This course will provide a hands-on introduction to programming in Matlab with a special focus on applying it to create psychological experiments and to analyze human behavioral data. After a general introduction to the basic ingredients of programming (variables, loops, good programming styles etc.), we will use Matlab to write little experiments and to collect, analyze and plot real data. This will involve simple reaction time experiments but the course will also offer an introduction to collecting and analyzing 3D human movement data with the Polhemus motion tracking system. Course participants will be required to do small programming assignments.

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.

Pls note, first class will be on 18 September, instead of the 17 September date.

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.

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:
1. An introduction to behavioural economics
2. Studies on other-regarding preferences
3. Studies on strategic decision making

The course provides an introduction into current-day philosophically inspired cognitive developmental theory and evolutionary perspectives of the nature of human concepts and their origins. The core reading for the course will be the book by Susan Carey entitled `The Origin of Concepts` (OUP, 2009). The in-depth reading and discussion of this representative book and some additional papers will cover the comparative analysis of the nature of processes of conceptual change, reorganization, and theory construction in cognitive development on the one hand, and in history of science, on the other.

Pls note, first class will be on 18 September, instead of the 17 September date.

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.

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