Gaze following is a fundamental component of triadic social interaction which includes events and an object shared with other
individuals and is found in both human and nonhuman primates. Most previous work has focused only on the immediate reaction
after following another’s gaze. In contrast, this study investigated whether gaze following is retained after the observation of the
other’s gaze shift, whether this retainment differs between species and age groups, and whether the retainment depends on the nature of the preceding events. In the social condition, subjects (1- and 2-year-old human children and chimpanzees) witnessed an experimenter who looked and pointed in the direction of a target lamp. In the physical condition, the target lamp blinked but the experimenter did not provide any cues. After a brief delay, we presented the same stimulus again without any cues. All subjects looked again to the target location after experiencing the social condition and thus showed a carryover effect. However, only 2-year-olds showed a carryover effect in the physical condition; 1-year-olds and chimpanzees did not. Additionally, only human children showed spontaneous interactive actions such as pointing. Our results suggest that the difference between the two age groups and chimpanzees is conceptual and not only quantitative.
International Journal of Humanities and Social Science Invention (IJHSSI) is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Jean Piaget's theory of cognitive development suggests that children move through four different stages of mental development. His theory focuses not only on understanding how children acquire knowledge, but also on understanding the nature of intelligence.
International Journal of Humanities and Social Science Invention (IJHSSI) is an international journal intended for professionals and researchers in all fields of Humanities and Social Science. IJHSSI publishes research articles and reviews within the whole field Humanities and Social Science, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Jean Piaget's theory of cognitive development suggests that children move through four different stages of mental development. His theory focuses not only on understanding how children acquire knowledge, but also on understanding the nature of intelligence.
Becoming a high-fidelity--Super--Imitator: What are the contributions of soci...Francys Subiaul
In contrast to other primates, human children’s imitation performance goes from low- to high-fidelity soon after infancy. Are such changes associated with the development of other forms of learning? We addressed this question by testing 215 children (26-59 months) on two social conditions (imitation, emulation)—involving a demonstration—and two asocial conditions (recall and trial-and-error)—involving individual learning—using two touchscreen tasks. The tasks required responding to either three different pictures in a specific picture order (Cognitive: Apple→Boy→Cat) or three identical pictures in a specific spatial order (Motor-Spatial Up→Down→Right). There were age-related improvements across all conditions. And imitation, emulation and recall performance were significantly better than trial-and-error learning. Generalized linear models demonstrated that motor-spatial imitation fidelity was associated with age and motor-spatial emulation, but cognitive imitation fidelity was only associated with age. While, this study provides evidence for multiple imitation mechanisms, the development of one of those mechanisms—motor-spatial imitation—may be bootstrapped by the development of another—motor-spatial emulation. Together, these findings provide important clues about the development of what is arguably a distinctive feature of human imitation performance.
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Becoming a high-fidelity--Super--Imitator: What are the contributions of soci...Francys Subiaul
In contrast to other primates, human children’s imitation performance goes from low- to high-fidelity soon after infancy. Are such changes associated with the development of other forms of learning? We addressed this question by testing 215 children (26-59 months) on two social conditions (imitation, emulation)—involving a demonstration—and two asocial conditions (recall and trial-and-error)—involving individual learning—using two touchscreen tasks. The tasks required responding to either three different pictures in a specific picture order (Cognitive: Apple→Boy→Cat) or three identical pictures in a specific spatial order (Motor-Spatial Up→Down→Right). There were age-related improvements across all conditions. And imitation, emulation and recall performance were significantly better than trial-and-error learning. Generalized linear models demonstrated that motor-spatial imitation fidelity was associated with age and motor-spatial emulation, but cognitive imitation fidelity was only associated with age. While, this study provides evidence for multiple imitation mechanisms, the development of one of those mechanisms—motor-spatial imitation—may be bootstrapped by the development of another—motor-spatial emulation. Together, these findings provide important clues about the development of what is arguably a distinctive feature of human imitation performance.
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Optimiser votre présence sur plusieurs places de marchéPierre-Alain Baly
Ebay, Priceminister, Amazon, Pixmania, Fnac, Cdiscount, RueduCommerce … ce sont autant de places de marchés sur lesquelles il est aujourd’hui indispensable d’être présent pour vendre. Cependant afin d’être performant sur ces plus grandes places de marché mondiales, il est primordiale de bien en connaître le fonctionnement et les particularités.
Cognitive Development The last two decades .docxpickersgillkayne
Cognitive Development
“The last two decades of infancy research have seen dramatic changes in the
way developmental psychologists char
acterize the earliest stages of cognitive
development. The infant, once regarded
as an organism driven mainly by sim
ple sensorimotor schemes, is now seen
as possessing sophisticated cognitive
skills and even sophisticated concepts
that guide knowledge acquisition”
(Madole and Oakes 1999, 263).
“What we see in the crib is the great
est mind that has ever existed, the
most powerful learning machine in
the universe” (Gopnik, Meltzoff, and
Kuhl 1999, 1).
The term cognitive development
refers to the process of growth and
change in intellectual/mental abilities
such as thinking, reasoning and
understanding. It includes the acquisi
tion and consolidation of knowledge.
Infants draw on social-emotional,
language, motor, and perceptual
experiences and abilities for cognitive
development. They are attuned to
relationships between features of
objects, actions, and the physical
environment. But they are particularly
attuned to people. Parents, family
members, friends, teachers, and care
givers play a vital role in supporting
the cognitive development of infants by
providing the healthy interpersonal or
social-emotional context in which
cognitive development unfolds. Caring,
responsive adults provide the base
from which infants can fully engage in
behaviors and interactions that pro
mote learning. Such adults also serve
as a prime source of imitation.
Cultural context is important to
young children’s cognitive develop
ment. There is substantial variation
in how intelligence is defined within
different cultures (Sternberg and
Grigorenko 2004). As a result, dif
ferent aspects of cognitive function
ing or cognitive performance may be
more highly valued in some cultural
contexts than in others. For example,
whereas processing speed is an aspect
of intelligence that is highly valued
within the predominant Western con
ceptualizations of intelligence, “Ugan
dan villagers associate intelligence
with adjectives such as slow, careful,
and active” (Rogoff and Chavajay 1995,
865.). Aspects of intelligence that have
to do with social competence appear to
be seen as more important than speed
��
C
O
G
N
IT
IV
E
D
E
V
E
L
O
P
M
E
N
T
60
in some non-Western cultural contexts
(Sternberg and Grigorenko 2004). Cer
tainly, it is crucial for early childhood
professionals to recognize the role that
cultural context plays in defining and
setting the stage for children’s healthy
cognitive functioning.
Research has identified a broad
range of cognitive competencies and
described the remarkable progres
sion of cognitive development during
the early childhood years. Experts in
the field describe infants as active,
motivated, and engaged learners who
possess an impressive range of cogni
tive competencies (National Research
Council and Institute of.
Cognitive Development
“The last two decades of infancy research have seen dramatic changes in the
way developmental psychologists char
acterize the earliest stages of cognitive
development. The infant, once regarded
as an organism driven mainly by sim
ple sensorimotor schemes, is now seen
as possessing sophisticated cognitive
skills and even sophisticated concepts
that guide knowledge acquisition”
(Madole and Oakes 1999, 263).
“What we see in the crib is the great
est mind that has ever existed, the
most powerful learning machine in
the universe” (Gopnik, Meltzoff, and
Kuhl 1999, 1).
The term cognitive development
refers to the process of growth and
change in intellectual/mental abilities
such as thinking, reasoning and
understanding. It includes the acquisi
tion and consolidation of knowledge.
Infants draw on social-emotional,
language, motor, and perceptual
experiences and abilities for cognitive
development. They are attuned to
relationships between features of
objects, actions, and the physical
environment. But they are particularly
attuned to people. Parents, family
members, friends, teachers, and care
givers play a vital role in supporting
the cognitive development of infants by
providing the healthy interpersonal or
social-emotional context in which
cognitive development unfolds. Caring,
responsive adults provide the base
from which infants can fully engage in
behaviors and interactions that pro
mote learning. Such adults also serve
as a prime source of imitation.
Cultural context is important to
young children’s cognitive develop
ment. There is substantial variation
in how intelligence is defined within
different cultures (Sternberg and
Grigorenko 2004). As a result, dif
ferent aspects of cognitive function
ing or cognitive performance may be
more highly valued in some cultural
contexts than in others. For example,
whereas processing speed is an aspect
of intelligence that is highly valued
within the predominant Western con
ceptualizations of intelligence, “Ugan
dan villagers associate intelligence
with adjectives such as slow, careful,
and active” (Rogoff and Chavajay 1995,
865.). Aspects of intelligence that have
to do with social competence appear to
be seen as more important than speed
��
C
O
G
N
IT
IV
E
D
E
V
E
L
O
P
M
E
N
T
60
in some non-Western cultural contexts
(Sternberg and Grigorenko 2004). Cer
tainly, it is crucial for early childhood
professionals to recognize the role that
cultural context plays in defining and
setting the stage for children’s healthy
cognitive functioning.
Research has identified a broad
range of cognitive competencies and
described the remarkable progres
sion of cognitive development during
the early childhood years. Experts in
the field describe infants as active,
motivated, and engaged learners who
possess an impressive range of cogni
tive competencies (National Research
Council and Institute of ...
THEORIES OF INTELLECTUAL DEVELOPMENTPiaget’s TheoryWe begin wi.docxsusannr
THEORIES OF INTELLECTUAL DEVELOPMENT
Piaget’s Theory
We begin with the theory of the famous Swiss psychologist, Jean Piaget (Gruber & Voneche, 1995). Piaget disagreed with the behaviorist notion that children come into this world as “blank slates” who simply receive and store information about the world from other people (Driver, Asoko, Leach, Mortimer & Scott, 1994). Instead, Piaget argued that, at all ages, humans actively interact with their world, and through those interactions try to interpret and understand it in terms of what they already know. He also thought that humans change the ways in which they interact with and interpret the world as they grow older and more experienced. What is important for teachers to understand is (1) how children are likely to interact with and interpret the world at particular ages and (2) what factors lead children to move from less sophisticated to more sophisticated forms of interaction and interpretation.
In describing how children interact with and interpret the world, Piaget proposed four stages of intellectual development. He believed that these stages were universal, that is, that children everywhere, regardless of culture or experience passed through the same stages. He also believed that children progressed through the stages in an invariant order, that is, all children move from simpler, less adequate ways of thinking to increasingly more complex, sophisticated ways of thinking. Piaget did allow that some children might develop faster than others and that some might never achieve the highest stage(s) of thinking.
