Stereotypes and associated emotions drive discriminatory behavior across numerous consequential contexts. These biases against marginalized social groups have important implications for real-world social decisions, including hiring, voting, health, and housing decisions. Psychologists have traditionally studied how people evaluate different ethnic and cultural groups (and their members) in isolation, but in the real world people commonly make judgments and decisions over sets of people. For example, hiring decisions involve the assessment of multiple candidates at once. Across a series of experiments, we harness insights from computational models of decision-making to examine whether choice set construction---or choice architecture---can be used to influence decision-makers' preferences in consequential social decisions. I will review several findings including a combination of field data and lab experiments to examine the effect of alternatives, or decoys, on social evaluations and decisions in hiring and election contexts.
After 20 years of studying the relation between language and the mental representation of numbers, I’ve come to the conclusion that three things are true. (1) Numbers are unrelated to language; (2) Numbers are related to language in general; and (3) Numbers are related to particular languages. These sound like contradictory statements, but I will explain during my talk how all of them can be true, depending on what one means by ‘language’ and what one means by ‘number.’
Pain and emotional distress are realities that affect us all. Preventing, resolving, and sometimes accepting pain and distress motivates many human endeavors, ranging from spiritual practices to medical interventions. Understanding the brain basis of pain and emotion could transform how we understand these fundamental facets of human life, but currently, there are no human brain measures adequate for determining whether one is angry or sad, whether pain is physical or emotional, or whether one is feeling pain that is intense or mild. In this talk, I describe a series of studies aimed at beginning to address these questions. Combining functional neuroimaging with machine learning techniques, we have developed brain markers capable of indicating the intensity of pain and negative emotion in individual participants with > 90% accuracy, with no prior knowledge of an individual's experience. In addition to their use as markers, such maps can provide insight into the structure of the neurophysiological representations underlying pain and distress. Our findings to date suggest that specific types of aversive experiences are encoded in separate, population-based patterns that are co-localized in similar gross anatomical circuits. These studies are part of a transformational shift in how neuroimaging data is being used, from early 'blob-based' brain-mapping studies to the development of predictive maps with tangible translational potential. They show that as the field progresses, we may be able to map specific types of subjective experience to specific brain circuits. This endeavor enables cross-species mapping of mechanisms, translational work on treatment development, and new ways of understanding and relieving human suffering.
Everyday behaviors require a high degree of flexibility, in which prior experience is applied to inform behavior in new situations. Such flexibility is thought to be supported by memory integration, a process whereby related experiences become interconnected in the brain through recruitment of overlapping neuronal populations. In this talk, I will discuss our work demonstrating that memory integration relies on hippocampal–prefrontal circuitry and allows for acquisition of new knowledge beyond what we directly experience. I will show how such knowledge is flexibly deployed to promote new learning and higher-level cognitive functions such as reasoning and concept formation. I will also discuss developmental data exploring the relationship between maturation of hippocampal-prefrontal circuitry and the emergence of reasoning ability. I will show that children and adolescents are less likely to link new experiences to their existing memories, limiting their ability to reason about the relationships among distinct events.
Hearing is operational from the third trimester of gestation. Infants thus first experience language in the womb. In this talk I will present a series of near-infrared spectroscopy experiments with newborns suggesting that this prenatal experience may already shape how infants perceive and start learning about language. As maternal tissues act as low-pass filters, fetuses mainly experience the prosody of speech, fine details necessary for the identification of words are mostly suppressed. I will show that at birth infants already recognize the prosodic properties of the language(s) they heard in utero, they weigh prosody as a strong cue to package the speech stream into relevant units. I will link this early prosodic experience to theories of prosodic bootstrapping assumed to operate later during language acquisition.
Announced on our day of birth or even months before, sex and gender are perhaps the most central social categories that affect our lives regardless of the society into which we are born. While the study of how we come to understand our own gender and the influence gender has on our lives has been central to the study of human psychology for decades, nearly all research to date has focused on people who experience “typical” gender identity (gender identity that aligns with one's sex). In this talk, I will discuss our recent work exploring gender development and mental health in an increasingly visible group of children—transgender and gender nonconforming youth—for whom gender and sex diverge considerably. I will explore how studying gender diverse children enhances our understanding of gender more broadly and how basic social cognitive tasks can be useful in addressing ongoing debates about gender diverse children.
Since the ancient Greeks there has been a tension between those who emphasize the similarities between humans and animals, and those who focus on the differences. In this talk I show that modern biology validates, and indeed requires, both perspectives, arguing that human cognition is based on broadly shared building blocks, but also includes several distinctive cognitive characteristics that are either rare or non-existent in non-human animals. I illustrate this perspective with examples from color vision and animal tool use, before turning to human language, where shared and exclusive components both play important roles.
