Courses

Cognitive, Computational and Social Neurosciences

Academic Year 2016 - 2017

Advanced Neuroimaging

Abstract:
Early brain functional studies, based on MRI , PET or EEG, focused on univariate analyses, in which the activity of each region is processed independently from each other. Nowadays, multivariate machine learning techniques have been developed to model complex, sparse neuronal populations. This course will provide an introduction to new methods and cutting-edge machine-learning techniques in the neuroimaging field by exploring multivariate statistical modeling of brain-activity data and computational modeling of brain information processing. Specifically, the course focuses on machine learning decoding and encoding perspectives in fMRI and novel methods (e.g., Representational Similarity Analysis) to explore and analyze brain data. A comprehensive review of model validation and statistical inference is provided.
In addition, hardware and software implementation recently allowed to combine different neural measures with different spatial and temporal resolutions within the same experimental session. The course also discusses the transdisciplinary approach combining different neuroimaging techniques in unique methodological frameworks and the advent of ultrahigh field neuroimaging.
Hours:
30
Professors/Lecturers:
Tbd; Nicola Vanello (Università degli Studi di Pisa); Mauro Costagli (Fondazione IMAGO7 Pisa); Andrea Leo (Centro di Ricerca "E. Piaggio")
Compulsory for:
Cognitive, Computational and Social Neurosciences

Advanced Seminars (long seminar without exam)

Abstract:
TBD
Hours:
30
Professors/Lecturers:
Maria Luisa Catoni (IMT Lucca); Tbd
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Cognitive, Computational and Social Neurosciences

Advanced Topics of Networks

Abstract:
Complex Networks are an ubiquitous presence in Economic and Financial systems and in the era of massive production of electronic data coming from all sort of devices it is of crucial importance to have the right tools to manage and extract from them all the valuable information. To this aim during this course we will develop both the basic theoretical tools and the practical coding technics to tackle these kind of systems, ranging from the International Trade and the Financial Networks, to the World Wide Web and the Social Networks.

In particular Complex Networks Theory proved to be successful in the process of handling this enormous quantity of data and in order to apply these concepts to the various cases it is crucial to define a clear strategy and guidelines to represent the system data in the shape of a Network.

We shall present some cases of study and introduce the computational instruments to handle this data. The course will be based on the text "Data Science and complex networks" G. Caldarelli A. Chessa OUP 2016.

Prerequisites: Networks
Hours:
20
Professors/Lecturers:
Guido Caldarelli (IMT Lucca); Alessandro Chessa (IMT Lucca); Michelangelo Puliga (IMT Lucca)
Specializing course for:
Economics, Management and Data Science
Also available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering

Basic Neuro-Linguistics

Abstract:
Language springs from distributed, basic as well as higher sensory and cognitive functions. The course will explore the evolutionary and neural bases of language development, from the low-level perceptual-motor stage to the combinatory, attentive, mnemonic processes driving morphonsyntax and eventually, semantics and conceptualization.
Hours:
14
Professors/Lecturers:
Alessandra Rampinini (IMT Lucca)
Compulsory for:
Cognitive, Computational and Social Neurosciences
Also available for:
Analysis and Management of Cultural Heritage

Basic Principles and Applications of Brain Imaging Methodologies to Neuroscience

Abstract:
The course aims at introducing the fundamentals of brain metabolism and brain imaging methodologies. Neuroimaging techniques provided cognitive and social neuroscience with an unprecedented tool to investigate the neural correlates of behavior and mental functions. Here we will review the basic principles, research and clinical applications of positron emission tomography (PET), functional magnetic resonance imaging (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG), non-invasive brain stimulation tools. Solid background in the concepts common to many types of neuroimaging, ranging from study design to data processing and interpretation, will be discussed to address neuroscientific questions. In particular, we will first review the basics of neurophysiology to understand the principles of brain imaging. Then, methodologies of data processing for the main brain imaging tools will be provided to the students with hands-on sessions: students will become familiar with the main pipelines for PET, fMRI and EEG data reconstruction, realignment, spatio-temporal normalization, first and second-level analyses. At the end of the course, students are expected to have general background knowledge of the basic principles, methodologies and applications of the most important brain functional techniques and to be prepared to evaluate the applicability of, and the results provided by, these methodologies for different problems in cognitive and clinical neuroscience.
Hours:
64
Professors/Lecturers:
Emiliano Ricciardi (IMT Lucca); Monica Betta (IMT Lucca); Simone Rossi (Università degli Studi di Siena); Luca Cecchetti (IMT Lucca); Luca Turella (Università degli Studi di Trento)
Compulsory for:
Cognitive, Computational and Social Neurosciences

