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Individuals who have no or almost no communication ability cannot share their inner thoughts and feelings and must rely on caregivers to make choices for them. Sometimes those choices involve a high degree of insecurity regarding what the patient really wants and needs. A method of increasing the understanding of distress is measuring the autonomic nervous system (ANS). Well-known methods of accessing the ANS are heart rate (HR), heart rate variability (HRV) and electrodermal activity (EDA). By investigating HR, HRV and EDA simultaneously, the aim is to increase insight into the interplay between ANS on the one side and distress and wellbeing on the other. Physical touch may affect ANS, possibly with a therapeutic potential. Especially may C-tactile afferent stimulating touch, such as soft brushing or stroking on hairy skin, be associated with reduced distress (McGlone et al., 2014). The non-verbal population may in general receive far less physical contact than a healthy population. Most studies on CT-optimal touch are conducted on children, and we lack a clear understanding on how CT-optimal touch affect a non-verbal population. This research project aims to investigate biomarkers of physical touch and its effect on distress and calmness in a non-verbal population.

In the following study we wish to examine the differences in lateral electrodermal activity patterns in diverse performing situations.

The following study aims to measure how people react in a challenging social situation, i.e., being observed by a camera. The participants’ task is to regulate their state of arousal via biofeedback of the electrodermal activity. By comparing two groups, a biofeedback trained group and an untrained group, the study will investigate whether biofeedback helps individuals to better cope with stressful situations, such as being observed by a camera. This project was funded by Stiftung Aktion Österreich-Ungarn / Osztrák-Magyar Akció Alapítvány (112ÖU2)

In the following study we wish to explore factors determining emotional arousal patterns in a performance situation. The level of electrodermal activity (EDA) shows the activity of the sympathetic nervous system, and thus, the actual level of emotional arousal. Although most studies consider EDA constant across the body, recent evidence points out that lateral differences exist: level of arousal may be different on the dermatomes due to effects of several underlying factors (see the Multiple Arousal Theory for further details, e.g. Picard et al., 2016). Our prior results confirmed that fear and sadness conveyed by short musical segments shows right sided laterality (Kasos et al., 2020). Another research group used an experimental setup with stress inducing Stroop test measurements (Svetlák et al., 2013) and found increased EDA on the right phalanges while performing the verbal color-naming Stroop task, as compared to rest periods. We collected electrodermal activity (EDA) data from the left and right wrists of right handed participants while playing Tetris. We assume that during the course of the game emotional arousal increases in most subjects due to the rising cognitive demand dictated by the task: shorter and shorter time-intervals are allowed for successful completion of turning the shapes in an optimal way as the stack of objects build up. We also assume that laterality will increase towards the end of the game. We expect a considerable individual difference in both level and laterality, as well as real-time changes of these indices; partly explained by state and trait stress characteristics and performance outcome.