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Classical models of antisocial behavior propose that violence arises out of a failure of lateral prefrontal cortex (LPFC) to “put the brakes” on aggressive impulses originating in subcortical regions such as the amygdala and striatum. A new, alternative model proposes that LPFC does not directly inhibit aggressive impulses, but instead flexibly modulates the value of aggressive acts via corticostriatal circuits. I will present the first empirical evidence directly supporting the alternative model. In a series of behavioral, pharmacological and neuroimaging experiments we observed healthy adults as they decided whether to anonymously inflict pain on themselves or strangers in exchange for money. We find that most people would rather harm themselves than others for profit. This moral preference correlated with neural responses to profit, where participants with stronger moral preferences had lower dorsal striatal responses to profit gained from harming others. LPFC encoded profits gained from harming others, but not self, and tracked the blameworthiness of harmful choices. Moral decisions modulated functional connectivity between LPFC and the profit-sensitive region of dorsal striatum. Increasing central dopamine levels with the dopamine precursor levodopa eliminated moral preferences. The findings suggest moral behavior is linked to a neural devaluation of reward realized by a prefrontal modulation of striatal value representations. This mechanism implies that the moral value of actions is flexibly guided by neural representations of social norms. If norms change, so then do the values that guide actions. Supporting this view, re-framing decisions to harm others as being in service of a noble cause eliminated moral preferences. The flexibility of value representations in the brain may hold the key to understanding why people with good intentions can sometimes do terrible things.
Social behavior is often shaped by the rich storehouse of biographical information that we hold for other people. During our daily social interactions we rapidly and flexibly retrieve a host of biographical details about individuals in our social network, which often guide our decisions as we navigate complex social interactions. Even abstract traits associated with an individual, such as their political affiliation, can cue a rich cascade of person-specific knowledge. I will discuss research from my laboratory showing that a distributed neural circuit, with a hub in the anterior temporal lobe, allows us to rapidly retrieve person knowledge by coordinating interactions with a distributed network to support the flexible retrieval of person attributes.
The infinite generative potential of human language derives from our ability to analyze complex linguistic input into simpler units, store those units in memory, and productively recombine those units into new expressions. This is the cycle of comprehension, acquisition, and production through which human languages persist and change through the history of a speech community. But what are these units of comprehension, acquisition, and production? The tension between combinatorial and holistic representation of complex linguistic expressions plays a central role in debates on language processing and acquisition. Here I describe work combining probabilistic models and new large datasets to investigate this tension and uncover the respective contributions of productive knowledge and direct experience. In processing, we focus on binomial expressions (salt and pepper - pepper and salt), finding a frequency-driven tradeoff between the two knowledge sources and a frequency-dependent level of idiosyncrasy in binomial ordering preference across binomials in the language. The former is explained by a rational model of learning from limited experience; the latter we account for with an evolutionary model of transmission of ordering preferences over time. In acquisition, we focus on determiner-noun combinations (“the ball”, “a cold”) and develop a novel Bayesian model to infer the strength of contribution of productive knowledge evident in child speech. We find evidence of low initial levels of productivity and higher levels later in development, consistent with the hypothesis that the earliest months of multi-word speech are not generated using rich grammatical knowledge, but that grammatical productivity emerges rapidly thereafter.
A substantial body of evidence suggests that neural activity in the alpha frequency band (8-12 Hz) covaries with the locus of covert spatial attention, such that attention to one visual field yields a sustained decline in alpha power at contralateral electrode sites. In our work, we have exploited this covariation by using an inverted encoding model to reconstruct spatial response profiles (termed channel tuning functions, or CTFs) based on the topography of alpha activity on the human scalp. Thus, in a task that required the storage of locations in working memory, we observed a graded profile of activity across spatial channels that peaked at the stored location during both the encoding and delay periods of the task. These spatial CTFs provide an opportunity to quantify the basic tuning properties of online spatial memories to examine how the precision of neural representations changes with manipulations of the probability of storage or the number of items stored. In addition, I’ll show that the same method can be used to track the locus and timing of covert attention, as well as the retrieval of spatial representations from long term memory. These findings demonstrate the integral role that alpha band activity plays in the online representation of space, and provide a powerful new approach for tracking these representations during during ongoing cognition and without requiring overt behavioral responses.
How do children acquire a language? Decades of work have provided a roadmap of principles and mechanisms for early language learning as attested by small-scale laboratory tasks. But there is not yet a convincing empirical synthesis of this work that addresses both the systematicity and ubiquity of language learning and the variability of learning trajectories across children. In this talk I will describe some initial steps towards such a synthesis. This research integrates high-density data from individual children learning a single language and summary data from tens of thousands of children learning more than a dozen languages. Taken together, the data support a hybrid picture in which children slowly accumulate knowledge in rich social contexts but also show evidence for surprisingly fast grammatical abstractions.
In highlighting young children’s receptivity to, and appraisal of, potential informants, recent research on children’s early cultural learning has neglected their self-appraisals and their concomitant information seeking. Recent evidence shows that human toddlers spontaneously signal their own cognitive states; they use non-verbal gestures (e.g., a shoulder shrug and/or flipping of the palms upward and outward) together with explicit statements (“I don’t know”) to convey their ignorance. They also explicitly affirm what they know (“I know…”) and query the knowledge of an interlocutor (“Do you know…?”). Alongside such self-monitoring, toddlers also display an interrogative stance toward potential informants. They ask for information via pointing, via simple factual questions, and via explanation-seeking questions. Granted that children are likely to vary considerably in the responses they receive to such information seeking, they are likely to arrive at different assessments of the scope of human knowledge, the magnitude of their own comparative ignorance, and the potential role of question-asking in mitigating such ignorance.
