Culture and Developmental Systems, Volume 38 E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Geisteswissenschaft
- Serie: Minnesota Symposia on Child Psychology
- Sprache: Englisch
The latest on child psychology and the role of cultural and developmental systems
Now in its 38th volume, Minnesota Symposia on Child Psychology: Culture and Developmental Systems contains the collected papers from the most prestigious symposia in the field of child development. Providing scholars, students, and practitioners with access to the work of leading researchers in human development, it outlines how the field has advanced dramatically in recent years—both empirically and conceptually.
The updated collection outlines the latest information and research on child psychology, including the cultural neuroscience of the developing brain in childhood, the role of culture and language in the development of color categorization, socioemotional development across cultures, and much more.
- Find out how much math is 'hard wired,' if at all
- Explore the development of culture, language, and emotion
- Discover cultural expressions and the neurobiological underpinnings in mother-infant interactions
- Examine the cultural organization of young children's everyday learning
Written for generalists and specialists alike, Minnesota Symposia on Child Psychology offers the most up-to-date information on the central processes of human development and its implications for school success, as well as other areas.
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Veröffentlichungsjahr: 2016
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Table of Contents
Cover
Title Page
Copyright
Preface
Contributors
Chapter 1: Cultural Neuroscience of the Developing Brain in Childhood
Introduction
Theories in Cultural Neuroscience of the Developing Brain
Methods in Cultural Neuroscience Research of the Developing Brain
Empirical Progress in Cultural Neuroscience of the Developing Brain in Childhood
Future Directions in Cultural Neuroscience of the Developing Brain in Childhood
Implications of Cultural Neuroscience of the Developing Brain
References
Chapter 2: The Role of Culture and Language in the Development of Color Categorization
Color Categories and Reasons to Investigate Them
Contributions from Developmental Science
Unresolved Issues and New Developmental Questions
Conclusions
References
Chapter 3: How Much Mathematics Is “Hardwired,” If Any at All: Biological Evolution, Development, and the Essential Role of Culture
Introduction
Nativism in Cognitive Development, Cognitive Neuroscience, and Animal Cognition
Quantity‐Related “Hardwired” Capacities? Yes,…Are They Mathematical? No
Aren't Number‐to‐Space Mappings “Hardwired”? No
What Can We Learn from the History of Mathematics? A Lot
Are Results in Experimental Studies on Number‐Line Mappings Consistent with Historical Records? Yes
Biocultural Issues for Child Psychology and Developmental Theory: Is Snowboarding “Hardwired”? No, It Is Not
References
Chapter 4: Culture, Language, and Emotion: Explorations in Development
Introduction
Culture as Instantiated through Language
Culture as Instantiated through Emotion and Emotion Regulation Strategies
Limitations of Both “Cultural” and “Cross‐Cultural” Approaches to the Development of Language and Emotion Regulation
Can We Move beyond Metaphors?
References
Chapter 5: Cultural Expressions and Neurobiological Underpinnings in Mother–Infant Interactions
Introduction
Parenting
Parenting Practices
Autonomic Nervous System
Central Nervous System
Frontiers
Conclusions and Final Thoughts
References
Chapter 6: The Cultural Organization of Young Children's Everyday Learning
An Uneasy Peace
Culture: The “Thorn” in Developmental Theory
Human Development: Becoming a Cultural Being
Theoretical Potential of an Expanded Model of Development
Putting Yucatec Mayan Children's Development into Context
Early Social Interactions
The Role of Children's Play (and Work)
Attentional Stance: Focused versus Open
Negotiating a Stable Peace among Developmental Claims
References
Chapter 7: Socioemotional Development across Cultures
Introduction
Conceptual and Methodological Issues in Research on Culture and Human Development
The Contextual‐Developmental Perspective: A Theoretical Framework for Cross‐Cultural Research on Socioemotional Development
Culture and Shyness‐Inhibition
The Display of Shyness‐Inhibition in Chinese and North American Children
Parents' and Peers' Attitudes toward Shyness‐Inhibition
Shyness‐Inhibition and Adjustment Outcomes
Issues and Future Directions
References
Chapter 8: Two Senses of Cultural Relativity
Introduction
Cultural Relativism: An Introduction to Two Senses
Verstehen Relativism and Its Application
Verstehen Relativism, Warfare, and the Training of Civilized People
The Problem of Trade‐offs
Child Labor and Child Schooling: Another Likely Trade‐off?
Egalitarian Cultural Relativism and Moral Perspectives
Strong Cultural Relativism: An Internally Inconsistent Idea
Difficulties with Two Psychological Defenses of Strong Relativism
Arguments from Benevolent Informed Intentions, and the Problem of Unequal Power
Gender Inequality
Moral Equality through Neutralization Because of Conformity
The Different Causes of Conformity; Conformity as Motivated, Not Inertial
Arguments about Effective Functioning
Qualifying and Restricting the Arguments
References
Author Index
Subject Index
End User License Agreement
List of Illustrations
Chapter 1: Cultural Neuroscience of the Developing Brain in Childhood
Figure 1.1 The cultural neuroscience framework.
Figure 1.2 Model of cultural neuroscience.
Figure 1.3 Cultural influences on medial prefrontal cortex (MPFC) response during self‐judgments. (a) Example of self‐judgment task; (b) MPFC response during culturally congruent self‐judgments; (c) Degree of cultural collectivism predicts MPFC response to culturally congruent self‐judgments.
Figure 1.4 Cultural influences on empathic neural response. (a) Example of painful and nonpainful emotional scenes; (b) Other‐focusedness predicts anterior cingulate cortex (ACC) and right anterior insula (right AI) empathic response to group members in Koreans to a greater extent relative to Caucasian Americans.
Figure 1.5 Racial identification predicts default mode network response during empathy in African American (AA) and Caucasian American (CA) young adults (a) Example of painful and nonpainful emotional scenes; (b) Racial identification predicts empathic neural response within the default mode network.
Figure 1.6 Cultural differences in N2 response during behavioral inhibition in Chinese Canadian and European Canadian children (adapted from Lahat, et al., 2009). (a) Go/No‐Go task performed by children; (b) Mean amplitude response of the N2 waveform in the right (top) and left (bottom) hemisphere during Go and No‐Go trials in Chinese Canadian and European Canadian children.