Piaget’s claims about stages of intellectual development have faced many criticisms, as you have no doubt read in your human development text. For example, it has been suggested that development is much more gradual and piecemeal than implied by the notion of a stage (Santrock, 2008, 2009). Nevertheless, these stages still provide a useful framework for teachers. In particular, Piaget’s stages provide clues about how students will interpret and approach many of the problems that you pose, as well as clues about the types of problems and experiences that are most likely to engage students and be beneficial for them (Elliott, Kratochwill, Littlefield & Travers, 2000; Feinburg & Mindess, 1994; Santrock, 2008).
The four stages that Piaget proposed are described briefly below. Please note that the age ranges listed are only approximations.
Sensorimotor period. This stage characterizes the thinking of children up until the age of 2 years. During this stage, infants and toddlers learn about the world by acting on it directly through motoric and sensory activities, such as sucking, grasping, and looking. In this way, they gradually learn about the physical properties of objects and develop rudimentary understanding of space, time, and causality.
Preoperational period. This stage characterizes the thinking of children between the ages of 2 and 6 years. Preoperational chil.
Cognitive and social development are key areas of development WilheminaRossi174
Cognitive and social development are key areas of development since
how infants undergo these two areas of development play an important role in
determining their cognitive and social capabilities as adults. This essay
examines what is currently known about cognitive and social development,
how these developmental processes may differ in cultural contexts where
breastfeeding is more prevalent, and how studies can be conducted to
determine if these developmental processes occur at an earlier age or in a
different manner in such a cultural context.
Cognitive development focuses on how the processes involved in
acquiring, processing, and organizing information develop in humans (Oakley,
2004). The two most important theories of cognitive development are the
theories of Jean Piaget and Lev Vygotsky.
Jean Piaget stated that cognitive structures are modified through the
processes of assimilation and accommodation. Assimilation is the process
through which new information is incorporated into an individual’s existing
cognitive structures, whereas accommodation is the process through which
new cognitive structures are formed in order to fit new information that is
encountered (Altman et al., 2017).
Piaget also theorized that there are four stages of cognitive
development. The first stage is the sensorimotor period which starts at birth
and lasts until the age of 2 where infants are learning about the world through
their sensory and motor abilities. The next stage, the preoperational period,
occurs from ages 2 to 7 and it is characterized by increased abilities in
symbolic thinking and language use. The third stage is the concrete
operational period which occurs between the ages of 7 to 12 where a child’s
ability to reason about concrete ideas significantly increases. The final stage
is the formal operational period which occurs after the age of 12,
characterized by the ability to reason about hypothetical problems and the
ability to think abstractly (Altman et al., 2017).
In contrast to Piaget, Lev Vygotsky’s theory focused on the influence
that social interactions have on cognitive development. Vygotsky stated that
there are three factors that shape a child’s cognitive development: culture,
language, and the zone of proximal development (ZPD) (Oakley, 2004).
Vygotsky believed that culture is important in shaping cognitive development
since what knowledge a child acquires and how that knowledge is acquired is
determined by the culture that the child is a part of. Vygotsky stated that
language has an important role in cognitive development since the world is
understood and represented using language (Oakley, 2004). The third factor,
ZPD, is the distance between a child’s abilities on their own and a child’s
potential abilities that can be developed with some guidance and support
(Oakley, 2004).
Social development refers to the development of social understanding
and the acquiring of social skills. Two key areas of social development are the
devel ...
Ape and Human Cognition What’s theDifferenceMichael To.docxRAHUL126667
Ape and Human Cognition: What’s the
Difference?
Michael Tomasello and Esther Herrmann
Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
Abstract
Humans share the vast majority of their cognitive skills with other great apes. In addition, however, humans have also evolved a
unique suite of cognitive skills and motivations—collectively referred to as shared intentionality—for living collaboratively,
learning socially, and exchanging information in cultural groups.
Keywords
apes, culture, cognition, evolution, cooperation
Surely one of the deepest and most important questions in all of
the psychological sciences is how human cognition is similar to
and different from that of other primates. The main datum is this:
Humans seemingly engage in all kinds of cognitive activities that
their nearest primate relatives do not, but at the same time there is
great variability among different cultural groups. All groups have
complex technologies but of very different types; all groups use
linguistic and other symbols but in quite different ways; all
groups have complex social institutions but very different ones.
What this suggests is that human cognition is in some way bound
up with human culture. Here we argue that this is indeed the case,
and we then try to explain this fact evolutionarily.
Similarities in Ape and Human Cognition
The five great ape species (orangutans, gorillas, chimpanzees,
bonobos, humans) share a common ancestor from about 15 mil-
lion years ago, with the last three sharing a common ancestor
from about 6 million years ago (see Fig. 1 for a picture of chim-
panzees). Since great apes are so closely related to one another
evolutionarily, it is natural that they share many perceptual,
behavioral, and cognitive skills.
Great ape cognitive worlds
Many different studies suggest that nonhuman great apes (here-
after great apes) understand the physical world in basically the
same way as humans. Like humans, apes live most basically in
a world of permanent objects (and categories and quantities of
objects) existing in a mentally represented space. Moreover,
they understand much about various kinds of events in the
world and how these events relate to one another causally (see
Tomasello & Call, 1997, for a review). Apes’ and other
primates’ cognitive skills for dealing with the physical world
almost certainly evolved in the context of foraging for food.
As compared with other mammals, primates may face special
challenges in locating their daily fare, since ripe fruits are pat-
chy resources that are irregularly distributed in space and time.
Other studies suggest that great apes understand their social
worlds in basically the same way as humans as well. Like
humans, apes live in a world of identifiable individuals with
whom they form various kinds of social relationships—for
example, in terms of dominance and ‘‘friendship’’—and they
recognize the third-party social relationships that.
Ape and Human Cognition What’s theDifferenceMichael To.docxfestockton
Ape and Human Cognition: What’s the
Difference?
Michael Tomasello and Esther Herrmann
Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
Abstract
Humans share the vast majority of their cognitive skills with other great apes. In addition, however, humans have also evolved a
unique suite of cognitive skills and motivations—collectively referred to as shared intentionality—for living collaboratively,
learning socially, and exchanging information in cultural groups.
Keywords
apes, culture, cognition, evolution, cooperation
Surely one of the deepest and most important questions in all of
the psychological sciences is how human cognition is similar to
and different from that of other primates. The main datum is this:
Humans seemingly engage in all kinds of cognitive activities that
their nearest primate relatives do not, but at the same time there is
great variability among different cultural groups. All groups have
complex technologies but of very different types; all groups use
linguistic and other symbols but in quite different ways; all
groups have complex social institutions but very different ones.
What this suggests is that human cognition is in some way bound
up with human culture. Here we argue that this is indeed the case,
and we then try to explain this fact evolutionarily.
Similarities in Ape and Human Cognition
The five great ape species (orangutans, gorillas, chimpanzees,
bonobos, humans) share a common ancestor from about 15 mil-
lion years ago, with the last three sharing a common ancestor
from about 6 million years ago (see Fig. 1 for a picture of chim-
panzees). Since great apes are so closely related to one another
evolutionarily, it is natural that they share many perceptual,
behavioral, and cognitive skills.
Great ape cognitive worlds
Many different studies suggest that nonhuman great apes (here-
after great apes) understand the physical world in basically the
same way as humans. Like humans, apes live most basically in
a world of permanent objects (and categories and quantities of
objects) existing in a mentally represented space. Moreover,
they understand much about various kinds of events in the
world and how these events relate to one another causally (see
Tomasello & Call, 1997, for a review). Apes’ and other
primates’ cognitive skills for dealing with the physical world
almost certainly evolved in the context of foraging for food.
As compared with other mammals, primates may face special
challenges in locating their daily fare, since ripe fruits are pat-
chy resources that are irregularly distributed in space and time.
Other studies suggest that great apes understand their social
worlds in basically the same way as humans as well. Like
humans, apes live in a world of identifiable individuals with
whom they form various kinds of social relationships—for
example, in terms of dominance and ‘‘friendship’’—and they
recognize the third-party social relationships that ...
Social Learning in Humans and Nonhuman Animals: Theoretical and Empirical Dis...Francys Subiaul
In this special issue, we present a synthesis of work that consolidates what is currently known and provides a platform for
future research. Consequently, we include both new empirical
studies and novel theoretical proposals describing work with both human children and adults and a range of nonhuman animals. In this introduction, we describe the background of this special issue and provide a context for each of the eight articles it contains. We hope such introduction will not only help the reader synthesize the interdisciplinary views that characterize this broad field, but also stimulate development of new methods, concepts, and data.
Social Cognition (1)The gullibility of children is a.docxjensgosney
Social Cognition (1)
The gullibility of children is a discontinuous process. (4)
Acknowledge the different needs of other children, their emotions, and their preferences (2)
Gullibility of children
Nurture highly plays a role in this example (3)
Domain-general processes highly apply (5)
Running head: DEVELOPMENT 1
DEVELOPMENT 5
Cognitive Development of Children
Student’s Name
Institution
Date
By the age of four years, children become highly aware of the information provided to them by adults, their parents are their individual caregivers. Gullibility refers to the susceptibility of a person to getting fooled easily or manipulated by an individual. In regards to their development, children between the ages of three to five years are typically unable to formulate and create their sense of separate self from their caregivers (Forrester, 2013).This fact means that children are highly affected by the perceptions of their parents towards them. Also at an early age, most children usually see themselves through the reflection imposed from the eyes of their caregivers. The message conveyed through the various communication processes by parents is highly robust and affects their level of self-regard. A great example is where parents view their children as incompetent in all aspects of both academic and social excellence. These perceptions of inferiority lead children to grow eventually old seek acceptance and a particular life direction from others. As the children see themselves as inferior due to the influence of the parents on their perception, another person’s viewpoints might impact their beliefs. This issue is due to the children profoundly unable to make incisive inquiries needed in proper decision making (Greenspan, 2008). As a result, children are cornered into make choices that counter their better sense of judgment.
1. Development stage of Theory of Mind
In the chosen example, the development stage of the theory of the mind is social cognition. This phase is the primary facet of the ability of a child to interact appropriately with other children and also to see the world through their lenses. The fundamental fact of this knowledge mainly lies in the development of the theory of the mind. Theory of the mind refers to the comprehension of different people as capable individuals that have their various states such as feelings, motives wants, and thoughts (Pennington, 2012) .Around three to four years in children, a significant development occurs whereby children become aware that the ideas inside their minds might not be implicitly true. An instance of gullibility is whereby children are allowed to find out that a similar candy box contained pens and asked what their friend would think of the exact contents of the box before knowing what truly is inside the box.
2. Support of theory
Concerning the theory within.
