UNIVERSITY OF CALGARY. The Effects of Prenatal Cortisol Concentrations on Working. Memory Performance in Preschool Children. Emily E.

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1 UNIVERSITY OF CALGARY The Effects of Prenatal Cortisol Concentrations on Working Memory Performance in Preschool Children by Emily E. Cameron A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE GRADUATE PROGRAM IN CLINICAL PSYCHOLOGY CALGARY, ALBERTA SEPTEMBER, 2016 Emily E. Cameron 2016

2 Abstract Working memory has been shown to predict future cognitive and academic outcomes, making the successful development of working memory crucial. Extensive animal literature has reported a relationship between elevated maternal cortisol in utero and poorer working memory performance in offspring, while this association has not been replicated in humans. The current study aims to investigate the effect of maternal cortisol exposure on working memory development in preschool aged children. Maternal salivary cortisol was collected over two consecutive days at three prenatal assessments. Child working memory was assessed at age 3-4 years. Results indicated that there was no association between a working memory composite score and maternal cortisol; however, the current study was underpowered. Individual subtest analyses revealed significant three-way interactions for two subtests with infant biological sex and gestational age. Future research should investigate the relationship between prenatal cortisol and working memory under varying conditions of stress in children. ii

3 Acknowledgements I would like to express my sincere gratitude to my primary supervisor, Dr. Lianne Tomfohr- Madsen, and co-supervisor, Dr. Gerald Giesbrecht, for their guidance, motivation, and immense knowledge. I would also like to thank my thesis committee members for their encouragement, insightful comments, and challenging questions. Lastly, my accomplishments would not have been possible without the financial support of the Social Sciences and Humanities Research Council (SSHRC) and Alberta Children s Hospital Research Institute. iii

4 Table of Contents Abstract.. ii Acknowledgements...iii Table of Contents...iv List of Tables......v List of Figures....vi Introduction...1 Method..12 Results...19 Discussion.21 References.29 Tables Figures...47 Appendix A Self-Ordered Pointing Task..51 Appendix B Spatial Span Task.52 Appendix C WPPSI-IV.53 Appendix D NEPSY-II.54 iv

5 List of Tables Table 1 Principle Component Analysis Component Matrix for the Correlations Between WMI, Memory for Designs, SOPT Maximum Span, and SST Maximum Span and the Estimated Components...42 Table 2 Parameters in the Model for the Relationship Between the Working Memory Composite and Maternal AUCg.. 43 Table 3 Parameters in the Model for the Interactions Between Working Memory, Infant Sex, and Gestational Age for Maternal AUCg Table 4 Parameters in the Model for the Relationship Between the Working Memory Composite and Maternal CAR Table 5 Parameters in the Model for the Interactions Between Working Memory, Infant Sex, and Gestational Age for Maternal CAR..46 v

6 List of Figures Figure 1 The primary hypothesis testing the direct relationship between prenatal cortisol exposure and later working memory performance in preschool children. 47 Figure 2 The secondary hypothesis testing if the relationship between prenatal cortisol exposure and later working memory performance in preschoolers is moderated by infant sex...48 Figure 3 Scree plot for the principle component analysis of working memory subtests exhibiting a single component Figure 4 Graph of the significant interaction between gestational age (centered at 6-months gestation), infant sex, and the memory for designs subtest, which illustrates that low working memory in females and high working memory in males at age 3-4 years is associated with decreased maternal CAR across pregnancy while low working memory in males and high working memory in females is associated with increased maternal CAR across pregnancy vi

7 Introduction The ability to hold and manipulate information in memory is a vital skill for successful navigation of daily life. Working memory refers to the distinct functional system that holds and processes new and previously stored information to perform a task (Cowan, 2008). It is a vital component of the umbrella system known as executive functioning and, as a result, working memory is involved in the management of lower-order cognitive functions (Baddeley, 2012; Chan, Shum, Toulopoulou, & Chen, 2008). Many researchers consider working memory to be essential for success on all executive tasks (Senn, Espy, & Kaufmann, 2004). It is also thought to contribute to the development of more specialized executive functions through gradually increasing the processing capacity of the brain throughout development and into early adulthood (Smidts, Jacobs, & Anderson, 2004). A number of models, which differ mostly in emphasis and terminology, have been proposed to explain the underlying mechanism of working memory (Baddeley, 2012). One of the more widely accepted and well investigated theories known as the multicomponent model of working memory suggests that working memory consists of an attentional controller, the central executive, that controls two subsystems known as the phonological loop and visuo-spatial sketchpad, which in turn interface through the episodic buffer (Baddeley, 2000). This model emphasizes the widely distributed role of working memory in the incorporation of visual, spatial, and auditory information and the manipulation and integration of that information to complete goal-oriented actions. Research on working memory in young children has reported that distinct domain-specific components develop differentially, providing significant support for the multicomponent model of working memory (Hornung, Brunner, Reuter, & Martin, 2011). 1

