The Master's Degree in Cognitive Science offers 3 tracks:

All the 3 tracks also include an extensive internship and a research project where students acquire an invaluable direct exposure to the scientific research practice having access to the laboratories at CIMeC, working with CIMeC PIs and their groups, and gaining hands-on experience with cutting-edge research technologies.

Cognitive Neuroscience Track

Cognitive neuroscience is the study of the mind and brain, and it is concerned with the neural and cognitive bases of how and why people perceive, think and act the way they do. The CN track trains students to combine a variety of behavioural and neuroimaging techniques to understand the neuro-cognitive mechanisms underlying human cognitive functions, from perception to motor control, from language and memory to conceptual processing. It offers a range of theoretical and practical courses in basic and advanced cognitive neuroscience and neurobiology, in healthy individuals and in neuropsychological patients, and courses in advanced signal processing and data analysis with a special focus on brain imaging (EEG, MEG, functional and anatomical MRI) and brain stimulation techniques (TMS, tDCS). This track prepares students to pursue a research-oriented career in the field of human cognitive neuroscience, whether in academia or industry.

Cognitive Neuroscience Track - mandatory courses
Course Content
Foundations of Cognitive Psychology and Neuroscience 1 This course will examine how we perceive, pay attention, remember, plan and represent ours and others’ actions. It will explore the neuroanatomical and neurophysiological basis of cognitive functions, considering evidence from functional neuroimaging and clinical studies. The teaching methods will include lectures, demonstrations, patient videos, class discussion. By the end of this course, students will have gained a much better understanding of the basic topics in cognitive psychology and neuroscience and will be able to describe the different methods
Foundations of Cognitive Psychology and Neuroscience 2 This course will explore the neuroanatomical and neurophysiological basis of higher-level cognitive functions, such as language, conceptual processing and mathematical thinking. It considers evidence from human behaviour, electrophysiology, and functional neuroimaging during the life-span, and also adopts a comparative perspective. The teaching methods will include lectures, demonstrations, patient videos, class discussion. By the end of this course, students will have gained a much better understanding of the basic topics in cognitive psychology and neuroscience and will be able to describe the different methods.
Advanced Cognitive Psychology and Neuroscience This course will sample from across cognitive psychology and neuroscience, offering an in-depth look into a selection of contemporary and influential topics. This course will involve the reading, active discussion and presentation of original research papers and review articles. At the end of the course the students will be able to: understand the main notions and the key problems related to the specific topic addressed in the module and to analyse critically the scientific literature.
Research Design This course first Introduces students to fundamental concepts in scientific research and experimental design.  In the second part it covers core topics in descriptive and inferential statistics.  Students in the CogNeuro track will be taking this as a 9CFU course that includes a separate, more in depth hands-on unit in inferential statistics and advanced descriptive methods. 
Neurolinguistics This course will cover the anatomo-functional correlates of language and will describe the main deficits that can appear following lesions of these structures, and  how these deficits can be investigated. At the end of the course, the students should be able to run experimental studies to investigate the different stages of  language processing.
Introduction to Computer Programming (Matlab) 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.
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 neuroanatomy, cellular function of excitable cells, synaptic transmission and plasticity, sensory processing, visceral homeostatic and non-homeostatic control, the voluntary and affective motor systems, brain states (sleep, motivation), neural bases of flexible behavior and neuropharmacology. At the end of the course, the students should be able to make informed inferences on which neural bases are associated to any given behavior of the human repertoire.
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 methods used in cognitive neuroscience research. The programme contains specialized modules on the theory and methods of functional and structural magnetic resonance imaging as well as electro- and magneto-encephalography 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.
Cognitive Neuroscience Track - 2 elective courses among
Course Content
Clinical Neurology and Neuropsychology The aim of this course is to provide basic concepts and knowledge on the clinical neurosciences, with emphasis on behavioral and psychological aspects. The student will be introduced to the main categories of disorders of the nervous system, focusing mainly on the etiology, physio-pathological mechanisms, and impact on behavior. In a second section we will address the topics of clinical and cognitive neuropsychology. The course will cover the history of neuropsychology, the main neuropsychological syndromes, and the essential methodological tools for neuropsychological diagnosis. This course should provide the students with the basic knowledge to understand brain disorders and their role as model to test hypotheses in the cognitive neurosciences.
Fundamental Hands on Functional Neuroimaging Analysis 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.
Cognitive neuroscience of infant development This module provides students with an advanced and in depth view of ongoing research in the field of infant cognition. The module takes the format of a journal club, where students will read and present research papers on cognitive development. The module convenor will facilitate the discussion, creating a learning friendly atmosphere of open debate, where all participants are encouraged to engage in the discussion, expressing their opinion about open problems in cognitive development, making critical comments and asking clarification questions. The course will cover empirical studies, contemporary theories and research techniques, including neuroscience methods, in the field of cognitive development of human infants (below 2 years of age). Special attention will be dedicated to social cognitive development.
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.
Scientific Communication The goal of the course is to improve students’ proficiency in presenting scientific research. Multiple modalities of communication are addressed including conference presentation, poster preparation, and manuscript drafting. Students learn through demonstrations and exercises, how to most effectively present scientific discoveries. The overall goal of the course is to sharpen the students’ verbal, written, and visualization skills to make them effective communicators of scientific material. An additionall module will be dedicated to the use of social media for scientific dissemination to the general public.  