Similar to Carryover effects of joint attention to repeated events in chimpanzees and young children (20)
Working Memory Constraints on Imitation and EmulationFrancys Subiaul
Does working memory (WM) constrain the amount and type of information children copy from a model? To answer this question, preschool age children (n = 165) were trained and then tested on a touch-screen task that involved touching simultaneously presented pictures. Prior to responding, children saw a model generate two target responses: Order, touching all the pictures on the screen in a target sequence 3 consecutive times and Multi-Tap, consistently touching one of the pictures two times. Children’s accuracy copying Order and Multi-Tap was assessed on two types of sequences: low WM (2 pictures) load and high WM (3 pictures) load. Results showed that more children copied both Order and Multi-Tap on 2- than on 3-picture sequences. Children that copied only one of the two target responses, tended to copy only Order on 2-picture sequences but only Multi-Tap on 3-picture sequences. Instructions to either copy or ignore the multi-tap response did not affect this overall pattern of results. In sum, results are consistent with the hypothesis that WM constrains not just the amount but also the type of information children copy from models; Potentially modulating whether children imitate or emulate in a given task.
Gorillas’ use of the escape response in object choice memory testsFrancys Subiaul
The ability to monitor and control one’s own cognitive states, metacognition, is crucial for effective learning and problem solving. Although the literature on animal metacognition has grown considerably during last 15 years, there have been few studies examining whether great apes share such introspective abilities with humans. Here, we tested whether four gorillas could meet two criteria of animal metacognition, the increase in escape
responses as a function of task difficulty and the chosenforced
performance advantage. During testing, the subjects participated in a series of object choice memory tests in which a preferable reward (two grapes) was placed under one of two or three blue cups. The apes were required to correctly select the baited blue cup in this primary test. Importantly, the subjects also had an escape response (a yellow cup), where they could obtain a secure but smaller reward (one grape) without taking the memory test. Although the gorillas received a relatively small number of
trials and thus experienced little training, three gorillas
significantly declined the memory tests more often in difficult
trials (e.g., when the location of the preferred reward conflicted with side bias) than in easy trials (e.g., when there was no such conflict). Moreover, even when objective cues were eliminated that corresponded to task difficulty, one of the successful gorillas showed evidence suggestive of improved memory performance with the help of escape response by selectively avoiding trials in which he would be likely to err before the memory test actually proceeded. Together, these findings demonstrate that at least some gorillas may be able to make optimal choices on the basis
of their own memory trace strength about the location of the preferred reward.
Four studies using a computerized paradigm investigated whether children’s imitation performance is content-specific and to what extent dependent on other cognitive processes such as trial-and-error learning, recall and observational learning. Experiment 1 showed that 3-year olds’ could successfully imitate what we refer to as novel cognitive rules (e.g., First→Second→Third) which involved responding to three different pictures whose spatial configuration varied randomly from trial to trial. However, these same children failed to imitate what we refer to as novel motor-spatial rules (e.g., Up→Down→Right) which involved responding to three identical pictures that remained in a fixed spatial configuration from trial to trial. Experiment 2 showed that this dissociation was not due to a general difficulty encoding motor-spatial content as children successfully recalled, following a 30s delay, a new motor-spatial sequence that had been learned by trial and error. Experiment 3 replicated these results and further demonstrated that 3-year olds can infer a novel motor-spatial sequence following the observation of a partially correct and partially incorrect response; a dissociation between imitation and observational learning (or goal emulation). Finally, Experiment 4 presented 3-year olds with ‘familiar’ motor-spatial sequences (e.g., Left→Middle→Right) as well as ‘novel’ motor-spatial sequences (e.g., Right→Up→Down) used in Experiments 1-3. Three-year olds had no difficulty imitating familiar motor-spatial sequences. But, again, failed to imitate novel motor-spatial sequences. These results suggest that there may be multiple, dissociable imitation learning mechanisms that are content-specific. More importantly, the development of these imitation systems appear to be independent of the operations of other cognitive systems including trial and error learning, recall and observational learning.
Curious monkeys have increased gray matter density in the precuneusFrancys Subiaul
Curiosity is a cornerstone of cognition that has the potential to lead to innovations and increase the behavioral repertoire of individuals. A defining characteristic of curiosity is inquisitiveness directed toward novel objects. Species differences in innovative behavior and inquisitiveness have been linked to social complexity and neocortical size. In this study, we observed behavioral actions among nine socially reared and socially housed capuchin monkeys in response to an unfamiliar object, a paradigm widely employed as a means to assess curiosity. K-means hierarchical clustering analysis of the behavioral
responses revealed three monkeys engaged in significantly more exploratory behavior of the novel object than other monkeys. Using voxel-based-morphometry analysis of MRIs obtained from these same subjects, we demonstrated that the more curious monkeys had significantly greater gray matter density in the precuneus, a cortical region involved in highly integrated processes including memory and self-awareness. These results linking variation in precuneus gray matter volume to exploratory behavior suggest that monitoring states of self-awareness may play a role in cognitive processes mediating individual curiosity.
The Ghosts in the Computer: The Role of Agency and Animacy Attributions in “...Francys Subiaul
Three studies evaluated the role of 4-year-old children’s agency- and animacy-attributions when learning from a computerized ghost control (GC). In GCs participants observe events occurring without an apparent agent, as if executed by a “ghost” or unobserved causal forces. Using a touch-screen, children in Experiment 1 responded to three pictures in a specific order under three learning conditions: (i) trial-and-error (Baseline), (ii) imitation and (iii) Ghost Control. Before testing in the GC, children were read one of three scripts that determined agency attributions. Post-test assessments confirmed that all children attributed agency to the computer and learned in all GCs. In Experiment 2, children were not trained on the computer prior to testing, and no scripts were used. Three different GCs, varying in number of agency cues, were used. Children failed to learn in these GCs, yet attributed agency and animacy to the computer. Experiment 3 evaluated whether children could learn from a human model in the absence of training under conditions where the information presented by the model and the computer was either consistent or inconsistent. Children evidenced learning in both of these conditions. Overall, learning in social conditions (Exp. 3) was significantly better than learning in GCs (Exp. 2). These results, together with other published research, suggest that children privilege social over non-social sources of information and are generally more adept at learning novel tasks from a human than from a computer or GC.
Dissecting the Imitation Faculty: The Multiple Imitation Mechanisms (MIM) Hyp...Francys Subiaul
Is the imitation faculty one self-contained domain-general mechanism or an amalgamation of multiple content-specific systems? The Multiple Imitation Mechanisms (MIM) Hypothesis posits that the imitation faculty consists of distinct content-specific psychological systems that are dissociable both structurally and functionally. This hypothesis is supported by research in the developmental, cognitive, comparative and neural sciences. This body of work suggests that there are dissociable imitation systems that may be distinguished by unique behavioral and neurobiological profiles. The distribution of these different imitation skills in the animal kingdom further suggests a phylogenetic dissociation, whereby some animals specialized in some (but not all possible) imitation types; a reflection of specific selection pressures favoring certain imitation systems. The MIM hypothesis attempts to bring together these different areas of research into one theoretical framework that defines imitation both functionally and structurally.
Since the last common ancestor shared by modern humans, chimpanzees and bonobos, the lineage leading to Homo sapiens
has undergone a substantial change in brain size and organization. As a result, modern humans display striking differences from the living apes in the realm of cognition and linguistic expression. In this article, we review the evolutionary changes that occurred in the descent of Homo sapiens by reconstructing the neural and cognitive traits that would have characterized the last common ancestor and comparing these with the modern human condition. The last common ancestor can be reconstructed to have had a brain of approximately 300–400 g that displayed several unique phylogenetic specializations of development, anatomical organization, and biochemical function. These neuroanatomical substrates contributed to the enhancement of behavioral flexibility and social cognition. With this evolutionary history as precursor, the modern human mind may be conceived as a mosaic of traits inherited from a common ancestry with our close relatives, along with the addition of volutionary specializations within particular domains. These modern human-specific cognitive and linguistic adaptations
appear to be correlated with enlargement of the neocortex and related structures. Accompanying this general neocortical expansion, certain higher-order unimodal and multimodal cortical areas have grown disproportionately relative to primary cortical areas. Anatomical and molecular changes have also been identified that might relate to the greater metabolic demand and enhanced synaptic plasticity of modern human brain’s. Finally, the unique brain growth trajectory of modern humans has made a significant contribution to our species’ cognitive and linguistic abilities.
Do Chimpanzees Learn Reputation by Observation? Evidence from Direct and Ind...Francys Subiaul
Can chimpanzees learn the reputation of strangers indirectly by observation? Or are such stable behavioral attributions made exclusively by first-person interactions? To address this question, we let seven chimpanzees observe unfamiliar humans either consistently give (generous donor) or refuse to give (selfish donor) food to a familiar human recipient (Exps. 1 and 2) and a conspecific (Exp 3). While chimpanzees did not initially prefer to beg for food from the generous donor (Exp 1), after continued opportunities to observe the same behavioral exchanges, four chimpanzees developed a preference for gesturing to the generous donor (Exp 2), and transferred this preference to novel unfamiliar donor pairs, significantly preferring to beg from the novel generous donors on the first opportunity to do so. In Experiment Three, four chimpanzees observed novel selfish and generous acts directed toward other chimpanzees by human experimenters. During the first half of testing, three chimpanzees exhibited a preference for the novel generous donor on the first trial. These results demonstrate that chimpanzees can infer the reputation of strangers by eavesdropping on third-party interactions.
Cognitive Imitation in 2-Year Old Children (Homo sapiens): A comparison with...Francys Subiaul
Here we compare the performance of two-year old human children with that of adult rhesus macaques on a cognitive imitation task. The task was to respond, in a particular order, to arbitrary sets of photographs that were presented simultaneously on a touch sensitive video monitor. Because the spatial position of list items was varied from trial to trial, subjects could not learn this task as a series of specific motor responses. On some lists, subjects with no knowledge of the ordinal position of the list items were given the opportunity to learn the order of those items by observing an expert model. Children, like monkeys, learned new lists more rapidly in a social condition where they had the opportunity to observe an experienced model perform the list in question, than under a baseline condition in which they had to learn new lists entirely by trial and error. No differences were observed between the accuracy of each species’ responses to individual items or in the frequencies with which they made different types of errors. These results provide clear evidence that monkeys and humans share the ability to imitate novel cognitive rules (cognitive imitation).
What makes the human mind different from the minds of other animals? Here, the cognitive abilities of human and non-human primates are compared and contrasted in three general domains (a) self-awareness, (b) social cognition, and (c) physical cognition. Our analysis of the data is framed in terms of an overarching theory of human cognitive specialization. We postulate that many aspects of the human and the non-human primate mind are remarkably conserved. As a result, human and non-human primates share many cognitive and behavioral capabilities. However, we will argue that despite the many similarities between the human and non-human mind, one fundamental feature of our species’ psychology is its ability to interpret observable variables in terms of unobservable (causal) forces. Consequently, while animals can develop rules premised on observable causes, humans can reason about both observable and unobservable causes, resulting in the kind of cognitive and behavioral flexibility that characterizes our species.