Description According to attachment theory (Bowlby, 1969; 1982), infants are biologically predisposed to form emotional bonds with their caregivers. For instance, behaviors such as crying are designed to elicit caregivers’ proximity, which in turn encourage timely and appropriate caregiving. This interaction helps infants learn about their own emotional states and develop expectations about their social partners (Alblow et al., 2013; Leerkes et al., 2009; Speck et al., 2023). Moreover, responding to infant distress helps regulate the infant's behaviors and physiology, supporting the development of attachment relationships (Boyce & Ellis, 2005; Hofer, 2006). The security of parent–infant attachments varies across individuals based on how caregivers fulfill their role, with these variations occurring independently of shared genetic factors (Bokhorst et al., 2003; Groh et al., 2017). Sensitive caregiving—defined as acknowledging, accurately interpreting, and responding to infant signals in an appropriate and contingent manner—is a key component of the caregiving environment that shapes attachment quality. Such caregiving promotes attachment security by enhancing infants’ confidence that their attachment needs will be reliably met by caregivers (Ainsworth et al., 1978; Verhage et al., 2016). As a result, children develop a “secure base,” allowing them to explore their environment while feeling safe (Waters & Cummings, 2000). In contrast, insecure attachment is thought to arise from specific forms of caregiver insensitivity. For example, insecure-avoidant attachment, characterized by reluctance to seek comfort from caregivers during times of uncertainty and a tendency to suppress the expression of negative emotions, is theorized to result from harsh and rejecting caregiving. This type of caregiving discourages infants from expressing attachment behaviors. Moreover, insecure-resistant attachment, marked by emotional overwhelm during uncertainty and simultaneous caregiver-seeking behavior, is thought to develop in response to inconsistent or unresponsive caregiving, which amplifies infants’ expression of attachment signals. A notable feature of this system, is its recognition of the organization of infant behavior: while infants may employ different behavioral strategies, as represented by secure or insecure attachment behaviors, to manage their attachment needs, they share a common goal—to maintain proximity to their caregiver (Cassidy, 1994; Groh et al., 2019; Sroufe & Waters, 1977). Attachment behaviors are particularly significant as they strongly predict later socioemotional outcomes, regulatory capacity, and a range of interrelated health and behavioral outcomes. Early attachment security, for instance, plays an important role in shaping children's social competence and mitigating externalizing problems (Groh et al., 2017). Additionally, attachment is fundamental to infant stress regulation, which supports exploration, learning, independence, and healthy relationships (Rees, 2007). More specifically, the attachment relationship facilitates emotional regulation before infants develop self-regulation, calibrating the hypothalamic-pituitary-adrenal (HPA) axis adaptive to their environment (Groh & Narayan, 2019; Gunnar & Donzella, 2002). Disruptions in this system can impair calming mechanisms and contribute to behavioral difficulties, anxiety, depression, and post-traumatic stress disorder (Schore, 2005). Furthermore, attachment disturbances may weaken immune function, delay healing, and increase susceptibility to psychosomatic illness through autonomic dysfunction (Picardi et al., 2007). Although the evidence is less conclusive, insecure attachment has also been associated to increased symptom reporting, engagement in health-risk behaviors—including substance use and treatment nonadherence (Maunder & Hunter, 2001)—and intergenerational parenting difficulties. It may also predispose children to issues such as temper problems, homelessness, promiscuity, early pregnancy, and criminal behavior (Rees, 2007). Together, these findings underscore the importance of understanding the factors that contribute to the development of secure or insecure attachment relationships. This study aims to advance our understanding of the antecednets of infants’ attachment behaviors. Specfiically, the study examines whether infant attachment behaviors are associated with environmental predictors and maternal physiological regulation. Specifically, we investigate whether expectant mothers’ autonomic responses, captured using electrodermal activity (EDA), while observing a video of an infant in distress predict their infants’ attachment behaviors at 7 months in a distressing caregiving context induced by the Still Face Paradigm. In this study, socioeconomic status (SES) and social support were selected as environmental predictors, conceptualized as factors representing environmental harshness and unpredictability to examine their relationships with both maternal autonomic responses and infant attachment behaviors. Finally, for our outcome measure, we expanded on the dimensional classification of attachment proposed by Fraley and Spieker (2003), and expanded upon by Raby, Fraley, and Roisman, (2021), by coding infants’ avoidant, resistant, and attentive behaviors on a 3-point scale developed by Kogan & Carter (1996). Environmental Harshness and Unpredictability Harsh and unpredictable environment refers to external conditions, including general resource scarcity, that increase morbidity and mortality risks, and rates at which they vary over time and space(Ellis et al., 2009). These environmental stressors are closely linked to lower parenting quality –such as reduced sensitivity—and, in turn, contribute to maladaptive socioemotional outcomes in children (Ellis et al., 2009). On one hand, low parental investment can be conceptualized as a proxy of the environmental harshness and unpredictability because children perceive environmental cues through the parent-child relationship quality (Yang et al., 2023). On the other hand, it can also be conceptualized as a direct consequence of environmental harshness and unpredictability, as it may reflect parents’ cumulative exposure to various extrinsic risks (Belsky et al., 1991) such as unequal access to resources and its impact on parents’ mental health (Roubinov and Boyce, 2017), as well as the strain that unreliable and unpredictable environments place on caregivers, depleting their adaptive capacities and compromising their ability to provide sensitive and nurturing care (Doan and Evans, 2020). Importantly, Yang et al. (2023) found that parenting investment moderates children's adaptive calibration in response to environmental harshness and unpredictability, further clarifying that while parenting quality itself serves as a direct indicator of children's socioemotional outcomes (Ainsworth et al., 1978), it also operates in between, influencing the relationship between other environmental factors and socioemotional development While factors may indicate environmental harshness and unpredictability—such as disengagement, parental maltreatment, and harsh neighborhood conditions—financial status is one of the commonly used indicators across studies (Suor et al., 2017; Mededovic, 2019; Warrant & Barnett 2020). Specifically, socioeconomic status (SES) is often used as a measure of environmental harshness, based on the assumption that limited economic resources challenge famililes’ coping capacities (Belsky et al., 2012; Simpson et al., 2012; Li et al., 2018; Warren & Barnett 2020). Low childhood SES can also reflect early exposure to environmental unpredictability, as children from lower-SES backgrounds tend to experience a more frequent residential changes, unpredictable routines, and inconsistent caregiving compared to their higher-SES counterparts (Evans et al., 2005; Leventhal & Brooks-Gunn, 2000; Dickerson et al., 2019). Consistent with the relationship between environmental harshness and parenting quality, SES has been shown to influence parenting practices (Hoff et al., 2002; Conger et al., 2010) and is directionally linked to maternal sensitivity (Belsky et al., 2012). Similarly, Koşkulu et al. (2021) found that higher-SES mothers were more sensitive and engaged in higher-quality parent-child interactions in a mediation analysis. This aligns with the well-established link between parenting quality, socioemotional development, and attachment behaviors. Children raised in low-SES environments are more likely to experience inconsistent or coercive parenting, leading to poorer inhibitory control and emotion regulation. They are also at greater risk of developing insecure attachment styles, particularly characterized by anxiety and avoidance (Vaughn et al., 1999; Sakman et al., 2023; Conejero & Rueda, 2023; Bian & Wu, 2023). Social support is another indicator of environmental harshness and unpredictability, as it aligns with the definition of resource scarcity that influences morbidity and mortality (Ellis et al., 2009). Social support contributes to resource availability, as it reflects a stable perception of one’s social context (Green et al., 2007) and determines access to psychological and material resources that enhance stress coping (Cohen, 2004). Additionally, it can serve as a marker of morbidity and mortality risk, as low social support and social isolation have been identified as significant risk factors for adverse health outcomes, including cardiovascular disease and ischemic stroke (Mookadam, 2004; Freak-Poli et al., 2021). Consistent with these definitions, social support is positively associated with parental mental well-being. Parents who perceive sufficient positive social support tend to experience better mental health (Lakey & Cronin, 2008; Acoba, 2024) and greater parental efficacy (Suzuki et al., 2009; Fierloos et al., 2023), which in turn contributes to improved parenting skills (Abidin, 1992; Andresen & Telleen, 1992), greater responsiveness (Crnic et al., 1986), and more positive child-rearing attitudes (Álvarez et al., 2021). Similarly, social support has been shown to buffer the impact of antenatal depressive symptoms on maternal emotional availability (MacMillan et al., 2021), correlate with perceived competence and satisfaction among at-risk mothers (Brown et al., 2018), and be positively linked to maternal love (Can et al., 2024). Social support is also associated with infant attachment security and socioemotional development. Research has linked higher levels of social support to increased security in infant-mother attachment at 12 months (Crnic et al., 1986) and enhanced attachment security in socially at-risk families (Jacobson & Frye, 1991). More recent findings suggest that social support fosters infant socioemotional development and competence (Schuijers et al., 2024), reducing externalizing and internalizing problems while promoting prosocial behaviors (Hosokawa & Katsura, 2024). However, some studies have reported null findings (Li, 2023), indicating that further research is needed to clarify the extent of these associations. Electrodermal Activity Electrodermal activity (EDA), previously referred to as Galvanic skin response, is one of the most widely used physiological measures of autonomic nervous system (ANS) activity. EDA reflects sweat levels in the palmar sweat glands. It has been applied to a broad range of psychological constructs, including stress, affect, and arousal, and serves as both a predictor and correlate of normal and abnormal behaviors (Chaspari et al., 2015; Cacioppo et al., 2016). EDA is unique among systems measuring ANS responses because it provides a direct, quantifiable representation of skin sympathetic nerve activity uncontaminated by the parasympathetic nerve activity. This makes it a reliable indicator of sympathetic arousal (Boucsein et al., 2012; Bach, 2014; Braithwaite et al., 2015). Specifically, increases in skin conductance level (SCL)—which reflect long-term tonic EDA states rather than responses to specific stimuli (Boucsein et al., 2012)—have traditionally been linked to the behavioral inhibition system. Regulated at the bulbar level of the reticular formation, this system is hypothesized to function as an anxiety mechanism, inhibiting behaviors in response to threatening or non-rewarding stimuli (Cacioppo et al., 2016; Fowles, 1980; Speck et al., 2023). Maternal arousal plays a crucial role in adaptive parenting, as emotions can either facilitate or disrupt sensitive caregiving, depending on their intensity (Dix, 1991; Teti & Cole, 2011). Excessive arousal may lead parents to inhibit their responses to a crying infant (Speck et al., 2023), as lower SCL reactivity has been associated with more sensitive parenting behaviors (Emery et al., 2014) and heightened SCL reactivity has been linked to an increased risk of impulsive and harsh discipline toward infants (Joosen et al., 2013). Recent findings further suggests that mothers’ SCL reactivity to an unfamiliar infant cry predicts later insecure-avoidant attachment behaviors in their own infants (Speck et al., 2023). Together, these findings suggest SCL as a key physiological marker of maternal caregiving behaviors and their intergenerational influence on infant attachment patterns. Environmental harshness and unpredictability are also thought to influence sympathetic arousal. In a widely recognized study by Ellis and his colleagues (2005), both highly supportive and highly stressful home environments were found to predict development of heightened sympathetic nervous system reactivity. Although few studies have specifically examined the role of SES and social support in shaping maternal SNS reactivity, several relevant findings suggest how harsh environments may contribute to autonomic regulation over time. For example, individuals who experienced less sensitive maternal caregiving in childhood exhibited greater increases in SCL during distressing situation (Raby et al., 2015), suggesting that early adversity may alter sympathetic responses. Other studies have explored the influence of SES and social factors on autonomic responses, though findings do not necessarily support long-term effects. For instance, subjective social stress and exposure to violence have been linked to increased heart rate variability (Schnell et al., 2013; Mellman et al., 2018), and exposure to provoking social context has been associated with greater increase in systolic blood pressure (Gallo et al., 2000). Additionally, EDA signal covariation has been observed between individuals in close relationships, such as dating couples, suggesting another potential social influence on autonomic regulation (Timmons et al., 2023). Low SES has also been linked to consistently higher heart rate and shorter pre-ejection period, also indicating altered autonomic function (Johnson et al., 2017). Current Study This study has two aims. The first is to to examine whether environmental factors (specifically SES and social support) during the prenatal period predict young infants’ attachment behaviors during the Still Face Paradigm. The second aim is to test whether these longitudinal associations are due to expectant mothers’ autonomic responses measured by SCL reactivity to a video of an unfamiliar infant crying. This study is unique in that, while previous research has explored associations between social support, SES and autonomic responses (Schnell et al., 2013; Johnson et al., 2017), to our knowledge, no studies have specifically examined whether these factors predict maternal sympathetic nervous system (SNS) activity. Additionally, while prior research has established links between environmental harshness/unpredictability and SNS activity (Ellis et al., 2005), as well as between SNS activity and maternal parenting quality and infant attachment behaviors (Emery et al., 2014; Speck et al., 2023), no studies have investigated whether SNS activity accounts for the association between the environmental harshness/unpredictability and infant attachment behaviors. By examining how social support and SES, as indicators of environmental harshness and unpredictability, predict maternal caregiving capacity shown by autonomic response, and in turn, shape infant attachment relationships, this study aims to provide a more comprehensive understanding of how infants may develop adaptive or maladaptive attachment strategies in early life. Our first hypothesis is that SES and social support will be negatively associated with infants’ later insecure-resistant and insecure-avoidant attachment behaviors. This prediction is based on prior findings linking SES to insecure attachment (Sakman et al., 2023), social support to secure attachment (Jacobson & Frye, 1991), and SES to later social competencies and behavioral problems in infants (Schuijers et al., 2024; Hosokawa & Katsura, 2024). This hypothesis also aligns with the understanding that avoidant attachment behaviors often emerge from harsh parenting and resistant attachment behaviors result from inconsistent parenting (Groh et al., 2019). Since low parenting investment is considered a proxy of environmental harshness and unpredictability (Yang et al., 2023), and given that SES and social support may reflect both both harsh and unpredictable environment (Belsky et al., 2012; Dickerson et al., 2019), it is reasonable to expect that SES and social support will correlate with both forms of insecure attachment. Our second hypothesis is that greater SCL reactivity to an unfamiliar infant’s distress signal will help account for the negative relationship between SES and avoidant-insecure attachment behaviors in infants, as well as the mothers’ perceived social support and avoidant-insecure attachment behaviors. This prediction is based on evidence that higher SES and stronger social support are associated with more child-centered and sensitive parenting practices, whereas lower SES and limited social support are linked to lower parenting quality and higher attachment anxiety of children (Conger et al., 2010; Sakman et al., 2023; Crnic et al., 1986). Additionally, this hypothesis builds on findings by Speck et al. (2023), which suggest that maternal autonomic responses predict infants’ avoidant attachment behaviors.

