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Course programme for the Academic Year 2018/2019

The Master's Course in Cognitive Science has two tracks - Cognitive Neuroscience (CN) and Languange and Multimodal Interaction (LMI).

Cognitive Neuroscience Track

Mandatory courses

Foundations of Brain Imaging

This course will cover the foundations of neuroimaging techniques commonly used in cognitive neuroscience. Students will obtain a basic understanding (i.e., methodological foundation) of non-invasive brain imaging and neurostimulation techniques used in cognitive neuroscience research. The programme contains specialized modules on the theory and methods of functional and structural magnetic resonance imaging; electro- and magneto-encephalography; transcranial electric and magnetic stimulation, as well as multimodal approaches. At the end of the course, students should be able to describe the basic principles, advantages, limitations and cognitive neuroscience application examples of the neuroimaging methods discussed.

9 credits

Foundations of Cognitive Neuroscience

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 clinical 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. This first part of the course will concentrate on language, memory, perception and attentional mechanisms. At the end of the course, the students should be able to know basic topics in cognitive neuroscience and describe appropriate cognitive neuroscience methods.

9 credits

Foundations of Cognitive Psychology

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. At the end of the course, students should be able to analyze critically the scientific literature on cognitive psychology topics and summarize content of a scientific article with a proper lexicon.

9 credits

Introduction to Human Language

This module is an introduction to language science (linguistics) covering phonetics and phonology, morphology and lexical knowledge, syntax, phrase semantics, discourse, and anaphora. No previous knowledge of linguistics is required. Students attending this module will become familiar with the main current issues and methodologies in the field, and will be able to read the relevant technical literature.

6 credits

Introduction to Computer Programming

The course introduces computer programming, focusing on those aspects that are most relevant to behavioral and neuroimaging studies in cognitive neuroscience. At the end of the course, the students should be able to master the computer language proposed.

6 credits

Neural Foundations of Human Behavior

This course has been designed to cover basic anatomical and functional aspects of the central nervous system. Specific topics covered include neuronal function, synaptic transmission, sensory processing, movement, sleep and neural plasticity. At the end of the course, the students should be able to summarize our understanding of the functional organization of the human brain.

6 credits

Research Design

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 research on cognitive science topics. Discussions also include presentations of research to various audiences, abstracts, reviews, grant process, and scientific ethics.

6 credits

Internship

The internship is a period of training done by the student within the degree program, in order to achieve moments of alternation between study and work and to facilitate future career developments.

15 credits

Master Thesis

The final examination is an important moment in the pathway of study for two primary reasons. First, it allows for verification of the student’s capacity to integrate content from the program and apply this knowledge to his/her own empirical research. Second, it allows for assessment of the student’s skills in formulating, writing and discussing a scientific argument.

30 credits
Two elective courses (12 credits) among:

Clinical Neuropsychology

The aim of this course is to provide an introduction to clinical neuropsychology. The student will be introduced to methods of clinical neuropsychological assessment and rehabilitation. A range of neuropsychological test procedures will be introduced. The student will also be introduced to the neuropsychological profile of a range of neurological disorders assessment and rehabilitation of neuropsychological disorders. At the end of the course, students should be able to describe the main neuropsychological disorders and to know the main assessment and rehabilitation procedure.

6 credits

Current Issues in Neuroscience: Animal Models

The course would provide the theoretical and empirical foundations of comparative research on animal cognition. It will cover all the traditional topics in animal cognition - perception, learning and memory, categorization, thinking and reasoning, and communication/language. Practical in the animal cognition lab will be part of the course.

6 credits

Current Topics in Brain Connectivity

In this seminar course, we will read and discuss up-to-date scientific contributions in the field of general brain connectivity, focusing on both functional and anatomical connectivity measures. The goal of this introductory course is to provide a basic knowledge of the state-of-the-art methods and concepts of accessing brain connectivity measures. The course is based on active learning and participation. At the end of the course, students will acquire a good overview of the current debates on brain connectivity and they will learn the appropriate terminology and computational concepts. They will familiarize with the concepts of experimental connectivity measures and they will be able to critically access new publications on the topic.

6 credits

Developmental  Neuroscience

This course will address molecular, cellular, anatomical and functional aspects of central nervous system development. Specific topics will include embryonic development, postnatal critical periods of visual, auditory and language areas, neurodevelopmental disorders and neural basis of adolescent behavior. At the end of the course, the students should be able to acquire an updated view of our understanding of human brain development and its impact on brain pathologies.