The imitation faculty in monkeys: Evaluating its features, distribution and e...Francys Subiaul
Despite more than 100 years of research, there is no agreement among experts as to whether or not monkeys can imitate. Part of the problem is that there is little agreement as to what constitutes an example of ‘imitation.’ Nevertheless, recent research provides compelling evidence for both continuities and discontinuities in the psychological faculty that mediates imitation performance. A number of studies have shown that monkeys are capable of copying familiar responses but not novel responses that require the use of tools, for example. And, while these studies have been interpreted to mean that monkeys cannot engage in ‘imitation learning’ or novel imitation, research employing a cognitive imitation paradigm—where rhesus monkeys had to copy novel serial rules pertaining to the order of pictures, independently of copying specific motor responses—has provided convincing evidence of novel imitation in monkeys. Rather than suggesting that monkeys are poor imitators, these results suggest that monkeys can learn novel cognitive rules but not novel motor rules, possibly because such skills require derived neural specializations mediating fine and gross motor movements; If true, such evidence represents an important discontinuity between the imitation skills of monkeys and apes with significant implications for human cognitive evolution.
Experiments on imitation typically evaluate a student’s ability to copy some feature of an expert’s motor behavior. Here we describe a type of observational learning in which a student copies a cognitive rule, rather than a specific motor actions. Two rhesus macaques were trained to respond, in a prescribed order, to different sets of photographs that were displayed on a touch-sensitive monitor. Because the position of the photographs varied randomly from trial to trial, sequences could not be learned by motor imitation. Both monkeys learned new sequences more rapidly after observing an expert execute those sequences than when they had to learn new sequences entirely by trial and error.
The cognitive structure of goal emulation during the preschool years. Francys Subiaul
Humans excel at both mirroring others’ actions (imitation) as well as others’ goals and intentions (emulation). Since most research has focused on imitation, here we focus on how social and asocial learning predict the development of goal emulation. We tested 215 preschool children on two social conditions (imitation, emulation) and two asocial conditions (trial-and-error and recall) using two touchscreen tasks. The tasks involved responding to either three different pictures in a specific picture order (Cognitive: Apple→Boy→Cat) or three identical pictures in a specific spatial order (Motor-Spatial Up→Down→Right). Generalized linear models demonstrated that during the preschool years, Motor-Spatial emulation is associated with social and asocial learning, while Cognitive emulation is associated only with social learning, including Motor-spatial emulation and multiple forms of imitation. This result contrasts with those from a previous study using this same dataset showing that Motor-Spatial and Cognitive imitation were neither associated with one another nor, generally, predicted by other forms of social or asocial learning. Together these results suggests that while developmental changes in imitation are associated with multiple—specialized—mechanisms, developmental changes in emulation are associated with age-related changes and a more unitary, domain-general mechanism that receives input from several different cognitive and learning processes, including some that may not necessarily be specialized for social learning.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Nucleic Acid-its structural and functional complexity.
Carryover effects of joint attention to repeated events in chimpanzees and young children
1. PAPER
Carryover effect of joint attention to repeated events in
chimpanzees and young children
Sanae Okamoto-Barth,1,2
Chris Moore,3
Jochen Barth,2
Francys Subiaul2,4
and Daniel J. Povinelli2
1. Department of Economics & Department of Cognitive Neuroscience, Maastricht University, The Netherlands
2. Department of Biology & Cognitive Evolution Group, University of Louisiana, USA
3. Department of Psychology, Dalhousie University, Canada
4. Mind, Brain Evolution Cluster, Department of Speech and Hearing Sciences, The George Washington
University & the Ape Mind Initiative, The Smithsonian National Zoological Park, USA
Abstract
Gaze following is a fundamental component of triadic social interaction which includes events and an object shared with other
individuals and is found in both human and nonhuman primates. Most previous work has focused only on the immediate reaction
after following another’s gaze. In contrast, this study investigated whether gaze following is retained after the observation of the
other’s gaze shift, whether this retainment differs between species and age groups, and whether the retainment depends on the
nature of the preceding events. In the social condition, subjects (1- and 2-year-old human children and chimpanzees) witnessed
an experimenter who looked and pointed in the direction of a target lamp. In the physical condition, the target lamp blinked but
the experimenter did not provide any cues. After a brief delay, we presented the same stimulus again without any cues. All
subjects looked again to the target location after experiencing the social condition and thus showed a carryover effect. However,
only 2-year-olds showed a carryover effect in the physical condition; 1-year-olds and chimpanzees did not. Additionally, only
human children showed spontaneous interactive actions such as pointing. Our results suggest that the difference between the two
age groups and chimpanzees is conceptual and not only quantitative.
Introduction
By the end of their first year, human infants become sen-
sitive to information specifying where others are looking.
The ability to follow the gaze of other individuals is a
critical component of joint attention, defined as looking
toward the object of others’ attention. Infants show a
specific developmental trajectory in this ability (see
Moore, 2008). In this first year, human infants follow their
mother’s gaze to the appropriate side (e.g. Scaife & Bruner,
1975), at first when there are objects already in their
immediate field of view (e.g. D’Entremont, Hains & Muir,
1997), and later even when objects are outside their
immediate field of view (e.g. Corkum & Moore, 1995). By
the beginning of the second year, infants will follow their
mother’s gaze towards particular objects even when vari-
ous objects are present, and between 12 and 18 months
they can direct their attention to objects that are located
behind them or in containers (e.g. Butterworth & Coch-
ran, 1980; Butterworth & Jarrett, 1991; Moll & Tomasello,
2004). Joint attention is considered by some to be an early
social cognitive ability leading to the later development of
the ability to infer others’ mental states (cf. Baron-Cohen,
1995; Tomasello, 1995).
However, eye-gaze is not the only cue to another’s
focus of attention. The orientation of the whole head,
body, and hand (e.g. pointing) are similarly good indi-
cators of attention and interest, and are used in our daily
interactions with others. Pointing in particular is con-
sidered an important component of joint attention as an
indicator of particular objects, locations, or events. At
about 12 months, infants begin to follow pointing to
distant locations (Butterworth & Jarrett, 1991; Desro-
chers, Morissette & Ricard, 1995; Lempers, 1979; Leung
& Rheingold, 1981; Murphy & Messer, 1977).
Gaze following is also found in a number of nonhu-
man primates. The use of gaze shifts as social cues has
various evolutionary advantages. For instance, gaze
shifts may index the location of predators, dominants,
potential mates or food sources. Several field studies
suggest that primates follow the gaze of conspecifics
(e.g. Chance, 1967; Menzel & Halperin, 1975; Whiten &
Byrne, 1988). A number of laboratory studies have also
investigated gaze following in nonhuman primates.
Address for correspondence: Sanae Okamoto-Barth, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht
University, P.O. Box 616, 6200 MD Maastricht, The Netherlands; e-mail: s.barth@maastrichtuniversity.nl
Ó 2010 Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.
Developmental Science (2010), pp 1–13 DOI: 10.1111/j.1467-7687.2010.00996.x
2. Within a gaze-following task paradigm, various stud-
ies with chimpanzees have demonstrated that they follow
the gaze direction of other individuals (e.g. Itakura,
1996; Povinelli & Eddy, 1996; Tomasello, Call & Hare,
1998; Okamoto-Barth, Call & Tomasello, 2007; see
Emery, 2000, for review). However, interpreting this
behavior is not straightforward, as it may represent either
a simple reflexive tendency to visually orient in the
direction of another individual’s visual orientation or a
more cognitively complex process of knowing that the
other ‘sees’ something. For instance, studies using several
different types of barriers have found that chimpanzees
actually position themselves so as to gain a good viewing
angle at the location to which another individual is
looking (Tomasello, Hare & Agnetta, 1999; Okamoto,
Tanaka & Tomonaga, 2004; Bräuer, Call & Tomasello,
2005). This type of ‘perspective angling’ develops at
around 12 months of age in humans (Moll & Tomasello,
2004), and has also been documented in chimpanzees
and bonobos (Okamoto-Barth et al., 2007). Okamoto-
Barth et al. (2007) reported that chimpanzees and
bonobos followed gaze more often when the experi-
menter looked through a barrier with a window than one
without a window. These results, combined with others
showing that these species also follow gaze around bar-
riers (Bräuer et al., 2005; Povinelli & Eddy, 1996; Tom-
asello et al., 1999), suggest that chimpanzees and
bonobos have some understanding of the referential
nature of looking. However, the sophistication of this
ability in chimpanzees is not as present as in human
infants. For instance, in one study (Tomasello, Hare,
Lehmann & Call, 2007), a human experimenter ‘looked’
to the ceiling either with his eyes only, head only (eyes
closed), both head and eyes, or neither. Great apes fol-
lowed gaze to the ceiling based mainly on the human’s
head direction (although eye direction played some role
as well). In contrast, human infants relied almost exclu-
sively on eye direction in these same situations. But the
knowledge about how this skill differs between species is
still fragmentary.
Most previous work with both human and nonhuman
primates has focused on the immediate reaction such as
whether subjects followed gaze of others towards a par-
ticular target. However, in daily life, our action towards
events or objects, which we share with others, is often
more of a prolonged interaction about ongoing events.
The duration and nature of these gaze-following episodes
during interaction has so far not been well investigated.
In the context of gaze following, Itakura (2001) reported
that human infants (average 11 months old) gazed longer
at a stimulus that was blinking or had been pointed at by
the mother than a stimulus which was not blinking and
had not been pointed at by the mother. When the stim-
ulus was presented a second time (after a delay), infants
gazed longer at the stimulus that the mother had pointed
at during the earlier trial (‘carryover effect’) than at the
stimulus that had been blinking in the earlier trial. This
result has been interpreted to mean that a social cue (e.g.
joint attention episode) captures a child’s attention better
and for a longer period of time than a non-social cue (e.g.
stimulus change episodes ⁄blinking object).
However, why did the infants keep their attention
longer for the social cue than for the blinking object? The
object which was pointed at was referentially highlighted
and the blinking object was saliently (and physically)
highlighted. So, looking at objects might have a different
meaning depending on whether a cue has an apparent
referential meaning or just a physical salience. The ques-
tion then is whether the social referential nature of
pointing (or gazing) carries more conceptual meaning and
that is why it keeps children’s attention longer than cues of
only physical salience. One plausible explanation is that
there are developmental stages that were not addressed in
Itakura’s study (no comparison of age differences was
made, the subjects had a mean age of 11 months).