8 Neurodevelopmental studies on working memory ability across childhood show a linear improvement as the associated brain structures continue to develop and be refined (Gathercole, Pickering, Ambridge, & Wearing, 2004; Kwon, Reiss, & Menon, 2002; Nagy, Westerberg, & Klingberg, 2004). Working memory research throughout the preschool period has found that there is a consistent improvement in both the phonological loop and visuo-spatial sketchpad, such that capacity continues to increase and updating and manipulation abilities are further refined (Garon, Bryson, & Smith, 2008). Possibly the most noticeable difference across development is the increase in working memory capacity. Specifically, children aged 3-4 years can retain approximately two items in working memory compared to nearly double that by age seven (Simmering, 2012). Consequently, working memory tasks for this age group consist of simple designs (e.g., familiarize-recognize, observe-perform paradigms; Reznick, 2009) with minimal instructions (Wechsler, 2012). Neurodevelopmental research also supports that the ability to update information held in mind and manipulate representations in mind develops later than simple retention. For example, before the age of seven the phonological loop consists of phonological store only, as spontaneous rehearsal does not occur consistently (Gathercole & Hitch, 1993; Gathercole, Pickering, Ambridge, & Wearing, 2004). Overall, the ability to update memory improves from age 3 to 5 years along with working memory capacity and continues to develop until well into adulthood (Ewing-Cobbs et al., 2004; Luciana, 2003). Importance of working memory in childhood Working memory plays a critically important role in learning and remembering new information, and consequently it is implicated in a variety of school-related problems and clinical disorders (Holmes, Gathercole, & Dunning, 2009; Hutchinson, Bavin, Efron, & Sciberras, 2012; Mulder, Pitchford, & Marlow, 2011). In preschool children, working memory has been shown to 2

9 predict later reading and mathematic ability, such that low working memory is positively correlated with lower academic achievement (Holmes et al., 2009). Similarly, working memory in 4-year-old children has been shown to be predictive of concurrent reading and mathematic achievement, an advantage that was maintained when reassessed at age seven (Bull, Espy, & Wiebe, 2008). Further, working memory in children and teenagers has been shown to predict word recognition and comprehension abilities (Swanson & Howell, 2001). In addition to its importance to executive functioning, working memory is also considered to be part of more general cognitive function. An intelligence quotient (IQ) refers to an overall score on a standardized cognitive assessment comprised of verbal comprehension, visual spatial, fluid reasoning, working memory, and processing speed domains, which together form the construct of intelligence. IQ is typically used to predict academic outcomes; however, a longitudinal study of working memory and IQ in 5-year-old children reported that working memory was a strong predictor of academic attainment over six years and accounted for more unique variance than IQ (Alloway & Alloway, 2010). Additionally, an association between working memory and general fluid intelligence, which is the ability to reason and solve new problems independently of previously obtained knowledge (Jaeggi, Buschkuehl, Jonides, & Perrig, 2008), has been reported in undergraduate students (Conway, Cowan, Bunting, Therriault, & Minkoff, 2002). These findings suggest that early working memory is a unique indicator of later cognitive functioning. Due to its connection to concurrent and future academic and intellectual abilities, the successful development of working memory is imperative to the promotion of positive outcomes in children. Further, working memory has been repeatedly shown to be predictive of future cognitive and academic outcomes while the individual 3

10 components of the multicomponent model of working memory, namely short-term and long-term memory, contribute minimally in comparison (Conway et al., 2002; Swanson, 1994). Early infancy factors that influence the development of working memory During early infancy, the child s environment further influences development. The extant research supports an income-achievement gap such that low socioeconomic status during childhood predicts working memory deficits in young adulthood (Evans & Schamberg, 2009; Lipina, Martelli, Vuelta, & Colombo, 2005). In contrast, secure parent-child attachment and high levels of positive parenting factors, such as maternal mind-mindedness and autonomy-support, were reported to be important factors to support the development of executive functions, including working memory, in 12- to 36-month-olds (Bernier, Carlson, Deschênes, & Matte- Gagné, 2012). Infant temperament in the first year of life is also an established predictor of working memory performance in preschool children (Wolfe & Bell, 2007). These findings support the notion that early life experiences play a significant role in working memory maturation. Recent research investigating neurodevelopmental processes underlying working memory reported that neuronal activation within the superior frontal and intraparietal cortex regions of the brain continue to increase and develop until age 18 (Klingberg, Forssberg, & Westerberg, 2002). As noted by Klingberg and colleagues (2002), the frontal and parietal areas of the brain have a known association with the control of working memory and thus the development of these regions through myelination and pruning likely plays a critical role in working memory development. Woodward and colleagues (2005) reported that preterm children with lower working memory performance at age two compared to full-term controls showed decreased tissue volume in the regions associated with working memory functioning (i.e., 4