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Cognitive neuroscience has witnessed two decades of rapid growth, thanks in large part to the continued development of fMRI methods. In my talk, I will question what this work has told us about brain function, and will propose some new directions that I see as being crucial to the ultimate success of cognitive neuroscience. First, I will discuss the need for approaches that allow selective associations between mental operations and representations and brain activity. Related to this, I will discuss the need to develop and test formal ontologies of cognitive processes. Finally, I will discuss the need to make research practices in neuroimaging more reproducible.
Recently, twin narratives have arisen in both the scholarly literature and in the popular press that depict infants as a. moral judges and b. inherently altruistic. Each of these narratives has a set of corollaries or associated claims: that moral knowledge is built in, thorough, and relatively impervious to experience, and that infants’ moral behavior is unlearned, virtuously motivated, prolific and indiscriminate. In my talk, I will examine these narratives and claims in the context of my laboratory’s research on infants’ sensitivity to distributive fairness norms and infants’ prosocial behavior. Our results contextualize and temper these narratives and claims. First, infants’ socio-moral knowledge emerges over the course of development, is marked by individual differences, and may lack some components of a mature moral response. Second, infants’ prosocial behavior is influenced by experience, and impacted by variables that affect the personal costs and interpersonal benefits of acting prosocially. Together, these findings reveal the limits and limitations of infants’ socio-moral cognition and behavior.
The selection of information from our cluttered sensory environments is one of the most fundamental cognitive operations performed by the primate brain. In the visual domain, the selection process is thought to be mediated by a static spatial mechanism – a ‘spotlight’ that can be flexibly shifted around the visual scene. This spatial search mechanism has been associated with a large-scale network that consists of multiple nodes distributed across all major cortical lobes and includes also subcortical regions. To identify the specific functions of each network node and their functional interactions is a major goal for the field of cognitive neuroscience. In my lecture, I will challenge two common notions of attention research. First, I will show behavioral and neural evidence that the attentional spotlight is neither stationary nor unitary. In the appropriate behavioral context, even when spatial attention is sustained at a given location, additional spatial mechanisms operate flexibly in parallel to monitor the visual environment. Second, spatial attention is assumed to be under ‘top-down’ control of higher order cortex. In contrast, I will provide neural evidence indicating that attentional control is exerted through thalamo-cortical interactions. Together, this evidence indicates the need for major revisions of traditional attention accounts.
Drawing on the Appraisal-Tendency Framework (Lerner & Keltner, 2000; 2001), I will present a series of studies from my lab revealing that incidental anger systematically biases judgment and decision making by heightening perceptions of controllability and certainty, decreasing perceptions of risk, and increasing risk taking. I then will present a series of studies (also from my lab) revealing the ways in which such superficially “biased” responses prove to be both biologically adaptive and financially lucrative, especially for males. Taken together, the studies make clear that simple conclusions about the role of emotion in rationality obfuscate complex patterns of human behavior. Angry decision makers exhibit a predictable pattern of responses but the normative consequences of such responses hinge on specific situational contingencies.
Children learn language from hearing it around them, but much of the language they hear isn’t perfectly clear. Some children hear degraded speech signals through a cochlear implant; others may hear speech from speakers with unfamiliar accents. And nearly all children hear a great deal of their language input in the presence of background noise, including competing speech.
Recent work suggests that children are affected by background noise much more than are adults, limiting the extent to which they can benefit from the language input they receive, and leading to a catch-22: young children who are still trying to learn language have a greater need for understanding speech in noise, but are simultaneously less equipped to do so. Similarly, these children are particularly in need of high-quality speech signals; yet at least for some children, the speech they hear can be quite degraded. I will be discussing recent findings on toddler’s ability to recognize known words and learn new ones from signals that are either degraded (as through a cochlear implant), or occur in the presence of multiple people talking simultaneously.
Cooperation, where people pay costs to benefit others, is central to successful human societies. But why are people willing to incur the individual costs involved in cooperating? One set of explanations involves long-term self-interest: if I cooperate with you today, that may make you (or others who find out about my cooperation) more likely to cooperate with me in the future. But people also cooperate even such future consequences are not enough to make cooperation pay off. I explore such "pure" cooperation from using the dual-process perspective from cognitive psychology and behavioral economics, which contrasts cognitive processes that are fast and automatic but inflexible (“intuitive” processes) with those that are effortful and controlled but flexible (“deliberative” processes). I propose the "Social Heuristics Hypothesis" whereby people internalize typically successful behaviors as intuitive heuristics for social interaction. Because most of our important interactions (e.g. those with our co-workers, friends, and family) are long-term rather than anonymous and one-shot, I argue that we intuitively apply a ‘future consequences’ heuristic: our intuitions support strategies which are payoff-maximizing in the presence of future consequences. Deliberation, on the other hand, shifts us towards behavior that is payoff-maximizing in the specific situation at hand. I will present behavioral data from economic game experiments that supports this account: meta-analysis of thousands of participants shows that inducing subjects to carefully deliberate undermines cooperation in 1-shot games (where non-cooperation is payoff-maximizing), but has no effect in games where it can be payoff-maximizing to cooperate.
