Title Instructor Credit
Academic Writing for Cognitive Scientists

This course aims at improving oral and written presentation skills that are vital for Cognitive Scientists. How does one write an abstract, a methods section, or a results section for an empirical paper? How can experimental results be presented most effectively? What are good strategies for dealing with reviewers’ comments when revising a paper? How does one write a review? What is important to keep in mind when writing a research proposal? What makes for a good oral presentation?

Natalie Sebanz
Guenther Knoblich
Action and agency: causal and teleological interpretations

Course description: The purpose of this course is to introduce students into some contemporary debates over the nature and understanding of actions and agency. Although intentional actions are commonly explained with reference to agents’ goals, many contemporary philosophical and psychological accounts of action presuppose that the teleology implicit in such explanations cannot be fundamental.

Gergely Csibra
Ferenc Huoranszki
Action and agency: causal and teleological interpretations

The purpose of this course is to introduce students into some contemporary debates over the nature and understanding of actions and agency. Although intentional actions are commonly explained with reference to agents’ goals, many contemporary philosophical and psychological accounts of action presuppose that the teleology implicit in such explanations cannot be fundamental.

Ferenc Huoranszki
Gergely Csibra
Agent Based Models

Course code: CNSC 6001

Course level: Doctoral

Office hours: upon agreement

Course Description

Complex systems are abundant: The society, the economy, the financial system, food webs, energy supply systems are just some examples. The recent development of information technology opened unprecedented opportunities in studying them. On the one hand due to making available huge amounts of data, on the other hand by offering computer power for simulating them.

János Kertész 2.0
Algorithms and Data Structures

The course provides a gentle and still up to date introduction into Algorithms used in our everyday life. The main goal is to understand why certain strategies using huge data implemented on even on the fastest computer would not give the answer in a life time, while a clever modification solves the problem in seconds on a laptop, and how to find some feasible strategies.


TBA 2.0
Analogies and Metaphors

Not a day goes by without any of us using a metaphor or making an analogy between two things. Not only do analogies and metaphors populate our everyday mental and linguistic lives, but they are also ubiquitous in science, philosophy, law, politics, economics, history, art, architecture, and even mathematics. This omnipresence of analogies and metaphors has brought scholarly attention to their function and meaning, the study of which is now decisively interdisciplinary, including important contributions from philosophy, linguistics, cognitive science, and art theory.

Mathieu Charbonneau 2.0
Bayesian data analysis

Course Description

József Fiser 2.0
Bayesian Data Analysis

This course will provide an introduction to practical methods for making inferences from data using probabilistic models for observed and missing data.  This approach is an alternative to frequentist statistics, the presently dominant inference technique in sciences, and it supports a common-sense interpretation 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. 

József Fiser 2.0
Behavioural Economics

Research Course

In this course, we will read and discuss papers about the psychological factors that underpin decision-making, focusing on decisions taken when interacting with others.


The course will have three parts:


  1. An introduction to decision theory and behavioural economics


Christophe Heintz 2.0
Behavioural Game Theory

In this course, we will read and discuss papers about the psychological factors that underpin decision-making, focusing on decisions taken when interacting with others.


The course will have three parts:


  1. An introduction to decision theory and behavioural economics


Christophe Heintz 2.0
Cognitive Science and Policy Making

How can cognitive science inform policy-making? Can policy be improved by taking findings of cognitive science into account?

            Traditional policy making assumes that citizens are rational agents who always take the best decisions for themselves. Yet, findings in behavioral economics and cognitive psychology show that it is not the case: people are “predictably irrational.” This fact might open new avenues for making policies that foster individual decisions that are better for both the individual taking them and society.

Christophe Heintz 2.0
Communicative and cultural knowledge transmission
György Gergely 2.0
Critical Concepts in the History of Cognitive Science

This is not  a professional history of cognitive science class. It does not teach professional skills of research on primary resources, or conceptual analysis. Its main aim is to show how some of the crucial issues and concepts of cognitive science  showed up in modern European intellectual history, and how these concepts and their accompanying debates shape present day cognitive science. After a brief exposé of the overall history of CogSci by the instructor 5 crucial notions shall be discussed, always with a classical paper and present day approach.

Csaba Pléh 2.0
Critical perspectives on human nature


Maria Kronfeldner 2.0
Data Analysis 4: seminar2: R


tba 0.5
Data and Network Visualization

Prerequisites: You need to be proficient with Python to take this course – read the “to satisfy the prerequisite” section below

Course schedule: this course will take place twice a week during the second half of the term, starting on November 2, 2017.