Description According to attachment theory (Bowlby, 1969; 1982), infants are biologically predisposed to form emotional bonds with their caregivers. For instance, behaviors such as crying are designed to elicit caregivers’ proximity, which in turn encourage timely and appropriate caregiving. This interaction helps infants learn about their own emotional states and develop expectations about their social partners (Alblow et al., 2013; Leerkes et al., 2009; Speck et al., 2023). Moreover, responding to infant distress helps regulate the infant's behaviors and physiology, supporting the development of attachment relationships (Boyce & Ellis, 2005; Hofer, 2006). The security of parent–infant attachments varies across individuals based on how caregivers fulfill their role, with these variations occurring independently of shared genetic factors (Bokhorst et al., 2003; Groh et al., 2017). Sensitive caregiving—defined as acknowledging, accurately interpreting, and responding to infant signals in an appropriate and contingent manner—is a key component of the caregiving environment that shapes attachment quality. Such caregiving promotes attachment security by enhancing infants’ confidence that their attachment needs will be reliably met by caregivers (Ainsworth et al., 1978; Verhage et al., 2016). As a result, children develop a “secure base,” allowing them to explore their environment while feeling safe (Waters & Cummings, 2000). In contrast, insecure attachment is thought to arise from specific forms of caregiver insensitivity. For example, insecure-avoidant attachment, characterized by reluctance to seek comfort from caregivers during times of uncertainty and a tendency to suppress the expression of negative emotions, is theorized to result from harsh and rejecting caregiving. This type of caregiving discourages infants from expressing attachment behaviors. Moreover, insecure-resistant attachment, marked by emotional overwhelm during uncertainty and simultaneous caregiver-seeking behavior, is thought to develop in response to inconsistent or unresponsive caregiving, which amplifies infants’ expression of attachment signals. A notable feature of this system, is its recognition of the organization of infant behavior: while infants may employ different behavioral strategies, as represented by secure or insecure attachment behaviors, to manage their attachment needs, they share a common goal—to maintain proximity to their caregiver (Cassidy, 1994; Groh et al., 2019; Sroufe & Waters, 1977). Attachment behaviors are particularly significant as they strongly predict later socioemotional outcomes, regulatory capacity, and a range of interrelated health and behavioral outcomes. Early attachment security, for instance, plays an important role in shaping children's social competence and mitigating externalizing problems (Groh et al., 2017). Additionally, attachment is fundamental to infant stress regulation, which supports exploration, learning, independence, and healthy relationships (Rees, 2007). More specifically, the attachment relationship facilitates emotional regulation before infants develop self-regulation, calibrating the hypothalamic-pituitary-adrenal (HPA) axis adaptive to their environment (Groh & Narayan, 2019; Gunnar & Donzella, 2002). Disruptions in this system can impair calming mechanisms and contribute to behavioral difficulties, anxiety, depression, and post-traumatic stress disorder (Schore, 2005). Furthermore, attachment disturbances may weaken immune function, delay healing, and increase susceptibility to psychosomatic illness through autonomic dysfunction (Picardi et al., 2007). Although the evidence is less conclusive, insecure attachment has also been associated to increased symptom reporting, engagement in health-risk behaviors—including substance use and treatment nonadherence (Maunder & Hunter, 2001)—and intergenerational parenting difficulties. It may also predispose children to issues such as temper problems, homelessness, promiscuity, early pregnancy, and criminal behavior (Rees, 2007). Together, these findings underscore the importance of understanding the factors that contribute to the development of secure or insecure attachment relationships. This study aims to advance our understanding of the antecednets of infants’ attachment behaviors. Specfiically, the study examines whether infant attachment behaviors are associated with environmental predictors and maternal physiological regulation. Specifically, we investigate whether expectant mothers’ autonomic responses, captured using electrodermal activity (EDA), while observing a video of an infant in distress predict their infants’ attachment behaviors at 7 months in a distressing caregiving context induced by the Still Face Paradigm. In this study, socioeconomic status (SES) and social support were selected as environmental predictors, conceptualized as factors representing environmental harshness and unpredictability to examine their relationships with both maternal autonomic responses and infant attachment behaviors. Finally, for our outcome measure, we expanded on the dimensional classification of attachment proposed by Fraley and Spieker (2003), and expanded upon by Raby, Fraley, and Roisman, (2021), by coding infants’ avoidant, resistant, and attentive behaviors on a 3-point scale developed by Kogan & Carter (1996). Environmental Harshness and Unpredictability Harsh and unpredictable environment refers to external conditions, including general resource scarcity, that increase morbidity and mortality risks, and rates at which they vary over time and space(Ellis et al., 2009). These environmental stressors are closely linked to lower parenting quality –such as reduced sensitivity—and, in turn, contribute to maladaptive socioemotional outcomes in children (Ellis et al., 2009). On one hand, low parental investment can be conceptualized as a proxy of the environmental harshness and unpredictability because children perceive environmental cues through the parent-child relationship quality (Yang et al., 2023). On the other hand, it can also be conceptualized as a direct consequence of environmental harshness and unpredictability, as it may reflect parents’ cumulative exposure to various extrinsic risks (Belsky et al., 1991) such as unequal access to resources and its impact on parents’ mental health (Roubinov and Boyce, 2017), as well as the strain that unreliable and unpredictable environments place on caregivers, depleting their adaptive capacities and compromising their ability to provide sensitive and nurturing care (Doan and Evans, 2020). Importantly, Yang et al. (2023) found that parenting investment moderates children's adaptive calibration in response to environmental harshness and unpredictability, further clarifying that while parenting quality itself serves as a direct indicator of children's socioemotional outcomes (Ainsworth et al., 1978), it also operates in between, influencing the relationship between other environmental factors and socioemotional development While factors may indicate environmental harshness and unpredictability—such as disengagement, parental maltreatment, and harsh neighborhood conditions—financial status is one of the commonly used indicators across studies (Suor et al., 2017; Mededovic, 2019; Warrant & Barnett 2020). Specifically, socioeconomic status (SES) is often used as a measure of environmental harshness, based on the assumption that limited economic resources challenge famililes’ coping capacities (Belsky et al., 2012; Simpson et al., 2012; Li et al., 2018; Warren & Barnett 2020). Low childhood SES can also reflect early exposure to environmental unpredictability, as children from lower-SES backgrounds tend to experience a more frequent residential changes, unpredictable routines, and inconsistent caregiving compared to their higher-SES counterparts (Evans et al., 2005; Leventhal & Brooks-Gunn, 2000; Dickerson et al., 2019). Consistent with the relationship between environmental harshness and parenting quality, SES has been shown to influence parenting practices (Hoff et al., 2002; Conger et al., 2010) and is directionally linked to maternal sensitivity (Belsky et al., 2012). Similarly, Koşkulu et al. (2021) found that higher-SES mothers were more sensitive and engaged in higher-quality parent-child interactions in a mediation analysis. This aligns with the well-established link between parenting quality, socioemotional development, and attachment behaviors. Children raised in low-SES environments are more likely to experience inconsistent or coercive parenting, leading to poorer inhibitory control and emotion regulation. They are also at greater risk of developing insecure attachment styles, particularly characterized by anxiety and avoidance (Vaughn et al., 1999; Sakman et al., 2023; Conejero & Rueda, 2023; Bian & Wu, 2023). Social support is another indicator of environmental harshness and unpredictability, as it aligns with the definition of resource scarcity that influences morbidity and mortality (Ellis et al., 2009). Social support contributes to resource availability, as it reflects a stable perception of one’s social context (Green et al., 2007) and determines access to psychological and material resources that enhance stress coping (Cohen, 2004). Additionally, it can serve as a marker of morbidity and mortality risk, as low social support and social isolation have been identified as significant risk factors for adverse health outcomes, including cardiovascular disease and ischemic stroke (Mookadam, 2004; Freak-Poli et al., 2021). Consistent with these definitions, social support is positively associated with parental mental well-being. Parents who perceive sufficient positive social support tend to experience better mental health (Lakey & Cronin, 2008; Acoba, 2024) and greater parental efficacy (Suzuki et al., 2009; Fierloos et al., 2023), which in turn contributes to improved parenting skills (Abidin, 1992; Andresen & Telleen, 1992), greater responsiveness (Crnic et al., 1986), and more positive child-rearing attitudes (Álvarez et al., 2021). Similarly, social support has been shown to buffer the impact of antenatal depressive symptoms on maternal emotional availability (MacMillan et al., 2021), correlate with perceived competence and satisfaction among at-risk mothers (Brown et al., 2018), and be positively linked to maternal love (Can et al., 2024). Social support is also associated with infant attachment security and socioemotional development. Research has linked higher levels of social support to increased security in infant-mother attachment at 12 months (Crnic et al., 1986) and enhanced attachment security in socially at-risk families (Jacobson & Frye, 1991). More recent findings suggest that social support fosters infant socioemotional development and competence (Schuijers et al., 2024), reducing externalizing and internalizing problems while promoting prosocial behaviors (Hosokawa & Katsura, 2024). However, some studies have reported null findings (Li, 2023), indicating that further research is needed to clarify the extent of these associations. Electrodermal Activity Electrodermal activity (EDA), previously referred to as Galvanic skin response, is one of the most widely used physiological measures of autonomic nervous system (ANS) activity. EDA reflects sweat levels in the palmar sweat glands. It has been applied to a broad range of psychological constructs, including stress, affect, and arousal, and serves as both a predictor and correlate of normal and abnormal behaviors (Chaspari et al., 2015; Cacioppo et al., 2016). EDA is unique among systems measuring ANS responses because it provides a direct, quantifiable representation of skin sympathetic nerve activity uncontaminated by the parasympathetic nerve activity. This makes it a reliable indicator of sympathetic arousal (Boucsein et al., 2012; Bach, 2014; Braithwaite et al., 2015). Specifically, increases in skin conductance level (SCL)—which reflect long-term tonic EDA states rather than responses to specific stimuli (Boucsein et al., 2012)—have traditionally been linked to the behavioral inhibition system. Regulated at the bulbar level of the reticular formation, this system is hypothesized to function as an anxiety mechanism, inhibiting behaviors in response to threatening or non-rewarding stimuli (Cacioppo et al., 2016; Fowles, 1980; Speck et al., 2023). Maternal arousal plays a crucial role in adaptive parenting, as emotions can either facilitate or disrupt sensitive caregiving, depending on their intensity (Dix, 1991; Teti & Cole, 2011). Excessive arousal may lead parents to inhibit their responses to a crying infant (Speck et al., 2023), as lower SCL reactivity has been associated with more sensitive parenting behaviors (Emery et al., 2014) and heightened SCL reactivity has been linked to an increased risk of impulsive and harsh discipline toward infants (Joosen et al., 2013). Recent findings further suggests that mothers’ SCL reactivity to an unfamiliar infant cry predicts later insecure-avoidant attachment behaviors in their own infants (Speck et al., 2023). Together, these findings suggest SCL as a key physiological marker of maternal caregiving behaviors and their intergenerational influence on infant attachment patterns. Environmental harshness and unpredictability are also thought to influence sympathetic arousal. In a widely recognized study by Ellis and his colleagues (2005), both highly supportive and highly stressful home environments were found to predict development of heightened sympathetic nervous system reactivity. Although few studies have specifically examined the role of SES and social support in shaping maternal SNS reactivity, several relevant findings suggest how harsh environments may contribute to autonomic regulation over time. For example, individuals who experienced less sensitive maternal caregiving in childhood exhibited greater increases in SCL during distressing situation (Raby et al., 2015), suggesting that early adversity may alter sympathetic responses. Other studies have explored the influence of SES and social factors on autonomic responses, though findings do not necessarily support long-term effects. For instance, subjective social stress and exposure to violence have been linked to increased heart rate variability (Schnell et al., 2013; Mellman et al., 2018), and exposure to provoking social context has been associated with greater increase in systolic blood pressure (Gallo et al., 2000). Additionally, EDA signal covariation has been observed between individuals in close relationships, such as dating couples, suggesting another potential social influence on autonomic regulation (Timmons et al., 2023). Low SES has also been linked to consistently higher heart rate and shorter pre-ejection period, also indicating altered autonomic function (Johnson et al., 2017). Current Study This study has two aims. The first is to to examine whether environmental factors (specifically SES and social support) during the prenatal period predict young infants’ attachment behaviors during the Still Face Paradigm. The second aim is to test whether these longitudinal associations are due to expectant mothers’ autonomic responses measured by SCL reactivity to a video of an unfamiliar infant crying. This study is unique in that, while previous research has explored associations between social support, SES and autonomic responses (Schnell et al., 2013; Johnson et al., 2017), to our knowledge, no studies have specifically examined whether these factors predict maternal sympathetic nervous system (SNS) activity. Additionally, while prior research has established links between environmental harshness/unpredictability and SNS activity (Ellis et al., 2005), as well as between SNS activity and maternal parenting quality and infant attachment behaviors (Emery et al., 2014; Speck et al., 2023), no studies have investigated whether SNS activity accounts for the association between the environmental harshness/unpredictability and infant attachment behaviors. By examining how social support and SES, as indicators of environmental harshness and unpredictability, predict maternal caregiving capacity shown by autonomic response, and in turn, shape infant attachment relationships, this study aims to provide a more comprehensive understanding of how infants may develop adaptive or maladaptive attachment strategies in early life. Our first hypothesis is that SES and social support will be negatively associated with infants’ later insecure-resistant and insecure-avoidant attachment behaviors. This prediction is based on prior findings linking SES to insecure attachment (Sakman et al., 2023), social support to secure attachment (Jacobson & Frye, 1991), and SES to later social competencies and behavioral problems in infants (Schuijers et al., 2024; Hosokawa & Katsura, 2024). This hypothesis also aligns with the understanding that avoidant attachment behaviors often emerge from harsh parenting and resistant attachment behaviors result from inconsistent parenting (Groh et al., 2019). Since low parenting investment is considered a proxy of environmental harshness and unpredictability (Yang et al., 2023), and given that SES and social support may reflect both both harsh and unpredictable environment (Belsky et al., 2012; Dickerson et al., 2019), it is reasonable to expect that SES and social support will correlate with both forms of insecure attachment. Our second hypothesis is that greater SCL reactivity to an unfamiliar infant’s distress signal will help account for the negative relationship between SES and avoidant-insecure attachment behaviors in infants, as well as the mothers’ perceived social support and avoidant-insecure attachment behaviors. This prediction is based on evidence that higher SES and stronger social support are associated with more child-centered and sensitive parenting practices, whereas lower SES and limited social support are linked to lower parenting quality and higher attachment anxiety of children (Conger et al., 2010; Sakman et al., 2023; Crnic et al., 1986). Additionally, this hypothesis builds on findings by Speck et al. (2023), which suggest that maternal autonomic responses predict infants’ avoidant attachment behaviors.