11 dorsolateral prefrontal cortex, sensorimotor, parietooccipital, premotor areas) suggesting that brain injury or interference during developmentally sensitive periods in-utero and in childhood leads to poorer working memory later in life. Unfortunately, imaging data was not available for full-term infants; therefore it was not possible to compare preterm and full-term brain volume as it relates to working memory performance. Thus, early cerebral structural development is influential for development of working memory and interference during maturation may have detrimental effects. Prenatal factors that influence the development of working memory Although the predictive nature of working memory for the outcomes of academic achievement has been well researched, less is known about in-utero and early life factors that predict the development of working memory. Brain development begins during gestation and is susceptible to in-utero influences. The fetal programming hypothesis refers to functional and structural changes in a fetus s brain during sensitive periods of development when the cellular activity is most vulnerable to being influenced by the intrauterine environment (Gluckman & Hanson, 2004). This hypothesis has been used to identify risk factors for poor developmental outcomes, understand mechanisms associated with in-utero influences, and create interventions to promote positive cognitive development. Research supports a programming effect by both positive and negative exposures in utero on the developing fetal brain that may result in a lifelong impact (Entringer, Buss, & Wadhwa, 2012; Moisiadis & Matthews, 2014). Fetal development is susceptible to influence from both factors external to and within the maternal milieu. In humans, the effects of maternal factors on cognitive development have been well researched with findings suggesting that maternal infection (Brown et al., 2009), hormone dysregulation (de Escobar, Obregón, & del Rey, 2004; Gicquel & Le Bouc, 2005), nutrient 5

12 deficiency (Hynes, Otahal, Hay, & Burgess, 2013), and psychological state (Koutra et al., 2012; Van den Bergh et al., 2005) can negatively affect brain development in-utero resulting in executive function deficits in childhood. These studies provide support that in-utero development is sensitive to multiple influences, which can lead to executive function deficits. Maternal cortisol as predictor of working memory in preschoolers Cortisol is a glucocorticoid hormone released by the adrenal gland as the end product of the Hypothalamus-Pituitary-Adrenal (HPA) axis. Cortisol exhibits a variety of functions within the body, such as increasing blood sugar through gluconeogenesis (Khani & Tayek, 2001), regulating sleep (Buckley & Schatzberg, 2005; Vgontzas & Chrousos, 2002), suppressing the immune system through anti-inflammatory pathways (Chiappelli, Manfrini, Franceschi, Cossarizza, & Black, 1994; Marshall et al., 1998), regulating stress response (Young, Abelson, & Lightman, 2004), and influencing memory consolidation (McGaugh & Roozendaal, 2002). Cortisol reactivity in human children has also been shown to play a critical role in executive functions, such as shifting mental set, inhibition, and working memory (Blair, Granger, & Razza, 2005). In-utero exposure to maternal cortisol is essential for a developing fetus, as cortisol plays an important role in directing development of infant organ systems (Mulder et al., 2002) and cognition (Davis & Sandman, 2010). Through animal studies, the mechanism of the programming effect of prenatal cortisol on infant development has been established such that a small but significant amount of prenatal maternal cortisol successfully passes through the placenta unmetabolised to reach the fetus (Gitau, Cameron, Fisk, & Glover, 1998). Although cortisol is necessary for typical infant development, exposure to higher than average 6

13 concentrations of maternal cortisol may lead to detrimental infant outcomes (Bergman, Sarkar, Glover, & O Connor, 2010; Seckl, 2007). While pregnancy is characterized by large changes in cortisol production (Allolio et al., 1990), highly elevated concentrations can also become pathological leading to negative outcomes for the fetus (Bergman et al., 2010; Seckl, 2007). Mean cortisol in non-pregnant women is approximately nmol/l during the morning peak and 2 nmol/l in the evening (Aardal & Holm, 1995). In a normal pregnancy, maternal cortisol concentrations increase throughout pregnancy peaking in the final weeks before childbirth and reaching concentrations more than twice as high as in non-pregnant controls (Allolio et al., 1990; Hampson, Phillips, Soares, & Steiner, 2013). Higher cortisol concentrations are associated with adverse developmental outcomes, such as a more difficult temperament, increased externalizing behavioural problems, and decreased cognitive functioning (Bergman et al., 2010; Gutteling et al., 2005; O Connor, Heron, Golding, Beveridge, & Glover, 2002). Elevated maternal cortisol levels directly and indirectly affect infant neurodevelopment (Davis, Glynn, Waffam, & Sandman, 2011; Seckl, 2007). Specifically, as glucocorticoids, such as cortisol, easily cross the blood-brain barrier, maternal cortisol directly impacts infant neurodevelopment (Sousa, Madeira, & Paula-Barbosa, 1998). This exposure has been repeatedly shown in animal studies to increase HPA axis response in the fetus (Seckl, 2007) and elicit longterm increases in HPA axis activity (Koehl et al., 1999). The alterations to fetal HPA axis functioning following elevated maternal cortisol has been hypothesized to involve modification of regulatory processes of the central drive to the HPA axis, such as reduced expression of central glucocorticoid and mineralocorticoid receptor systems (Kapoor, Dunn, Kostaki, Andrews, & Matthews, 2006; Koehl et al., 1997). This reduction results in a marked increase in plasma 7

