Master in Cognitive Science
Language and Multimodal Interaction track

Communication via language and other modalities is a fundamental component of human activity.
It is therefore not at all surprising that the technologies originated from the scientific study of these activities are having a major impact on modern society. It is sufficient to think about the role played by Google in everyday life, or the crucial  importance of interface design in the success of technologies such as the iPhone.

The Language and Multimodal Interaction track provides students with the interdisciplinary training  necessary to operate in this area, whether in an academic environment or in an industrial setting.

The two-year Master's course combines a solid foundation in scientific and cognitive methods - modules  in mathematics,  language science, neuroscience, and psychology, including  an introduction to advanced methods such as eye tracking, EEG, and fMRI - with an extensive training in computational methods for the statistical analysis of large amounts of language and perceptual data, and in interface design.  Theoretical knowledge will be supplemented by the experience acquired in substantial practical projects carried out in research and industry labs.
 

Courses (mandatory and elective)

Text Processing (6 ECTS, mandatory)

This course introduces the fundamental techniques to acquire and process textual data, providing students with the necessary background for more advanced HLT study. The first part of the module focuses on the acquisition and pre-processing of large corpora. The next part covers methods for the automatic annotation of data, including lemmatization, part-of-speech and named-entity tagging, and parsing. Next, language modeling techniques are introduced, in particular for word prediction. Finally, methods for extracting semantic knowledge from text are introduced, including lexical acquisition using vector-based representations, word sense disambiguation, and coreference resolution. The module has a practical focus and includes substantial lab experience.

Research Design (9 ECTS, mandatory)

This course will cover some fundamentals of algebra, probability theory, and statistics. Furthermore the course will cover all aspects of a research project, such as , sample sizes, measures, and type of experimental designs. Students will present and comment on their own research projects in progress. Discussions also include presentations of research to various audiences, abstracts, reviews, grant process, and scientific ethics.

Computational methods for data analysis (6 ECTS, mandatory)

Machine learning is the essential key in solving complex problems in several research area such as HCI, pattern recognition, natural language processing, computer vision, etc. The goal of this course is to provide the basic elements in machine learning that will allow the students to understand further problems in the abovementioned areas. The course will cover supervised and unsupervised learning and will focus on clustering, classification, Support Vector Machines, and Bayesian Networks.

Cognitive Psychology (6 ECTS, mandatory)

Cognitive Psychology is the study of the mental processes underlying our ability to perceive, pay attention, think, categorize, use language and remember. Historically, cognitive psychology began with the information processing approach but we will also explore recent research on topics such as emotions and numerical cognition, and will include insights from neuropsychology, neuroimaging and lifespan development. The teaching methods will include demonstrations, class discussion and lectures and will emphasize the critical link between theory and experimentation.

Foundations of Cognitive Neuroscience (9 ECTS, mandatory)

This course will examine the neural basis of higher mental functions, including brain systems supporting perception, object recognition, attention, memory, spatial functions, language, and decision making. We will explore the neuroanatomical and neurophysiological basis of cognitive functions, considering evidence form functional neuroimaging and patients studies. Cognitive neuroscience approaches to disorders such as autism, schizophrenia, and Alzheimer’s disease will also be explored. The teaching methods will include lectures, demonstrations, patient videos, class discussion and practical sessions in different neuroimaging labs. The course will concentrate on language, memory, perception and attentional mechanisms.

HCI & Multimodal Systems (9 ECTS, mandatory)

This course addresses the fundamentals of Human-Computer Interaction with emphasis on interaction design for multimodal systems. The main part of the course will introduce the core of User-Centered Design providing concepts and hands-on practice on techniques for collecting user needs, lo-fi and hi-fi prototyping, formative and summative evaluation. In the final part of the course, students will work in teams to focus on a number of specific advanced topics, such as tabletop interaction, mobile computing, ubiquitous computing etc.

Knowledge Representation (6 ECTS, mandatory)

The course aims at providing participants with the conceptual and technological tools which will allow them to understand, evaluate and use state-of-the-art semantic and knowledge-based technologies for network-based applications, such as knowledge portals, e-commerce platforms, e-* applications.

Computational Vision (6 ECTS, elective)

This course will cover the basic concepts in computer vision. First, the class will present an introduction to low level image analysis methods, including image formation, edge detection, color analysis, feature detection, and image segmentation. further, we are going to discuss more advanced topics including methods for reconstructing three-dimensional scene information using techniques such as depth from stereo, structure from motion, and shape from shading. Finally, the course will present the techniques for motion and video analysis as well as three-dimensional object recognition approaches.

Cognitive Linguistics (6 ECTS, elective)

The course focuses on how language semantically organizes information in the mind. The course presents the fundamental notions of CL: space and cognitive grammar,radial and schematic networks, conceptual metaphors, image-schema, mental space, base-and prototype categorization. Knowledge from this course can be applied to the following fields: bilingualism (L1 and L2 teaching), information retrieval based on images, branding and web marketing, construction of web pages, virtual reality systems, visual communication of visual interfaces, and language of signs.

Independent Studies (6 ECTS, elective)

This course will entail reading and presenting papers and experiments from the recent literature that cover topics studied in the courses fundamentals of cognitive psychology and neuroscience.

Hands on fMRI data analysis (6 ECTS, elective)

This class focuses on fMRI data analysis, i.e. the statistics of fMRI data analysis and how that should influence your design decisions. By understanding the statistical concepts of fMRI data analysis, students will understand the rationale of the preprocessing pipeline in fMRI and the types of choises fMRI reserachers have to make when designing their esperiments. By actually modelling and analyzing fMRI data students will get a deeper understanding of fMRI data analysis and at the same time gain experience that will make it easier for them to read fMRI papers and to perform their own imaging studies in the future.

Neural decoding (6 ECTS, elective)

 

The neural basis of decision making (9 ECTS, elective)

Throughout the course, the primary goals are to: (1)Learn about the academic field of decision neuroscience, its major theories, results, and debates.(2)Become a critical consumer of research findings by learning the methodological standards for evaluating the soundness of such studies.(3)Develop the ability to effectively write and speak about decision theories, results, and debates.(4)Acquire some practical skills for designing and analyzing an experiment in the field of decision neuroscience.

 

For the second year an extensive internship and a research project leading to the Master's dissertation are scheduled.

 

Click here if you want to see the academic calendar and here for the schedule of the classes for this semester