The application of psychophysiology in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of an array of physiological signals and analysis techniques. One of the most widely used signals is electrodermal activity, or EDA, also known as galvanic skin response or GSR. This signal is commonly used as a proxy for physiological arousal, but recent advances of interpretation and analysis suggest that traditional approaches should be revised. We present a short review on the application of EDA in human-computer interaction. This paper aims to serve as a primer for the novice, enabling rapid familiarisation with the latest core concepts. We put special emphasis on everyday human-computer interface applications to distinguish from the more common clinical or sports uses of psychophysiology. This paper is an extract from a comprehensive review of the entire field of ambulatory psychophysiology, including 12 similar chapters, plus application guidelines and systematic review. Thus any citation should be made using the following reference: B. Cowley, M. Filetti, K. Lukander, J. Torniainen, A. Henelius, L. Ahonen, O. Barral, I. Kosunen, T. Valtonen, M. Huotilainen, N. Ravaja, G. Jacucci. The Psychophysiology Primer: a guide to methods and a broad review with a focus on human-computer interaction. Foundations and Trends in Human-Computer Interaction, vol. 9, no. 3-4, pp. 150--307, 2016.

Electrodermal activity (EDA) is one of the most widely used techniques for automatic emotion recognition. Lately, great efforts have been made to increase EDA information extraction from signal processing and feature engineering and selection tasks, with the main purpose of maximizing the predictive power of such models. However, far too little attention has been paid to understanding the emotional models underlying such affective states recognition systems with EDA and the inferential value of such statistical learning models. A systematic review and meta-analysis of the literature on emotion recognition from EDA will be conducted. Journal articles, conference papers, and electronic preprints published between January 2010 and December 2020 will be selected. We will primarily investigate the characteristics of the affective model used (e.g. categorical and dimensional models of affective states). Secondarily, the characteristics of the EDA measurements and statistical models used for the automatic recognition task will be explored. It is expected to analyze common features in the state of the art, and based on this to make recommendations for future work in the field.