14 cortisol and longer duration in HPA axis response, as fewer receptors are available to stop the response (Kapoor et al., 2006; Koehl et al., 1997). Working memory is particularly vulnerable to the negative effects of increased cortisol as the hippocampus and specific regions of the prefrontal cortex (PFC; e.g., dorsolateral and ventrolateral PFC) are highly populated with glucocorticoid receptors and thus a key target for the negative-feedback actions of glucocorticoids (Szuran, Pliska, Pokorny, & Welzl, 2000). Further, chronic cortisol exposure can lead to dendritic reorganization in the medial PFC (Radley et al., 2004). Glucocorticoid hormones act on glucocorticoid receptors in the PFC to increase dopamine, which subsequently leads to deficits in working memory performance (Arnsten & Goldman-Rakic 1998; Morrow, Roth, & Elsworth, 2000). Thus, the hypothesized mechanism for a relationship between maternal cortisol exposure and infant working memory is as such: reduced regulation of the HPA axis in infants would result in higher basal cortisol and longer duration of activity, which in turn would lead to increased dopamine efflux in the PFC and consequently deficits in working memory performance. Animal studies have noted that increased HPA axis activity is associated with poorer cognitive function, specifically learning and memory deficits (e.g., impairment of maze learning; Huizink, Mulder, & Buitelaar, 2004; Lupien et al., 1998). Thus, animal studies suggest that the relationship between elevated maternal cortisol exposure and memory impairments may in part be mediated by infant HPA axis activity; however, the pathways found in animal studies have not been fully replicated in humans. Recent research has extended the animal literature to show that elevated prenatal cortisol leads to increased HPA axis activity in human infants (Davis et al., 2011; Glover, O Connor, & O Donnell, 2010). Nevertheless, the long-term implications of the programming effect of cortisol have not been well documented in humans. In adult human 8

15 studies, it has been well established that increased HPA axis activity leads to prolonged basal cortisol elevations, which is associated with hippocampal atrophy and impairment in specific memory abilities (Jacobson & Sapolsky, 1991; Lupien et al., 1998). Conversely, the impact of early exposure to cortisol on memory development in young children is not known. Only one study has investigated potential relationships between elevated exposure to prenatal cortisol and later memory in children and reported no association (Gutteling et al., 2006). However, the study had methodological concerns that may have affected findings, such as including infant sex as a confounding variable but not looking at sex differences or timing of prenatal exposure. Learning and working memory outcomes were investigated in 6-year-old children in a Dutch population using the Test of Memory and Learning (TOMAL, Reynolds & Bigler, 1994; Gutteling et al., 2006). At the time of the study, the TOMAL was only validated in American children and, as a result, the study s first author translated the measure to Dutch. As there was no existing standardization sample to compare the results to nor was there clinical cutoff scores available for the Dutch population, these results should be viewed with caution. To address the gap in the literature, there is a need for a prospective research design that follows women and their infants from pregnancy to early childhood with attention paid to variation across individuals in timing and concentrations. Further, longitudinal evaluation of the impact of prenatal cortisol exposure on infant memory should utilize cortisol collection from both infants and mothers and well-validated measures for child working memory with corresponding clinical norms. Differences in fetal programming effects by infant sex and across gestation Recent literature suggests sex differences in response to certain intrauterine exposures (Horton, Kahn, Perera, Barr, & Rauh, 2012; Tibu et al., 2014). For example, prenatal exposure to 9

16 maternal anxiety has been associated with decreased vagal reactivity in males but increased vagal reactivity females (Tibu et al., 2014). Additionally, research on exposure to insecticides that have a well-documented nocuous effect on later working memory in children showed that males experienced a greater detriment when exposed to the insecticide prenatally, supporting that males may be more susceptible to working memory deficits compared to females (Horton et al., 2012). The effect of maternal cortisol levels in-utero on neurological maturation has also been observed earlier and more robustly in female versus male offspring (Glynn & Sandman, 2012); however, a sizeable literature exists in support of higher risk for morbidity and viability in offspring in response to maternal cortisol in males over females (Sandman, Glynn, Davis, 2013). In summary, the effects of prenatal exposures appear to differ across sex and impact different regions and/or functions of the developing brain and should be a considered when examining the relationship between maternal cortisol and working memory outcomes. Gestational age may also affect the impact of exposure on developmental outcomes. Brain structures associated with working memory performance develop differentially such that portions of the structures develop between approximately week 6 15, while other areas develop between week (Rice & Barone, 2000). Maternal cortisol concentration has been shown to differentially affect infant behaviour based on time of exposure, such that exposure to elevated prenatal cortisol at weeks gestation significantly predicted increased behavioural negative reactivity in infants while earlier exposure did not (Davis et al., 2007). Elevated prenatal cortisol (i.e., 1 SD increase) in early pregnancy but not late pregnancy is associated with larger right amygdala volume in female offspring, which mediated the relationship between maternal cortisol and more affective problems in girls, but not boys, during childhood (Buss et al., 2012). Using the Bayley Scales of Infant Development (BSID), Davis and Sandman (2010) investigated the 10

