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Course programme for the Academic Year 2017/2018

The Master's Course in Cognitive Science has two tracks - Cognitive Neuroscience (CN) and Languange and Multimodal Interaction (LMI). 
The opportunity to activate some or all of the elective courses outlined will be evaluated each Academic Year.

Cognitive Neuroscience Track

Mandatory courses

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 analyse critically the scientific literature on cognitive psychology topics and summarize content of a scientific article with a proper lexicon.

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

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. 

9 credits

Foundations of Brain Imaging 

This course will cover basic neural anatomy and methodology for the application of the main techniques used in cognitive neuroscience, such as functional and structural Magnetic Resonance Imaging, Transcranial Magnetic Stimulation, Magnetoenchelalography and EEG. At the end of the course, the students should be able to describe the main techniquest used in Cognitive Neuroscience.

6 credits

Computational Methods for Data Analysis

Computational methods such as machine learning are essential in solving complex problems in research area such as neuroimaging, HCI, pattern recognition, natural language processing, computer vision, etc. The goal of this course is to provide the basic elements in computational methods such as machine learning that will allow the students to understand further problems in the abovementioned areas.

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

Internship

15 credits

Master Thesis

30 credits
One elective course (6 credits) among:

Intro 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

Advanced Topics in Language/Cognition

This course is designed for students who already have a strong background in the study of language. This advanced course provides an opportunity for an in-depth study of a particular area of language science. At the end of the module the student will be able to: understand the main notions and the key problems related to the specific topic addressed in the module; know the technical terminology related to the problem at issue; know the way in which the problem has been addressed through time (i.e. the history of the problem); understand at least the gist of the relevant technical literature and be able to read new literature independently.

6 credits
Two elective courses (12 credits) among:

Neural Decoding

This course examines the methods used in cognitive neuroscience to link patterns of neural activity to specific stimuli or brain states. In particular, the course focuses on the application of neural decoding and “mind reading” with fMRI.

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

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

Current Debates in Cognitive Neuroscience

This advanced course provides an opportunity for an in-depth study of a current issues and debates in the area of cognitive neuroscience.

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

Clinical Neuroscience

This course examines the application of neuroscience methods to the clinical setting. Topics include the application of neuroimaging in the daily hospital setting and advanced MR techniques for clinically oriented research on neurogenerative and neuropsychiatric diseases. The course includes lectures, case studies and practicals.

6 credits

Advanced Topics in Perception and Attention

This course is designed for students who already have a background in the study of perception and attention. This advanced course provides an opportunity for an in-depth study of current work in perception and attention, through seminars, readings and discussions. At the end of the course the student will be able to: understand the main notions and the key problems related to the specific topic addressed in the module and to read new literature independently.

6 credits

Advanced Topics in Cognition

This course is designed for students who already have a background in the study of cognition. This advanced course provides an opportunity for an in-depth study of a particular area of cognition, through seminars, readings and discussions. At the end of the course the student will be able to: understand the main notions and the key problems related to the specific topic addressed in the module and to read new literature independently.

6 credits

The Neuro-Cognitive Basis of Negation

This course will cover what it means to understand negation, drawing on work in computational and neurobiological models of psychology, social cognition, and linguistics.  Its aim is to expose students to a body of highly interesting and provocative work on negation. We will discuss major lines of thought on the topic beginning with pioneering work in the 1960s and continuing to present day.  We will discuss behavioral studies, as well as those using tools of neuroscience such as EEG, MEG and fMRI. Students attending this course 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

Philosophy of Language

Philosophy of language is a field of research intersecting many others in Cognitive Science, such as linguistics, anthropology, ontology, perception, mind, and cognition. The course focuses on how different languages semantically organize information in the mind. The course presents the fundamental notions of semantics, conceptualization, categorization, and conceptual spaces. At the end of the course, the students should be able to present and discuss the key papers on the topic.