Chapter 2: The Role of Culture and Language in the Development of Color Categorization
Figure 2.1 The mean distribution of basic color terms for the Munsell stimulus array, for English speakers (top) and Berinmo speakers (bottom). Dots in the top figure indicate the chosen best example of each color category (from Heider, 1972). Numbers in the bottom figure indicate number of participants who chose that stimulus as the best example of the color category.
Figure 2.2 World Color Survey color naming plots for speakers of nine languages. Each plot shows the modal naming response for speakers of a language that has five basic color terms. The rectangular shape corresponds to the WCS stimulus grid (with Munsell value [lightness] on the y‐axis and hue on the x‐axis). Regions shaded in the same lightness indicate regions of the stimulus grid where stimuli were given the same name. The percentages reported after the language name indicates the percentage match between the boundaries in the modal naming plot and those for the Berinmo language. The figure therefore shows striking similarity in color naming across these languages even though the languages are genetically and geographically distinct.
Figure 2.3 Analysis of the distribution of color terms from WCS nonindustrialized languages indicates clustering around particular points in color space. The figure shows the WCS stimulus grid (y = lightness, x = hue, 320 colors within the grid). Outer contour lines show the location of 100 category centroids for WCS languages. Each subsequent inner contour indicates an increment of 100 more. Dots show the location of the centroids for English terms, and these fall near the peaks of the clusters in the WCS distribution.
Figure 2.4 Modal grouping maps for four groups of participants (G1: beginning color namers; G2: developing color namers; G3: accurate color namers; adults). The x‐axis refers to Munsell hue codes, the y‐axis to Munsell value (lightness), and each square represents a colored stimulus. The shading of the squares indicates grouping of colors on the grouping task (same shading indicates stimuli grouped together according to modal responses). The numbers in each square correspond to the modal number of participants who allocated the stimulus to that stimulus group. The figure shows the similarity of color grouping irrespective of color naming ability.
Figure 2.5 Mean accuracy (+/–1 se) at identifying the colored target when paired with a same‐category (within) or different‐category (between) foil, for toddlers who had learned the names of the colors and had an appropriate category boundary (name boundary) or an inappropriate category boundary (reverse name boundary) and those who had not learned the color names (no name boundary).
Figure 2.6 Mean accuracy (+/–1 se) at identifying the colored target when paired with a same‐category (within) or different‐category (between) foil, for blue‐green and blue‐purple stimulus sets, for toddlers who were classified as not knowing (don't know) or knowing (know) the basic terms for the relevant colors.
Figure 2.7 The top panel provides infant data from Bornstein et al. (1976). Infants were habituated to a given wavelength (indicated by dots on the figure) and then shown novel wavelengths (indicated by vertical bars). The horizontal connection between dot and bar indicates no difference in mean looking times for those two wavelengths, and a gap indicates that there was a significant difference in looking time. The “infant summary” row indicates the ranges of wavelength that infants treat as equivalent. The bottom panel provides adult color naming functions (percentage of total point value corresponds to frequency of color term use) using naming data from Boynton and Gordon (1965). The correspondence between the infant and the adult data can clearly be seen in the alignment of the location of the significant differences in infant looking data and the crossover points in the adult color naming functions.
Figure 2.8 Mean novelty preference (+/−1 se) for novel colors that are from the same‐category (within) or different‐category (between) as the familiar color and where novel‐familiar hue differences were small (near) or large (far). The dashed line indicates the point at which there is no preference for the novel color over the familiar color.
Figure 2.9 Grand averaged ERP waveforms elicited during the 1700 ms following stimulus onset (0 ms) for 7‐month‐old infants in response to a frequently presented standard color (dashed line waveform), an infrequent deviant color of a different category from the standard (black line waveform), and an infrequent deviant color from the same category as the standard (gray line waveform). The top plot gives the waveforms for electrode Fz (frontal midline) and the bottom plot for electrode C3 (central left). The category effect can be seen clearly for the Negative Central ERP component (negative peak around 400 ms) at Fz and in the slow waves (1150 ms onward) at C3.
Figure 2.10 Eye‐movement latency (log transformation of eye‐movement initiation time in ms) to colored targets in the left or right visual field (L/RVF) on same‐ or different‐category colored backgrounds for toddlers who do (namers) and do not (learners) know the color terms for the colored targets and backgrounds. Error bars are within‐subjects' 90% confidence intervals.
Chapter 3: How Much Mathematics Is “Hardwired,” If Any at All Biological Evolution, Development, and the Essential Role of Culture
Figure 3.1 A clay tablet known as YBC 7289 from the Old Babylonian period, from the Yale Babylonian Collection. The tablet, from the first third of the second millennium BC, is one of the few containing drawings. It shows numbers associated with measurements but no depiction of number lines. According to contemporary historians of Mesopotamian mathematics, Old Babylonians did not operate with number‐line concepts despite manifesting sophisticated notions of number and arithmetic.
Figure 3.2 The introduction of the number line in 17th‐century Europe. The figure shows the top of page 265 of John Wallis's
Treatise of Algebra
, published in 1685, chapter 66, “Of Negative Squares and Their Imaginary Roots.” This passage seems to be the first explicit characterization of a number line for operational purposes in the history of mathematics.
Figure 3.3 The first page of chapter 1 of John Napier's
A Description of the Admirable Table of Logarihmes
published in 1616 (English edition), in which he introduces his definition of logarithm via an explicitly depicted number‐to‐line mapping.
Figure 3.4 A diagram from page 392 of Descartes's first edition of
La Géometrie
, published in 1637. Contrary to what has been claimed, Descartes did not introduce the number line in this classic volume through the invention of coordinate systems.
Figure 3.5 An illustration of the number line from a manual from the National Council of Teachers of Mathematics (in the United States) intended for children in kindergarten to fifth grade. The manual includes practice questions, such as “If I take a hop of 5 and then a hop of 4, where will I land?”
Figure 3.6 College‐level students' responses to a number mapping task, by stimulus modality and reporting condition. Data are mean perceived response intensity (nonspatial reporting) and mean response location on the line (spatial reporting), with corresponding standard errors of the mean.
B
log
indicates the relevant unstandardized weight (plus/minus standard error) of the logarithmic regressor in a multiple regression analyses with linear and logarithmic predictors. Gray‐scaled graphs indicate a significant
p
‐value for the corresponding
B
log
weight (based on a
B
log
/(standard error)
t
ratio with df = 7 in each case; black indicates a nonsignificant
p
‐value).