17 effects of increased exposure to cortisol on human infant cognitive development as a function of gestational age and reported that elevated cortisol in early gestation (15 weeks) was associated with lower scores on the mental development index of the BSID whereas exposure in late gestation (37 weeks) was associated with higher scores in the first year postpartum. The previous study that reported a null association between prenatal cortisol and infant working memory may not have considered differences across gestation. Objectives and Hypotheses of the Current Study Exposure to maternal cortisol prenatally has been repeatedly shown to lead to lower cognitive developmental scores (Bergman et al., 2010; Davis & Sandman, 2010); however, less is known about the impact on working memory specifically. Prospective studies that examine the relationship between prenatal maternal cortisol exposure and working memory performance in 3- year-olds are needed. Thus, the current study s primary aim is to extend previous findings from animal models, which demonstrate that increased exposure to prenatal cortisol is associated with lower working memory performance in offspring in a human population (refer to Figure 1 in Appendix A). The primary hypothesis of the current study is that increased prenatal cortisol exposure will predict poorer working memory performance in human 3-year-olds on the Wechsler Preschool and Primary Scale of Intelligence Fourth Edition (WPPSI-IV), A Developmental Neuropsychological Assessment Second Edition (NESPY-II), Spatial Span, and the Self-Ordered Pointing Task. The secondary aims are to investigate if (i) infant sex moderates the relationship between prenatal cortisol levels and working memory in 3-year-olds (refer to Figure 2 in Appendix A) and (ii) whether this relationship changes across gestation. The secondary hypotheses are that (i) males will show greater sensitivity (i.e., poorer memory 11

18 performance) to increasing maternal cortisol compared to females and that (ii) there will be a trajectory effect of gestational age. Method Participants Women and children who were enrolled in an ongoing longitudinal study of nutrition during pregnancy (the Alberta Pregnancy Outcomes and Nutrition [APrON] study) participated. Women were eligible to participate if they were 27 weeks gestation with normal singleton pregnancies. Exclusion criteria for the sub-sample used in the current study included any of the following during pregnancy: a) taking a steroid medication, b) smoking, c) consuming alcohol or street drugs, d) tendency for oral bleeding (potentially leading to falsely elevated cortisol values (Kivlighan et al., 2004)), or e) known fetal or pregnancy complications (e.g., preeclampsia, fetal genetic anomalies, and gestational diabetes). Data collection for women who had recent dental work or were ill were rescheduled for a later date. Before data collection, participants provided informed consent. The study procedures were approved by the University of Calgary Conjoint Health Research Ethics Board. Data were collected between July 2010 and December Procedures Women self-collected saliva at home for 2 consecutive days at three prenatal assessment time points defined as first (<13 weeks), second (14 26 weeks), and third trimester (27 42 weeks). Collection of saliva occurred exclusively on weekdays to avoid potential weekendweekday differences in stress and diurnal cortisol (Schlotz, Hellhammer, Schulz, & Stone, 2004). Whole saliva was obtained from under the tongue of participants on the following schedule: upon waking (allowing for individualized wake times), 30 minutes after waking, and semi- 12

19 randomly after the anchor times of 1130 and 2000 hours. Participants were asked to refrain from consuming food, caffeine, citric drinks, and dairy, to avoid vigorous exercise or brushing teeth in the 30 minutes before the sample collection. Following the procedures described by Smyth and colleagues (1998), semi-random signals via a personal digital assistant (PDA) occurred once within 15 minutes after the anchor times to minimize changes in mood related to anticipation of the signal. To facilitate adherence to the study protocol, the PDA was programmed to allow a 20- minute response window following the signal, after which data were considered missing and thus not included in analyses. Each time the PDA signaled to the participant a unique code corresponding to a pre-labeled saliva tube was provided and the participant was to place the saliva roll under her tongue. Participants then completed a PDA-administered psychological distress questionnaire during saliva collection (these data are not reported as part of the current study). Time of each assessment was recorded by the PDA, allowing precise modeling of diurnal patterns. When the children were between the ages of 3-4 years, they completed a neuropsychological test battery during two 2-hour laboratory sessions as part of the larger study. One testing period consisted of the Wechsler Preschool and Primary Scale of Intelligence Fourth Edition (WPPSI-IV) and an Executive Function battery that included the Self-Ordered Pointing Task and Spatial Span task while the other session included seven subtests from A Developmental Neuropsychological Assessment Second Edition (NESPY-II) and the Movement Assessment Battery for Children Second Edition (Movement ABC-2). Children were accompanied by their parent(s) during the testing session and provided with breaks as required. Upon completion of each laboratory session, children received a small prize for their participation. 13

20 Measures Demographics. Demographic information (e.g., maternal race/ethnicity) was collected during the first assessment time point from mothers. Demographics were included in analyses to explore potential covariates of the relationship between maternal cortisol and child working memory. Gestational age. Gestational age was collected at each prenatal assessment through maternal self-report. Prenatal trimester was represented as a continuous variable for each trimester: first (<13 weeks gestation), second (14-26 weeks gestation), and third trimesters (>26 weeks gestation). Infant Sex. Infant sex was collected at the first postpartum time point and was included in the analyses as a potential moderator. Sex was represented as a categorical variable with two values (e.g., binary variable). Males were assigned a value of 0 and females were assigned a 1 for all analyses. Maternal Basal Cortisol. Saliva samples were stored in the laboratory at -20 C, until they were shipped frozen to Salimetrics, State College, PA for analysis. Salivary cortisol was assayed from all samples using a highly sensitive enzyme immunoassay that has a lower limit of sensitivity of µg/dl, standard curve range from to 3.0 µg/dl, and average intra-assay and inter-assay coefficients of variation of 3.5% and 5.1%, respectively. Method accuracy was determined by spike and recovery, and linearity, determined by serial dilution. To confirm reliability, a random 10% of samples were assayed in duplicate. The mean value from duplicate samples was used for data analysis. Maternal cortisol level was investigated using area under the curve with respect to ground (AUC g ), which is an index of the cumulative amount of cortisol secreted during the day and takes into account state-like and trait-like characteristics (Pruessner, 14

