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The Master's Course in Cognitive Science has two tracks

  • Cognitive Neuroscience
  • Languange and Multimodal Interaction

 

Cognitive Neuroscience Track

First year

Mandatory courses

Course Credits (ECTS)

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 noninvasive 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

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

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

Introduction to Human Language

6

Introduction to Computer Programming

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

6

Neural Foundations of Human Behaviour

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

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

Free choice courses

The curriculum provides for the acquisition of 12 ECTS credits without scientific disciplinary sector constraints chosen from the teaching activities that are specifically activated by degree course and published annually in the manifesto of studies or among those activated by the University.

12

2 elective courses (12 credits)

Course Credits (ECTS)

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

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

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

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 behaviour. 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

Hands on Methods

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 modelling and analysing 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

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

 

Second year

Mandatory courses

Course Credits (ECTS)

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

Master Thesis

30

 

Language and Multimodal Interaction Track

First year

Mandatory courses

Courses Credits (ECTS)

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

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

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

Functional Anatomy of Language

6

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

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 analyse new data. The class focuses on case studies in the analysis of different components of natural language.

9

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

Free choice courses

The curriculum provides for the acquisition of 12 ECTS credits without scientific disciplinary sector constraints chosen from the teaching activities that are specifically activated by degree course and published annually in the manifesto of studies or among those activated by the University.

12

 

2 elective courses (12 credits)

Course Credits (ECTS)

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

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

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

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

 

Second year

Mandatory courses

Course Credits (ECTS)

Internship

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

15

Master Thesis

30
Aggiornato il
14 February 2019