Electrodermal activity (EDA) is one of the most widely used techniques for automatic emotion recognition. Lately, great efforts have been made to increase EDA information extraction from signal processing and feature engineering and selection tasks, with the main purpose of maximizing the predictive power of such models. However, far too little attention has been paid to understanding the emotional models underlying such affective states recognition systems with EDA and the inferential value of such statistical learning models. A systematic review and meta-analysis of the literature on emotion recognition from EDA will be conducted. Journal articles, conference papers, and electronic preprints published between January 2010 and December 2020 will be selected. We will primarily investigate the characteristics of the affective model used (e.g. categorical and dimensional models of affective states). Secondarily, the characteristics of the EDA measurements and statistical models used for the automatic recognition task will be explored. It is expected to analyze common features in the state of the art, and based on this to make recommendations for future work in the field.

scoping review

3D printable housing for the BITalino Electrodermal Activity (EDA) Sensor (http://www.bitalino.com) by André Magro from BEE Very Creative (https://beeverycreative.com)

Folder: AN EXPERIMENT TO TEST APPARENT REMOTE ACTION (RA) EFFECTS ON ELECTRODERMAL ACTIVITY; STAR GATE was an umbrella term for the Intelligence Community effort that used remote viewers who claimed to use clairvoyance, precognition, or telepathy to acquire and describe information about targets that were blocked from ordinary perception. The records include documentation of remote viewing sessions, training, internal memoranda, foreign assessments, and program reviews. The STAR GATE program was also called SCANATE, GONDOLA WISH, DRAGOON ABSORB, GRILL FLAME, CENTER LANE, SUN STREAK. Files were released through CREST and obtained as TIF files by the Black Vault and converted to PDF by That 1 Archive.

The research project aims to test a pain management protocol by integrating electrodermal activity (EDA) biofeedback and the acceptance principle of mindfulness. Participants in the study will be randomly assigned to either a control or experimental group, with both groups undergoing the cold pressor test (CPT) as a standardized measure of pain. The experimental group will receive a short pain management training utilizing EDA biofeedback to monitor and regulate physiological responses, coupled with acceptance principles to cultivate psychological resilience. By combining these modalities, the study aims to explore the effects of physiological regulation and psychological acceptance in enhancing pain management strategies. The control group will also receive a similar short pain management training with progressive muscle relaxation and mindfulness mediation with an explicit aim to enhance emotional regulation for better pain tolerance, but without the EDA biofeedback and the practice of acceptance of pain.

Traditional EDA research is based on unilateral measurements taken from the non-dominant hand . The unilateral measurement approach assumes that arousal is the same across the body at a given time and a “one true arousal” can be measured from the non-dominant hand. This idea has dominated research until very recently. On the other hand, more recent theorie (such as Multiple Arousal Theory, MAT) predicts that EDA could vary on different dermatomes, depending on several underlying generators of EDA (e.g. situational factors and the person’s actual psychological state). This novel approach calls for multi-site measurements.

The measurement and analysis of Electrodermal Activity (EDA) offers applications in diverse areas ranging from market research, to seizure detection, to human stress analysis. Unfortunately, the analysis of EDA signals is made difficult by the superposition of numerous components which can obscure the signal information related to a user's response to a stimulus. We show how simple pre-processing followed by a novel compressed sensing based decomposition can mitigate the effects of the undesired noise components and help reveal the underlying physiological signal. The proposed framework allows for decomposition of EDA signals with provable bounds on the recovery of user responses. We test our procedure on both synthetic and real-world EDA signals from wearable sensors and demonstrate that our approach allows for more accurate recovery of user responses as compared to the existing techniques.

When people face obstacles, expectations, or circumstances that they view as dangerous, overpowering, or beyond their capacity to handle, they feel stress, a physiological and psychological reaction. In this publication, we have collected signals from a variety of participants using both Electrocardiography (ECG) and Electrodermal Activity (EDA). Each person has two electrodes put on their fingertips to capture signals in the BIOPAC MP36 system under three different conditions: stress, deep breathing technique (DBT), and repose. Following the acquisition of all data in the BIOPAC system, the signals are sent to the KUBIOS program, which uses them to extract significant HRV (Heart Rate Variability) properties. The KUBIOS program extracts 38 characteristics in total, and several graphs are created for stress analysis based on these data. These graphs give us a clear idea about variation in different HRV parameters wherein subject is under supine, DBT and stressed conditions. Through the analytical study, we observed that stress index is higher when subjects are put under stressed state while as, stress index came out to be lower during DBT state. This clearly shows that EDA signals are effectively analyzing variations in different HRV parameters and is able to recognize stress in healthy subjects.

Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Final Report- -Objective E, Task 6 AN EXPERIMENT TO TEST APPARENT REMOTE ACTION (RA) EFFECTS ON ELECTRODERMAL ACTIVITY By: G. SCOTT HUBBARD SRI International WILLIAM W. BRAUD Mind Science Foundation PETER J. McNELIS, DSW CONTRACTING OFFICER'S TECHNICAL REPRESENTATIVE 333 Ravenswood Avenue Menlo Park, California 94025 U.S.A. (415) 326-6200 Cable: SRI INTL MPK TWX: 910-373-2046 December 1986 1 cp9 aL_ ved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 ed For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Final Report- -Objective E, Task 6 December 1986 Covering the Period 1 October 1985 to 30 September 1986 AN EXPERIMENT TO TEST APPARENT REMOTE ACTION (RA) EFFECTS ON ELECTRODERMAL ACTIVITY By: G. SCOTT HUBBARD SRI International WILLIAM W. BRAUD Mind Science Foundation PETER J. McNELIS, DSW CONTRACTING OFFICER'S TECHNICAL REPRESENTATIVE ROBERT S. LEONARD, Executive Director Geoscience and Engineering Center 333 Ravenswood Avenue ? Menlo Park, California 94025 ? U.S.A. ved For RekeaissE2000/0B1110 sICIAf-RDM6-Qt 7S89ROWH06 60001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 I INTRODUCTION A new study was conducted* to ascertain whether an apparent remote action (RA) influence on the electrodermal activity (EDA) of an individual could be explained by intuitive data sorting (IDS). In order to enhance the likelihood of obtaining a statistically significant result, SRI International elected to award a subcontract to the Mind Science Foundation (MSF) for an experiment that would be an extension of previously published work.t Electrodermal activity is identical to galvanic skin response (GSR) which is the phasic (ac) fluctuation in skin conductance, as distinguished from the tonic (dc) skin resistance (i.e., basal skin resistance or BSR). The claim put forward by the Mind Science Foundation is that RA by one individual (the "influencer") can directly affect the EDA of another (the subject). We believe that their data may be completely explained by a model developed at SRI International which does not require the existence of RA. Our model (Intuitive Data Sorting--IDS) postulates that some individuals possess an ability to anticipate periods when the EDA of a participant is "quiet," and they are able to act upon this information. In other words, in the absence of all overt information about the EDA, individuals are able to "sort" EDA records into two bins--one with large values (activity periods), one with small values (calming periods)--by initiating the collection of data at the opportune moment. The IDS model is capable of differentiating between causal and informational effects. In order to develop an appropriate protocol for these experiments, it was decided in advance to first conduct a pilot experimental series and then a formal (or confirmation) experiment. The details of these experiments may be found in Appendices A and B, respectfully. The balance of this report is a critical analysis of those experiments. * This report constitutes Objective E, Task 6, detailing an experiment to determine possible RA effects on living systems. t Braud, W., and Schlitz, M., "Psychokinetic Influence on Electrodermal Activity, The Journal of Parapsychology, Vol. No. 47, No. 2, pp. 95-119 (June 1983). Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 simply observing the subject's electrodermal chart tracing, and making sensorily and logically informed guesses about the optimal times to press the button and initiate sampling (on the basis of knowledge of the likely time course of the subject's autonomic activity). In the absence of experimental artifact and any overt knowledge of the participant's electrodermal activity, the MSF wished to determine whether it was possible for the influencer to select a starting time for an RA experiment such as to give a significant correlation between the effort periods and the electrodermal measurements. If IDS is the operative mechanism, it was expected that the MULTIPLE-SEEDS condition would enhance the effect. The dependent variable in this experiment is the EDA. To claim evidence for a statistical anomaly, they required that the psychoenergetic effect (expressed as a percentage) be significantly different from the mean chance expectation (MCE). This measure is obtained by dividing the participant's EDA during the calm-aim effort period by the sum of the EDAs during the activate-aim and calm-aim periods over the course of the trial. In the absence of psi effect, the MCE is 50 percent. Three statistical analyses were planned: 1. The first analysis would be a comparison of the psi scores (calm-aim percentage scores) for the two conditions [MULTIPLE-SEEDS (IDS) and SINGLE-SEED (RA)]. This analysis would involve a matched (dependent) t test performed on the 32 pairs of scores. Because no directional prediction was made in this case, a two-tailed test was planned, with alpha set at 0.05. 2. The second analysis would be a determination of whether a psi effect occurred in the SINGLE-SEED condition. For this analysis, a single-mean t test would be used to compare the 32 psi scores with an MCE of 50 percent. Because a directional (i.e., psi-hitting) prediction was made in this case, a one-tailed test was planned, with alpha set at 0.05. 3. The third analysis would be a determination of whether a psi effect occurred in the MULTIPLE-SEED condition. For this analysis, a single-mean t test would be used to compare the 32 psi scores with an MCE of 50 percent. Because a directional prediction was also made in this case, a one-tailed test was planned, with alpha set at 0.05. Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 bo to IDS Condition RA Condition Figure 1 Timing Diagram of Events in MULTIPLE-SEEDS (IDS) and SINGLE-SEED (RA) Conditions for a Given EDA Record. Note that by varying the rest period, the same EDA data is recorded in both activate-aim periods. time --- b1 In Figure 1, "b" represents a button press by the influencer, which initiates a trial, and "t" is the subsequent tone heard by the influencer alerting him to begin an effort period. As described earlier, the RA condition was distinguished from the IDS condition by fixing all future delay times (e.g., t1 - b1) at the initial button press, bo. In the IDS condition, the delay times were determined at the time of each button press. Notice, however, that by interposing a variable rest period, the two experimental conditions can now become indistinguishable. As is shown in Figure 1, by appropriately adjusting his rest period in the RA condition, the influencer could completely negate the effect of the previously determined delay time and achieve the same results as in the IDS condition. In other words, the same EDA data would be recorded for an effort period in either condition. Only if there were no Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 IV CONCLUSIONS AND RECOMMENDATIONS As is clear from the preceding discussion, the study proposed and performed by the MSF did not provide a valid test of the IDS hypothesis in a putative bio-RA experiment. To be fair in our criticism, it must be acknowledged that it is quite difficult to completely eliminate all possible IDS opportunities in any experiment where the effect of interest is a small statistical perturbation in a time varying output. This difficulty becomes particularly apparent when the experimenter is required to simultaneously satisfy the competing demands of a double-blind protocol and the human need for rest periods. There appear to be two paths that can serve to more clearly separate IDS from RA. One method is to require that the effect under investigation be sufficiently "large" so as to demonstrate a clearly functional relationship between variables. Such an effect size should approach an infinite signal-to-noise ratio. In disciplines that depend on signal averaging, manipulation of noisy data, or large numbers of measurements to extract meaningful information, a practical definition of an infinite signal-to-noise ratio is 7 to 8 a. Examples may be found in radar technology, interplanetary satellite communications, and high-energy physics. Unfortunately, the effect sizes in typical statistical RA experiments are essentially always 2 or. For those statistical RA experiments whose effect sizes are 2 a, but where the data sample size (e.g. sequence length in random number generators) can be varied over several orders of magnitude, another approach is dictated by the IDS model. As was demonstrated in our FY 1984 report on IDS, a causal "force" will result in a very different relationship of effect size to sequence length when compared with a purely informational process. During FY 1987, the MSF will be conducting a new group of experiments using the hemolysis rate of red blood cells as the target variable. The intent would be to examine whether a proposed RA influence can slow the rate of hemolysis. Because the number of cells under examination can be varied by dilution over several orders of magnitude, the IDS model could be tested in the following way. We suggest that a separate group of samples be treated with a saline solution that would imitate the proposed RA effect. The balance of the experiment would be conducted in the usual way with control and experimental samples of varying cell number. Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Appendix A POSSIBLE ROLE OF INTUITIVE DATA SORTING IN BIOLOGICAL PSYCHOKINESIS: William Braud and Marilyn Schlitz Mind Science Foundation Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 value. This method, when applied to the present data, yields an overall z = 3.98, which has an associated p = 0.000034. Thus, the observed psi effect is a reliable and robust one. We have been interpreting the obtained psi effect as a psychokinetic (causal) influence of the subject's autonomic nervous system activity by the distant, isolated influencer. An alternative possibility, however, is that the effect may be contributed totally or partially by an "intuitive data sorting (IDS)" process. The influencer or experimenter psychically, yet unconsciously, scans the future electrodermal activity stream of the subject and begins an experimental session at a time that maximizes the degree of fit between the ongoing electrodermal activity and the prescribed schedule of influence and control epochs. Stated somewhat differently, the experimenter might psychically and unconsciously sort the subject's electrodermal data into two "bins" so that significantly more of the activity in the prescribed direction falls in the influence bins than in the control bins (see May et al., 1985).2 According to this "informational" model, psi functioning is still in evidence, but is of an informational rather than a causal (psychokinetic) sort. The present pilot study is designed to test a hypothesis that is suggested by the IDS model. According to this hypothesis, the effectiveness of intuitive data sorting is proportional to the number of opportunities provided for such sorting. It is hypothesized that a single opportunity to psychically sort a future data stream may not be as effective as multiple opportunities for such sorting. Thus, the scoring rate might be greater if the person who initiates the sampling epochs in a bio-PK session is given the freedom to initiate each epoch at whim (and have, for example, 20 opportunities for intuitive data sorting) than it would be if the person were allowed only a single data sorting opportunity. On the other hand, according to a causal psychokinetic interpretation of the bio-PK effect, the scheduling of the sampling epochs should not influence the results; (i.e., the PK effect should be the same whether or not the influencer or experimenter has many or few degrees of freedom in deciding when to initiate sampling epochs. Subjects Twenty-five individuals participated in this pilot study. Five persons served as influencers and twenty persons served as subjects; each influencer worked with four subjects. The first author (W. Braud) served as experimenter for half of the sessions, while the second Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 accomplished by watching randomly changing patterns of colored squares of light on a 12-inch display screen 2 meters away, and by listening to prerecorded computer-generated random tones through headphones. The subject was asked to allow his or her mind to be as "random" as possible, observing thoughts, images, and feelings as they spontaneously arose without clinging to any of them. The subject was asked to make herself or himself open to and accepting of a distant mental influence by the influencer, but not to try to consciously guess when influence attempts might be made. The subject, of course, was unaware of the number, timing, or scheduling of the various influence attempts. The experimenter returned to the influencer's room and consulted a sealed envelope to learn the influence epoch sequence for the session. A set of these sequence envelopes had been prepared before hand by an assistant who was not otherwise involved in the