21 Kirschbaum, Meinlschmid, & Hellhammer, 2003). Cortisol awakening response (CAR) was investigated using the waking and 30 minutes after waking assessments, and was calculated using area under the curve with respect to increase (AUC i ) with the equations described by Pruessner and colleagues (2003). Child Working Memory Performance. Working Memory performance was assessed through subtests of the WPPSI-IV and NESPY-II, and two additional executive function tasks. Subtests used to measure memory from the WPPSI-IV included picture memory, which requires a child to recall a series of pictures, and zoo locations, which requires a child to recall the locations of animal cards on a grid. These subtests provide a composite score on the Working Memory Index (WMI), which was used for statistical analyses. Tasks measuring working memory in adults typically rely on a simultaneous, competing cognitive demand to evaluate performance; however, measuring working memory in young children is methodologically difficult due to limited working memory capacity (Simmering, 2012) and lack of ability to use rehearsal tactics or understand complex instructions (Wechsler, 2012). Thus, the WPPSI-IV subtests utilize proactive interference as a competing cognitive processing demand (Wechsler, 2012). Proactive interference ensues when a previously seen item interferes with memory for a present item, which increases difficulty and working memory load for subsequent items (Makovski & Jiang, 2008; Piaget, 1952). One subtest from the NEPSY-II was also used to measure working memory in children - memory for designs (MD), which requires a child to recall the location of designs in a grid from a stack of designs. This subtest also relies on proactive interference to ensure it is a measure of working memory, as opposed to short-term memory. Subtest scaled score from MD, which is a continuous variable, was used for analysis. 15

22 Two additional experimental tasks used to measure working memory are experimental tasks for which no norms are available but which were included to provide a diverse set of tasks all with related underlying working memory requirements. In the Self-Ordered Pointing Task (Petrides & Milner, 1982), children are presented with a set of 2, 3, 4, 5, 6, 7, or 8 picture stimuli on a single sheet of paper. Each set of pictures is presented repeatedly for as many times as the number of stimuli in that set with a unique spatial arrangement each time. On each sheet of paper, the child is required to choose a different picture, one they have not previously selected in that set, and avoid pointing to the same picture more than once. Thus, this task assesses a child s ability to generate and monitor a sequence of responses in working memory without the use of spatial cues (Petrides, 1994; Petrides, 1996). The Total Errors and Maximum Span scores were used in analyses. The Spatial Span Task (SST) is based on the Corsi block task (Milner, 1971) and requires a child to remember a given sequence and then point to a series of objects in that specified order. This task is a nonverbal working memory counterpart to Digit Span, which uses verbal working memory (Vandierendonck, Kemps, Fastame, & Szmalec, 2004). Simple memory storage in the visual domain is strongly associated with processing more so than verbal memory storage (Alloway, Gathercole, & Pickering, 2006). This suggests that, in addition to proactive interference as a test of working memory, a visual storage task also puts processing demands on a child and is therefore an evaluation of working memory (Wechsler, 2012). Overall score on the SST were used in the analysis. Maternal Anxiety. Maternal anxiety was assessed at 3, 6, 12, 24, and 36 months postpartum using an abbreviated Symptom Checklist-90-R (SCL-90-R; DeRogatis, Lipman, & Covi, 1973), including the 10-item anxiety scale. Postpartum anxiety scores from each time point 16

23 were aggregated into one value of postpartum anxiety for statistical analysis to determine if maternal anxiety should be included as a covariate in the model. Maternal Depression. Maternal depression was assessed at 3, 6, 12, 24, and 36 months postpartum using the Edinburgh Postnatal Depression Scale (EPDS; Cox, Holden, & Sagovsky, 1987), a 10-item self-report measure. Postpartum depression scores from each time point were aggregated in one value of postpartum depression for statistical analysis to determine if it should be included in the model as a covariate. Covariates. Several covariates are established predictors of working memory, such as gestational age at birth, maternal race/ethnicity, maternal education, maternal depression, maternal anxiety, birth order, and prenatal medical risk (Davis & Sandman, 2010; Woodward et al., 2005). Analyses were conducted with and without covariates to investigate the relationship between maternal prenatal cortisol and child working memory. Statistical Procedures Statistical analyses were conducted using IBM SPSS Statistics Pearson correlations and t tests were conducted to explore variation in working memory in 3-year-olds related to the covariates: gestational age at birth, infant gender, maternal education, maternal race/ethnicity, maternal depression, maternal anxiety, birth order, and prenatal medical risk. Covariates related to the outcomes at p <.15 were included in all analyses. To control for type I error rate with the numerous outcome measures, a principle component analysis (PCA) was conducted with the standardized residuals for each outcome measure to determine if a working memory composite score could be created. Results of the PCA are discussed below. 17