6 credits

Hands on Methods Course

The first part of the class focuses on fMRI data analysis, i.e. the statistics of fMRI data analysis and how that should influence your design decisions and conclusions. By understanding the statistical concepts of fMRI data analysis, students will understand the rationale of the preprocessing pipeline in fMRI and the types of choices fMRI researchers have to make when designing their experiments. By actually modeling 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. The second part of the course involves the hand on analysis of MEG data.

6 credits

Neuroscience

This course will look at a number of the major neural systems in detail, examining their structure and function.  Contemporary studies will provide much of the teaching material and a strong emphasis will be placed on the latest developments in each field. Subjects to be covered will include the visual system, the auditory system, motor pathways, attention mechanisms, eye movements and memory. 

6 credits

Language and Multimodal Interaction Track

Mandatory courses

Computational Linguistics

The course introduces the basics of computational linguistics by giving an overview of the field. It then focuses on the syntax and semantics of natural language familiarizing students with lexicalized formal grammars and computational semantics models. The second part of the course introduces students to multimodal models by considering in particular language and vision modalities. Students will hence gain a good overview of the field, its methods and main long-term goals. 

9 credits

Current Topics in Language and Brain

In the first part of the course, we will address how different data sources have been used in the past to draw inferences on the relationships between language and the brain, and if/how the same sources can be used to complement current neuroimaging techniques. In the second part of the course, we will focus on three topics: the functional neuroanatomy of reading/writing, and how the brain adapted to the development of written language; the neural underpinnings of (morpho) syntactic skills; the neural correlates of phonological working memory.

6 credits

Foundations of Cognitive Psychology

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. At the end of the course, students should be able to analyze critically the scientific literature on cognitive psychology topics and summarize content of a scientific article with a proper lexicon.

9 credits

Functional Anatomy of Language  

This course provides information about the organization of the brain and its networks, focusing on the neural correlates of language and how, during the years, this knowledge has evolved. It provides also some basic information on the effects of brain lesions.

6 credits

Introduction to Human Language

This module is an introduction to language science (linguistics) covering phonetics and phonology, morphology and lexical knowledge, syntax, phrase semantics, discourse, and anaphora. No previous knowledge of linguistics is required.

6 credits

Introduction to Machine Learning for Natural Language Processing

This class presents a survey of methods from the fields of statistics and machine learning aimed at extracting generalizations from example data, and use them to automatically analyze new data. The class focuses on case studies in the analysis of different components of natural language.

6 credits

Research Design

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. At the end of the course, the students should be able to design an experiment.

6 credits

Internship

This module is an introduction to language science (linguistics) covering phonetics and phonology, morphology and lexical knowledge, syntax, phrase semantics, discourse, and anaphora. No previous knowledge of linguistics is required.

15 credits

Master Thesis

The final examination is an important moment in the pathway of study for two primary reasons. First, it allows for verification of the student’s capacity to integrate content from the program and apply this knowledge to his/her own empirical research. Second, it allows for assessment of the student’s skills in formulating, writing and discussing a scientific argument.

30 credits
Two elective courses (12 credits) among:

Computational Skills for Text analysis 

The course introduces computer programming, focusing on those aspects that are most relevant to text processing: regular expressions, text segmentation, and extraction of lexical and linguistic information from text.

6 credits

Foundations of Cognitive Neuroscience

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 clinical 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. This first part of the course will concentrate on language, memory, perception and attentional mechanisms. At the end of the course, the students should be able to know basic topics in cognitive neuroscience and describe appropriate cognitive neuroscience methods.

6 credits

Human Language Technologies

The course introduces how to computationally approach and manage human language technologies. The topics covered are creation of annotated corpora, syntax (e.g. parsing), semantics (e.g. similarity, word sense disambiguation), until more advanced issues of pragmatics such as affective and emotion recognition, computational treatment of persuasive and creative language. Particular attention will be given to the use of out-of-the-shelf NLP tools, so that the students can gain hands on experience.

6 credits

Logical Structures in Natural Language

A general introduction to the study of meaning in natural language using the tools of formal semantics. Topics include the relation of predicate logic with natural language operators; lexical semantics, compositional semantics, nominal and verbal quantifications; modification; event semantics; genericity, and the semantics of grammatical features.

6 credits

 

Aggiornato il
20 June 2018