Course Level: Master and PhD

Office: 609 Nador 11

Office hours: TBA or by appointment

Cross-listed: Cognitive Science, Economics, Network Science

Brief introduction to the course

Roberta Sinatra 2.0
Data Management with Python

Instructor: Anikó Hannák (, office hours: Tuesdays 4:00pm-5:30pm by appointment)
Credits: 2 (4 ECTS)
Term: Winter 2017-2018

Ancsa Hannak 2.0
Data Mining and Big Data Analytics
Course code: CNSC 6006

Office: N11 308

Course schedule: This course will take place during the first half of the winter term, starting on January 10th 2018.

Office hours: by appointment

Teaching Assistant: Milán Janosov

Rossano Schifanella 2.0
Development of Perception and Action

Perception and action are the complements of each other.  No action could exist without perception and perception relies ultimately on action. Together they form functional systems around which adaptive behavior develop. According to this view, the starting point of development is not a set of reflexes triggered by external stimuli, but a set of action systems that are activated by the infant. Thus, dynamic systems are formed in which the development of the nervous system and the development of actions mutually influence each other.

Claes von Hofsten 2.0
Empirical and philosophical issues in the study of human cooperation and communication

The importance, diversity, and richness of the forms of cooperation and communication human engage in are without par among animal species. These interactions are in a relationship of mutual enhancement with four factors: evolved psychological capacities, protracted cognitive development, complex sociality, and culture.

Dan Sperber 2.0
Engines of Development

We will examine a number of fundamental questions, issues, and findings in the study of infant and preschool cognition over the last 35 years and suggest some current prospects. We will pose, refine, and begin to answer some of the big questions about the nature of the human mind and its capacities. 

Alan Leslie 2.0
Evolutionary Psychology

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.

Prof. Clark Barrett 2.0
Experimental Research Methods

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 communicat

József Fiser 2.0
How to design good experiments in Cognitive Science

The aim of the course is to enhance the participants’ understanding of how research questions in Cognitive Science can be addressed with experimental designs. The course will enable participants to turn well-formulated questions about the mind and brain into experiments that produce interpretable results. The course also aims at improving participants’ ability to judge whether experiments do or do not support the conclusions drawn from them.

Guenther Knoblich 2.0
Human interaction through music: psychological and social foundations of group music-making Peter Keller 2.0
Infant Cognition

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.

Gergely Csibra
György Gergely
Ágnes Melinda Kovács
Introduction to Cognitive Science

This course will give a broad overview of the fundamental concepts, findings, and methods in Cognitive Science, the interdisciplinary study of the mind. It will start with a short historical overview. The following five lectures will highlight important approaches to Cognitive Science that are represented at the department. Five more lectures will introduce important research methods in Cognitive Science using domains of study represented at the department. In the last session students will present research ideas.



Guenther Knoblich 2.0
Introduction to EEG methods in Cognitive Science

This course introduces students to the use of electroencephalography (EEG) for measuring brain
function to access cognitive mechanisms in humans. This is a practical course, where students
receive hands-on experience in recording and analyzing EEG data, as well as in designing
experiments and interpreting findings using this method.

Gergely Csibra 2.0
Introduction to language and social cognition

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?

Anne Tamm 2.0
Joint Action

This course will cover recent theories and empirical research on joint action. The focus will be on ongoing research in our lab. Specific topics include the role of thinking and planning ahead as well as research focusing on basic perceptual and motor processes that allow people to perform highly coordinated actions such as playing a piano duet together. We will discuss behavioral and neuroscience experiments with a focus on studies that have been conducted by members of our lab.

Natalie Sebanz
Guenther Knoblich
JustData - University Wide Course

Short Syllabus

Big Data is all around us – facebook users, records on citizens, the network of neurons in the brain, routes of migrants, impact of publications. The Data itself is neither good or evil, however, it can be used for either purposes. The availability and analysis of big data opens up enormous opportunities for research, but is not without serious dangers. The course explores the amazing potential and the dark side of Big Data.

Miklós Koren
Arieda Muço
Chrys Margaritidis
Jozsef Martin, Transparency International Hungary)
Roberta Sinatra
Karoly Boroczky

Brief introduction to the course:

While probability theory describes random phenomena, mathematical statistics teaches us how to behave in the face of uncertainties, according to the famous mathematician Abraham Wald. Roughly speaking, we will learn strategies of treating randomness in everyday life. Taking this course is suggested  between  the Probability and Multivariate Statistics courses.


The goals of the course:

Marianna Bolla 3.0
Matlab for Experiments and Data Analysis

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.

Guenther Knoblich
Cordula Vesper
Matrix Computations with Applications

Brief introduction to the course:

The course will cover most standard matrix manipulations. There will be ample examples and applications described.

