• This course will provide an introduction to practical methods for making inferences from data using probability models for observed and missing data. This approach is an alternative to frequentist statistics that is the presently dominant inference techniques and it supports a common-sense interpretations of statistical conclusions by using probabilities explicitly to quantify uncertainty of inferences. The course will introduce Bayesian inference starting from first principles using basic probability and statistics, elementary calculus and linear algebra. The course will progress by first presenting the fundamental Bayesian principle of treating all unknowns as random variables, and by introducing the basic concepts (conjugate, noninformative priors) and the standard probability models (normal, binomial, Poisson) through some examples. Next, it will discuss multi-parameter problems, and large-sample asymptotic results leading to normal approximations to posterior distributions. We continue with hierarchical models, model construction and checking, and finish the topics with sensitivity analysis, and model comparison. Learning the software package of JAGS will allow students to fit complex Bayesian models with minimal programming expertise. Familiarity with Matlab or C++ programming is required.

  • VENUE CHANGE: As of October 10, venue is Frankel Leo 30-34, Room 206.

    What decisions do we take when they involve others' choices and welfare? Studies show that people do take into consideration the consequences that their decisions will have on others. They also predict what others will do and decide accordingly.

    We will read and discuss papers about the psychological factors that underpin decision-making when interacting with others. We will see that these decisions depend on social or “other-regarding” preferences and we look at different attempts to specify what these preferences are. The decisions taken when interacting with others also depend on how others are predicted to behave. We will investigate how these predictions are formed and their effects on decision-making.

    The course will have three parts: an introduction to experimental economics, studies on other-regarding preferences and studies on strategic cognition.



  • Cognitive mechanisms of cultural knowledge transmission

    Recent advances in social cognitive science have radically transformed our thinking about the role of cognition in explaining culture. Historically the study of the origins, transmission, and the variety of human cultural forms was considered to be the proper domain of human anthropology and was thought to be only loosely related to the domain of the psychological study of human learning and cognition. However, the new perspective provided by advances in developmental psychology, cognitive anthropology, and evolutionary psychology have changed this picture in theoretically significant and empirically fruitful ways. The course will explore the multiple ways in which the evolutionary approach to the study of social cognitive mechanisms of the human mind has contributed to recent advances in our understanding of the evolutionary origins of cumulative culture in humans and the proliferation, maintenace, and faithful transmission of shared cultural knowledge across generations of human social groups. We will analyse the far-reaching theoretical and methodological implications of the integrated study of cognition and culture for cross-cultural and comparative research. The new framework provided by cognitive anthopology and evolutionary psychology provides new explanatory models to account for the stability as well as variability of cultural forms in different knowledge domains and their faithful intergenerational transmission and maintenance in human societies. We will overview recent proposals about how the human capacity for ostensive communication that allows for the efficient the cooperative transfer of relevant information across individuals may have been originally selected for as a specialized cognitive mechanism (Natural Pedagogy) to enable the trust-based intergenerational transfer of generic knowledge about natural, artefact, and social kinds shared by and trasmitted across human cultural groups. We will also explore recent theoretical models to account for the evolutionary origins of various kinds of cultural belief systems and social practices that emerge and stabilize in human social groups, such as religious and supernatural beliefs, as examples of cognitively partially opaque knowledge structures that form and proliferate by exploiting as memetic free-riders the various social cognitive adaptations specialized and selected for different primary functions during hominid evolution.



  • Clark Barrett

    If brains and minds are products of evolution, how have evolutionary processes shaped them to do what they do? In this course we will investigate how evolutionary theory and methods can be combined with the study of development, genetics, cognition, and neuroscience to attempt to deconstruct the mind’s functional structures and understand how they evolved. In particular, we will focus on a diversity view of mental adaptations: namely, that the brain’s adaptations do not come in a few rigid or monolithic types, but rather comprise a diversity of forms with very different evolutionary histories and designs, some very old and some new, that interact in a complex mosaic. First, we will examine the evolutionary process and how it shapes specialized mechanisms designed to process information in the service of behavior. Using case studies, we will look at how flexibility is part of, rather than distinct from, specialized design. Then we will turn to the question of development, and how evolution shapes developmental mechanisms that have functioning cognitive systems as their developmental target. Next we will turn to the hierarchical nature of brain evolution, and the question of how new mechanisms evolve within a mosaic of older adaptations, and what this means for the empirical study of evolved mechanisms in the brain. Finally, we will turn to the question of human uniqueness, and how it can properly be understood in the context of the hierarchical diversity view of mental adaptations developed in the course.

