Cognitive Science Colloquium
All meetings take place on Thursdays, 3.30-5.30 pm in Bioscience Research Building 1103, unless otherwise indicated.
September 11 — Gary Dell (Psychology & Linguistics, University of Illinois).
Title: What Freud got right about speech errors.
Abstract: 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.
September 18 — Robert Kurzban (Psychology, Penn).
Title: Strategic morality
Abstract: 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.
October 9 — Ann Bradlow (Linguistics, Northwestern).
Title: Linguistic experience and speech-in-noise recognition
Abstract: 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.
October 16 — Laura Schulz (Brain and Cognitive Sciences, MIT).
Title: Inferential economics: Children's sensitivity to the cost and value of information
Abstract: 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".
October 23 — Celeste Kidd (Brain and Cognitive Sciences, Rochester).
Title: Rational approaches to learning and development
Abstract: 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.
November 13 — Joan Silk (School of Human Evolution and Social Change, Arizona State).
The Phylogeny and Ontogeny of Altruistic Social Preferences
Abstract: 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.
Note: this meeting has now been returned to its original location, Bioscience Research Building 1103.
Varieties of Statistical Learning
Abstract: 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.