001), Z = 0.42, p = .68, or PSVT:R (Male: r = 0.67,p = .001; Female: r = 0.59, p = .001), Z = 0.97, p = .32.
    20. . Table 2 shows that male andfemale students were equally accurate in terms of both their absoluteand relative accuracy for all spatial measures except for the relativeaccuracy of performance on the PSVT:R. Surprisingly, female studentsdisplayed higher relative accuracy on the PSVT:R than did male stu-dents. Apparently they were better able to discriminate correct fromincorrect responses, even though males performed better on the test.
    21. There were no significant sex differences in performance onthe Paper Folding test or the Spatial Relations test, but male studentsdid outperform female students on the PSVT:R. Although females per-formed as well as male students on several spatial tasks, female studentsconsistently predicted lower performance than male students on allspatial tasks. They generated lower mean CJs, global predictions, andglobal postdictions for each test, producing significant sex differences inevery task and for each prediction type except for global predictions forthe Paper Folding test.
    22. Consistent with previous findings, male students per-formed significantly better on the symmetry span task than femalestudents. There were no sex differences in performance on the Raven'sProgressive Matrices task.
    23. .

      Students may be better or worse at spatial reasoning depending on the context. Specifically, they may be better at spatial reasoning in an academic context than in a daily life context, or vice versa. For this reason, tests of spatial abilities in academic contexts and daily life contexts were kept separate.

    24. .

      This study evaluated male and female students for sex differences in visual spatial working memory, general fluid intelligence, and subjective assessment of performance ability and experience in several contexts using a modified version of the Spatial Experience Questionnaire (sex differences have previously been found in these areas).

    25. .

      Metacognitive monitoring accuracy is calculated by comparing task performance accuracy to task performance judgements.

    26. Absolute accuracy (also referred to as calibration) refers towhether the average magnitude of an individual's judgments corre-sponds to their overall level of performance. Relative accuracy refers toone's ability to discriminate between correct and incorrect spatial taskdecisions (i.e., manifest higher confidence for correct than for incorrectitem responses). In the current experiment, we compared sex differ-ences for both absolute and relative accuracy on measures of spatialorientation and spatial visualization.
    27. .

      Male students might pay more attention to wholistic cues when solving spatial problems than female students do, which might in turn cause sex differences in item-level monitoring accuracy (metacognition).

    28. Sex differences in spatial strategy use could also cause sex differ-ences in item-level monitoring accuracy. Metacognitive monitoring isan inferential process that involves evaluating cues (e.g. item char-acteristics, processing fluency, etc.) that are present at the time of amonitoring judgment and applying beliefs or heuristics to infer thequality of these processes (Dunlosky & Tauber, 2014; Koriat, 1997;Schwartz, Benjamin, & Bjork, 1997).
    29. These differences instrategy preference may be due to differences in the accuracy of mon-itoring strategy effectiveness.
    30. They also adopt differentstrategies than male students to solve spatial problems (Allen &Hogeland, 1978; Goldstein, Haldane, & Mitchell, 1990; Kail, Carter, &Pellegrino, 1979; Lohman, 1986; Miller & Santoni, 1986; Peña,Contreras, Shih, & Santacreu, 2008; Prinzel & Freeman, 1995; Raabe,Höger, & Delius, 2006; Tapley & Bryden, 1977).
    31. The limited research examining sex differences in monitoring spa-tial cognition is especially surprising because sex differences in spatialcognitive performance have been indirectly linked to metacognitivevariables
    32. .

      Evidence suggests that women evaluate their spatial performance less accurately than men, but only for a mental rotation task. Sex differences in confidence judgments about spatial performance have not been evaluated for other spatial tasks.

    33. Only a few studies have explored whether there are sex differencesin metacognitive monitoring accuracy in non-spatial domains (Hertzog,Dixon, & Hultsch, 1990; Lichtenstein & Fischhoff, 1981; Lundeberg,Fox, & Punćcohaŕ, 1994).
    34. Taken to-gether, the limited available evidence suggests that sex differences maybe present in some domains (memory for categorical lists, narrative textrecall) and not others (general knowledge), and there does not appearto be clear evidence for a general male or female advantage in mon-itoring ability.
    35. Despite this large body of research examining sex differences inspatial cognitive performance, few experiments have focused on po-tential sex differences in metacognitive monitoring accuracy in spatialdomains (e.g., Cooke-Simpson & Voyer, 2007; Estes & Felker, 2012).
    36. .