    Learning Outcomes

    By the end of this course, students will be conversant in the fundamentals of contemporary evolutionary theory as it applies to mind and behavior. They will learn how recent trends in biology, including evolutionary developmental biology (evo-devo) and genetics, apply to questions in psychology and neuroscience. They will be familiar with current debates about how the human mind evolved and develops, such as debates over nativism, modularity, plasticity, culture, human universals and human nature. By the end of the course, students will be able to develop hypotheses about the evolution and design of cognitive mechanisms, and generate proposals for testing these hypotheses.

  • This course will cover the basic topics of Experimental Statistics and Research Methods for Behavioral Sciences. It will comprise the subjects of scales, descriptive statistics, frequentist inferential statistics including independent and repeated measure t-tests, one- and two-way ANOVAs, effect sizes, correlational and regression analysis, and selected nonparametric methods. In addition, the basics of Bayesian statistics will be introduced and contrasted with frequentist statistics. The course will also survey the details of designing, conducting, analyzing, interpreting, and communicating scientific psychological research. Finally, students will learn how to use SPSS for statistical analysis.
  • This course introduces students to the ongoing research at the Cognitive Development Center. It provides an overview of contemporary theories and research techniques of cognitive development of human infants below 2 years of age, focusing on the domain of social cognition. The course also involves laboratory practice to familiarize students with research techniques including behavioral, eye-tracking and neuroimaging methods.




  • This course will give a broad overview of the fundamental assumptions and findings in Cognitive Science, the interdisciplinary study of the mind. The lectures in the first half of the course will cover the main ideas that have been driving the study of the human mind for the last fifty years. These will include the view that the mind functions like a digital computer, the view that the mind functions like a neural network, and the view that the mind should be conceived of as a dynamical system closely tied to the environment. The lectures in the second half will give an overview of important topics in Cognitive Science including perception, memory, thinking, and language.


  • Humans are special in having a communication system that employs complex language(s) and advanced social cognition. This course offers an introduction to current research on how these advanced human capacities interact. Language is discussed as a cognitive ability as well as a central feature of human social interaction. During the meetings we discuss how the prominent models and theories of language explain linguistic phenomena that relate to social cognition. What is universal, what is language or culture specific? How are our linguistic concepts and categories connected to social cognitive categories and capacities? How do these two powerful cognitive abilities feed into each other? We will discuss linguistic phenomena from known and exotic languages that, via their special link to social cognition, inform us about how the social mind works. The linguistic topics include evidentiality, generics, duals, possessives, causation, number-measure-mass-count phenomena, negation, case, transitivity, and verbs. The social cognitive topics that are related to them include ostensive communication, reputation maintaining, gossip, epistemic vigilance, Theory of Mind, joint action, norms and values, perspective taking, empathy and the perception of self. The course will also introduce methods, resources and tools (surveys, experiments, databases, corpora) that help us clarify the relationships between social cognitive and linguistic phenomena.


  • This course will cover recent theories and empirical research addressing the human ability to perform actions together. We will review theories highlighting the role of thinking and planning ahead as well as theories focusing on basic perceptual and motor processes that allow people to perform highly coordinated actions such as dancing a tango together. We will discuss research articles reporting behavioral and neuroscience experiments in this rapidly growing field. The course will also provide an overview of the different research methods that have been used in joint action research.


  • This course will be built around the contemporary research of vision. First, it will cover the classical approaches of low and high-level vision, visual learning, the neural implementation of perception and learning in the brain, and computational models. Next, it will critically evaluate the state-of-the-art and explore alternative approaches to the same issues. Specifically, it will discuss the probabilistic view on vision, and how it changes the research questions in focus. We will investigate how statistical learning, rule learning, perception and cue-combination as probabilistic inference can expand the range of interpretable phenomena in vision. We will also cover the issue of possible neural embodiment of such computations and review evidence that supports such an interpretation.