Figure 3.7 Detail from data reported in Dehaene et al. (2008a, 2008b) showing the mean response location on the line segment that participants picked as corresponding to the numerosities 1, 2, and 3—numbers for which Mundurukú speakers have a well‐established lexicon. Data are mean ± standard error of the mean. The top row (a) shows values for 16 American participants; the middle row (b) shows values for 33 Mundurukú participants; and the bottom row (c) shows values for 7 Mundurukú uneducated adults. If participants understand the task and spontaneously map numbers to the line, they should systematically map the lowest stimulus number (“1”) with the response location “1”—that is, with the left end of the line segment presented to them. American participants (a) accurately and systematically mapped “stimulus number 1” with “response location 1.” Mundurukú participants, however, systematically failed to establish this fundamental number–space mapping (b). Crucially, data reported exclusively in the corresponding “Supporting Online Material” (Dehaene et al., 2008b) show that the Mundurukú uneducated adults—the most relevant subgroup for testing the innate mental number line hypothesis—failed to do this in a more dramatic way (c). For words and tones, this group even failed to establish the fundamental property of order. These results suggest that the number‐line intuition is not universal.
Figure 3.8 Pointing responses for stimulus numerosities 3 and 6 (dots) during the number‐line task.
Figure 3.9 Responses to three different types of number stimuli on the number‐line task. Graphs show proportions of responses on segment sections with corresponding repeated measures ANOVA statistics. In stark contrast with schooled Yupnos (middle column) and California controls (right column), unschooled Yupnos (left column) did not use the extent of the segment when mapping intermediate numbers and numerosities, producing instead a bicategorical mapping without a metric (a distance function). Schooled Yupnos (middle column) did use the line but tended to manifest a bias toward the endpoints.
Chapter 4: Culture, Language, and Emotion: Explorations in Development
Figure 4.1 Acoustic signal for
kan4kan zhei4‐ge ping2guo3,
recorded by a native Mandarin speaker and rendered via FinalCut software.
Figure 4.2 Examples of the word
apple
that a child might hear.
Figure 4.3 A schematic representation of infant in evoked response potential experiment (a) that showed mismatch negativity response to native (English) phonetic contrasts versus nonnative (Mandarin) contrasts (b) and a hierarchical linear growth modeling curve of vocabulary growth between 14 and 30 months for infants with +1 and –1 standard deviation to the native contrast (left) versus the nonnative contrast (right) when tested at 7.5 months of age.
Chapter 6: The Cultural Organization of Young Children's Everyday Learning
Figure 6.1 Minimize cultural differences.
Figure 6.2 Minimize importance of environment.
Figure 6.3 Minimize universal outcomes.
Figure 6.4 An integrative model of competing claims.
Guide
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Minnesota Symposium on Child Psychology
Culture and Developmental Systems
Volume 38
Edited by
Maria D. Sera
Michael Maratsos
Stephanie M. Carlson
Copyright © 2017 by John Wiley & Sons, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
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ISBN 9781119247654 (Hardcover)ISBN 9781119301974 (ePDF)ISBN 9781119301967 (ePub)
First Edition
Preface
Someone once said that the important questions in science do not change, only our answers to them do. That is a good thing because when the topic of culture emerged as a potential one for this symposium, I had the feeling that we had done it before. Indeed we had, and not too long ago. In 1999, Ann Masten organized a symposium called Cultural Processes in Child Development. Ann's opening remarks to that volume ended with the hope that the volume would usher in a “cultural renaissance” in developmental science. Organizing another symposium on the topic is a testament to that insight.
The role of culture in human development is undeniable. No child today has to figure out how to control fire, invent the wheel or the alphabet. For at least the last 70,000 years, the advancement of humans has depended on cultural innovation. Every generation gets information critical to its success from the generations that precede it. Yet answers to questions regarding the role of culture in human development seem to vacillate from one extreme to the other—from culture being everything, to cultures being really all the same and so not impacting development in meaningful ways. In my own line of work, questions about the role of language on thought—a line that can be encompassed within the broader umbrella of cultural relativity—have yielded apparently contradicting answers. Empirical work on the topic began with a paper by Roger Brown and Eric Lenneberg published in 1954 showing that colors for which English speakers agreed on a name were better remembered than colors for which speakers did not agree on a name (these were focal hues, or the prototypes of English colors). The stage seemed to be set for work on linguistic (and cultural) relativity—that differences across speakers of different languages would analogously yield differences across speakers of those languages in thought. That view of relativity came to a dead halt in the early 1960s and 1970s when studies showed that: (1) cones in the primate retina differentially absorb hues that corresponded to the English color prototypes—blue, yellow, and green—suggesting a strong physiological basis for color perception; (2) adults whose languages had different color terms categorized colors the same way as English speakers did, suggesting that color perception was universal and language had no effect; and (3) infants—who do not know any words—also categorize colors the same way as do English adults, suggesting that color perception could not be affected by language. What followed might be viewed as the “dark ages” of nativism and universalism of the 1970s and 1980s. I wrote in the early 1990s that color might not have been the best domain in which to look for effects of language on cognition, and started looking for effects in domains that change with development. At about the same time, John Lucy published an argument about why the color work was flawed. The “renaissance” began. Between 1990 and today, there has been an explosion of work on the role of language on cognition. Effects of language have been shown on object perception, categorization, space, number, emotion recognition, and other concepts. But even with all the evidence in support of relativity, significant questions remain. For instance, even though 1954 might seem like a long time ago, it is not long enough to bring about the evolutionary change required to alter the physiological structure of the primate retina. How can the old work showing universal tendencies be reconciled with the more recent work in support of relativity? Significant progress has been made, and chapter 2 of this volume begins to reconcile the evidence on the role of culture (via language) on color categorization specifically.
More generally, the goal of the 38th Minnesota Symposium was to bring together scholars that examine a wide range of cultural factors, from genes to governments, in development. These scholars also represent different stages of academic careers—from recently minted PhDs to scholars who published early seminal papers. The volume begins with an exploration of how culture might have selected for certain genes, which in turn might shape neural functioning (in chapter 1). Chapter 2 moves to the role of culture via language on perception. Chapter 3 reviews the essential role of culture in mathematical thinking. Chapter 4 highlights cross‐cultural differences in the earliest stages of language development and their implications for theories of development. Chapter 5 highlights differences and similarities across cultures in parenting practices. Chapter 6 offers a picture of learning by children who do not go to regular (formal) schools—the way Homo sapiens learned for all but the last few hundred years. Chapter 7 illustrates how social emotional behaviors, such as shyness, can be differentially valued and perceived across different cultures. The final chapter makes explicit different ways of thinking about cultural relativity with examples from different points in history, countries, religions, and governing bodies. All make original contributions to a better understanding of culture and development.