To better understand the development of the gaze-
following ability and particularly the way in which gaze
cues might be taken to carry meaning extended over
time, it is important to know how infant gaze following
will change with age and from when they show the car-
ryover effect. We were thus motivated by the following
questions: Do 1-year-old and 2-year-old infants display
different reactions after following gaze or looking at a
physical salient event? If so, when and how does such a
difference emerge in human development? For instance,
reaction time of looking at the target after following the
cues and looking at the same target again after some
delay might be different between ages, especially in the
case of children, which may carry some conceptual
meaning to the event. Moreover, some communicative
actions such as spontaneous pointing or task-related
vocalization might occur as well. Previous research sug-
gests that infants of 1 year of age already have a motive
for sharing experiences with others as psychological
agents (e.g. Tomasello, Carpenter, Call, Behne & Moll,
2005). They also begin to produce declarative pointing
when they are about 1 year old (Tomasello & Camaioni,
1997). Such skills might be different in a social or
physical context.. Additionally, we are also interested in
age differences and whether there is any difference
between human infants and other primates, such as
chimpanzees. Since social signals might carry important
information, reactions to social signals might be different
from reactions to physical signals.
To that end, the current study modified the paradigm
of Itakura (2001) to test two groups of human infants
(1-year-olds, 2-year-olds) and adult chimpanzees. In his
study, two line-drawing stimuli were presented next to
each other on a computer screen, and the infants sat on
the lap of their mother to look at the stimuli from the
same direction. The mother pointed at one stimulus
while making a positive comment; ‘Look, it’s very cute’.
Pointing plus a positive comment from the mother might
have a strong influence on the infant about one target
stimulus and might affect the result in such a way that
children kept their attention fixed for longer on that
2 Sanae Okamoto-Barth et al.
Ó 2010 Blackwell Publishing Ltd.
3. stimulus (carryover effect) compared to the blink con-
dition. To control for this, we had an experimenter who
was the same for all children and chimpanzee subjects,
and did not make any verbal reference to the stimuli.
Additionally, the experimenter sat facing the subjects,
and the stimuli were placed in the view of both
subjects and the experimenter. In one condition, subjects
witnessed a human experimenter look at and point in the
direction of a target object. In the other condition, a
target object blinked by itself but the human experi-
menter did not do anything. Following a brief delay after
this first phase, we presented the same objects again. Our
goal is to shed light on both the ontogeny and phylogeny
of reactions after salient events that are highlighted by
social and physical cues.
Experiment 1: Human children
In Experiment 1 we first explored if the older children
perform like 1-year-old children (Itakura, 2001) in a
gaze-following task. To do so, we tested 1-year-olds, and
compared their results to a group of 2-year-olds. We
modified the methods and test settings from Itakura
(2001), increased age groups, number of trials, and
measuring where the child first looked rather than
looking duration and reaction time of their looking
behavior. Additionally, we also scored incidences of task-
related communicative actions (such as spontaneous
pointing, vocal reactions).
Methods
Participants
Twenty-four children participated in the experiment
(1-year-olds, N = 12 and 2-year-olds, N = 12; 1-year-olds:
mean age M = 14.6 months, range = 11–18, standard error
of the mean (SEM) = 0.75; 2-year-olds: M = 23.8 months,
range = 23–25; SEM = 0.21). There were an equal number
of males and females in each group. The children were
recruited by using standard Center for Child Studies’
recruiting procedures, and from the database of parents
who had previously signed up their children for partici-
pation in cognitive development studies at the Center for
Child Studies located at the University of Louisiana.
Apparatus and materials
Two identical lamps were used (22 cm · 22 cm · 30 cm).
The lamps were mounted on the edges of walls (244 cm ·
76.2 cm) in a testing room at the Center for Child Studies
(see Figure 1). Each lamp was operated by remote con-
trol. When the light fixtures were turned on, the lamps lit
up to reveal a picture. Twenty-four pairs of identical
images (21.5 cm · 27.9 cm) printed on transparency film
were used as stimuli (one for each lamp) and were
changed after each trial. The pictures were inserted in the
front-slit of the lamp. When the light was turned on, the
images became visible. Two standard office chairs (one
was rotatable) were used: one for experimenter 1 (E1),
and the rotatable chair for the child to sit with his or her
parent. Four cameras (two wide angle cameras and two
cameras focused on the subject, see Figure 1) were used
to record a picture of the experiment and were controlled
on a monitor in an adjacent room by the second exper-
imenter (E2). The timing of the experiment and light
fixtures were also controlled by E2.
Procedure
Warm-up period. Children visited the Center individu-
ally with their parents. Upon arrival, the child played
with the experimenters in the waiting room for approx-
imately 10–20 minutes to allow them to become familiar
with the experimenters and the environment. During this
time, the child’s parent read and signed a consent form
describing the study. The parent was also given instruc-
tions about their participation in the study. Once the
child appeared comfortable, he or she and their parent
were escorted to the testing room.
Testing. Each trial began with the parent and child in their
starting position: seated in the rotating chair, facing the
back wall of the room to not see the images on the lamps
and preparation of the next trial by E1. E1 was seated in
the other chair, facing toward the child and parent.
Testing consisted of three conditions: Control, Blink,
and Social. The order of conditions was counterbal-
anced. Each testing condition consisted of three
phases: (a) First presentation phase (Phase 1), (b) Inter-
presentation interval, and (c) Second presentation phase
Wide angle
Camera 1
Focal subject
CCD Camera 2
Focal subject
CCD Camera 1
Wide angle
Camera 2
M
sss
E1
Figure 1 Aerial view of the experimental setting. ‘E1’ =
experimenter 1, ‘S’ = subject, ‘M’ = mother.
Carryover effect of joint attention to repeated events 3
Ó 2010 Blackwell Publishing Ltd.
4. (Phase 2) (see Figure 2). Each testing condition had four
trials, totaling 12 testing trials per subject. Subjects
received a new pair of images on each trial. The 24 image
pairs were randomly administered across trials within
each subject.
Before each trial, E1 said ‘ready’, indicating to the
parent to turn around and face E1. During all trials,
except for trials in the Social condition, E1 faced for-
ward, stared straight ahead to a designated neutral point,
and avoided eye contact with the child, and kept her
hands on her lap (neutral position). Once the child and
parent were in the starting position, E2 began the fol-
lowing sequence per trial:
First presentation phase (phase 1): E2 remotely swit-
ched on both lamps, making the pictures visible for 7
seconds, and then switched off the lamps. E2 controlled
the duration by using a stopwatch.
Inter-presentation interval (interval): E2 kept the lamps
in off-mode for 7 seconds, so that they were not visible to
the subject.
Second presentation (carryover) phase (phase 2): E2
switched on both lamps again, making the images visible
to the subject, and then turned them off again after 7
seconds.
Once the lamps were turned off, E1 indicated to the
parent to turn around with the child to face the opposite
side of the room again. Once the parent and child had
returned to their starting positions (with their backs
turned to E1), E1 changed the images to prepare for the
next trial. This sequence was the basic flow of the testing
trials and was identical in the Control condition.
In the Social condition, the basic flow of trials was the
same except for phase 1; E1 pointed and looked (turned
her head) at one of the two lamps during phase 1 for 7
seconds. During the interval and phase 2, E1 maintained
her ‘neutral position’.
In the Blink condition, the basic flow of the trial was
the same except for phase 1. Once both lamps were
turned on, E2 caused one of the two lamps to blink (one
flash per second) during phase 1. The remaining phases
were the same as the control and social conditions.
Conditions, directions in which the experimenter poin-
ted, and the locations of the blinking lamp were coun-
terbalanced within subjects. For coding purposes, we
specified the stimulus for each condition (see Figure 2).
The stimulus (picture-image on the lamp) which was
pointed at by the experimenter during phase 1 is referred
to as ‘blink-target’, and the same stimulus (which is no
longer being pointed to) is referred to as ‘pointed-target’
for phase 2. The stimulus which blinked during phase 1 is
‘blink-target’, and the same stimulus (which is no longer
blinking) is ‘blinked-target’ for phase 2.
Coding
We analyzed the children’s behavior based on which lamp
they looked at first. These measurements were coded in
phase 1, interval and phase 2. For coding, video materials
from the two focal subject cameras were used (see Fig-
ure 1). The cameras were located at each lamp. That is, if
the children looked at the lamp the coder could see the
children’s face in frontal view (on the video screen from
camera 1). This was judged to be that the child was
looking at the lamp (which is located just above camera 1)
and was coded as ‘looking-left’ or ‘looking-right’ from
the coder’s (and E1’s) perspective. If the child did not
look at the camera during the whole trial period (e.g. the
child looked at the ceiling, looked at the experimenter, or
Standard
(for the experiment 2)
No picture and but lamps turn on (21 sec.)
Phase 1
First presentation phase (7 sec.)
(Picture and both lamps turn on)
Phase 2
Second presentation phase (7 sec.)
(Picture and both lamps turn on)
Inter-Presentation
Interval (7 sec.)
(Both lamps turn off)
Blink
Control
Social
Blink-Target
Point-Target
Blinked-Target
Pointed-Target
Figure 2 The flow of the experiment.
4 Sanae Okamoto-Barth et al.
Ó 2010 Blackwell Publishing Ltd.
5. looked behind them), then this trial was coded as
‘no looking’. Additionally, in cases where the subjects
showed some spontaneous communicative actions such
as spontaneous pointing or task-related vocal reactions,
the incidences and their direction were also scored. The
main observer (SB) classified the children’s behaviors,
according to the categories described above, from the
video recordings. To assess inter-observer reliability, an
additional coder (CC) watched 25% of all trials and
rated the children’s behavior after training in coding.
The inter-observer reliability was calculated by means
of Cohen’s kappa. The agreements and kappa results
between the observers were 94.8%, j = .91.
After coding, we defined as ‘carryover’ the behavioral
sequence in which the child looked during phase 2 at the
target stimuli in phase 1 after having looked at the target
stimuli during phase 1 (child looked at the targets in both
phases). Moreover, we coded the duration (reaction time)
from the first cue onset (moment at which the experi-
menter started to point or the lamp started to blink) to
initiation of the child’s head turn in phase 1. In phase 2,
the duration from the second cue onset (moment at
which both lamps turned on at the beginning of phase 2)
to initiation of the child’s head turn (moment at which
the child’s head started to turn again) was measured. All
durations (phase 1 and 2) were calculated for each cue
onset and initiation of head turn. The main observer
(SB) used the time display of the video equipment (frame
by frame analysis) to assess duration. To assess inter-
observer reliability, an additional coder (HR) watched
25% of all video recordings (as above) and rated the
children’s behavior after training in coding. The inter-
observer reliability was calculated by means of Cohen’s
kappa. The agreements and kappa results between the
observers were 88.6%, j = .84.