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Many psychologists, philosophers, and laypeople believe that empathy is necessary for moral judgment and moral action—the only problem with empathy is that we sometimes don’t have enough of it. Drawing on research into psychopathy, criminal behavior, charitable giving, infant cognition, cognitive neuroscience, and Buddhist meditation practices, I’ll argue that this is mistaken. Empathy is a poor moral guide. It is biased, short-sighted, and innumerate—we should try to do without it. We are much better off, in both public policy and intimate relationships, drawing upon a combination of reason and distanced compassion.
My 1991 proposal (in Consciousness Explained) that human consciousness be seen as a ‘user illusion’ met with incredulity in many quarters, in part because many people were unwilling or unable to abandon the idea of the primacy of the "first-person perspective”: (“How could I be wrong about my own conscious states?”) In the meantime, accumulating evidence and advances in theory have prepared the ground for a revival of this initially counterintuitive view, and a number of researchers are homing in on different versions of it.
The capacity for cognitive control, one of the defining characteristics of humancognition, is also remarkably limited. Typically, people cannot engage in more than a few — and sometimes only a single — control-demanding task at once. Limited capacity was a defining element in the earliest conceptualizations of cognitive control, it remains one of the most widely accepted axioms of cognitive psychology, and is even the basis for some laws (e.g., against the use of mobile devices while driving). It also plays a central role in normative (e.g., “bounded rationality”) models of cognitive control, which assume that the capacity limitation imposes an opportunity cost on the allocation of control, and that control policies are chosen so as to optimize payoff relative to this cost (e.g., the Expected Value of Control theory). Remarkably, however, the reason that the capacity for control is limited remains a mystery. Structural and/or metabolic constraints are commonly, if tacitly, assumed reasons. However, these seem unlikely, given the vast resources available to the human brain. In this talk, I will present an alternative account, that offers a computational explanation for the capacity constraints on cognitive control. This account suggests that constraints on controlled processing reflect an inherent tradeoff between a bias in learning for the development of efficient, and generalizable representations, and the performance efficiency afforded by dedicated representations that support parallel processing. I will describe theoretical results (involving simulations and analysis) in support of these ideas, and the beginnings of an empirical line of research designed to test them.
How do language and ideas propagate through communities? We use computational linguistics to extract social meaning from language to help understand this crucial link between individual cognition and social groups. I'll discuss the way economic, social, and psychological variables are reflected in the language we use to talk about food. I'll introduce the "ketchup theory of innovation" on the crucial role that interdisciplinarity plays in the history of innovation and how it can be discovered via language. Finally I'll show how computational methods can address the mystery of why linguistic innovation changes sharply across people's lifespan.
Wherever we find communities of human beings, we also find language. Moreover, cats, dogs and houseplants, despite living in the very same environment, all fail to display linguistic behavior. These basic observations suggest that language is unique to and definitional of our species. However, there is one population of ostensibly human creatures that is curiously silent when it comes to language, namely human infants. Might this mean that this distinctively human characteristic is absent from this population and hence that we shouldn’t think of children as human until they have acquired a language? In this talk, I discuss specific features of the human capacity for language and identify ways in which linguistic structure comes from the human mind. I further show that this structure plays a causal role in language acquisition throughout development and hence provides the basis of our humanity at all stages of life.
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Humans are a social species and much of what we know we learn from others. To be effective and efficient learners, children must be selective about when to innovate, when to imitate, and to what degree. In a systematic program of interdisciplinary, mixed-methodological, and cross-cultural research, my objective is to develop an ontological account of how children flexibly use imitation and innovation as dual engines of cultural learning. Imitation is multifunctional; it is used to learn both instrumental skills and cultural conventions such as rituals. I propose that the psychological system supporting the acquisition of instrumental skills and cultural conventions is driven by two modes of interpretation: an instrumental stance (i.e., interpretation based on physical causation) and a ritual stance (i.e., interpretation based on social convention). What distinguishes instrumental from conventional practices often cannot be determined directly from the action alone but requires interpretation by the learner based on social cues and contextual information. I will present evidence for the kinds of information children use to guide flexible imitation. I will also discuss cross-cultural research in the U.S. and Vanuatu (a Melanesian archipelago) on the interplay of imitation and innovation in early childhood.
Music and language share important features, however these shared features have distinct functions in each domain. For example, although melody is a fundamental organizing structure in a song, it is far less important than the lexical and syntactic structure of a spoken sentence. From an early age, listeners are exposed to both music and language, and they must eventually acquire specific knowledge about the rules that govern sound structure in each domain. My research program examines the music-specific perceptual and cognitive processes that characterize music-specific melody and rhythm processing by experienced adult listeners, and compares these abilities with those of younger listeners and listeners with contrasting cultural or musical backgrounds. Part of acquiring musical and linguistic knowledge may include learning to differentially weigh acoustic features depending on the musical or linguistic context.
Vision depends on motion: we see things either because they move or because our eyes do. What may be more surprising is that large and miniature eye motions help us examine the world in similar ways - largely at the same time. In this presentation, I will discuss recent research from my lab and others suggesting that exploration and gaze-fixation are not all that different processes in the brain. Our eyes scan visual scenes with a same general strategy whether the images are huge or tiny, or even when we try to fix our gaze. These findings indicate that exploration and fixation are not fundamentally different behaviors, but rather two ends of the same visual scanning continuum. They also imply that the same brain systems control our eye movements when we explore and when we fixate - an insight that may ultimately offer clues to understanding both normal oculomotor function in the healthy brain, and oculomotor dysfunction in neurological disease.