Computational and theoretical modelling of Language and Cognition Track

Communication via language and other modalities is a fundamental component of human activity. It is therefore not surprising that the technologies originated from the scientific study of these activities are having a major impact on modern society. This track emphasizes the use of computational approaches to model and understand human cognitive functions, with a special emphasis on language. The program offers basic courses in theoretical and computational linguistics, computer science and cognitive neuroscience, allowing students to develop expertise in aspects of language and human cognition that AI systems could or should model. The program also offers courses on research design and evaluation methods, which help students acquire the necessary skills to evaluate and improve the design of models and contribute to data collection and evaluation.  Examples of professional outcomes include working as AI enablers, helping develop unbiased intelligent systems that meet human needs, or support health practitioners working on cognitive impairments.

Computational and theoretical modelling of Language and Cognition Track - mandatory courses
Course Content
Foundations of Cognitive Psychology and Neuroscience The aims of the course are to provide students with a broad understanding of the mental processes underlying cognitive functions. It will explore the neuroanatomical and neurophysiological basis of cognitive functions, considering evidence from functional neuroimaging and clinical studies. In doing so, students will also learn about the goals of cognitive psychology and cognitive neuroscience research and the methods that are being employed to reach these goals.
Introduction to Computer Programming (Python) 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, word embeddings.
Research Design This course first Introduces students to fundamental concepts in scientific research and experimental design.  In the second part it covers core topics in descriptive and inferential statistics. 
Mathematical basics for Cognitive Science The course introduces the basics of linear algebra, a beautiful and useful part of mathematics. We will move gradually from numbers to vectors to subspace, analyze different ways to understand a matrix (e.g., eigenvalues and eigenvectors), and conduct special operations (e.g., the derivative). Theory and exercises will allow students, at the end of the course, to grab the essence of mathematics: see the meaning in the numbers and their patterns. 
Machine Learning for NLP This class provides a survey of methods from the fields of statistics and machine learning, showing how they extract generalizations from example data and use them to automatically analyze new data. The course focuses on case studies in the area of natural language, illustrating how different techniques are deployed in the investigation of core linguistic questions.
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. 
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. Both symbolic and statistical approaches are discussed. Students will hence gain a good overview of the field, its methods and main long-term goals. 
Computational Modelling of Perception The course introduces the students to state-of-the-art research in computational modelling of visual perception with a particular focus on Deep Convolutional Neural Networks of object recognition. The course will tackle the main achievements of machines in mimicking human perception but at the same time it will address the large gaps still remaining to capture the full complexity of representational space that underlies human object vision with a particular focus on the critical role played by the interaction between different cognitive domains. The second part of the course introduces students to multimodal models by considering in particular language and vision modalities.
Computational and theoretical modelling of Language and Cognition Track - 2 elective courses among
Course Content
Machine Learning for NLP II The field of Natural Language Processing evolves at a tremendous pace. This class focuses specifically on introducing state-of-art NLP systems, and deepening students' understanding of the latest research questions in computational linguistics. Students get to exercise their code reading skills by inspecting the internals of freely available neural models. They also learn to review and critique existing systems from different theoretical standpoints. Knowledge of the content addressed in “Machine Learning for Natural Language Processing” is a prerequisite for attending this course.
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.
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. 
Semantics and Cognition The past decade has seen increasing interaction between cognitive science and formal semantics. The course aims at giving an overview of the trends and methods in this emerging research area. We will focus on experimental and computational modeling work that tries to explain constraint cross-linguistic semantic variation in terms of cognitive limitations such as learnability, complexity, or information processing bottlenecks.

 Fundamental Behavioural Neuroscience Track

The FBN track trains students to combine behavioural, electrophysiological and molecular biology in animals of different species to unveil the neural underpinnings of basic sensory and cognitive functions with a comparative perspective. It offers a range of theoretical courses in basic and advanced neurobiology and neuroscience, in healthy animals and in animal models of clinical conditions, and a set of hands-on courses in fundamental behavioural neuroscience data recordings and analyses. Behavioural techniques include conditioning, imprinting and preference choice, and neuroscientific techniques include  single cell recordings, two-photon calcium imaging, immunohistochemical and fluorescent microscopy, gene expression analysis, genome editing, neuronal cell culture and viral-mediated gene transfer. This track prepares students to pursue a research-oriented career in the field of fundamental cognitive and behavioural neuroscience, whether in academia or industry.