The Minnesota Symposium has always been a joint intellectual exercise, and this one was no exception. I want to thank Stephanie Carlson and Michael Maratsos for their shared enthusiasm for the topic and their efforts with selecting speakers, organizing the event on which this volume is based, and editing the chapters. I also want to thank all who contributed chapters. They are, in the order that their chapters appear in the volume: Joan Y. Chiao, Anna Franklin, Rafael Núñez, Twila Tardif, Marc H. Bornstein, Suzanne Gaskins, Xinyin Chen, and Michael Maratsos. I also want to thank Delores Mordorski for helping to organize the event and Eric Hart for his sharp editorial eye and help with the chapters. We also thank Patricia Rossi and Jeevarekha Babu at Wiley for keeping us on task. And last but certainly not least, I want to thank the graduate students at the Institute of Child Development who help with the event in so many ways, especially Jose Causadias and Sandra Ahumada. The symposium would not have been the same without you.
Maria D. Sera
Contributors
Marc H. Bornstein, PhD
Senior Investigator
Child and Family Research
Eunice Kennedy Shriver National Institute of Child Health and Human Development
National Institutes of Health, Public Health Service
Stephanie M. Carlson, PhD
Professor
Institute of Child Development
University of Minnesota
Xinyin Chen, PhD
Professor
Applied Psychology—Human Development Division
Graduate School of Education
University of Pennsylvania
Joan Y. Chiao, PhD
International Cultural Neuroscience Consortium
Anna Franklin, PhD
Professor
The Sussex Colour Group and Baby Lab
School of Psychology
University of Sussex
Suzanne Gaskins, PhD
Professor Emerita
Department of Psychology
Northeastern Illinois University
Michael Maratsos, PhD
Professor
Institute of Child Development
University of Minnesota
Rafael Núñez, PhD
Professor
Department of Cognitive Science
University of California, San Diego
Maria D. Sera, PhD
Professor
Institute of Child Development
University of Minnesota
Twila Tardif, PhD
Professor
Department of Psychology
University of Michigan
CHAPTER 1Cultural Neuroscience of the Developing Brain in Childhood
Joan Y. Chiao
INTRODUCTION
From infancy to adolescence, social contact with parental caregivers, kin, and peers provide the earliest means of cultural transmission. Learning how to perceive, interpret, and respond to people and objects in the environment, infant brains acquire preferences and knowledge of cultural norms, practices, and later beliefs, attitudes, and values from caregivers that independently and interactively shape subsequent neurobiological maturation along with genes. By childhood, the conscious mind develops a continuous subjective experience that is stored as autobiographical memory. This emergence of conscious experience in the form of autobiographical memory represents a pivotal change in the ability to store and transmit cultural information from one's self to another during development.
How does culture shape the mind and brain in childhood? How does learning to acquire and transmit culture occur developmentally? These questions represent some of the most compelling research directions in cultural neuroscience. The goal of this chapter is to provide an overview of research in cultural neuroscience and to introduce a cultural neuroscience framework of the developing brain that provides insight into the promotion of healthy child development.
THEORIES IN CULTURAL NEUROSCIENCE OF THE DEVELOPING BRAIN
Research in cultural neuroscience addresses the origins of human diversity. Where does human diversity come from? Dynamic biocultural constructivism theory posits that culture and biology interact along three primary time scales: phylogeny, ontogeny, and situation (Li, 2003) and a series of interactive processes with developmental plasticity across distinct levels shapes cognitive and behavioral development. Cultural neuroscience is an interdisciplinary field that integrates theory and methods from anthropology, cultural psychology, neuroscience, and genetics to understand diversity in human behavior across multiple time scales (Chiao & Ambady, 2007; Chiao, Cheon, Pornpattanangkul, Mrazek, & Blizinsky, 2013). (See Figure 1.1)
Figure 1.1 The cultural neuroscience framework.
Source: Adapted from Chiao & Ambady, 2007.
There are at least three mechanisms by which the human brain acquires culture throughout development: experience‐dependent neural plasticity, mirror neurons, and culture–gene coevolution. Behavior or experience‐dependent neural plasticity refers to cortical organization that is affected by developmental, experiential, and cultural influences. Several structural features of the brain prune and grow as a function of distinct developmental stages. Functional changes in the developing brain also occur in response to neuronal maturation. The term mirror neurons refers to brain regions within the premotor and motor cortex that contain neurons that respond when both observing and performing an action (Iacoboni, 2009; Losin, Iacoboni, Martin, & Dapretto, 2012). Activity within mirror neurons is present during infancy during viewing of goal‐directed movement (Del Giudice, Manera, & Keyers, 2009; Nyström, 2008). By adulthood, mirror neurons demonstrate a preferential response for reinforced goal‐directed movement. For instance, ballet dancers will respond not only when performing a pirourette but also when observing another perform a pirourette; furthermore, mirror neuron response is heightened when experts observe and perform actions within their expertise (e.g., ballet dancers observing ballet) (Calvo‐Merino, Grèzes, Glaser, Passingham, & Haggard, 2006). Mirror neurons form the biological basis of action‐based cultural learning and play an important early role in the acquisition of cultural competence.
The term culture–gene coevolutionary theory refers to the notion that cultural and genetic selection operate in tandem to shape the human mind, brain, and behavior (Boyd & Richerson, 1985; Cavalli‐Sforza & Feldman, 1981). Darwinian natural selection asserts that adaptive behavior results from environmental or ecological pressures on genomes. Coevolutionary theory asserts that adaptive behavior is the result of both cultural and genetic selection in response to environmental or ecological pressures. One example of culture–gene coevolution is morality. Recent cultural neuroscience evidence across nations shows that allelic variation of the serotonin transporter gene (5‐HTTLPR) predicts moral justification due in part to cultural selection (Mrazek, Chiao, Blizinsky, Lun, & Gelfand, 2013). More specifically, nations with greater frequency of short‐allele carriers of the 5‐HTTLPR are more likely to demonstrate low tolerance for morally deviant behavior due to increased preference for cultural tightness. Another example of culture–gene coevolution is mental health (Chiao & Blizinsky, 2010; Figure 1.2).