Results
First-look behavior
To clarify the overall picture of comparison of looking
behavior between 1- and 2- year-olds, Figure 3 shows the
1-year-olds 2-year-olds
Carryover effect;
Social: 63.8%
Blink: 51.4%
Carryover effect;
Social: 69.6%
Blink: 61.8%
n.s. n.s.
n.s.
*
*
*
*
***
n.s. n.s. n.s.n.s.* *
CONTROL TOTAL
0
20
40
60
80
100%
SOCIAL TOTAL
BLINK TOTAL
CONTROL TOTAL
SOCIAL TOTAL
BLINK TOTAL
0
20
40
60
80
100%
0
20
40
60
80
100%
0
20
40
60
80
100%
0
20
40
60
80
100%
0
20
40
60
80
100%
n.s. n.s.
*
Phase 1
Phase 2 Phase 1 Phase 2
n.s. n.s.
1ST-R 1ST-L 2ND-R 2ND-L
1ST-P 1ST-NP 2ND-P 2ND-NP
1ST-B 1ST-NB 2ND-B 2ND-NB
1ST-P 1ST-NP 2ND-P 2ND-NP
1ST-B 1ST-NB 2ND-B 2ND-NB
1ST-R 1ST-L 2ND-R 2ND-L
**
*
Figure 3 Average ‘looking’ responses during phases 1 and 2 for 1- and 2-year-olds. ‘1ST-R’ = right side lamp and ‘1ST-L’ = left side
lamp during phase 1. ‘1ST-P’ = point-target stimulus for the social condition (pointing and looking by the experimenter) and ‘1ST-NP’
= non-target stimulus (the stimulus which was not pointed to or looked at by the experimenter) during phase 1. ‘1ST-B’ = blink-target
stimulus and ‘1ST-NB’ = non-target stimulus (the stimulus which did not blink) for the blink condition during phase 1. The same
abbreviations are used for phase 2 (‘2ND-’). Asterisk (*) marks indicate p <. 05.
Carryover effect of joint attention to repeated events 5
Ó 2010 Blackwell Publishing Ltd.
6. percentage of looking trials for the control, social and
blink conditions for both phase 1 and 2 for both age
groups.
A Wilcoxon signed ranks test (two-tailed) was con-
ducted with first-look and direction of looking. In the
control condition, the first-look for both left and right
stimuli was almost the same in both phase 1 and 2 for
both age groups. No significant differences in first-looks
were found between right and left in both phases (1-year-
olds: phase 1, T(11) = ).51, p = .61; phase 2, T(11) =
).94, p = .35, 2-year-olds: phase 1, T(11) = ).43, p = .67;
phase 2, T(11) = ).32, p = .75). This result shows that
children did not have a bias responding to one particular
direction. In the social condition, there was a significant
difference between children’s first-look towards the
point⁄pointed-targets and the non-targets in both phases.
This was true for both age groups (1-year-olds: phase 1,
T(11) = )3.21, p = .001; phase 2, T(11) = )2.65, p = .008,
2-year-olds: phase 1, T(11) = )3.32, p = .001; phase 2,
T(11) = )2.75, p = .006). The fact that children fre-
quently looked towards the targets shows that children’s
looking was affected strongly by the experimenter’s ac-
tions. Moreover, this behavioral pattern was carried into
phase 2 (‘carryover effect’) in both age groups.
However, a different pattern emerged in the blink
condition. As in the social condition, both age groups
showed a similar behavioral pattern in phase 1. Inter-
estingly, this pattern disappeared in the 1-year-old group
but remained in the 2-year-old group (1-year-olds:
phase 1, T(11) = )2.60, p = .009; phase 2, T(11) = ).12,
p = .90, 2-year-olds: phase 1, T(11) = )2.23, p < .05;
phase 2, T(11) = )2.11, p < .05). That is, 1-year-olds did
not show a ‘carryover’ effect in the blink condition;
2-year-olds did.
Furthermore, we compared looking behavior between
the social and blink conditions. In phase 1, even though
the 1-year-olds looked at the targets in the social con-
dition frequently, there was no statistical difference
between conditions among 1-year-olds (T(11) = )1.87,
p = .062), whereas 2-year-olds showed a more robust
behavioral response in the social condition than in the
blink condition (T(11) = )2.28, p = .023). In phase 2, a
comparison of children’s behavior in both conditions
resulted in an age group difference (1-year-olds: T(11) =
)2.33, p < .05, 2-year-olds: T(11) = )1.52, p = .13), such
that in phase 2, 1-year-olds looked more frequently to
the pointed-target than to the blinked-target. In contrast,
2-year-olds showed a similar response pattern in both
conditions: their looking preference towards both pre-
viously highlighted (pointed⁄blinking) stimuli were kept
in phase 2.
Carryover effect
We compared the correlation between first-looks in phase
1 and phase 2 to estimate if looking behavior in phase 1
was carried over to phase 2, and what kind of stimuli
influenced the behavior. One-year-olds showed a carry-
over effect in the social condition but not in the blink
condition (Spearman’s rank correlation (one-tailed);
social condition: 63.8%, rho = .548, N = 12, p < .05, blink
condition: 51.4%, rho = .456, N = 12, p = .068). Although
looking behavior towards the blinked-target and the non-
target was not different in phase 2 as we described above,
it relatively frequently showed a ‘carryover’ pattern
(51.4%). However, we did not find any statistical support.
On the contrary, 2-year-olds showed the carryover effect
in both the social and the blink conditions (social
condition: 69.6%, rho = .540, N = 12, p < .05, blink
condition: 61.8%, rho = .525, N = 12, p < .05).
Response time
Since the two age groups showed different behavioral
patterns, we analyzed response time during ‘correct’
responses in which they looked at the target stimulus in
each phase (1 and 2, Figure 4). A paired sample t-test was
conducted with the duration of each presentation for both
social and blink conditions and age groups. There was a
significant difference for 1- and 2-year-olds only in the
social condition in phase 2 (paired sample t-test: t(11) =
)2.34, p < .05). Comparison between phase 1 and phase 2
in the social condition of 2-year-olds showed a marginally
significant difference (t(11) = )1.96, p = .075). Even
though there was no significant difference in statistics, as a
general trend 1-year-olds responded faster in phase 2 in
the social condition compared to the blink condition in
which they responded more slowly in phase 2. In contrast,
the graph line was reversed in phase 2 in the social con-
dition for both age groups. Two-year-olds showed slow
responses in phase 2 in the social condition.
Spontaneous communicative actions by children
We also scored the incidences of spontaneous pointing
by children. Table 1 shows for both age groups the per-
centage of spontaneous pointing in the control, social
and blink conditions in phases 1 and 2.
0
0.5
1
1.5
2
2.5(ms) 1-year-olds
2-year-olds
1ST-B 2ND-B 1ST-P 2ND-P
*
+
Figure 4 Average response time during correct response trials
(subjects showed ‘looking’). ‘*’ mark indicates p <. 05. ‘+’
mark indicates p < .10.
6 Sanae Okamoto-Barth et al.
Ó 2010 Blackwell Publishing Ltd.
7. In general, spontaneous pointing was most frequently
observed in the social condition in both age groups.
A Wilcoxon signed ranks test was conducted with the
spontaneous pointing reaction and its direction. In the
control condition, the pointing reaction observed for
both left and right stimuli was not different between
phase 1 and phase 2 for either age group (1-year-olds:
phase 1, T(11) = )1.0, p = .32; phase 2, T(11) = )1.86,
p = .06, 2-year-olds: phase 1, T(11) = ).63, p = .53;
phase 2, T(11) = )1.34, p = .18). In the social condition,
spontaneous pointing was more frequently observed than
in the control and blink conditions. Among the 2-year-
olds group, there was also a significant difference
between children’s spontaneous pointing towards the
point⁄pointed-targets and the non-targets in both phases
(1-year-olds: phase 1, T(11) = )1.41, p = .16; phase 2,
T(11) = )1.13, p = .26; 2-year-olds: phase 1, T(11) =
)2.57, p < .05; phase 2, T(11) = )2.07, p < .05). How-
ever, in the blink condition, neither age group showed
differential pointing reactions towards the blink⁄blinked
targets and the non-targets in either presentation phase
(1-year-olds: phase 1, T(11) = )1.00, p = .32; phase 2,
T(11) = ).58, p = .56, 2-year-olds: phase 1, T(11) =
).58, p = .56; phase 2, t(11) = )1.00, p = .32). Most
importantly, both age groups spontaneously pointed
more frequently towards the point-targets than the blink-
targets in phase 1 (1-year-olds: T(11) = )2.12, p < .05,
2-year-olds: T(11) = )2.72, p < .05). This could also be
explained by imitation (e.g. Horner & Whiten, 2005)
since they had a pointing model in the social condition
but not in the blink condition. Moreover, 2-year-olds
(and 1-year-olds with marginal significance) spontane-
ously pointed more frequently towards the point-targets
in phase 1 than towards the pointed-targets in phase
2 (1-year-olds: T(11) = -.29, p = .56, 2-year-olds: T(11)
= )2.06, p < .05). These results suggest that the spon-
taneous pointing was triggered by seeing the experi-
menter’s pointing action. Spontaneous pointing was also
frequently accompanied with looking at the experimenter
and the lamps alternately.
Furthermore, although they were not quantitatively
measured we also observed children’s vocal reactions.
This was observed more in the 2-year-olds and in the
social condition in phase 1, and is consistent with the
other results. Given that 2-year-olds were more linguis-
tically and verbally mature than 1-year-olds, this finding
is, perhaps, not surprising. The common type of ver-
balization was naming the stimulus (e.g. ‘it’s a dog!’).
During phase 2, some children also pointed to the pre-
viously pointed stimulus and said ‘that side!’ to the
experimenter (note that the experimenter was not doing
anything in phase 2). Vocal reactions were also often
accompanied by spontaneous pointing and watching the
experimenter and the lamps alternately.
Discussion
Both 1-year-old and 2-year-old children looked to the
stimulus the experimenter pointed to or to the stimulus
that blinked in phase 1. Looking continued in phase 2 of
the social condition (pointing) for both age groups. And
whereas 2-year-olds continued to look in phase 2 of the
blinking condition, 1-year-olds did not. The performance
of 1-year-olds supports the finding from Itakura (2001)
in which younger children (only around 1-year-old (9–13
months) children were tested in Itakura’s study) looked
longer at the stimuli pointed to by their mother but not
to the stimuli that blinked. Our finding on 1-year-olds
also showed the carryover effect which represents an
effect only in the social condition for the 1-year-olds as
Itakura (2001) suggested. This supports their findings as
the experimenter was not the mother and the stimuli
were presented further apart from each other. On the
other hand, for the 2-year-olds the carryover effect was
consistent for both the social and blink conditions. The
carryover effect in the blink condition could be explained
as a change in interpretation of the stimuli shown by the
2-year-olds. For instance, 2-year-olds might have inter-
preted the blinking as a referential⁄symbolic event such
as a ‘red light’ means stop and ‘blinking’ means caution.