6 credits

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 rehabilation procedure.

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

Neurophysiological Bases of Language

The course will introduce students to neurolinguistics, and address the question of what can we learn from non invasive neurocognitive experiments about language processing in the brain. Most of the data discussed come from electropshiological and neuromiagins studies on healthy adults but theories and models will be discussed also in reference to data that comes from studies on language acquisition and loss.

6 credits

Current topics on Healthy Aging

The aim of the course is to provide students with a broad understanding of the current issues tackled by research on aging, mainly from the perspective of cognitive neuroscience. Other points of view (e.g., such as biology and engineering) will also be considered. Teaching methods will include lectures, readings and discussions. At the end of the course the student will be able to: understand the main notions and the key problems related to the specific topic addressed in the module and to read new literature independently.

6 credits

Language and Multimodal Interaction Track

Mandatory courses

Cognitive Psychology

The course 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 analyse critically the scientific literature on cognitive psychology topics and summarize content of a scientific article with a proper lexicon. 

6 credits

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

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.

9 credits

Understanding Cognitive Neuroscience  

The aims of the course are to provide students with a broad understanding of cognitive neuroscience including dominant theories of the neural underpinnings of a variety of cognitive processes and the research that has led to those theories. In doing so, students will also learn about the goals of cognitive neuroscience research and the methods that are being employed to reach these goals.

9 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

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

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

Internship

15 credits

Master Thesis

30 credits
One elective course (6 credits) among:

Intro 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

Advanced Topics in Language/Cognition

This course is designed for students who already have a strong background in the study of language. This advanced course provides an opportunity for an in-depth study of a particular area of language science.

6 credits
One elective course (6 credits) among:

Knowledge Representation

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.

6 credits

Computational Methods for Data Analysis

Computational methods such as machine learning are essential in solving complex problems in research area such as neuroimaging, HCI, pattern recognition, natural language processing, computer vision, etc. The goal of this course is to provide the basic elements in computational methods such as machine learning that will allow the students to understand further problems in the abovementioned areas. 

6 credits

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
One elective course (6 credits) among:

Intro to AI 

This course is an introduction to Artificial Intelligence from a cognitive perspective. It will cover knowledge representation and reasoning, learning, and natural language understanding, discussing in each area both the psychological evidence and computational models. The course includes lab work during which the students will acquire familiarity with artificial intelligence programming and tools.

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

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

HCI & Multimodal Systems 

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.

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

Computational Vision 

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.

6 credits

The Neuro-Cognitive Basis of Negation

This course will cover what it means to understand negation, drawing on work in computational and neurobiological models of psychology, social cognition, and linguistics.  Its aim is to expose students to a body of highly interesting and provocative work on negation. We will discuss major lines of thought on the topic beginning with pioneering work in the 1960s and continuing to present day.  We will discuss behavioral studies, as well as those using tools of neuroscience such as EEG, MEG and fMRI.

6 credits

Introduction to Computer Programming

The course introduces computer programming, focusing on those aspects that are most relevant for natural language processing. At the end of the course, the students should be able to master the computer language proposed.

6 credits

Neurophysiological Bases of Language

The course will introduce students to neurolinguistics, and address the question of what can we learn from non invasive neurocognitive experiments about language processing in the brain. Most of the data discussed come from electropshiological and neuromiagins studies on healthy adults but theories and models will be discussed also in reference to data that comes from studies on language acquisition and loss.

6 credits

Mind-Brain Interaction and Cognitive Constraints

The course presents some basic concept about mind/brain interaction and the biases that affect human performance. Such biases will be analyzed with reference to how people use and interact with technologies.

6 credits

Prototyping Interactive Systems

The course covers methodologies for designing and prototyping graphic user interfaces. Principles of design research and visual communication are presented in the context of interaction design, cognition and user behavior. Usability testing techniques will also be discussed.

6 credits

 

Aggiornato il
12 Luglio 2017