Figure 1.2 Model of cultural neuroscience.
Source: Chiao & Immordino‐Yang, 2013.
Cross‐national evidence shows that allelic variation of the 5‐HTTLPR predicts prevalence of anxiety and mood disorders in part due to cultural collectivism. Nations with greater frequency of short‐allele carriers of the 5‐HTTLPR show lower prevalence of anxiety and mood disorders due partially to increased cultural collectivism. These examples of culture–gene coevolution indicate that both cultural and genetic selection shape cognitive and neural architecture underlying morality and mental health.
METHODS IN CULTURAL NEUROSCIENCE RESEARCH OF THE DEVELOPING BRAINs
While recent evidence suggests distinct putative mechanisms for cultural influences on the mind and brain, less well understood are the specific developmental mechanisms by which culture influences behavior. The development of social and emotional behavior that is adaptive to one's cultural context depends on several biological factors, such as neuronal development and epigenetic expression. Understanding how culture affects social development may involve a number distinct kinds of empirical methods, including behavioral, neural, and genetic measures. Because social development refers to changes in social and emotional capacities across the life span, biological changes, such as neuronal growth or epigenetic expression, may provide foundational mechanisms or catalysts for triggering age‐appropriate social and emotional maturation. Cultural changes, such as immigration, acculturation, or sociopolitical shifts, may also affect the development of social and emotional capacities. Given the multilevel influences on social development, methods from distinct levels of analysis may provide the necessary tools to identify age‐related causal mechanisms of adaptive social and emotional behavior. An overview of methodological approaches to examining cultural influences on the developing brain during childhood is presented next.
Cultural Psychology
Cultural psychology examines how culture shapes human behavior. One branch of cultural psychology investigates how environmental and ecological factors, including natural disasters, population density, and food deprivation, shape cultural processes. There are several primary cultural systems that characterize a majority of the world's regions, including individualism‐collectivism or independent‐interdependence, tightness‐looseness, power distance, social dominance orientation, racial identification, long‐term–short‐term orientation, and masculinity‐ femininity (Gelfand et al., 2011; Hofstede, 2001; Markus & Kitayama, 1991). Individualism and collectivism, or independence and interdependence, comprises a primary cultural system that shapes the human self. Individualistic or independent cultures emphasize a notion of self that is distinct and unique from others. The ability to express one's self and to define one's self autonomously from social roles and relations comprises a fundamental way that culture shapes the self. By contrast, collectivistic or interdependent cultures highlight the importance of the self as defined in relation to others, including social roles and relationships. The ability to conform one's self to others and to define one's self as dependent or embedded in social roles and relations constitutes another foundational way that culture shapes the self. Cultural psychologists have shown that an environment factor, pathogen prevalence, is associated with individualism and collectivism such that collectivistic cultures may have developed to defend against the presence of infectious diseases (Fincher et al., 2008).
Tightness‐looseness refers to a cultural dimension that reflects the degree of tolerance or adherence to social norms. Tight cultures are more likely to exhibit situational constraint, such that appropriate behavior is constrained by daily situations. People living in tight cultures may prefer cautious and dutiful behavior, greater self‐regulation, greater self‐monitoring, and greater need for structure (Gelfand et al., 2011; Mrazek et al., 2013); by contrast, people living in loose cultures may prefer unique and autonomous behavior, greater self‐expression, greater ingenuity, and greater need for freedom. Cultural psychologists have shown that ecological threats, including population density, food deprivation, disease, and susceptibility to natural disasters and territorial conflicts, account for some of the variation and have led to geographic variation in tight and loose cultural norms. Regions that are affected by ecological threats are more likely to adhere to tight compared to loose cultural norms.
Power distance refers to the extent to which a geographic regions expects societal inequality. Nations that are high in power distance are more likely to accept and expect a hierarchical social order in which everybody occupies an expected social role. Nations with low power distance are more likely to expect an equal distribution of social power and to expect explanations for social inequality. Relatedly, social dominance orientation refers to the extent to which a person expects societal inequality among social groups (Pratto, Sidanius, Stallworth, & Malle, 1994). People high in social dominance orientation are more likely to seek hierarchical professional roles, compared to people low in social dominance orientation who are more likely to seek hierarchy‐attenuating social roles.
Racial identification is the degree to which a person identifies with members of their social group, and often refers to members of a social minority. Long‐term and short‐term orientations refer to the extent to which a nation emphasizes the past, present, and future. Nations with low long‐term orientation prefer to maintain cultural traditions and norms rather than societal or cultural change; by contrast, nations with short‐term orientation are more likely to seek efforts to modernize and change society toward the future. Masculinity is a cultural dimension that emphasizes social preferences typically associated with stereotypical male attributes, including achievement, heroism, assertiveness, and material success. Femininity is a cultural dimension that emphasizes stereotypical female attributes, including cooperation, caring, and quality of life. These cultural dimensions comprise primary systems of societal values that shape how groups and institutions create and maintain social norms of human behavior. The degree of adherence to a given cultural dimension is measurable with behavioral surveys that assess attitudes, values, and beliefs about a given culture. One's cultural identity may affect how a person responds when completing a behavioral survey; nevertheless, response biases within culture tend to be consistent and predictable, allowing for reliable interpretation of behavioral survey data and individual adherence to distinct cultural systems (Johnson, Kulesa, Cho, & Shavitt, 2005). Implicit measures of cultural attitudes may also provide important ways in which individual adherence to distinct cultural systems is observed (Brannon & Walton, 2013).
Understanding age‐related changes in cultural values may be limited depending on the type of cultural method. For instance, preverbal infants and young children may not be able to reliably provide accurate responses of their adherence to cultural norms; a number of developmental limitations, from self‐awareness and autobiographical memory to motor response, may impede one's ability to understand infant and child cultural values. However, safe and age‐appropriate behavioral measures, such as looking time, grasping, tongue protrusion, and crawling, may provide indirect ways to infer the cultural attitudes or normative preferences of infants and children. In older age, elderly persons may have similar difficulty in completing self‐report behavioral surveys, due to age‐expected cognitive decline. Changes in cognitive ability, such as memory and motor response, may provide a challenge to measurement of cultural values and attitudes of elderly persons. Nevertheless, due to the stability of social and emotional responses in older age, indirect measures, such as implicit attitude tests, may provide additional methods for understanding the culture of elderly persons.