There might also be the effect that they attribute the
lights’ blinking to be the existence of animate agency
because the lamps don’t turn on by themselves. The
response time of both age groups also suggests that the
difference between the two age groups is conceptual and
not only quantitative. In general, the 2-year-olds reacted
more slowly than the 1-year-olds except in phase 1 of the
social condition. For the blink condition, the response
was ‘automatically’ driven by a physical property since
they saw that the lamp itself was blinking. But for the
social condition, 1-year-olds became slower and their
reaction time was almost the same as the reaction time of
2-year-olds.. One possible explanation is that it takes
more time for 1-year-olds than for 2-year-olds to make a
spatial link between the pointing and the lamp. The
slower response from the 2-year-olds also confirms our
suggestion that 2-year-olds might be reasoning in terms
of symbolic interpretation of their environment or the
Table 1 Percentage of spontaneous pointing in the control, social and blink conditions in phases 1 and 2 for 1- and 2-year-olds.
The abbreviations are the same as in Figure 3
Control Social Blink
1ST-R 1ST-L 3RD-R 3RD-L 1ST-P 1ST-NP 3RD-P 3RD-NP 1ST-B 1ST-NB 3RD-B 3RD-NB
1-year-olds 12.5 (%) 6.3 12.5 0.0 12.5 4.2 14.6 8.3 0.0 4.2 8.3 6.3
2-year-olds 8.3 12.5 0.0 6.3 33.3 6.3 16.7 2.1 4.2 2.1 6.3 12.5
Carryover effect of joint attention to repeated events 7
Ó 2010 Blackwell Publishing Ltd.
8. attribution and existence of animate agency that might
have driven their interest here. Moreover, 2-year-olds
might interpret both the social and the blink conditions
as goal-directed events (see Subiaul, Lurie, Romansky,
Klein, Holmes & Terrace, 2007). If they interpret the
blink condition using symbolic rules, animate agency (in
this case by either the experimenter or their mother) or
goal-directed action, it may explain why the 2-year-olds
processed the blink condition in a similar way to the
social condition. It is plausible that because of their
social reasoning the 2-year-olds showed a carryover ef-
fect in both the social and the blink conditions.
Experiment 2: Chimpanzees
In the second experiment we assessed whether chim-
panzees respond in the various gaze-following conditions
in a fashion that is analogous to that reported for the
human children above. From previous studies (e.g.
Povinelli & Eddy, 1996) we assumed that chimpanzees
would look at the stimulus which was pointed to by E1
or was blinking in phase 1. However, we assumed that
they would behave differently in phase 2.
Methods
Subjects
Seven adult chimpanzees ranging in age from 16.4 to
17.3 years served as subjects. The animals have partici-
pated in numerous studies involving the interpretation of
social cues (such as the direction of eyes, head, body, and
pointing), among others (e.g. Povinelli & Eddy, 1996;
Barth, Reaux & Povinelli, 2005; see Povinelli, 2000, for a
detailed history of each subject).
Apparatus and materials
The same experimental setting (two identical lamps
placed on walls, pairs of picture images) as in Experi-
ment 1 were introduced in a testing room at the Cogni-
tive Evolution Group at the New Iberia Research Center,
New Iberia (see Figure 1). One wooden bench (30 cm ·
43 cm · 32 cm) was used, upon which Experimenter 1
(E1) sat. There was a transparent Lexan partition be-
tween the subject and E1. A stool (30.5 cm · 30.5 cm ·
19.5) in front of E1 was used for the subjects to sit on.
There was a small hole in front of the subject’s stool.
They could reach through this opening to retrieve a food
reward. This hole was covered by a transparent barrier
during the trial. Four cameras (two wide angle cameras
and two focal subject cameras) were used to record the
experiment and were shown on a monitor behind the
wall. The light fixtures were controlled by a second
experimenter (E2) who stayed behind the wall while
watching the experiment on a concealed monitor. A third
experimenter (E3) controlled the cameras remotely from
a separate room outside the testing room. E3 also
monitored the time and communicated the timing of the
trial sequence to E2 via earphone.
Training. Prior to testing, each subject participated in an
undetermined number of four-trial sessions. Subjects
were trained to sit on the stool and stay in front of the
experimenter for 20 seconds before they received a food
reward. This training was necessary for keeping the
subjects in the middle of the experimental setting during
the experiment. During the training, the apparatus was
configured according to Figure 1, except that images
were not presented. We defined sitting on the stool and
facing the experimenter as the required posture to start
participation in the experiment.
Once the subject had entered the test unit at the
beginning of each trial, the subject had 1 minute to sit on
the stool facing E1. E1 kept a neutral posture. As soon as
the subject sat on the stool, E2 turned on both lamps
simultaneously and started to measure the time with a
stopwatch (no images were presented in the lamps). After
20 seconds, E2 turned off the lamps. E2 lowered the
barrier to uncover the hole so E1 could give a food
reward to the subject. The trial ended when the subject
received the food reward or the subjects failed to sit on
the stool before the 20 seconds ended. If the subject did
not remain seated on the stool for 20 seconds, they did
not receive a food reward, and the trial ended. However,
both lamps were kept on until the subject left the test
unit. If the subject did not respond within the time limit
(1 minute), the trial was re-run immediately. Each session
had four identical trials. The subjects were required to
remain seated on the stool during all four trials within a
session to reach criterion. To advance to Testing, subjects
were required to perform correctly for at least one session
as a final criterion.
Testing. Testing consisted of eight four-trial sessions; one
standard trial and three testing trials with three different
conditions identical to Experiment 1 with children:
control, blink, and social conditions. Each condition
contained phase 1, interval, and phase 2 for presenting
the stimulus equivalent with Experiment 1 (see Figure 2).
Each testing condition had eight trials in total. There
were 3 conditions · 8 trials, 24 testing trials in total (plus
eight standard trials). The first trial in a session was
always a standard trial. Standard trials were adminis-
tered in the same fashion as the training trials. Only
when the subjects performed properly (remained on the
stool for 20 seconds) did they proceed to the testing
trials. If subjects failed to remain seated for 20 seconds,
the standard trial was re-run immediately. If subjects
failed again, the session did not continue for that day.
The basic testing procedure was the same as for the
training sessions. The following three trials included
three different condition trials. Conditions were not
repeated within sessions. All conditions and the location
(left or right) where the experimenter pointed to or the
8 Sanae Okamoto-Barth et al.
Ó 2010 Blackwell Publishing Ltd.
9. location of the blinking lamp were counterbalanced in a
session and across eight sessions.
Procedure
The basic procedure was the same as for Experiment 1.
All three conditions consisted of pairs of two identical
picture stimuli (see Figure 1) in each lamp on opposite
sides of the wall. No pair of pictures was repeated. One
experimenter (E1) sat on the wooden bench. E1 faced
forward, looking straight ahead to a designated point
on the Lexan glass without making eye contact with the
subjects while his hands were on his lap (neutral posi-
tion). The second experimenter (E2) was positioned at
the back of the test unit, behind the wall of the exper-
imental setting, to control the response barrier and the
shuttle door. Once the subject sat on the stool facing
towards E1, E2 turned on both lamps and E3 imme-
diately started to measure the time with a stopwatch for
phase 1. Once the lamps had been turned off after
phase 2, E1 gave a food reward to the subject irre-
spective of the response and the trial ended. All timings
for the lamp controls were passed on to E2 by E3 via
the earphone.
Coding
We analyzed the subjects’ behavior based on which lamp
they looked at first, based on same coding procedure as
in Experiment 1. The main observer (CP) classified the
subjects’ behavior, according to the categories described
above, from the video recordings. To assess inter-
observer reliability, an additional coder (SB) watched
50% of all video recordings and rated the subjects’
behavior after training in coding. The inter-observer
reliability was calculated by means of Cohen’s kappa.
The agreement and kappa results between the observers
were 92.5%, j = .86.
Results
First-look behavior
Figure 5 shows the percentage of first-looks in the con-
trol, social and blink conditions during phases 1 and 2.
A Wilcoxon signed ranks test (two-tailed) was con-
ducted with first-look and direction of looking. In the
control condition, the first-look for both left and right
stimuli was almost the same in phases 1 and 2. There was
no significant difference in their first-looks between right
and left in either presentation (phase 1, T(6) = ).95, p =
.34; phase 2, T(6) = ).67, p = .50). This result demon-
strates that the subjects did not have a bias to look in one
particular direction. In the social condition, there was a
significant difference between the subjects’ first-look
towards the point⁄pointed-targets and non-targets for
the both phases (phase 1, T(6) = )2.46, p = .014; phase 2,
T(6) = )2.21, p < .05). Frequent looking towards the
point-target in phase 1 shows that where subjects looked
was affected strongly by the experimenter’s pointing.
Moreover, this behavioral pattern was carried into phase
2 (‘carryover effect’). In the blink condition, the subjects
showed a similar behavioral pattern to the social condi-
tion in phase 1. However, this pattern was absent in
phase 2 (phase 1, T(6) = )2.38, p = .02; phase 2, T(6) =
)1.27, p = .21).
Furthermore, we compared subjects’ looking behavior
between the social and blink conditions. In phase 1, there
was no difference between conditions (T(6) = )1.62,
p = .11). However, a comparison of the subjects’
behavior in phase 2 showed a difference between the
blinking stimulus and the pointed stimulus in phase 1
(T(6) = )2.21, p < .05). During phase 2, subjects’
reaction to the pointed-targets was more robust than
their reaction to the blinked-targets. These differences in
subjects’ behavioral responses were absent for the non-
targets for both conditions (T(6) = )1.73, p = .084).
Carryover effect
We compared the correlation between first-looks in
phase 1 and phase 2 to estimate if the looking behavior in
Chimpanzees
Carryover effect;
Social: 57.7%
Blink: 34.9%
*
*
*
*
n.s.
n.s.
n.s.
CONTROL TOTAL
SOCIAL TOTAL
1ST-P 1ST-NP 2ND-P 2ND-NP
BLINK TOTAL
Phase 1
0
20
40
60
80
100%
0
20
40
60
80
100%
0
20
40
60
80
100%
n.s.
n.s.
Phase 2
*
*
n.s.
1ST-B 1ST-NB 2ND-B 2ND-NB
1ST-R 1ST-L 2ND-R 2ND-L
Phase 1
n.s.
n.s.
Phase 2
Figure 5 Average ‘looking’ responses during phases 1 and 2
for chimpanzees group. ‘*’ mark indicates p <. 05.
Carryover effect of joint attention to repeated events 9
Ó 2010 Blackwell Publishing Ltd.
10. phase 1 was carried over to the next presentation, and
what kind of stimuli influenced the subjects’ behavior.