Fundamental Behavioural Neuroscience Track - mandatory courses
Course Content
Foundations of Cognitive Psychology and Neuroscience I This course will examine how we perceive, pay attention, remember, plan and represent ours and others’ actions. It will explore the neuroanatomical and neurophysiological basis of cognitive functions, considering evidence from functional neuroimaging and clinical studies. The teaching methods will include lectures and class discussion. By the end of this course, students will have gained a much better understanding of the basic topics in cognitive psychology and neuroscience and will be able to describe the appropriate methods.
Introduction to Computer Programming (Matlab) 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 will have developed the specific skills needed for cognitive and behavioural sciences and built a solid foundation in computer language to form the basis for future development.
Research Design This course first Introduces students to fundamental concepts in scientific research and experimental design. In the second part it covers core topics in descriptive and inferential statistics. Students in the FBN track will be taking this as a 9CFU course that includes a separate, more in depth hands-on unit in inferential statistics and advanced descriptive methods.
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 neuroanatomy, cellular function of excitable cells, synaptic transmission and plasticity, sensory processing, visceral homeostatic and non-homeostatic control, the voluntary and affective motor systems, brain states (sleep, motivation), neural bases of flexible behavior and neuropharmacology. At the end of the course, the students should be able to make informed inferences on which neural bases are associated to any given behavior of the human repertoire.
Animal Cognition and Neuroscience The course will first address basic mechanisms of animal cognition and then specific topics will be discussed with practicals in the laboratory making use of different kinds of animal model systems, in particular avian brains, fish brains and invertebrate brains.
Brain Development and Disease This course will address molecular, cellular, anatomical and functional aspects of central nervous system development and major neuropsychiatric/neurological disorders. Specific topics will include embryonic development, postnatal critical periods for acquisition of sensory, motor and cognitive functions, neurodevelopmental disorders, and major neurodegenerative diseases. 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.
Neurolinguistics This course will cover the anatomo-functional correlates of language and will describe the main deficits that can appear following lesions of these structures, and how these deficits can be investigated. At the end of the course, the students should be able to run experimental studies to investigate the different stages of language processing.
Fundamental Behavioural Neuroscience Track - 2 elective courses among Group A
Course Content
Cellular and Molecular Neuroscience The main purpose of the course is to provide students with a general understanding of the fundamental molecular properties of neurons and neuronal networks. The course will also examine the basic principles of neuronal communication, including synaptic transmission and synaptic signaling, and their modulation. The course will also describe the main animal models and experimental methodologies used in neuroscience. The course also involves practical laboratory activities, exploring up to date cellular and molecular techniques currently used in neuroscience.
Comparative Neuroanatomy and Evolution Brains come in many different shapes, sizes and internal structures, which all evolved to cope with environmental pressures. This course will provide students with a survey on the evolution of central nervous systems in animals, with a main focus on vertebrate brains. By the end of the course, students will be able to recognise major structures composing vertebrate brains across species and navigate through the fundamental organization of the nervous systems using the basic principles of brain evolution.
Invertebrate Neuroscience The course aims at introducing students to a wide variety of invertebrate animal models (e.g. cephalopods, insects, nematodes), some of which have been historically fundamental to the birth and advancement of neuroscience. Through different case studies, this course will show the importance of choosing a specific animal model (and the techniques that can be applied to it) to try to answer specific scientific questions about the evolution and function of neurocognitive systems.
Fundamental Behavioural Neuroscience Track - 2 elective courses among Group B
Course Content
Clinical Neurology and Neuropsychology The aim of this course is to provide basic concepts and knowledge on the clinical neurosciences, with emphasis on behavioral and psychological aspects. The student will be introduced to the main categories of disorders of the nervous system, focusing mainly on the etiology, physio-pathological mechanisms, and impact on behavior. In a second section we will address the topics of clinical and cognitive neuropsychology. The course will cover the history of neuropsychology, the main neuropsychological syndromes, and the essential methodological tools for neuropsychological diagnosis. This course should provide the students with the basic knowledge to understand brain disorders and their role as model to test hypotheses in the cognitive neurosciences.
Cognitive neuroscience of infant development This module provides students with an advanced and in depth view of ongoing research in the field of infant cognition. The module takes the format of a journal club, where students will read and present research papers on cognitive development. The module convenor will facilitate the discussion, creating a learning friendly atmosphere of open debate, where all participants are encouraged to engage in the discussion, expressing their opinion about open problems in cognitive development, making critical comments and asking clarification questions. The course will cover empirical studies, contemporary theories and research techniques, including neuroscience methods, in the field of cognitive development of human infants (below 2 years of age). Special attention will be dedicated to social cognitive development.
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.

Free choice courses for all tracks

Students have to choose 2 courses among one of the following:

  • Advanced Hands on fMRI Analysis
  • Advanced Hands on M/EEG Analysis
  • Advanced Topics in Perception and Attention
  • Advanced Topics in Reasoning and Decision Making
  • Advanced Topics in Motor Cognition
  • Multimodal Electrophysiological Recording and Stimulation
  • Neuroimaging for data science
  • Advanced Language/Cognition
  • Language and Social Cognition
  • Grounded Language Processing
Aggiornato il
3 February 2023