Computer Programming and Methodology

Abstract:
This course aims at introducing to students principles and methodologies of computer programming. Emphasis is on good programming style, techniques and tools that allow efficient design, development and maintenance of software systems. The course focuses on the design of computer applications drawing attention to modern software engineering principles and programming techniques, like object-oriented design, decomposition, encapsulation, abstraction, and testing. A significative case study is used to allow students to experiment with the principles and techniques considered in this course. Depending on the background of the class, Java, C++, and/or Python are considered in the course.
Hours:
20
Professors/Lecturers:
Michele Loreti (Università degli Studi di Firenze)
Available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Contextual Analysis and Individual Objects: Arts, Sciences, Techniques, Beliefs (the course includes research field trips)

Abstract:
Art objects, objects of use (cultural, exchange, prestige). The circulation of ideas, believes and technologies through the circulation of objects. Tools for the contextual analysis of art-objects.
Hours:
30
Professors/Lecturers:
Linda Bertelli (IMT Lucca)
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Cognitive, Computational and Social Neurosciences

Critical Thinking (long seminar without exam)

Abstract:
Critical Thinking is an introductory course in the principles of good reasoning. Its main focus lies in arguments, their nature, their use and their import. Unlike a course in pure Logic, which would spell out universal formal rules of correct reasoning, Critical Thinking is more concerned with the unruly nature of real argumentation that does not allow unambiguous and definite formalization. The course is designed to serve as a methodical preparation for more effective reasoning and improved cognitive skills. Its ambition is to develop those intellectual dispositions that are essential for effective
evaluation of truth claims as well as for making reasonable decisions based on what we know or
believe to know. It is more about the quality of our beliefs and the reasons that support them than about their content. It will make ample use of examples taken from real world case studies, books, scientific or newspaper articles. Students will be encouraged to participate in the discussion over each example, and to find out more of their own.
Hours:
10
Professors/Lecturers:
Stefano Gattei (Chemical Heritage Foundation, Philadelphia)
Compulsory for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences
Also available for:
Economics, Management and Data Science

Cultural Heritage and Law

Abstract:
International Law, EU Law, and Domestic Law on Cultural Heritage. Basic elements of comparative law. Definition of Cultural Heritage. The institution of protection of cultural heritage in Italy. Fundamental principles and main public interests: protection, circulation, access. Problems and cases (Case law). - European Landscape Convention and Domestic Law on Landscape. Basic elements of comparative law. Principles and main issues: definition of landscape; levels of governance; public law instruments.Problems and cases (Case law).
Hours:
60
Professors/Lecturers:
Lorenzo Casini (IMT Lucca)
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Cognitive, Computational and Social Neurosciences

Decision-Making in Economics and Management

Abstract:
The main goals of the course are:

(1) to take economic theories and methodologies out into the world, applying them to interesting questions of individual behavior and societal outcomes;

(2) to develop a basic understanding of human psychology and social dynamics as they apply to marketing contexts;

(3) to become familiar with the major theory and research methods for analyzing consumer behavior; (4) to develop market analytics insight into consumer actions.

Most of time will be devoted to close reading of research papers, including discussion of the relative merits of particular methodologies. Students will participate actively in class discussion, engage with cutting-edge research, evaluate empirical data, and write an analytical paper. The course aims at enabling students to develop and enhance their own skills and interests as applied microeconomists.
Hours:
20
Professors/Lecturers:
Massimo Riccaboni (IMT Lucca); Zhen Zhu (IMT Lucca)
Compulsory for:
Analysis and Management of Cultural Heritage; Economics, Management and Data Science
Also available for:
Cognitive, Computational and Social Neurosciences

Forensic and Legal Psychology

Abstract:
tbd
Hours:
12
Professors/Lecturers:
Pietro Pietrini (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences; Economics, Management and Data Science