The capacity to remember the past in vivid detail develops considerably during childhood and emerges from the contribution of several psychological processes. I will highlight the contribution of two classes of these, relational binding processes and metacognitive processes. Relational binding processes support the integration of the various features of an event (e.g., what, when, where) into a memory representation that captures the most important aspects of an experience. Metacognitive processes confer the ability to reflect on memory quality, which might support decision making (e.g., decisions to act on the basis of the content of one’s memory). Behavioral and neuroimaging evidence will be discussed.
Language is often used to describe the changes that occur around us – changes in either state (“I cracked the glass…”) or location (“I moved the glass onto the table…”). To fully comprehend such events requires that we represent the ‘before’ and ‘after’ states of the object. But how do we represent these mutually exclusive states of a single object at the same time? I shall summarise a series of studies, primarily from fMRI, which show that we do represent such alternative states, and that these alternative states compete with one another in much the same way as alternative interpretations of an ambiguous word might compete. These studies also show that whereas the representations of distinct but similar objects (e.g. a glass and a cup) interfere with one another in proportion to their similarity, representations of the distinct states of the same object interfere in proportion to their dissimilarity. This interference, or competition, manifests in a part of the brain that has been implicated in resolving competition. Furthermore, activity in this area is predicted by the dissimilarity, elsewhere in the brain, between sensorimotor instantiations of the described object’s distinct states. I shall end with new data (still too hot to touch) whose interpretation is a first step towards a brain mechanism for distinguishing between object types, tokens, and token-states. [Prior knowledge of the brain is neither presumed, required, nor advantageous].
I will discuss two new studies from my lab that focus on general questions about the cognitive science and neural implementation of speech and language. I come to (currently) unpopular conclusions about both questions. Based on a first set of experiments, using fMRI and exploiting the temporal statistics of speech, I argue for the existence of a speech-specific processing stage that implicates a particular neuronal substrate (the superior temporal sulcus). In a second set of experiments, using MEG, I go on to develop how temporal encoding can form the basis for more abstract, structural processing. The results demonstrate that, during listening to connected speech, cortical activity of different time scales is entrained concurrently to track the time course of linguistic structures at different hierarchical levels. Critically, entrainment to hierarchical linguistic structures is dissociated from the neural encoding of acoustic cues and from processing the predictability of incoming words. These results demonstrate syntax-driven, internal construction of hierarchical linguistic structure via entrainment of hierarchical cortical dynamics. The conclusions — that speech is special and language syntactic-structure-driven — provide new neurobiological provocations to the prevailing view that speech is hearing and that language is statistics.
A common pivot in debates about the nature of human language concerns the role of experience in shaping language development. While many have found young learners to be prodigious statistical learners and to display clear effects of quantity and quality of input on their ultimate language outcomes, others have focused on cases where the input is impoverished relative to the ultimate acquired knowledge. In this talk, I examine the properties of the learner that make input informative, providing a bridge between these two research traditions.
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Most primates seem specialized for social life, yet how biology shapes complex social behaviors remains poorly understood. To address this gap, we study the biology and behavior of rhesus macaques in both the laboratory and the field. Recent work in the lab shows that monkeys favor giving rewards to another monkey, particularly if he is more familiar or subordinate, rather than give the rewards to no one. Oxytocin—a hormone implicated in social bonding—makes monkeys more giving. Finally, giving behavior selectively activates cells in medial frontal cortex, an area previously implicated in empathy in humans. In a separate study, we found inactivating this area impairs social learning. By contrast, when monkeys play a competitive game against each other, they rapidly develop unpredictable behaviors that serve to hide their intentions. Planning deceptive feints activates a population of neurons in the lateral frontal cortex, an area linked to deceptive planning in humans; inactivating these cells impairs deceptive planning. In the field, we find that intraspecific variation in social behavior and cognition has fitness consequences and emerges, in part, from genes that regulate neuromodulatory function. Together, our findings suggest deep homologies in the biological origins of complex social function in primates.
Probabilistic models of human cognition have been widely successful at capturing the ways that people represent and reason with uncertain knowledge. In this talk I will explore the ways that this probabilistic approach can be applied to systematic and productive reasoning -- in particular, natural language pragmatics and semantics. I will first describe how probabilistic programming languages provide a formal tool encompassing probabilistic uncertainty and compositional structure. I'll illustrate with a examples from inductive reasoning and social cognition. I will then present a framework for language understanding that views literal sentence meaning through probabilistic conditioning and pragmatic enrichment as recursive social reasoning grounded out in literal meaning. I will consider how this framework provides a theory of the role of context in language understanding, focusing on examples from implicature, vague adjectives, and figurative speech (hyperbole and irony).