The goals of the course:

The main goal of the course is to further strengthen students’ understanding of linear algebra and that they understand ways of applying it to other areas of algebra and mathematics.  They are expected to reach an ability of seeing the interdependencies among the various linear algebraic objects.

Pál Hegedűs 3.0
Philosophy of Science: Core Contemporary Issues

The way science works raises deep and pressing philosophical questions. Is there a way to demarcate science from non-science? How is scientific knowledge made reliable? Is it giving us access to reality or is it merely a tool for successful prediction? The so-called “analytic” project (following Barker & Kitcher’s terminology) within philosophy of science focused on these and similar (by now) classic issues: the demarcation of science, confirmation, realism, the nature of theories, the relations among theories, laws of nature and explanation.

Maria Kronfeldner 2.0
Political Philosophy 2.: Cognitive science and policy making Christophe Heintz 4.0
Probabilistic modeling: From perception to sequential decisions

Elective Course

Instructors :

Constantin Rothkopf, Vising Professor from Technische Universität Darmstadt and Jozsef Fiser, Associate Professor, CEU.

József Fiser 2.0

The course introduces the fundamental tools in probability theory.

Tóth Imre Péter 3.0
Religion, Ritual and Cultural Transmission

While explaining religion has been central to social anthropology from its beginnings, it has also become a focal topic of theoretical interest and empirical investigation in recent naturalistic approaches to the origins and social transmission of cumulative cultural knowledge.

György Gergely
Vlad Naumescu
Scientific Python Fall 2017/2018

IMPORTANT: This course can accommodate a maximum of 30 students. Priority is given to Mathematics students (Master and PhD) and Network Science PhD students. All other students are selected based on the entry test score. Students that take the course for grade have priority over auditors. All students, both registered and in the waiting list must take the entry test on the first day.

Brief introduction to the course:

Roberta Sinatra 3.0
Semantic - Pragmatic Development Nausicaa Pouscoulous 2.0
Social and cognitive sciences approaches to religion

Explaining religion has been a main goal of the social sciences and in particular of anthropology. It has now become an important goal for naturalistic approaches to culture (cognitive and evolutionary). This course will explore both the tensions and the potential complementarities between social-scientific and naturalistic approaches by looking at the way they frame and try to answer central questions in the study of religion and in particular of beliefs and ritual (NB: the specific topics and readings will be different from last year).



Dan Sperber 2.0
Social Cognition

What are the psychological bases of the rich social interactions and cultural life that characterise human societies? This course will review some of the answers provided by recent studies in cognitive psychology, evolutionary psychology and social anthropology. It will cover a wide range of topics related to social cognition and human sociality, including:

Christophe Heintz 2.0
Statistical Models of Perception, Action, Cognition

Biological organisms make choices and often the possible outcomes of their choices are uncertain.  Several different fields focus on how organisms cope with uncertainty: decision making in psychology, micro-economics, foraging theory in biology, motor planning in psychology, and perceptual judgment in psychology. The foci of research in all of these areas overlap considerably but the terminologies an differ considerably. What these areas share is a common statistical framework, Bayesian decision theory.

Laurence T Maloney 2.0
Statistics for Experimental Research

Core Course

József Fiser 2.0
The Origin of Concepts

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).

György Gergely 2.0
Topics in Cognitive Science

Core Course

This course will review some key topics in cognitive science with a focus on the themes that are being developed in the department.


Goal of the course

Christophe Heintz 2.0
Topics in the Philosophy of Psychology

In this course we will discuss the interpretation of certain concepts that are used as explanatory constructs by empirical psychological and neuroscientific research. Arguably, the use of concepts like ‘free will’, ‘embodied cognition’, ‘intention’, ‘essence’ and others sometimes involves controversial, and often hidden, assumptions, which might misguide empirical research or lead to misinterpretation of its results.

Gergely Csibra
Hanoch Ben-Yami
Topics in the Philosophy of the Human and Social Sciences

The way scientists and scholars study human beings, their culture and society has often been considered to be different from the way other objects of science are studied, be it because of the reflexivity, freedom or the normativity involved in studying human beings. In addition, none of the academic disciplines is studying humans as humans, be it biological disciplines such as evolutionary biology, social sciences or the humanities.

Maria Kronfeldner 4.0
Understanding and Misunderstanding

We can achieve understanding at many different levels – from sensing that someone sitting next to us is cold to knowing that we agree or disagree with someone on, say, a certain environmental policy. This course will explore the individual level processes that can lead to understanding in human interaction and discuss how the nature of these processes influences the way in which misunderstandings arise.

Guenther Knoblich
Natalie Sebanz