Foundations of Probability and Statistical Inference

Abstract:
This course aims at introducing, from an advanced point of view, the fundamental concepts of probability and statistical inference. Some proofs are sketched or omitted in order to have more time for examples, applications and exercises.
In particular, the course deals with the following topics:

• probability space, random variable, expectation, variance, cumulative distribution function, discrete and absolutely continuous distributions, random vector, joint and marginal distributions, joint cumulative distribution function, covariance,
• conditional probability, independent events, independent random variables, conditional probability density function, order statistics,
• multivariate Gaussian distribution,
• probability-generating function, Fourier transform/characteristic function,
• types of convergence and some related important results,
• point estimation, interval estimation, hypothesis testing, linear regression, introduction to Bayesian statistics.

Students may be exonerated up to a maximum of 10 hours according to their background.
Hours:
30
Professors/Lecturers:
Irene Crimaldi (IMT Lucca)
Compulsory for:
Economics, Management and Data Science
Also available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering

Funding and Management of Research and Intellectual Property (long seminar without exam)

Abstract:
The long seminar aims at providing an overview on the management of intellectual property rights (copyright transfer agreements, open access, patents, etc.). Funding opportunities for PhD students, post-docs, and researchers are also presented (scholarships by the Alexander von Humboldt Foundation; initiatives by the Deutscher Akademischer Austausch Dienst; scholarships offered by the Royal Society in UK; bilateral Italy-France exchange programmes; Fulbright scholarships; Marie Curie actions; grants for researchers provided by the European Research Council). For each funding scheme, specific hints on how to write a proposal are given.
Hours:
10
Professors/Lecturers:
Marco Paggi (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Game Theory

Abstract:
Mechanism Design. Revelation principle, Dominance and Nash Implementation. Strategic and Axiomatic Bargaining. Asymmetric Information and Optimal Contracts. Moral Hazard and Adverse Selection models. Signaling and Screening Models. Applications. Static games of complete information: definition of a game; normal form representation; strongly and weakly dominated strategies; Nash Equilibrium (NE); mixed strategy equilibrium. Applications of NE and introduction to market competition; Cournot competition; Bertrand competition; externalities; public goods. Dynamic games of complete information: definition of a dynamic game; extensive form representation; perfect and imperfect information; Backward Induction equilibrium; Subgame Perfect equilibrium. Repeated games: Definition; one-shot deviation property; folk theorem; application to Rubinstein bargaining. Static games of incomplete information: Bayesian games; Bayesian Nash equilibrium. Dynamic games of incomplete information: perfect Bayesian equilibrium; signalling games, cheap talk.
Prerequisites: Optimal Control
Hours:
30
Professors/Lecturers:
Nicola Dimitri (Università degli Studi di Siena)
Compulsory for:
Economics, Management and Data Science
Also available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering

Introduction to Cognitive and Social Psyschology

Abstract:
This course will provide an introduction to general themes in Cognitive and Social Psychology. In the first part of the course, we will review seminal findings that had a major impact on our knowledge of cognitive processes and social interactions, as well as more recent studies that took advantage of neuroimaging, electrophysiology and brain stimulation methods to shed new light on decision-making and social behaviors. During the second part of the course, students will be asked to perform a brief presentation of a research article and to critically discuss positive aspects and limitations of the study. The course will include seminars and lectures by renowned researchers in the field and will educate PhD candidates about the influence of social aspects of the human nature on cognitive and brain functioning (and vice-versa) in an intellectually motivating manner.
Hours:
32
Professors/Lecturers:
Pietro Pietrini (IMT Lucca); Emiliano Ricciardi (IMT Lucca)
Available for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Introduction to Networks

Abstract:
The course will provide an introduction to the mathematical basis of Complex Networks and to their use to describe, analyze and model a variety of physical and economic situations.