The development of social and emotional behavior occurs within cultural systems and may be influenced by change in one's experience to distinct cultural systems. Processes of cultural change include immigration, acculturation, and sociopolitical shifts. Immigration refers to when a person moves from heritage to host culture and the changes in attitudes toward the heritage and host culture as a function of changes in geographic and national boundaries (Berry, 1997). Acculturation refers to the processes by which a person negotiates behaviors, attitudes, and beliefs between heritage and host cultures (Berry, 1997; Telzer, 2010). Possessing a multicultural identity may involve “frame switching” between heritage and host culture mind‐sets (Hong, Morris, Chiu, & Benet‐Martinez, 2000). Cultural priming is an empirical method that allows the researcher to cause a shift in cultural frames within a person with a multicultural identity by changing the person's exposure to cues in the social environment, for brief periods of time ranging from milliseconds to minutes. Both cultural self‐report surveys and cultural priming methods have been shown to reliably modulate neural responses associated with social (Chiao et al., 2009; Harada, Li, & Chiao, 2010) and emotional processing in young adults (Cheon et al., 2013; Mathur, Harada, & Chiao, 2012).
Developmental Human Neuroscience
Several neuroscience methods may facilitate the study of culture in the developing brain. Functional neuroimaging (fMRI) refers to noninvasive means of indirectly measuring neural activity with spatial resolution. One branch of fMRI important to social development is fetal neuroimaging. Fetal neuroimaging refers to measurement of fetal brain structure and function, such as the functional connectivity between brain regions that grow in utero (Anderson & Thomason, 2013). Brain regions that have been identified as important in social and emotional development, including the medial prefrontal cortex (MPFC), anterior cingulate, motor cortex, and superior temporal gyrus, are active from as early as 25 to 29 weeks in utero, indicating functional connectivity within social and emotional neural circuitry that begins to develop prebirth (Swartz, Carrasco, Wiggins, Thomason, & Monk, 2014). Developmental neuroimaging aims to examine the neural basis of age‐related changes of behavior postbirth (Luna, Velanova, & Geier, 2010). One way to identify the neural basis of age‐related changes of behavior is to focus on specific developmental periods where known age‐related behavioral changes occur. For instance, infancy is a developmental period characterized by acquisition of fundamental perceptual abilities that contribute to social and emotional cognition, such as social and emotional perception. Infant face and voice perception are one of the first social abilities that newborns acquire, and neural regions associated with visual processing of complex images are recruited to detect social cues (Dehaene‐Lambertz, Dehaene, & Hertz‐Pannier, 2002; Tzourio‐Mazoyer et al., 2002).
By early childhood, social and emotional cognition is sophisticated, as young children learn to detect deception, to feel what others feel, to understand their own social world and emotional states, and to interact with close others and peers. Adolescence is a developmental period of unique biological and social maturation, the gradual transition between childhood and adulthood lasting approximately 5 to 9 years from ages 12 to 19 (Luna et al., 2010). The capacity to regulate emotional and social responses in one's self and to influence others similarly becomes one of the primary ways that adolescence prepares the person for adulthood. By adulthood, the social and emotional brain has matured structurally and functionally to provide the biological basis for adaptive social and emotional behavior, as well as the capacity to ultimately provide parental, familial, and societal care (Adolphs & Anderson, 2013; Heatherton, 2011). During older adulthood, structural and functional changes in the human brain occur, including the gradual decline of neuronal structure and function that accompanies cognitive decline (Gutchess, 2014; Park & Gutchess, 2006). Notably, even with gradual cognitive decline in older adulthood, social and emotional capacities remain intact, indicating an important divergence between cognitive and socioemotional systems during older adulthood (Carstensen, 2006; Samanez‐Larkin & Carstensen, 2011). Hence, fMRI provides a potent and viable means of characterizing developmental changes in the human brain and behavior from fetus to old age.
Functional near‐infrared spectroscopy (fNIRS) is a neuroimaging method that allows for the indirect measurement of neural activity based on metabolic processes within the brain by optodes or light emitters and detectors (Lloyd‐Fox, Blasi, & Elwell, 2010; Vanderwert & Nelson, 2014). fNIRS measurement occurs while participants wear a cap during a given behavioral task. As a developmental neuroimaging method, fNIRS is preferred due to its low cost, ease of use with infants, greater spatial localization compared to fMRI, and portability or ease of use in naturalistic settings (Lloyd‐Fox et al., 2010; Vanderwert & Nelson, 2014). A majority of fNIRS studies have measured neural activity in infants during sleep, although more recent studies have also measured functional response in infants while they perform simple behavioral tasks, such as visual perception. For geographic regions where fMRI is prohibitively difficult due to infrastructural issues, fNIRS provides a reasonable and pragmatic method for studying neuronal maturation and behavior throughout development, from infancy to older adulthood.
Finally, the event‐related potential (ERP) represents one of the oldest electrophysiological methods that provide a direct, noninvasive means of measuring neural activity throughout development, from infancy to older adulthood. ERP allows for excellent temporal resolution of cortical measurement but relatively worse spatial resolution compared to fMRI. Like fNIRS, ERP allows for neuronal measurement by recording through a cap of electrodes from the scalp. This apparatus allows for more mobility compared to fMRI and may be suitable for studying developmental changes in geographic regions that require naturalistic or remote settings (Chiao, Pornpattananangkul, Stein, & Van Honk, 2015). The earliest studies of infant brain activity used ERP to show that waveforms generated from the ventral visual cortex, for instance, provided the neuronal response associated with social abilities, such as face perception (Courchesne, Ganz, & Norcia, 1981; De Haan & Nelson, 1997) and memory (Nelson & Salapatek, 1986). Age‐related developmental changes in neural mechanisms of face processing are detectable into older adulthood with ERP (Wiese, Kachel, & Schweinberger, 2013), providing an important method for understanding social and emotional development across cultural contexts.