      Men do not outperform women on all spatial tasks, and women outperform men on episodic memory tasks (especially verbal ones).

    37. Substantial sex differences in performance favoring males overfemales are present for many measures of spatial processing (Halpern &Collaer, 2005).
    38. .

      Women hold the belief that they are worse at spatial tasks than men and are therefore more anxious than men when engaging in spatial tasks, which may cause them to perform disproportionately worse on them. Therefore, it is important to determine sex differences in confidence about spatial tasks.

    39. .

      Spatial cognition is a complex construct used in mental operations that involve interacting with the spatial environment in various ways. As such, it is frequently used in many everyday tasks, as well as in STEM domains such as chemistry or physics.

    40. The current study evaluated sex differences in (1) self-perceptions of everyday and academic spatial ability, and(2) metacognitive monitoring accuracy for measures of spatial visualization and spatial orientation.
    41. Acrossmultiple spatial measures, female students displayed lower confidence in their item-level monitoring and globalassessments of performance than did male students, even when no actual differences in spatial performanceoccurred. Women were also less confident in their self-assessments of their visual-spatial ability for scientificdomains than were men. However, the absolute and relative accuracy of CJs did not differ as a function of sexsuggesting that women can monitor their spatial performance as well as men.



    1. This reveals an interesting pattern:for the left ROI, both ipsi- and contralateral attention conditionslead to a decrease in alpha power compared with pre-cue values.However, in the right ROI, we observed a contralateral decreasebut a slight ipsilateral increase.
    2. For the left ROI, the observed decreases were signifi-cant for both conditions (Fig. 6, p  0.05; significant time sam-ples indicated). For the right ROI, only the contralateral attentioncondition lead to a trend ( p  0.064).
    3. A lin-ear regression analysis showed that with decreasing cue reliabil-ity, there was a strong trend toward decreasing differences in thealpha-lateralization index between correct and incorrect trials(R 2  0.043, p  0.081). This effect was significant for reactiontimes: with decreasing cue reliability, the difference in the alpha-lateralization index between low- and high-RT trials becomessmaller and eventually flips from positive to negative values(R 2  0.135, p  0.01)
    4. As expected, in the 50% condition alpha-lateralization index val-ues were rather low and did not correlate with performance (data notshown): both correct and incorrect, and low- and high-RT trialsshowed similarly low alpha-lateralization index values (in the rangeof 0.01– 0.02; correct vs incorrect: t(17)  0.436, p  0.669; low vshigh RT: t(17)  0.375, p  0.712).
    5. For discrimination rate this effect was not sig-nificant (t(17)  0.638, p  0.532), for RT a near significant trend wasobserved (t(17)  2.048, p  0.056).
    6. This was further substantiated by analysis of the invalid cue trialsfrom the 75% condition, on which an opposite pattern was ob-served: high alpha lateralization was detrimental for performance oninvalid cue trials (Fig. 4C,D).
    7. This analysis showsthat a higher alpha-lateralization index precedes better perfor-mance: both correct trials and fast RTs are related to high alphalateralization values whereas incorrect trials and slow RTs showless alpha lateralization. Paired-sample t tests confirmed thatthese differences were significant (correct vs incorrect: t(17) 2.187, p  0.05; low vs high RT: t(17)  2.556, p  0.05).
    8. alpha-lateralization index showed no significant effect (R 2 0.000, p  0.964).
    9. This decrease could not be explained by a difference in overallipsilateral plus contralateral alpha power between the conditions(data not shown), as a similar test on the denominator (normal-ized per subject using the average power over conditions) in the
    10. There was a significant parametric decrease of thealpha-lateralization index with decreasing cue reliability (Fig.3B) as assessed by linear regression (R 2  0.150, p  0.01).
    11. The alpha lateralization was significanton sensor level both in the 100% (see before) and 75% condi-tion ( p  0.01 for two clusters above left and right sensori-motor regions). For the 50% condition the effect was muchweaker, however, a significant cluster was found in sensorsover left sensorimotor regions ( p  0.05).
    12. A cluster-based randomization test overthe 3D source space showed that the lateralized difference inalpha activity between attention-left and attention-right was sig-nificant for the right somatosensory source ( p  0.01) andshowed a trend for the left source ( p  0.062). Note that data ofonly 17 subjects was used for the source analysis.
    13. A time-frequency analysis of the lower frequencies (5–35Hz) showed that alpha lateralization was sustained through-out the 1 s before stimulus onset (Fig. 2 B) and that none of theother lower frequencies between 5 and 35 Hz showed a sub-stantial modulation.
    14. Spectral analysis revealed a lateralized pattern of alpha power. Acluster-based randomization test over the sensors further showedthat the alpha lateralization had two significant clusters of sensorsabove left and right sensorimotor regions ( p  0.05 for bothclusters) (Fig. 2 A).
    15. To summarize, the behavioral results confirmed the expectedoutcome: performance on invalid trials was significantly worsethan on valid trials, both in terms of discrimination rate and RT.Invalid cues had a more detrimental effect on RT for the 75%condition than for the 50% condition. Subjects were faster on the100% condition than on the 75% or 50% conditions.
    16. In terms of discrimination rate there were no differencesbetween the reliability conditions (100% vs 75%, t(17)  0.687,p  0.502; 100% vs 50%, t(17)  1.208, p  0.244), but subjectswere faster on the 100% condition compared with the other twoconditions (100% vs 75%, t(17)  2.445, p  0.05; 100% vs50%, t(17)  2.960, p  0.01).
    17. Therewas neither a significant effect of reliability on discrimination rate(F(1,17)  0.847, p  0.370), nor on RT (F(1,17)  1.479, p 0.241). There was a significant effect of validity both on discrim-ination rate (F(1,17)  6.534, p  0.05) and on RT (F(1,17) 23.239, p  0.001), with higher discrimination rates and lowerRTs for validly cued trials. Furthermore, the interaction effectbetween reliability and validity was not significant for discrimi-nation rate (F(1,17)  0.458, p  0.508), but showed a highlysignificant effect for RT (F(1,17)  11.715, p  0.01).
    18. .