24 The primary hypothesis, that higher prenatal cortisol exposure will lead to lower working memory performance in 3-year-olds, was tested using longitudinal multilevel modelling. The secondary hypothesis, that the relationship will be moderated by infant sex and change across gestational age, was analyzed by including the variables of gestational age and infant sex into the primary hypothesis model. The model included a three-way interaction between working memory performance, gestational age, and infant sex to test the effects of gestational age and infant sex. The model also included two-way interactions of working memory performance and gestational age as well as working memory performance and infant sex. Power Calculation GPower 3.1 was used to estimate the effect size that would be detected by the primary hypothesis regression analysis based on the fixed sample size of the longitudinal study. There have been no studies looking at the relationship between prenatal cortisol and working memory in 3-year-olds, but related literature (e.g., Davis & Sandman, 2010) suggests that a small (f 2 =.02) to medium (f 2 =.15) effect size is most accurate for the analysis. Using the conventional power illustrated in the literature (Cohen, 1992), a power analysis indicated that a small effect size of Cohen s f 2 =.044 will have an 80% chance of being detected with 180 participants (i.e., a conservative estimate of the total sample for this time point). With 350 participants (i.e., total sample size that still accounts for attrition at this time point), a small effect size of Cohen s f 2 =.023 will have an 80% chance of being detected. Although GPower 3.1 is not suited for conducting power analyses specifically for longitudinal multilevel modeling, the a priori power analysis for hierarchical linear regression is sufficient at this time to indicate the approximate sample required. 18

25 Results Participants Mothers (N=104) were primarily married (91.4%), white (88.6%), and university educated (74.3%) with an average age of years (SD 3.77). Children were an average of 3.76 years old at the time of testing with 53.8% and 46.2 % of the sample being biologically male and female, respectively. Working Memory Subtests To determine the relationships between working memory subtests administered (e.g., SOPT, SST, Memory for Designs, Zoo Locations, Picture Memory), a principle components analysis was run. Results of the analysis indicated only one factor with an eigenvalue of 1.90 that accounted for 47.57% of the variance. The scree plot confirmed the single factor, as seen in Figure 3. Thus, a working memory composite score was created using standardized residuals of each subtest accounting for age of the child for the longitudinal multilevel model analyses. Aim 1: Prenatal cortisol exposure and working memory performance in 3-year-olds Longitudinal multilevel modeling was used to assess the primary hypothesis that working memory performance in preschool children differs as a function of prenatal cortisol exposure. The working memory composite score was not significantly related to cortisol exposure in pregnancy for maternal CAR (t = -.677, p =.501) and AUCg (t = -.794, p =.430). Parameters estimated in the model can be seen in Table 2 and 4. Aim 2: Conditional effects of prenatal cortisol exposure on working memory in children To assess for potential conditional effects of prenatal cortisol on child working memory performance, longitudinal multilevel modeling was used with gestational age as the time variable and interaction terms included in the model for child sex and gestational age (Table 3 and 5). 19

26 Results indicated that the three-way interaction between working memory, child sex, and gestational age was not significant for maternal CAR (t = 1.420, p =.161) and AUCg (t =.736, p =.465). Thus, the two-way interactions were explored. Biological sex of the child was not a significant moderator for the relationships between maternal CAR (t = , p =.104) and AUCg (t = , p =.296) for the working memory composite score. Further, the interaction between working memory and gestational age was not significant for CAR (t = -.572, p =.570) and AUCg (t = -.838, p =.406). Exploratory Subtest Analyses Given the null findings described, post-hoc exploratory analyses were conducted with the standardized residuals used to create the working memory composite score to determine if individual subtests showed significant associations with maternal AUCg and CAR. Results indicated that the three-way interaction between memory for designs, child sex, and gestational age was significantly related to maternal CAR (t = 2.270, p =.026), as seen in Figure 4. Although the two-way interaction between memory for designs and child sex (t = , p =.003) and main effect of memory for designs (t = 2.343, p =.022) were also significant for maternal CAR, two-way interactions and main effects were not interpreted when three-way interactions were significant. There was a significant three-way interaction between SOPT total errors, gestational age, and child sex for maternal CAR (t = , p =.039). For maternal AUCg, the three-way interaction for SOPT maximum span achieved approached significance (t = 1.781, p =.079), while the two-way interaction between SOPT maximum span and child sex was significant (t = , p =.010). No other significant relationships were found between working memory tasks (e.g., memory for designs, SOPT, SST, WMI) and maternal cortisol (i.e., AUCg, CAR), p >

27 Discussion The present study examined the effects of prenatal exposure to maternal cortisol on working memory performance in 3- and 4-year-old children. The findings do not support the notion that performance on a composite score of working memory tasks in preschool aged children is related to maternal cortisol concentrations in-utero. Further, the current study found that the model remained nonsignificant when gestational age and infant sex were included. Overall, these findings are consistent with previous null findings from studies that have investigated the relationship between maternal prenatal cortisol and working memory performance. The current study provides further evidence that, unlike animal offspring, human fetuses may not be as developmentally vulnerable to high levels of cortisol prenatally. Although the main hypothesis of the current study was nonsignificant, analyses of individual working memory tasks indicated that there was an association in the predicted direction between maternal cortisol and aspects of working memory that may differ across tasks. Due to the small sample size, the current study was underpowered for all reported analyses. However, the findings from individual subtest analyses suggest that overall significance may result when the study reaches its full sample size. Results should be considered as pilot data, which will contribute to a larger data set for future publications. However, due to the lack of power, the explanation of the study s findings will continue for the null findings. The exploratory analysis of individual subtests provides support that an aggregated working memory performance score may not capture the full effect of maternal cortisol exposure. Of the tasks included in the analyses, memory for designs was one of the only subtests to exhibit a relationship with maternal CAR. Memory for designs is unique from the other subtests in that it is the only task that utilizes memory for abstract designs. Although the other working memory 21