Developmental Imaging Genetics
Developmental imaging genetics provides a foundational method for understanding the effect of genotype and genetic expression on the human brain and behavior (Casey, Foliman, Bath, & Glatt, 2010; Viding, Williamson, & Hariri, 2006). Imaging genetics studies combine measures of neural activity and behavior with genotype (Canli et al., 2006; Hariri et al., 2002) and epigenetic expression (Jack, Connelly, & Morris, 2012; Nikolova et al., 2014) to identify the effects of a given gene or functional polymorphism on brain and behavior. The earliest examples of imaging genetics examine the role of the 5‐HTTLPR on human brain function. Findings from early imaging genetics studies showed functional differences in the bilateral human amygdala as a function of allelic variation of the 5‐HTTLPR (Canli et al., 2006; Hariri et al., 2002). The earliest imaging epigenetic studies show that changes in genetic expression are associated with functional variation within social and emotional brain regions, including the superior temporal gyrus (Jack et al., 2012) and the human amygdala (Nikolova et al., 2014). Together, these results show for the first time genetic effects on functional human brain response in young adults and provide a necessary theoretical link between genetic and neural levels of analysis. These earliest imaging genetics studies are groundbreaking in their demonstration of the empirical ability to measure genetic effects on the human brain and behavior and provide a foundation for understanding how genes affect the human brain across development. More recently, imaging genetic studies have shown effects of multiple functional polymorphisms, including oxytocin, dopamine receptor polymorphism, brain‐derived neurotrophic factor (BDNF), and monoamine oxidase A (MAOA), on human brain function (Casey et al., 2010; Padmanabhan & Luna, 2014; Viding et al., 2006).
Distinct empirical approaches have been proposed in developmental imaging genetics. One empirical approach is to conduct longitudinal studies of genetic effects on the human brain and behavior. In longitudinal developmental imaging genetic studies, observations of brain–behavior relations would be measured consistently in genotype groups across distinct developmental periods. For instance, in order to examine whether there exists a developmental shift from infancy to childhood in the 5‐HTTLPR effect on the human amygdala, one might examine the degree of amygdala response during a socioemotional task in short‐ and long‐allele carriers of the 5‐HTTLPR from infancy to childhood in the same individuals. Another empirical approach is to identify developmental stage‐specific genetic effects on brain and behavior. For instance, to study cultural or biological changes associated with a specific developmental stage, such as adolescence, one might compare the genetic effect on brain function pre‐ and post‐ a given developmental stage with a cross‐sectional design.
Given the known mutual influence of cultural and genetic selection on human behavior, it is important to consider the independent and interactive influence of cultural and genetic effects on the developing brain. The onset of a particular developmental stage in brain and behavior occurs within a given cultural context and mind‐set of cultural dimensions of the individual. It is plausible that developmental changes in genetic effects on the human brain are due in part to developmental changes in cultural acquisition or knowledge. Similarly, developmental changes in genetic effects on the human brain may be necessary or catalysts for cultural acquisition or cultural change to occur within a given developmental period. For instance, acculturation to a given host culture may not be necessary unless the cultural change from heritage to host culture occurs after childhood. Similarly, racial identification or identifying with one's social group may not be fully possible within the functional maturation of prefrontal cortex during adolescence, due possibly to changes in genetic expression within a given brain region. Hence, understanding developmental changes in human biology, such as genetic expression and human brain function, is a fundamental goal to fully characterize the acquisition and maintenance of cultural competence across the life span.
Population Genetics
Recent advances in population genetics indicate that allelic variation within functional loci of specific genes may result from both natural and neutral selection mechanisms (Novembre & di Rienzo, 2009). Allelic variation that occurs due to natural selection may be associated with specific functional adaptations that alter the probability of health (Chiao & Blizinsky, 2013; Sasaki, LeClair, West, & Kim, in press; Wang & Sue, 2005). For instance, genes previously shown to be associated with psychological health, including 5‐HTTLPR and dopamine receptor polymorphism, show allelic variation across geography, likely due to natural selection mechanisms (Chiao & Blizinsky, 2013). By adulthood, people living in distinct cultural contexts show differential gene–behavior associations, indicating that genes interact with culture in the production of adaptive behavior (Kim et al., 2010; Sasaki, Kim, & Xu, 2011). Variation in allelic frequency of genes associated with psychological health may produce cultural adaptations appropriate for a given ecological or environmental niche, which subsequently trigger an optimized developmental trajectory within the individual. Understanding the allelic variability of a given candidate gene associated with human behavior may provide theoretical insight into how and why cultural differences exist in developmental trajectories of the brain for a given ecological or geographic niche, but not another.
EMPIRICAL PROGRESS IN CULTURAL NEUROSCIENCE OF THE DEVELOPING BRAIN IN CHILDHOOD
Much progress has been made in understanding developmental changes in the social and emotional brain, particularly in Western culture. For instance, more than two decades of human neuroimaging studies have been performed to characterize neural systems during development (Casey, Tottenham, Liston, & Durston, 2005). However, a majority of these developmental neuroimaging studies are WEIRD—that is, conducted within Western, educated, industrialized, rich, democracies (Chiao & Cheon, & 2010; Henrich, Heine, & Norenzayan, 2010). This fact suggests that developmental brain scientists may be generalizing from a narrow sample of the species, which is not safe. Such developmental neuroimaging studies may not reveal important neural and behavioral differences across cultures and thus may not be able to fully represent how culture affects the developing social and emotional brain during childhood. This section provides an introduction to specific social and emotional processes that may prove fruitful to study within the cultural neuroscience framework. By studying how developmental changes in social and emotional processing vary across cultures, we gain deeper insight into how people acquire the ability to adaptively interact with one another throughout the life span.
Self and Other Knowledge
One of the primary social capacities that emerge in the developmental transition from infancy to childhood is a sense of self. From birth to approximately 2 years of age, infants and young children experience infantile amnesia such that they lack continuous autobiographical memory of self‐experience. As infants become children, they gain the capacity to remember events as autobiographical. Cultural values, practices, and beliefs shape knowledge and awareness of the self (Markus & Kitayama, 1991; Triandis, 1995). Self‐construal style, or independence and interdependence, refers to how people define themselves and their relation with the world (Markus & Kitayama, 1991). Independent or individualistic selves value freedom and autonomy and think of themselves as distinct from others. By contrast, interdependent or collectivist selves value interconnection and social harmony and think of themselves as connected to others.