Broadly construed, statistical learning involves finding predictive patterns based on experiences of property distributions. Psychologists have developed many competing accounts of this kind of induction from instances. Characterizing the phenomena in terms of statistical learning provides a framework for comparing, and hopefully unifying, across alternatives. I will discuss two varieties of statistical learning especially relevant to research on cognitive development. The first concerns learning discriminative versus generative models. Sometimes people learn very narrow, special-purpose relations among properties (discriminative, such as p(x|y). Other times people learn more complete, general-purpose relations (generative, such as p(x,y). One hypothesis is that young children may be disposed to learn generative models. Some of children’s errors or limitations on learning tasks may stem from their trying to learn something more general than intended by the experimenter/teacher. A second variety of statistical learning distinguishes evidential from transductive inferences. Are experiences treated as a sample useful for drawing conclusions about a population (evidential), or are experiences treated as the population to be described (transductive)? This distinction provides a particular perspective on the “similarity-based” versus “theory-based” debate. Similarity-based accounts maintain that people make transductive inferences; theory-based accounts maintain that people make evidential inferences. It is this distinction that makes empirical studies of children’s sensitivity to sampling so critical in the theory vs. similarity debate.
Humans are an unusually prosocial species. We volunteer at food banks, recycle, vote, tithe, give blood, and go to war. We care about justice and fairness, and punish those that transgress against social norms. Although altruistic behavior is well-documented in other primates, the range of altruistic behaviors in other primate species, including the great apes, is much more limited than it is in humans. Moreover, when altruism does occur among other primates, it is typically limited to familiar group members—close kin, mates, and reciprocating partners. It is not clear whether some of the most compelling naturalistic examples of “altruistic” behavior among nonhuman primates, such as food sharing, are the product of other-regarding social preferences or more instrumental motives. I will discuss a body of experimental research which is designed to reveal the preferences that underlie behavior. These experiments suggest that chimpanzees are not consistently motivated to provide benefits to familiar partners, are tolerant of inequity, and act punitively only after personal losses. I will also discuss a body of parallel experiments conducted with children. This work shows that children behave very differently from other apes, and that the social preferences that underlie their behavior are influenced by both their age and the cultural context in which they live. Taken together, these data suggest that human social preferences are derived traits that evolved after the human/ape lineages split 5-8 million years ago.
Good decision-making requires the decision-maker to generate accurate expectations about what is likely to happen in the future. Adults' decisions, especially those pertaining to attention and learning, are guided by their substantial experience in the world. Very young children, however, possess far less data. In this talk, I will discuss work that explores the mechanisms that guide young children's early visual attention decisions and subsequent learning. I present eye-tracking experiments in both human and non-human primates which combine behavioral methods and computational modeling in order to test competing theories of attentional choice. I present evidence that young learners rely on rational utility maximization both to build complex models of the world starting from very little knowledge and, more generally, to guide their behavior. I will also discuss recent results from related on-going projects about learning and attention in macaque learners, as well as some data on other sorts of decision-making processes in children.
I will present some work suggesting that children selectively explore in ways that support information gain. That is, children recognize that information is valuable. However, information is also costly -- and the costs themselves are informative. Across a series of studies, I will suggest that children's sensitivity to both the cost and value of information affects how they teach and learn from others -- and also how they learn about others. I will discuss these findings with respect to the proposal that children's intuitive theory of action includes a "naive utility calculus".
The language(s) that we know shape the way we process and represent the speech that we hear. Since real-world speech recognition almost always takes place in conditions that involve some sort of background noise, we can ask whether the influence of linguistic knowledge and experience on speech processing extends to the particular challenges posed by speech-in-noise recognition, specifically the perceptual separation of speech from noise (Experiment Series 1) and the cognitive representation of speech and concurrent noise (Experiment Series 2). In Experiment Series 1, listeners were asked to recognize English sentences embedded in a background of competing speech that was either English (matched-language, English-in-English recognition) or another language (mismatched-language, e.g. English-in-Mandarin recognition). Listeners were either native or non-native listeners of the target language (usually, English), and were either familiar or unfamiliar with the background language (English, Mandarin, Dutch, or Croatian). This series of experiments demonstrated that matched-language is substantially harder than mismatched-language speech-in-speech recognition. Moreover, the magnitude of the mismatched-language benefit was modulated by long-term linguistic experience (specifically, listener familiarity with the background language), as well as by short-term adaptation to a consistent background language within a test session. Thus, we conclude that speech recognition in conditions that involve competing background speech engages higher-level, experience-dependent, language-specific knowledge in addition to general lower-level, signal-dependent processes of auditory stream segregation. Experiment Series 2 then investigated perceptual classification and encoding in memory of spoken words and concurrently presented background noise. Converging evidence from eye-tracking-based time-course, speeded classification, and recognition memory paradigms strongly suggests parallel (rather than strictly sequential) processes of stream segregation and word identification, as well as integrated (rather than segregated) cognitive representations of speech presented in background noise. Taken together, this research is consistent with models of speech processing and representation that allow interactions between long-term, experience-dependent linguistic knowledge and instance-specific, environment-dependent sources of speech signal variability at multiple levels, ranging from relatively early/low levels of selective attention to relatively late/high levels of lexical encoding and retrieval.