experiment. The envelopes has been prepared by using a table of random numbers and a method that minimized the preparer's degree of freedom in making arbitrary decisions about where to enter the table, and how to assign conditions to the random numbers [see Stanford (1981)5 for the rationale underlying this method]. The envelope indicated whether the influence epoch sequence was to be calm-activate-calm (CAAC) or its opposite (ACCA). This counterbalanced sequence was used for the 20 sampling epochs of a session. The experimenter entered the proper sequence into the computer program that controlled the experiment, and started playing the audio cassette that presented the subject's random tones. During the 5-minute adaptation period that followed, the experimenter described to the influencer the new element added to this pilot experiment to test the IDS hypothesis. The influencer was to press a button at what he or she intuitively felt to be the optimal time for beginning the next sampling epoch. The influencer was told that it might be possible to psychically, yet unconsciously, scan the future autonomic activity data stream of the subject and press the button so as to optimally sort the subject's activity into the appropriate sample epochs and thereby increase the scoring rate. The addition of this IDS option is, of course, accompanied by psychological factors such as beliefs and expectations that might obscure its true effectiveness. Therefore, a procedure was designed that would allow us to control for such psychological factors. This procedure required a contrast condition in which the influencer appeared to be initiating sampling epochs by means of his or her button pressing, but in reality was not. This was accomplished in the following manner. In the condition that we expected would optimize IDS, the influencer's button presses initiated sampling epochs after randomly determined variable delays. In this condition (the MULTIPLE SEEDS condition), the precise times of concurrence of the button presses were crucial in determining Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 influencer and the experimenter (and, of course, the subject) remained unaware of which conditions were in effect in the two respective sessions until the end of the second session, at which time a computer printout revealed the condition sequence. The order of the two conditions was determined randomly by a computer algorithm that was seeded before the first session. This algorithm was based upon the timing of a carriage return, which occurred while the experimenter was entering keyboard information about the subject's name, the date and time of the session, etc. Each of the two sessions required approximately 45 minutes for completion. The two sessions were separated by a brief break of 3 to 5 minutes duration. At the conclusion of the second session, the computer generated a printout of the subject's average electrodermal activity during each of the 20 sampling epochs of each of the two sessions, along with an indication of the order of the two (SINGLE- or MULTIPLE-SEEDS) conditions. The experimenter returned to the subject's room, removed the headphones and palmar electrodes, then returned with the subject to the experimenter's office where the influencer was now waiting. The influencer and the subject discussed their experiences during the sessions while the experimenter calculated the experimental results, based upon the printout. The three participants discussed the outcome of the experiment and then concluded their visit. All procedural details that have not been mentioned explicitly may be found in Braud and Schlitz (1983).3 That paper provides information about specific equipment, electrodermal sampling, etc. RESULTS OF THE PILOT EXPERIMENT For each session, percentage scores were calculated for the 10 calm-aim epochs and for the 10 activate-aim epochs. This was done by summing the mean electrodermal activity scores for each of the 20 recording epochs, then dividing this total activity score into the sum of the mean electrodermal activity scores for the 10 calm-aim epochs; the process was repeated for the activate-aim epochs. In the absence of a psi effect, these percentage scores should approximate 50 percent. A psi effect would be evidenced by a set of calm-aim percentage scores that were significantly lower than 50 percent. Our first analysis was a determination of whether the 20 subjects' SINGLE-SEED calm-aim percentage scores differed significantly from their MULTIPLE-SEEDS calm-aim Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 the button-press-determined variable delays before each sampling epoch lengthened each of the two formal experimental periods to approximately 40 minutes each. When time was added for (1) initial discussion before the first session, (2) a break between the two sessions, and (3) discussion following the second session, it was not uncommon for the entire length of the experiment to be 2-1/2 hours long. Of the five influencers (each of whom had to make four visits to the laboratory) all but one found the long sessions oppressive. We had originally planned to select the two influencers having the highest performance records for their sessions as the two "winners" of the pilot trials, and those two persons were to participate as the two influencers for the confirmation study--each influencer working with sixteen subjects. Only one of the five influencers was enthusiastic about this possibility; the other four influencers did not look forward to participating in additional sessions, now that they were aware of how lengthy the sessions were. Thus, during the pilot study, the influencers (with one exception) functioned with mixed feelings. They wished to do well in their sessions and score highly; on the other hand, they were aware that high scoring might earn them the dubious "reward" of participating in a large number of lengthy confirmation sessions. It is not unlikely that these mixed motivations may have led to less than optimal moods in the participants and could have negatively influenced the outcome of the pilot study. Interestingly, the highest scoring influencer was in fact the person who objected least to the session lengths, and who appeared to be undaunted by the possibility of additional confirmation trials. In light of these considerations, it was necessary for us to revise our plans for the confirmation study. Instead of having only two influencers, each working with sixteen subjects, we decided to ask eight influencers to work with four subjects each. This would greatly lessen the work load of the influencers. We also decided to drastically reduce the length of each session. This would be accomplished by (1) reducing the number of sampling epochs from 20 to 12, (2) eliminating the 5-minute adaptation period at the beginning of each session, (3) reducing the range of the variable delay between button-press and sampling epoch initiation to 30 to 40 seconds, and (4) reducing the duration of the break between a subject's two sessions to one minute. As a result of these changes, the new session lengths for the confirmation trials would be approximately 15 minutes each, and an entire two-session procedure could be accomplished in approximately 40 minutes, rather than the 2 1/2 hours required in the pilot study. It was our hope that these new conditions would render the sessions less trying, and would produce more optimal moods in all experimental participants. Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 REFERENCES (Appendix A) 1. Rosenthal, R., "Combining Results of Independent Studies," Psychological Bulletin, Vol. 85, pp. 185-193 (1978). 2. May, E., Radin, D., Hubbard, G., Humphrey, B, and Utts, J., "Psi Experiments with Random Number Generators: An Informational Model," Proceedings of 28th Annual Parapsychological Association Convention, Tufts University, Medford, Massachusetts (1985). 3. Braud, W., and Schlitz, M., "Psychokinetic Influence on Electrodermal Activity," Journal of Parapsychology, Vol. 47, pp. 95-119 (1983). 4. Schlitz, M., and Braud, W., Reiki-Plus Natural Healing: An Ethnographic/Experimental Study," Psi Research, Vol. 4, pp. 100-123 (1985). 5. Stanford, R., "Are We Shamans or Scientists?" Journal of the American Society for Psychical Research, Vol. 75, pp. 61-70 (1981). Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 INTRODUCTION For a number of years, researchers at the Mind Science Foundation have been engaged in studies of the distant mental influence of biological systems (i.e., "biological psychokinesis" or "bio-PK"). While the biological target systems for some of these studies have included the spatial orientation of fish, the locomotor activity of small animals, and the rate of hemolysis of human red blood cells, the system with which we have worked most often has been the electrodermal activity of another person. The experimental protocol of a typical electrodermal bio-PK experiment is as follows. The subject sits in a comfortable room watching a random colored-lights display and listening to random tones through headphones while his or her electrodermal activity is monitored via palmar electrodes. Concurrently, an "influencer" in another room (isolated from all possible conventional sensorimotor interactions with the subject) attempts to mentally influence the ongoing electrodermal activity of the subject according to a predetermined schedule known to the subject. The subject's spontaneous electrodermal activity (skin resistance responses) is objectively assessed during each of ten 30-second influence periods and each of ten 30-second noninfluence control periods by means of an analog-to-digital converter interfaced with a microcomputer. By chance, the average electrodermal activity during influence epochs should equal that during control epochs. A statistically significant excess of electrodermal activity in the prescribed direction (i.e., higher influence than control scores under an "activate aim" condition or lower influence than control scores under a "calm aim" condition) provides evidence for a psi effect in the experiment. The protocol just described has been used in a series of eleven electrodermal bio-PK experiments in which a total of 174 subjects have participated. An appropriate method for assessing the statistical significance of the entire series is the z-score addition method described by Rosenthal (1978, 1979).1 2' Here, one converts the studies' obtained p values into z-scores, sums these z-scores, and divides by the square root of the number of studies being combined; the result is itself a z-score that can be evaluated by means of an associate p References are listed at the end of Appendix B. Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 minute. As a result of these changes, the new session lengths for the confirmation trials were approximately 15 minutes each, and the entire two-session procedure could be accomplished in approximately 40 minutes, rather than the 2 1/2 hours required in the pilot study. It was our hope that these new conditions would render the sessions less trying and would produce more optimal moods in all experiment participants. Subjects Forty individuals participated in this confirmation study. Eight persons served as influencers and thirty-two persons served as subjects; each influencer worked with four subjects. The first author served as experimenter for half of the sessions, while the second author served as experimenter for the remaining half of the sessions. One of the eight influencers was the person who had had the highest performance record in the pilot study; this was also the person who had been least bothered by the lengths of the pilot sessions and who had been the most enthusiastic about participating in further experiments. The second influencer had participated successfully in prior electrodermal bio-PK experiments. The third influencer was a psi researcher who had a history of successful psychokinesis performances in his own experiments. The fourth and fifth influencers had participated successfully in several previous psi experiments at the Foundation. The sixth and seventh influencers were very interested in psychic healing and had had ostensible psi healing interaction in their everyday lives. The eighth influencer had participated in previous psi experiments at the Foundation as a subject and as a student experimenter, and had expressed an interest in the bio-PK confirmation experiment. Four influencers were males and four were females. The thirty-two subjects were selected from a pool of persons expressing interest in participating in bio-PK and other psi experiments. Some participants had previously enrolled in workshops presented by the two authors. Others were undergraduate students from a local college who participated as part of a course requirement. Eight (one-fourth) of the subjects had participated in prior psi experiments conducted at the Foundation; twenty-four (three-fourths) of the subjects were first-time participants. Twenty-two of the subjects were females, and ten were males. Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 The envelopes had been prepared through the use of a table of random numbers using a method that minimized the preparer's degree of freedom in making arbitrary decisions about where to enter the table, and how to assign conditions to the random numbers [see Stanford (1981) for the rationale underlying this method]. The envelope indicated whether the influence :poch sequence was to be calm-activate-activate-calm (CAAC) or its opposite (ACCA). This counterbalanced sequence was used for the 12 sampling epochs of a session. The experimenter entered the proper sequence into the computer, recorded the subject's basal skin resistance, then started the computer program that controlled the experiment and started playing the audio cassette that presented the subject's random tones. The new element that had been added to this experiment to test the IDS hypothesis was described to the influencer by the experimenter. The influencer was to press a button at what he or she intuitively felt to be the optimal time for beginning the next sampling epoch. The influencer was told that it might be possible to psychically, yet unconsciously, scan the future autonomic activity data stream of the subject, and press the button so as to optimally sort the subject's activity into the appropriate sampling epochs--thereby increasing the scoring rate. The addition of this IDS option is, of course, accompanied by psychological factors such as beliefs and expectations that might obscure its true effectiveness. Therefore, a procedure was designed that would allow us to control for such psychological factors. This procedure required a contrast condition in which the influencer appeared to be initiating sampling epochs by means of his or her button pressing, but in reality was not. This was accomplished in the following manner. In the condition that we expected would optimize IDS, the influencer's button presses initiated sampling epochs after randomly determined variable delays. In this condition (the MULTIPLE-SEEDS condition), the precise times of occurrence of the button presses were crucial in determining the delay periods, since the button presses selected the clock values that served as the different seeds for the pseudorandom algorithm that generated the values of the delays. Thus, button presses actually could be efficacious in determining sampling scheduling. In the contrast condition (the SINGLE-SEED condition), all random delay periods were determined by the first of the influencer's 12 button presses. The computer's clock value at the time of this first button press seeded the pseudorandom algorithm once and only once, and all other button presses "fetched" their random delays from the already determined outcome of that first seeding. The use of randomly varying delays between button presses and sampling epoch initiations accomplished two things: (1) they allowed the influencer and the experimenter to remain blind as to whether a SINGLE-SEED or MULTIPLE-SEEDS condition was in effect Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 At the conclusion of the second session, the computer generated a printout of the subject's average electrodermal activity during each of the 12 sampling epochs of each of the two sessions, along with an indication of the order of the two (SINGLE- or MULTIPLE-SEEDS) conditions. The experimenter returned to the subject's room, removed the headphones and palmar electrod;s, then returned with the subject to the experimenter's office where the influencer was now waiting. The influencer and the subject discussed their experiences during the sessions while the experimenter calculated the experimental results, based upon the printout. The three participants discussed the outcome of the experiment and then concluded their visit. All procedural details that have not been mentioned explicitly may be found in Braud and Schlitz (1983).3 That paper provides information about specific equipment, electrodermal sampling, etc. Three statistical analyses were planned: 1. A comparison of the psi scores (calm-aim percentage scores) for the two SEEDS conditions. This analysis would involve a matched (dependent) t test performed on the 32 pairs of scores. Since no directional prediction was made in this case, a two-tailed test was planned, with alpha set at 0.05. 2. A determination of whether a psi effect occurred in the SINGLE SEED condition. For this analysis, a single-mean t test would be used to compare the 32 psi scores with a mean chance expectation (MCE) of 50 percent. Since a directional (i.e, psi-hitting) prediction was made in this case, a one-tailed test was planned, with alpha set at 0.05. 3. A determination of whether a psi effect occurred in the MULTIPLE-SEED condition. For this analysis, a single-mean t test would be used to compare the 32 psi scores with a mean chance expectation (MCE) of 50 percent. Since a directional (i.e., psi-hitting) prediction was made in this case, a one-tailed test was planned, with alpha set at 0.05. RESULTS OF THE CONFIRMATION EXPERIMENT For each session, a total score was calculated for all 12 recording epochs (6 calm-aim and 6 activate-aim). This total score was divided into the sum of the mean electrodermal Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 DISCUSSION In the pilot study that preceded this experiment, no evidence of a psi effect was found in the data. We hypothesized that the absence of psi may have been contributed by negative moods in all participants (subjects, influencers, and experimenters) due to the extreme length of the experimental sessions (often 2 1/2 hours long). Therefore, we drastically shortened the session lengths, hoping to eliminate this negative factor. Our modifications (described in the Introduction) appear to have been successful, since evidence for psi did emerge in the present experiment. The major hypothesis that was being tested in this study (derived from an IDS conceptualization of the bio-PK effect) was that greater psi scoring would occur in the condition in which there were multiple opportunities for intuitive data sorting (i.e., the MULTIPLE-SEEDS condition) than in the condition in which there was only one such opportunity (i.e., the SINGLE-SEED Condition). The outcome of the Confirmation experiment was not consistent with this informational interpretation of the bio-PK effect. Significant psi-scoring occurred in the "older" condition, which had been in effect in all of our prior bio-PK research--namely, a SINGLE-SEED condition. Significant psi-scoring failed to emerge in the new condition, which was hypothesized to favor enhanced intuitive data sorting (i.e., the MULTIPLE-SEEDS condition). In fact, the superiority of the SINGLE-SEED condition over the MULTIPLE-SEEDS condition closely approached statistical significance. Had the conditions comparison actually reached significance, that finding of superior SINGLE-SEED condition performance would have been quite difficult to explain in IDS terms. As it is, the absence of MULTIPLE-SEEDS condition superiority is not consistent with an "informational" interpretation but is more congruent with a "causal" or "psychokinetic" interpretation of the bio-PK effect. The reason for the absence of a significant bio-PK effect in the MULTIPLE-SEEDS condition is not clear. We might speculate that the provision of a second, potentially effective, psychic task in that condition may have resulted in a form of "distraction," which could have disrupted the influencer's PK performance, mediated perhaps by an increased diffusion or "spreading thin" of the influencer's attention [see Braud (1978)8 for an elaboration of this "spreading thin" possibility]. If this were indeed the case, it would constitute a remarkable finding, since the potential effectiveness of the multiple button presses in the MULTIPLE-SEEDS but not in the SINGLE-SEED condition is not discernible at a conventional sensorimotor level (due to the double-blind stratagem by which the effectiveness Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 sampled, averaged, and printed for the 30-second intertrial or rest periods immediately preceding each of the 12 sampling epochs. The influencer typically pressed the button almost immediately after one sampling epoch in order to begin the next interval as quickly as possible; the latter interval consisted of the 0 to 10-second random delay yielded by the seeded algorithm, a 30-second intert:ial or rest period, and the 30-second sampling epoch itself. Thus, in the Confirmation experiment, mean electrodermal activity data were available for what closely approximated 24 successive 30-second periods. An autocorrelation coefficient calculated for Lag 2 would provide a good estimate of a possible trend for electrodermal activity at time t to be related to activity shortly after 30 to 40 seconds had elapsed. Such Lag 2 autocorrelation coefficients were calculated for each of the 32 sessions of the SINGLE-SEED condition, and for each of the 32 sessions of the MULTIPLE-SEEDS condition. The autocorrelations were found to be quite small and were not significantly different from zero for either the SINGLE-SEED condition (X = 0.059, t = 1.51, 31 df, p = 0.14, two-tailed) or the MULTIPLE-SEEDS condition (X = 0.027, t = 0.78, 31 df, p = 0.44, two-tailed). As an additional check of the trend artifact possibility, we calculated the overall correlation between the 64 LAG 2 autocorrelation coefficients and the 64 bio-PK scores (i.e., the percent calm-aim scores) of the Confirmation experiment. The correlation was nonsignificant and was extremely close to zero (r = - 0.00278); it indicated no relationship between psi scoring and electrodermal temporal trend at the appropriate time interval. Thus, both artifact possibilities may be effectively ruled out for this Confirmation experiment. * Finally, it could be argued that the SINGLE-SEED condition itself provides sufficient opportunity for effective intuitive data sorting, particularly if one ascribes a "goal-oriented" (see Schmidt, 1974)7 or "diametric" (see Foster, 1940;8 Nash, 19869) property to the psi process. There is a danger, however, in posting increasingly higher levels in which intuitive data sorting and goal-orientedness may operate, and that danger is that both of those notions *Autocorrelation coefficients (r k) were calculated according to the formula: (zt z) (zt+k-z) rk n Z (z Z)2 t=1 Where k = the lag number z t = raw score at time t n = total number of values being correlated z = mean score Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0 REFERENCES (Appendix B) 1. Rosenthal, R., "Combining Results of Independent Studies," Psychological Bulletin, Vol. 85, pp. 185-193 (1978). 2. Rosenthal, R., "The 'File Drawer Problem' and Tolerance for Null Results," Psychological Bulletin, Vol. 86, pp. 638-641 (1979). 3. Braud, W., and Schlitz, M., "Psychokinetic Influence on Electrodermal Activity," Journal of Parapsychology, Vol. 47, pp. 95-119 (1983). 4. Schlitz, M., and Braud, W., "Reiki-Plus Natural Healing: An Ethnographic/Experimental Study," Psi Research, Vol. 4, pp. 100-123 (1985). 5. Stanford, R., "Are We Shamans Or Scientists?" Journal of the American Society for Psychical Research, Vol. 75, pp. 61-70 (1981). 6. Braud, W., "Psi Conductive Conditions: Explorations and Interpretations," S. Shapin and L. Coly (Eds.), Psi and States of Awareness, Parapsychology Foundation, New York, pp. 29-31 (1978). 7. Schmidt, H., "Psychokinesis," E. Mitchell et al. (J. White, Ed.) Psychic Exploration: A Challenge for Science, New York, Putnam, pp. 190-191 (1974). 8. Foster, A., "Is ESP Diametric?" Journal of Parapsychology, Vol. 4, pp. 325-328 (1940). 9. Nash, C., "Parapsychology: The Science of Psiology," Thomas, Springfield, Illinois, pp. 202-203 (1986). Approved For Release 2000/08/10 : CIA-RDP96-00789R003800460001-0

High frequency psychophysiological data create a challenge for quantitative modeling based on Big Data tools since they reflect the complexity of processes taking place in human body and its responses to external events. Here we present studies of fluctuations in facial electromyography (fEMG) and electrodermal activity (EDA) massive time series and changes of such signals in the course of emotional stimulation. Zygomaticus major (ZYG, "smiling" muscle) activity, corrugator supercilii (COR, "frowning"bmuscle) activity, and phasic skin conductance (PHSC, sweating) levels of 65 participants were recorded during experiments that involved exposure to emotional stimuli (i.e., IAPS images, reading and writing messages on an artificial online discussion board). Temporal Taylor's fluctuations scaling were found when signals for various participants and during various types of emotional events were compared. Values of scaling exponents were close to 1, suggesting an external origin of system dynamics and/or strong interactions between system's basic elements (e.g., muscle fibres). Our statistical analysis shows that the scaling exponents enable identification of high valence and arousal levels in ZYG and COR signals.