Experimental Methods Module

Cognitive neuroscience is an interdisciplinary field that aims to investigate the neural underpinnings of the brain-behavior relationship and make predictions about human-environment interactions. To achieve this goal, a wide array of experimental methods is used. In this module, students are introduced to the methods used in cognitive neuroscience research, including behavioral, psycho-, and neurophysiological paradigms. Courses from this module cover both theoretical foundations and practical aspects linked to the use of these methods. The knowledge and skills obtained from this module will allow students to make informed methodological decisions while planning and conducting their own experiments, either as part of academic research or R&D projects.

Philosophy Module

The aim of the philosophy module is to teach students about philosophical issues arising at the interface of philosophy and cognitive science. Students will not only acquire an understanding of philosophical concepts related to research in cognitive science, including the notions of mind, information, language, and action, but will also learn about problems confronting cognitive science because of its special multidisciplinary and transdisciplinary character. Students will be able to critically assess the methodologies and research practices of cognitive science, synthesizing theories and findings from diverse disciplines to shed light on how they contribute to the development of the central themes of the field.

The courses of the module prepare students to conduct their own theoretical or empirical research in a way that applies philosophical concepts, theories and arguments in a broad range of theoretical and practical contexts: to deepen the understanding of available empirical findings, shed light on how cognitive science informs philosophical reflection, or help to solve practical problems – e.g., in business, industry or social life.

Language Module

Courses in this module are designed to explore the intricate interplay between cognition and linguistic processes. From introductory explorations in psycholinguistics to advanced seminars in modern syntax and semantics, students delve into the mechanisms underlying language processing, including language comprehension, production, and acquisition. The module offers cutting-edge methodologies in language processing, providing hands-on experience with computational tools for linguistic analysis and language models. Through theoretical frameworks, computational approaches, and empirical methodologies, these courses equip students with the analytical tools and conceptual frameworks necessary to investigate the complex dynamics of human language within cognitive systems.

Programming & Computer Modeling Module

Cognitive science as a discipline formed in 1950 following the observed analogies between the working of digital computers and intelligent behavior. Nowadays, computational models allow scientists to construct simulations and explanatory models of cognitive processes, bringing different theories of how our minds work to life. This module equips students with both practical Python programming skills for data analysis and numerical simulations and a deep dive into fundamental concepts like computation, algorithms, models, and simulations. Students will also be exposed to various modeling paradigms and their underlying assumptions. Ultimately, these newly acquired skills and models will be put to the test, tackling the big questions of the digital age: What are the limitations of Artificial Intelligence? How do the digital and analog realms relate to each other? How is the Internet reshaping our social connections?

Statistics & Machine Learning Module

With the development of digital computers and internet technologies we observe an explosion of data collected in all sorts of contexts, from specialized production processes in factories, to everyday human behavior. Statistical and computational techniques provide a robust toolkit for processing, visualizing, and summarizing this wealth of empirical data and making data-driven decisions. In this module students learn statistical techniques useful in the context of experimental social sciences and hypothesis testing, and a modern machine learning toolkit for knowledge discovery from larger datasets. They are introduced to modern neural networks and their practical applications.

Neuroscience Module

The module integrates neuroscience with psychophysiology, offering students the opportunity to gain a comprehensive understanding of the biological foundations of cognition and behavior. The courses within the module take an interdisciplinary approach to exploring the connections between the brain’s physiological structures and processes and mental functions such as perception, learning, memory, and decision-making. The program combines theoretical knowledge with practical skills, preparing students for advanced research and applications in neuroscience, psychology, and related fields.