Some current evolutionary theories of morality hold that the adaptations that underlie moral judgment and behavior function to deliver benefits (or prevent harm) to others. I’ll discuss several lines of research built around an alternative view. In particular, I’ll present evidence for the view that people adopt moral positions based on calculations of their self-interest. First, in an experimental study, subjects are presented with an economic decision making game and asked to evaluate the fairness (or unfairness) of each possible decision that players in the game might make. We find that subjects are morally self-serving, reporting that decisions that leave them worse off are more “unfair.” In a second body of work, people’s political views change depending on non-obvious factors that shift people’s perception of where their own interests lie. Finally, a third line of work speaks to the possibility that people’s political attitudes are derived not from their party affiliation or their political ideology, but instead derive from calculations of their interests. These results are consistent with a view of morality that suggests that people’s moral views are not adopted in order to aid others – or their group – but instead to advance their goals over various time spans.
Most people associate Sigmund Freud with the assertion that speech errors reveal repressed thoughts, a claim that does not have a great deal of support. I will introduce some other things that Freud said about slips, showing that these, in contrast to the repression notion, do fit well with modern theories of language production. I will illustrate using an interactive two-step theory of lexical access during production, which has been used to understand aphasic speech error patterns.
How can we study the biological evolution of the human capacity for music? Over the past century, theories of music’s origins have abounded, with little data to constrain them. One prominent debate has centered on the issue of adaptation: were human bodies and brains specifically shaped for musical behaviors by natural selection, or did music (like reading and writing) arise as a human creation without impetus from biology? This debate has gone on since Darwin’s time and will likely be with us for many years to come. In this talk I argue for a different approach to studying the evolution of our musical abilities, based on empirical research. I will discuss comparative studies with birds aimed at understanding the evolutionary history of human melodic and rhythmic processing. One set of studies focuses on our ability to recognize melodies when they are shifted up or down in pitch (transposed). The other set of studies focuses on our capacity to perceive a beat in music and move in synchrony with it. The results of these studies suggest that these two aspects of music processing likely involve cognitive and neural specializations which have distinct evolutionary histories.
When we think about our past, many of the events that come to mind are those that triggered an emotional response. This retrieval of a memory requires a series of processes to unfold: Information must be attended and encoded into memory, resist decay and interference over time, and be reactivated when the appropriate retrieval cue is processed. In this talk, I will discuss how the arousal (physiological response or feeling of excitation) and valence (pleasure or displeasure) of an event can affect the likelihood that each of these processes unfolds to give rise to memory.
When people talk, they gesture. We now know that these gestures are associated with learning. They can index moments of cognitive instability and reflect thoughts not yet found in speech. What I hope to do in this talk is raise the possibility that gesture might do more than just reflect learning––it might be involved in the learning process itself. I consider two non-mutually exclusive possibilities: the gestures that we see others produce might be able to change our thoughts; and the gestures that we ourselves produce might be able to change our thoughts. Finally, I explore the mechanisms responsible for gesture's effect on learning––how gesture works to change our minds.
How do humans come to have a “moral sense”? Are adults’ conceptions of which actions are right and which are wrong, of who is good and who is bad, who deserves praise and who deserves blame wholly the result of experiences like observing and interacting with others in one’s cultural environment and explicit teaching from parents, teachers, and religious leaders? Do all of the complexities in adult’s moral judgments reflect hard-won developmental change coupled with the emergence of advanced reasoning skills? This talk will explore evidence that, on the contrary, preverbal infants’ social preferences map surprisingly well onto adult moral intuitions. Within the first year of life, infants prefer those who help versus harm third parties, those who reward prosocial individuals and punish wrongdoers, and even privilege the intentions that drive actions over the outcomes they lead to. In the second year of life, toddlers direct their own helpful actions toward helpful individuals, and harmful actions toward harmful individuals. These results suggest that our adult moral sense is supported, at least in part, by innate mechanisms for sociomoral evaluation.
Humans use punishment and reward to modify each others' behavior, and we also learn from others' rewards and punishments. This simple dynamic animates much of our moral psychology, and I explore two of its consequences in detail. First, human punishment should be adapted to the contours and constraints of human learning. This can explain a peculiar feature of our moral judgments that philosophers call "moral luck": The fact that accidental outcomes play a large role in determining punishment. Second, the architecture of human learning should dictate when and how we choose to harm others. I borrow from current neurobiological models of reinforcement learning to understand why we deem some harmful actions impermissible and others permissible. These case studies illustrate the role that learning systems play as a basic organizing principle in the moral domain.
To what extent is human cognition augmented by language? Does language only enhance communication, with words acting as triggers for nonlinguistic concepts? Or does language play an active role in the very ability to construct and manipulate those concepts? I will present a series of experiments showing that language has pervasive and surprising effects on a range of cognitive abilities, such as learning new categories, deploying knowledge about familiar categories, and even basic perception: Hearing a word can literally change what one sees. I will conclude by discussing the “design features” of words that make them especially useful for constructing and manipulating mental representations.
The passive is one of the most thoroughly examined constructions in the world’s languages, across different theoretical and typological perspectives; yet there is often disagreement about category membership, particularly for constructions sometimes called “non-promotional” passives, which have no overt subject but govern an accusative object. In this talk I will discuss a new impersonal construction which has arisen in Icelandic in recent decades and which is gaining ground. Data has been collected in two nation-wide surveys. This syntactic innovation is a system-internal change that is not the result of borrowing, nor the result of any phonological change or morphological weakening in the language. I argue that the categorical indeterminacy of the New Impersonal is a result of two distinct grammatical analyses of the construction among native speakers. Other cases of this kind across several genetically unrelated languages will also be discussed.