Cross‐cultural behavioral studies of children in United States and China show cultural differences in the developmental trajectory of self‐knowledge (Wang, 2004). Cultural differences in notions of the self have been observed during development as early as 3 and 4 years of age (Han, Leichtman, & Wang, 1998; Wang, 2004). European American children are more likely to recall personal events with elaborate, detailed episodes, compared to Chinese and Korean children (Han et al., 1998). These findings suggest that unique childhood recollections characterize self‐knowledge in children raised in an individualistic compared to collectivistic culture. Furthermore, in a study of English‐Chinese bilingual children living in Hong Kong, children who were primed with individualism by speaking English were more likely to focus on autonomy and agency in their self‐construal, which led to detailed and self‐focused autobiographical memories. By contrast, children who were primed with collectivism by speaking Chinese were more likely to focus on relationship networks and social roles in their self‐construal and to recall relational or social autobiographical memories (Wang, Shao, & Li, 2010). Hence, cultural differences in self‐concept emerge early in childhood and maintain throughout development.
By young adulthood, cultural differences in self‐construal are neurally represented within the MPFC (Chiao et al., 2009; see Figure 1.3).
Figure 1.3 Cultural influences on medial prefrontal cortex (MPFC) response during self‐judgments. (a) Example of self‐judgment task; (b) MPFC response during culturally congruent self‐judgments; (c) Degree of cultural collectivism predicts MPFC response to culturally congruent self‐judgments.
Source: Adapted from Chiao et al., 2009.
In a cross‐cultural neuroimaging study of young adults, native Japanese living in Japan and Caucasian Americans living in the United States completed a self‐construal scale and a self‐knowledge task during scanning. Native Japanese showed greater MPFC response when processing contextual (e.g., “When talking to my mother, I am dutiful”) compared to general self‐statements (e.g., “I am dutiful”), whereas Caucasian Americans showed greater MPFC response during general compared to contextual self‐statements. Furthermore, irrespective of nationality, people who were more likely to endorse collectivistic cultural values showed increased MPFC response to contextual self‐statements. These findings demonstrate that cultural values of individualism and collectivism are predicted by neural response during self‐knowledge retrieval, in a culturally appropriate manner.
During the developmental transition from childhood to adulthood, the MPFC, along with other brain regions that comprise the default mode network, undergo significant changes in functional and structural connectivity. In particular, connectivity between the MPFC and posterior cingulate cortex is greater in adults compared to children, and maturation of this functional connection may comprise an important biological change in the development of self‐knowledge from childhood to adolescence (Supekar et al., 2010). One putative candidate for examining developmental changes in neural representations of the self across cultures is the MPFC and other brain regions of the default mode network. Based on prior behavioral studies, one possibility is that similar to adults, children may recruit MPFC to a greater extent when processing culturally congruent self‐knowledge; however, children may differentiate between individualistic and collectivistic self‐knowledge to a lesser extent compared to adults. Finally, the degree of connectivity between MPFC and posterior cingulate cortex may predict the degree to which children differentiate between individualistic and collectivistic self‐knowledge. Future cross‐cultural neuroimaging studies of the self across development are necessary to better understand the neurobiological mechanisms underlying the development of self across cultures.
Emotion
Another important psychological capacity that matures from infancy to childhood is emotion recognition. From infancy, humans respond to emotions expressed by others (Grossmann, Striano, & Friederici, 2006) and are able to distinguish between the emotional signals of own and other group members (Vogel, Monesson, & Scott, 2012). For instance, within the first 5 months of life, young infants distinguish between emotional faces of members of their own race and members of other races; however, by 9 months, infants distinguish the emotional faces of own‐race members only (Vogel et al., 2012). Notably, during childhood, the capacity to differentiate between positive and negative emotions, as well as to categorize emotions with verbal labels that imply mental states, emerges gradually (Widen & Russell, 2010), due to increased influence of cognition on emotion processing. However, less well understood is how culture affects the neural bases of emotion recognition during childhood.
Cultural differences in emotion emerge as a function of systems of values, practices, and beliefs (Elfenbein & Ambady, 2002; Kitayama & Markus, 1999; Mesquita & Frijda, 1992; Russell, 1991). Self‐construal style is a fundamental cultural dimension that affects how people perceive emotions (Elfenbein & Ambady, 2002), express and experience emotions (Kitayama & Markus, 1999), regulate their emotions (Ford & Mauss, 2015; Mauss & Butler, 2010), and conceptualize their ideal affect (Tsai, 2007). Cultural familiarity affects the degree to which people accurately perceive and recognize emotional expressions (Elfenbein & Ambady, 2002). People from the same cultural group demonstrate an in‐group advantage in emotion recognition such that they recognize emotions better when expressed by members of their group. People from interdependent cultures attend to the emotions of surrounding others to a greater extent relative to people from independent cultures (Masuda et al., 2008). Regulating emotions in social situations is more highly valued in interdependent relative to independent cultures (Kitayama & Markus, 1999; Mauss & Butler, 2010), and how people regulate their emotions, either by cognitive appraisal or emotion suppression, varies as a function of culture (Ford & Mauss, 2015). People living in interdependent cultures are more likely to utilize emotional suppression strategies for regulation, whereas people living in independent cultures are more likely to rethink their feelings or engage in cognitive reappraisal. Even the emotional states that people consider their “ideal affect” or emotional experience differs depends on cultural heritage (Tsai, 2007). Independent cultures emphasize positive emotions with high arousal, such as feelings of joy or elation; by contrast, interdependent cultures prize positive emotions of low arousal, such as feelings of calm.
By young adulthood, culture shapes different facets of emotion not only in behavior but also in neurobiology. Culture has been shown to affect bilateral amygdala response to fear faces (Chiao et al., 2008). In a cross‐cultural neuroimaging study, native Japanese living in Japan and Caucasian Americans living in the United States viewed emotional expressions of their own and other cultural group during scanning. Both native Japanese and Caucasian Americans showed greater bilateral amygdala response to fear faces expressed by own group members compared to other group members (Chiao et al., 2008). These findings indicate that amygdala response is heightened when processing the fear of a cultural group member, possibly due to the expectation that a member of one's own cultural group will be more likely to respond to one's fear or that the fear of a cultural group member may be more salient or relevant to one's self.
One possible mechanism underlying a cultural influence on amygdala response during emotion recognition is developmental changes in functional connectivity between the amygdala and cortical regions, such as the MPFC (Gee et al., 2013). During