Although chimpanzees did not show the carryover effect
significantly in either the social or the blink conditions,
the social condition had a stronger effect than the blink
condition (Social condition: 57.7%, Spearman’s rank
correlation (one-tailed); rho = .663, N = 7, p = .052,
Blink condition: 34.9%, rho = .233, N = 7, p = .308).
Discussion
Like the children, the chimpanzees showed looking
responses to the stimulus that blinked or that the
experimenter pointed at in phase 1. The looking response
continued into phase 2 in the social condition but not in
the blink condition. That is, chimpanzees failed to look
at the blinked-targets during phase 2. This result
resembles the response pattern demonstrated above for
1-year-olds. Specifically, chimpanzees, like 1-year-olds,
evidenced a marginal carryover effect (from phase 1 to
phase 2) only in the social condition. However, unlike
human children, we did not observe any spontaneous
communicative actions such as spontaneous pointing or
vocalizations towards the lamps and the experimenter.
General discussion
Using a gaze-following paradigm with a subsequent
event to measure the subjects’ response after their
experience of the environment and social interaction,
we investigated children’s behavior across different age
groups and differences in behavior between children
and chimpanzees. Human children of 1 and 2 years
and chimpanzees showed looking responses to the
location that blinked or to the location pointed to by
the experimenter during phase 1. All subject groups
continued to look to the target location in the social
condition. And while 2-year-olds continued to look in
the blink condition, 1-year-olds and chimpanzees did
not. Moreover, carryover effect analysis showed that
only 2-year-olds continued to look at the target stimuli
during phase 2 in both the social and blink conditions.
One-year-olds and chimpanzees showed this effect only
in the social condition. The response time of both age
groups also suggests that the difference between the
two age groups is conceptual and not only quantita-
tive. In general, the 2-year-olds reacted more slowly
than the 1-year-olds except in phase 1 of the social
condition.
Moreover, there are also qualitative differences in their
spontaneous action between the groups. First, human
infants (both 1-year-olds and 2-year-olds) showed some
spontaneous communicative signs including spontaneous
pointing and vocalizations directed to the lamps and the
experimenter. While 2-year-olds pointed or vocalized
more than 1-year-olds, chimpanzees made no attempt to
communicate with the experimenter either vocally or
non-vocally (e.g. banging on the glass, reaching for the
target or displaying).
Although we found several qualitative differences
in such communicative actions of children and chim-
panzees, we also found similarities. Various studies
with infant chimpanzees (e.g. Matsuzawa, Tomonaga
& Tanaka, 2006; Myowa-Yamakoshi, Tomonaga &
Matsuzawa, 2003; Okamoto, Tomonaga, Ishii, Kawai,
Tanaka & Matsuzawa, 2002) have shown that chimpan-
zees’ early social cognitive development resembles that of
humans; and, in fact, may be homologous. However,
comparative studies involving human infants and adult
chimpanzees may obfuscate potential homologies in
social cognition development. The present study found
similarities between human infants and chimpanzees in
some measures such as where subjects looked first as well
as species differences in the behavioral reactions towards
the lamps and the experimenter. For example, both
species followed the experimenter’s gaze and looked at
the stimulus that the experimenter pointed to. Younger
children and chimpanzees showed a similar carryover
effect pattern in the social condition. However, joint
attention episodes in our daily lives contain a more
temporal and dynamic dimension as ongoing interaction.
Younger children start to show their attempts to continue
the interaction by pointing or spontaneous vocalization.
On the other hand, we did not observe such reactions
from the chimpanzees at all. Thus, although social cues
held the subjects’ (children’s and chimpanzees’) attention
longer (the carryover effect) and appeared in a similar
way on a surface level, there are significant qualitative
differences. Our findings also suggest that important
facets of joint attention episodes are not only the looking
response or looking duration but also whether they treat
the social event as an ongoing interaction with others.
Some previous studies also reported differences in the
early development of infant chimpanzees. Okamoto,
Tanaka and Tomonaga (2004; see also Tomonaga,
Tanaka, Matsuzawa, Myowa-Yamakoshi, Kosugi,
Mizuno, Okamoto, Yamaguchi & Bard, 2004) reported
that after an infant chimpanzee followed the experi-
menter’s gaze and pointed towards attractive stimuli, he
did not try to look at the experimenter and the stimuli
alternatively, sharing attention. However, even if human
children had some prematurity in their early stage of
social cognition which looks homologous to that of
chimpanzees, they already showed a germination of the
fully-fledged social cognitive skill such as producing
communicative actions, and show differences in the later
stage of their development.
Among children, spontaneous pointing was most
common in the social condition. Children typically
pointed to the lamp that E had pointed to. Children
typically intermixed pointing to the lamps and looking
back at the experimenter in an alternating fashion; joint
attention in a triad relationship (attempt to share atten-
tion). Two-years-olds, in particular, pointed more during
phase 1. Children’s spontaneous pointing might be
10 Sanae Okamoto-Barth et al.
Ó 2010 Blackwell Publishing Ltd.
11. triggered by seeing the experimenter’s pointing as a
communicative signal. Previous studies that have exten-
sively investigated children’s pointing production report
that infants’ declarative pointing emerges at around 1
year of age with regard to its underlying socio-cognitive
understanding and motive to share experiences with
others (e.g. Liszkowski, Carpenter & Tomasello, 2007).
Our observation of spontaneous pointing from both
1- and 2-year-olds supports these results. However, the
pointing reactions in our study might also represent a
familiar motor imitation response where children, failing
to understand why the experimenter has pointed to a
given lamp, copy the model’s actions automatically.
Certainly, there is evidence suggesting that human chil-
dren are hyper-imitative at different stages in develop-
ment and in different contexts, particularly when they
don’t know what is going on in their environment (e.g.
Horner & Whiten, 2005). Conversely, children might
have pointed intentionally as a means of initiating a joint
referencing event. In any case, our result suggests that
seeing the experimenter’s pointing action triggered the
spontaneous pointing reactions by children. Since our
study did not intend to investigate directly eliciting
pointing actions, future research should include control
conditions such as the experimenter changing emotional
expression towards the stimuli or making eye-contact at
the beginning of a trial.
The social condition also triggered vocal reactions
from the children. Their vocalizations were often
accompanied with pointing at the lamps and looking at
the experimenter alternately. This observation clearly
supports the idea that the children (especially older
children) took the social condition joint attention epi-
sodes as an ongoing social event. As such, they tried to
respond to the experimenter by pointing to the same
object or saying something as part of a natural com-
municative interaction. This might answer our earlier
question about why social cues keep younger children’s
attention longer (carryover effect) than a salient object
does. Additionally, when the children pointed after⁄with
following the experimenter’s cues, their pointing often
alternated in direction. For instance, they pointed to the
stimulus pointed at by the experimenter, and then poin-
ted to the other stimulus and checked back with the
experimenter, and then again pointed to the stimulus that
had been pointed to. These sequential actions imply
children’s attempt to understand the communicative
intent of the model and resolve conflicting interpreta-
tions of the communicative event.
We also found that older infants keep their attention
longer even in the physically salient blinking condition,
unlike younger infants and chimpanzees (and also
11-months-olds in Itakura’s study). For older infants,
both social referentially highlighted objects and physical
saliently highlighted objects had an equivalent (or simi-
lar) impact on their understanding of the environment.
Although less frequent, older infants did show commu-
nicative actions towards the lamps and the experimenter,
especially in phase 2 in which the lamp was not blinking.
Why did they produce such actions even though there
was no pointing model in the blink condition? We
assume that it was because there were other people
present in the setting, as we have a tendency to reason
about our environment especially when we see some
unusual event happening (e.g. Subiaul et al., 2007). If
someone is present we like to share the event and try to
seek information from others. Maybe if there had been
no one in the test setting, they might not have produced
any communicative actions. Thus, their communicative
actions were produced in an attempt to understand their
environment and consider others as an information
source (and also as psychological agents) when sharing
the same event (or they might request sharing the event).
So there might be two tightly linked phases for such joint
‘conceptual’ attention. The first one is the phase of
automatic⁄reflexive gaze following (or attraction to sal-
ience) and the next one is the phase of comprehension
(understanding the contextual and conceptual meaning
of the environment). We very often consider ‘fully-
fledged’ joint attention as a triadic relationship with
child, adults and objects or an event (e.g. Tomasello,
1999). Do we do this just because we feel satisfaction in
following gaze and at the same time realizing that the
other individual is a psychological agent and is also
looking at the same thing? We might also, as a process of
social referencing, try to check whether the event itself
and emotional perception about it is equivalent or sim-
ilar to others’ experience. So motivation is not only
sharing attention with others but also sharing conceptual
and contextual aspects of the environment (such as
positive or negative events). Older subjects ‘actively’
interact with others and send a communicative signal
such as spontaneous pointing or vocalization, even
though the experimenter and their mothers are not
interactive (they quietly sat there with the infants and
were not looking at the blinking lamps). Thus, children
are no longer only receivers of communicative signals
from others; rather, they start to become senders of
communicative signal to others, and they become initi-
ators of communication.
In sum, our study demonstrated differences between
chimpanzees and 2-year-olds, and between 1- and 2-
year-old children during ongoing joint attention epi-
sodes. In particular, 1-year-olds’ and chimpanzees’
looking data showed some similarity on the surface but,
upon closer inspection such as children’s spontaneous
communicative actions, there are significant differences
as well. In the future, we should conduct more detailed
comparative examinations of the development of joint
attention behaviors as well as their underlying mecha-
nisms. In addition, such studies should be designed to
investigate the development of spontaneous communi-
cative actions. Future research will provide a clearer idea
of visual communication including joint attention and
the understanding of social-cognitive abilities in pri-
mates.
Carryover effect of joint attention to repeated events 11
Ó 2010 Blackwell Publishing Ltd.
12. Acknowledgements
The experiments with children and chimpanzees were
conducted at the University of Louisiana at the Center for
Child Studies and the Cognitive Evolution Group,
respectively. The research was supported by a James S.
McDonnell Foundation Centennial Award, and James S.
McDonnell Foundation award 21002093, to DJP. We
thank Conni Castille for assistance with recruitment and
testing of children as well as all the parents and children
who participated in the study. We thank Anthony
Rideaux, Leo Loston, Tobyn LaVergne and James Reaux
for assistance with the training and testing of the chim-
panzees. We would also like to thank three anonymous
reviewers for helpful comments on the manuscript. All
studies were reviewed and approved by the Institutional
Review Board and the Institutional Animal Care and Use
Committee of the University of Louisiana, Lafayette.
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Received: 25 November 2009
Accepted: 19 May 2010
Carryover effect of joint attention to repeated events 13
Ó 2010 Blackwell Publishing Ltd.