How do genes and experience interact to produce human cognition? I will discuss insights into this puzzle from studies of blindness. The first half of the talk will focus on how first-person sensory experience contributes to concepts. What do congenitally blind people know about seeing and light? One source of evidence comes from studies of “visual” verbs. Congenitally blind and sighted people made semantic similarity judgments on pairs of visual verbs (e.g. to glimpse) and non-visual verbs (e.g. to touch). We find that blind adults distinguish seeing from perception through other sensory modalities (e.g. to touch) and from amodal knowledge acquisition (e.g. to notice). Like sighted individuals, they make fine grained spatiotemporal distinctions among verbs of seeing (e.g. to peek vs. to stare). Blind adults also distinguish among verbs of light emission along dimensions of intensity (glow vs. blaze) and temporal continuity (blaze vs. flash). This knowledge about seeing is not limited to the meanings of words. Blind people make inferences about how others feel based on visual experience and these inferences depend on the same neural mechanisms as in sighted individuals. Together these data suggest that first-person sensory experience is not required to develop rich conceptual representations. The second half of the talk will focus on effects of experience on the neurobiology of language. Language processing typically relies on fronto-temporal cortices. I argue that “visual” areas of the occipital cortex are added to the language system in congenitally blind individuals. Language-related plasticity occurs during development: plasticity is observed in congenitally, but not late blind adults and emerges in blind children by 4-years-of-age. These findings suggest that brain regions that did not evolve for language can nevertheless acquire language processing capacities. These studies suggest that during development brain regions acquire cognitive functions through a constrained process of self-organization.
The study of cognitive development has often been framed in terms of the nativist/empiricist debate. Here I present a new approach to cognitive development – rational constructivism. I will argue that learners take into account both prior knowledge and biases (learned or unlearned) as well as statistical information in the input; prior knowledge and statistical information are combined in a rational manner (as is often captured in Bayesian models of cognition). Furthermore, there may be a set of domain-general learning mechanisms that give rise to domain-specific knowledge. I will present evidence supporting the idea that early learning is rational, statistical, and inferential, and infants and young children are rational, constructivist learners.
Children and adults are often motivated to explain the world around them and have strong intuitions about what makes something a good (or beautiful) explanation. Why are we so driven to explain, and what accounts for our explanatory preferences? In this talk I’ll present evidence that both children and adults prefer explanations that are simple and have broad scope, consistent with many accounts of explanation from philosophy of science. The good news is that a preference for simple and broad explanations can sometimes improve learning; The bad news is that under some conditions, a preference for simplicity can lead people to systematically misremember observations, and a preference for broad scope can encourage errors of overgeneralization. An important take-home lesson is that seeking, generating, and evaluating explanations plays an important role in human judgment and serves as a valuable window onto core cognitive processes such as learning and inference.
Statistical learning is the process of identifying patterns of probabilistic co-occurrence among stimulus features, essential to our ability to perceive the world as predictable and stable. Research on auditory statistical learning has revealed that infants use statistical properties of linguistic input to discover structure, including sound patterns, words, and the beginnings of grammar, that may facilitate language acquisition. Previous research on visual statistical learning revealed abilities to discriminate probabilities in visual patterns, leading to claims of a domain-general learning device that is available early in life, perhaps at birth. More recent research, however, challenges this view. Visual statistical learning appears to be constrained by limits in infants' attention and memory, raising the possibility that statistical learning, like rule learning, may be best characterized as domain-specific. Implications for theories of cognitive development will be discussed.
There is no doubt that cognitive control and language processing are intertwined: Prefrontal cortical regions that support the ability to resolve competition between multiple, incompatible representations are recruited for both language production and language comprehension. In this talk, I will explore a somewhat less intuitive hypothesis, namely that cognitive control has both benefits and costs for language processing. After introducing the motivation for this hypothesis, I will provide evidence from three experiments in which we manipulated frontally-mediated cognitive control processes using noninvasive brain stimulation (transcranial direct current stimulation; TDCS) and observed the consequences for different aspects of language processing. I will present results from one experiment that shows a benefit of cognitive control (a categorization task), a second that shows a cost of cognitive control (a different categorization task), and a third that shows both costs and benefits (a word production task).
In this talk, I will first introduce the proposal that human reasoning relies on an inherence heuristic, an implicit cognitive process that leads people to explain the patterns observed in the world in terms of the inherent features of their constituents. I will then provide evidence for this proposal, evidence that suggests the inherence heuristic is an automatic process that exerts a ubiquitous influence on how we make sense of the world. Its influence is detectable even in the first few years of life, as indicated by the developmental studies I will present. In the second part of the talk, I will argue that the inherence heuristic may be at the root of several other phenomena of great interest to cognitive and social scientists. In particular, I will highlight, and provide evidence for, the links between the inherence heuristic and (1) psychological essentialism (the common belief that natural and social categories are underlain by hidden, causally powerful “essences”) and (2) system justification (the tendency to believe that one’s sociopolitical system is fair, natural, and legitimate). In sum, this talk will illuminate a cognitive process that emerges early in life and has profound effects on many aspects of human psychology.
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