      This study asked whether somatosensory alpha activity, which occurs in anticipation of information processing, reflects how attentional resources are allocated. It also asked about the extent to which somatosensory alpha activity is top-down modulated by how much anticipation there is.

    19. .

      The brain is constantly receiving sensory information, and it needs to filter this information according to behavioral relevance in order to process it effectively. Hence, the brain might process sensory information more or less thoroughly depending on how relevant it anticipates that information to be. Oscillatory alpha band activity may modulate how thoroughly sensory areas process sensory information based on how demanding a related task is.

    20. Wehypothesized that prestimulus somatosensory alpha powerwould modulate with respect to attention and that thestrength of this modulation would increase parametricallywith cue reliability. Since we posit that alpha activity plays adirect role in modulating neuronal processing, we further hy-pothesized that prestimulus alpha would be predictive of so-matosensory discrimination performance.
    21. These results indicate that the somatosensory alpha rhythmserves the same functional role as posterior alpha.

      In visual spatial attention tasks, alpha activity decreases on the side of the brain opposite to the area being attended to and increases on the side of the brain opposite to the area being ignored, which suppresses distracting inputs and increases visual detection performance. In a somatosensory WM task, somatosensory alpha activity increased on the same side of the brain as the tactile stimulus and increased somatosensory WM performance.

    22. In support of such an alpha mechanism, visual attention isknown to modulate alpha activity over parieto-occipital cortex asmeasured with electroencephalography (Foxe et al., 1998).
    23. .

      Researchers used to think the alpha oscillations reflect cortical idling, but they now think it reflects the state of the underlying neural network when processing information. In this way, alpha oscillations are involved in cognitive processing.

    24. In particular,alpha activity might serve to direct the flow of information throughthe brain and allocate resources to relevant regions (Jensen andMazaheri, 2010). This is consistent with previous work suggestingthat sensory alpha activity is involved in directing focal attention(Pfurtscheller and Lopes da Silva, 1999; Suffczynski et al., 2001).
    25. Here, we investigated whether somatosensory alpha activity istop-down modulated according to the anticipation of sensoryinput. Further, we asked whether the alpha modulation has con-sequences for somatosensory discrimination performance.
    26. Thisstudy demonstrates that prestimulus alpha lateralization in the somatosensory system behaves similarly to posterior alpha activityobserved in visual attention tasks. Our findings extend the notion that alpha band activity is involved in shaping the functional architec-ture of the working brain by determining both the engagement and disengagement of specific regions: the degree of anticipation modu-lates the alpha activity in sensory regions in a graded manner. Thus, the alpha activity is under top-down control and seems to play animportant role for setting the state of sensory regions to optimize processing.
    27. The brain receives a rich flow of information which must be processed according to behavioral relevance. How is the state of the sensorysystem adjusted to up- or downregulate processing according to anticipation? We used magnetoencephalography to investigate whetherprestimulus alpha band activity (8 –14 Hz) reflects allocation of attentional resources in the human somatosensory system.