28 tasks include aspects of visual memory, each task uses pictures of objects the child is likely familiar with. This suggests that the relationship between maternal prenatal cortisol and working memory in children is stronger when tasks include abstract information over meaningful stimuli. Further, the other association with maternal CAR and AUC reported was for the SOPT, which is one of two tasks that required the child to remember pictures on a page. However, SOPT differs from the WPPSI s picture memory subtest in that it requires the child to choose a new picture each time the page is flipped. The task increases in difficulty until the child may be exposed to the same eight pictures within a trial. Picture memory, on the other hand, requires the child to remember one or two pictures on a page (exposed for a few seconds) and then select those pictures from a sequence. Thus, the SOPT task requires the child to hold much more information in mind in comparison to its counterpart on the WPPSI. This may indicate that the underlying processes involved in selecting novel pictures are more affected by cortisol than the processes required to choose previously seen pictures. Overall, the unique features between subtests may be instrumental in deciphering the effect, if any, of cortisol on working memory in children. Exposure to maternal cortisol prenatally has been repeatedly shown to lead to lower cognitive developmental scores (Bergman et al., 2010; Davis & Sandman, 2010). Yet the current study replicates previous null findings in 6-year-old children of a relationship between maternal prenatal cortisol and working memory specifically. In the study by Gutteling and colleagues (2006), maternal cortisol was measured on a single day for each pregnancy period. The authors concluded that the null finding might have been a result of the sampling procedures and recommended future studies examine cortisol over a series of days. The current study examined cortisol over two consecutive days; however, it is possible that this sampling time period is still insufficient to capture the true exposure of fetuses to maternal cortisol for the entire trimester 22

29 (Ross, Murphy, Adam, Chen, & Miller, 2014). Further, the current study did not measure maternal stress response, which may impact the fetus more than maternal basal cortisol levels. In the study by Entringer and colleagues (2009), the significant association found between reported maternal stress in pregnancy and memory performance in the young adults may be a result of the nature of the stress. Specifically, the authors measured whether the mother reported a stressful life event in pregnancy, which may better reflect exposure to prolonged maternal stress response and may not be a factor of basal cortisol levels. Lastly, as discussed by Gutteling and colleagues (2006), other HPA axis hormones may need to be addressed to fully elicit the relationship between maternal physiology and offspring working memory seen in animal studies. Discrepancies from Animal Research to Human Studies Despite the numerous animal studies reporting that prenatal stress and cortisol exposures decrease memory performance in offspring (Huizink, Mulder, & Buitelaar, 2004; Lupien et al., 2009), the current study replicated previous null findings of a similar relationship in human infants (Gutteling et al., 2006). One explanation for the lack of replication from animal to human studies is the nature of tasks used to measure working memory ability. In animal studies, the most common task is the Morris water maze, which requires the animal to navigate a large circular pool of water in an attempt to find a visible or invisible platform (Morris, 1984). Although this task has been extensively used to analyze working memory ability in animals, the testing environment may not be a fair comparison to the calm environment created in human studies. In the water maze task, animals are required to physically exert themselves until they have completed the task. Further, the water level in the pool is such that the animals are in a survival situation unless rescued by the experimenter or the platform is found. In contrast, working memory ability in humans is most often measured using standardized assessments 23

30 where the administrator attempts to put a child in a state where they are comfortable to get the best estimate of their true ability. For instance, the previous study that reported null associations between maternal cortisol and memory performance went so far as to administer the testing in the child s home environment to avoid biased results due to anxiety or nervousness (Gutteling et al., 2006). Although the testing setting is likely a novel situation for children and may induce some level of stress, children differ in the strength of their reactions and often visibly relax over the course of the assessment. For instance, it is often the case in animal studies that the working memory tasks would lead to HPA axis activation. In human studies, children often have parents present and the experimenter works to create a comfortable environment. Thus, there is likely little or no HPA axis activation. This difference in testing environments may play a crucial role in the null findings exhibited in the current study and previous findings. In the previously mentioned Entringer and colleagues (2009) study university students who reported that their mothers experienced a stressful event during pregnancy underwent a working memory task. Importantly, the authors found no effect of maternal prenatal group and working memory in the placebo group (i.e., under normal testing conditions). However, a significant association between maternal prenatal stress and working memory performance was observed after hydrocortisone (cortisol) was administered (Entringer et al., 2009). In combination, these findings provide evidence that the relationship between maternal cortisol and working memory in human infants may only be under conditions of stress. Additionally, a further explanation for the null findings in the current study may be that the current sample did not exhibit great variability in the degree of stress experienced, as indicated by the variability in cortisol levels. Similarly, the sample used in the previous study also reported only low to moderate stress levels (Gutteling et al., 2006). Without including 24