    1. This Mini-Review presents considerable evidence in sup-port of the thesis that females and males see the world dif-ferently and that this reflects corresponding sexdifferences in the human visual system
    2. In short, sex differ-ences in the human visual system, although controversial,are undeniable. Additional investigation of sex differencesin the human visual system would contribute to analready considerable amount of evidence in support of sexdifferences in the nervous system generally and stronglycounter the traditional assumption in many fields of neu-roscience research that sex differences are negligible ornonexistent (Cahill, 2006; Cahill and Aswad, 2015).
    3. Although some of these tasks (e.g., mental rotation) aresometimes associated with visual processing in the dorsalstream (Podzebenko et al., 2002), it is possible that sexdifferences observed in various measures of visuospatialability reflect differences in cognition rather than invision, which again highlights the requirement for addi-tional studies of sex differences in human perception andcognition in general.
    4. engage human visual and cognitive systems (including thedorsal visual stream), with fairly disparate tasks showingvarying degrees of sex differences in performance (Millerand Halpern, 2014).
    5. Over the past several decades, many studies have reportedsex differences in visuospatial ability, in particular, superi-or performance in males ( Maccoby and Jacklin, 1974;Linn and Petersen, 1985; Voyer et al., 1995). Unfortu-nately, visuospatial performance has been measured byextremely diverse stimuli and tasks that differentially
    6. .

      There may or may not be sex differences in the splenium of the corpus callosum. Some studies have reported the splenium ;to be larger and more bulbous in females. If there are sex differences in the splenium, then they might be related to sex differences in intrahemispheric vs. interhemispheric neural processing, word recognition, and reading.

    7. .

      It has been reported that males have a greater degree of cerebral laterality than females, which may result in sex differences in the development of reading ability or the functional organization of the brain for language more generally.

    8. In anexhaustive review of experiments on sex differences inlaterality, Hiscock et al. (1995) concluded that most if notall findings of vision-related sex differences in lateralitywere genuine.
    9. .

      The amygdala, which has a role in visual processing, differs by biological sex in terms of size and other functions. The female amygdala responds more strongly to negative emotional valence stimuli, while the male amygdala responds more strongly to positive emotional valence stimuli. There are also sex differences in amygdala activity while viewing sexual stimuli.

    10. .

      There are sex differences in face perception and the neural basis of face processing, implying sex differences in the brain areas underlying these functions. There are also sex differences in the brain area that perceives human bodies compared to non-body objects. In particular, this area is more active in males than in females when the person is viewing a threatening male.

    11. .

      The LOC is a ventral stream area that has shown strong fMRI responses to object vs. nonobject stimuli, implicating it in object perception. Sex differences in the LOC have not been investigated, but they should be since the LOC is involved in object size perception and there are sex differences in object size perception. Other sex differences in object recognition may be due to sex differences in cortical thickness in the ventral visual cortex.

    12. .

      This section of the article focuses on sex differences in the ventral visual stream, which supports conscious visual perception.

    13. .

      Some fMRI studies have shown sex differences in BOLD signals at the visual cortex, which may be related to sex differences in visual acuity and color perception.

    14. .

      Some EEG studies have shown that VEP waveform (which may be related to contrast sensitivity performance) differs by biological sex. It is yet unknown if these differences are due to underlying anatomical differences, gonadal hormone release differences, or differences in the visual cortex/retina.

    15. .

      Sex differences in motion perception have not been well-studied. One study suggested sex differences in the known motion processing areas of the human visual cortex, and another showed sex differences in biological motion perception.

    16. In short, although sex differencesin color vision may be related to both retinal and corticalfactors, additional studies are required to validate and elu-cidate such differences.
    17. .

      Several studies have demonstrated sex differences in color perception.

    1. .

      Small effect sizes, low power, and varying methodology may explain why literature about sex differences is mixed. There is probably a complex explanation as to what causes sex differences in visual perception, and those doing research on the subject should keep that in mind.

    2. We found that, for about a third of these tests, females performed significantly worse thanmales. In no paradigm did females outperform males.
    3. .

      Methodologically, this study suggests that between-subjects designs are most effective at controlling for confounds in studies about sex differences. Mechanistically, this study shows that sex differences are of complex origin and cannot be understood through simplistic explanations. Conceptually, this study suggests that sex differences in cognition could be what causes sex differences in vision.