LIST OF LECTURES

Lecture 1 Graph Theory Introduction:
Basic Definitions, Statistical Distributions, Universality, Fractals, Self-Organised Criticality

Lecture 2 Properties of Complex Networks:
Scale-Invariance of Degree Distribution, Small-World Effect, Clustering

Lecture 3 Applications:
Internet, WWW, Socio-technological systems, Economics, Biology

Lecture 4 Communities:
Community Detections, Algorithms to explore Graphs

Lecture 5 Different kind of graphs:
Vertices differences, Layered Vertices, Trees and Taxonomies

Lecture 6 Ranking:
Hierarchies, Spanning Trees,HITS, PageRank,

Lecture 7 Static Models of Graphs:
Erdos-Renyi, Small World

Lecture 8 Dynamical Models of Graphs:
Barabasi-Albert, Configuration models

Lecture 9 Fitness models:
Fitness model and Self-Organised Fitness Model

Lecture 10 Basic Ingredients of Models:
Growth Preferential Attachments, Log Normal Distribution, Multiplicative Noise
Hours:
10
Professors/Lecturers:
Guido Caldarelli (IMT Lucca)
Compulsory for:
Cognitive, Computational and Social Neurosciences
Also available for:
Analysis and Management of Cultural Heritage; Computer Science and System Engineering; Economics, Management and Data Science

Introduction to Neuropsychology

Abstract:
TBD
Hours:
12
Professors/Lecturers:
Francesca Garbarini (Università degli Studi di Torino)
Compulsory for:
Cognitive, Computational and Social Neurosciences

Introduction to Psychophysics

Abstract:
TBD
Hours:
10
Professors/Lecturers:
Tbd
Compulsory for:
Cognitive, Computational and Social Neurosciences

Leading Themes in Neuroscience

Abstract:
Every year, we will have a world-recognized neuroscientist to provide a masterclass on a specific topic related to the CCNS track.
Hours:
12
Professors/Lecturers:
Tbd
Compulsory for:
Cognitive, Computational and Social Neurosciences

Machine Learning and Pattern Recognition

Abstract:
Basics of pattern recognition and machine learning and real world applications in imaging, internet, finance. Similarities and differences. Decision theory, ROC curves, Likelihood tests. Linear and quadratic discriminants. Template based recognition and feature detection/extraction. Supervised learning (Support vector machines, Logistic regression, Bayesian). Unsupervised learning (clustering methods, EM, PCA, ICA). Current trends in Machine Learning. Prerequisites: Probability and basic random processes, linear algebra, basic computer programming, numerical methods.
Hours:
20
Professors/Lecturers:
Sotirios Tsaftaris (The University of Edinburgh)
Available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Management of Complex Systems: Approaches to Problem Solving

Abstract:
Methods and approach to problem solving. Problem analysis; analysis of complex systems (related to cultural heritage, such as a city of art organization, promotion, etc.). The course will include practical simulations. The course will be linked to a seminar on specific case studies.
Hours:
20
Professors/Lecturers:
Andrea Zocchi
Compulsory for:
Analysis and Management of Cultural Heritage
Also available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Management Science and Corporate Finance

Abstract:
Thi course has been cancelled.
Hours:
30
Professors/Lecturers:
Tbd
Compulsory for:
Economics, Management and Data Science
Also available for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering

Material Modeling of Excitable Biological Tissues

Abstract:
TBD
Hours:
6
Professors/Lecturers:
Alessio Gizzi (Campus Bio-Medico Roma)
Available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering

Matrix Algebra

Abstract:
This course is aimed to review the basic concepts of linear algebra:

1. Systems of linear equations: solution by Gaussian elimination, PA=LU factorization, Gauss-Jordan method.
2. Vector spaces and subspaces, the four fundamental subspaces, and the fundamental theorem of linear algebra.
3. Determinant and eigenvalues, symmetric matrices, spectral theorem, quadratic forms.
4. Cayley-Hamilton theorem, functions of matrices, and application of linear algebra to dynamical linear systems.
5. Iterative methods for systems of linear equations.
6. Ordinary lest squares problem, normal equations, A=QR factorization, condition number, Tikhonov regularization.
7. Singular-value decomposition, Moonre-Penrose pseudoinverse.
8. An economic application of linear algebra: the Leontief input-outpul model.
Hours:
10
Professors/Lecturers:
Giorgio Stefano Gnecco (IMT Lucca)
Available for:
Cognitive, Computational and Social Neurosciences; Economics, Management and Data Science

Networks

Abstract:
The course is structured into three modules: the first one will cover advanced topics in complex network theory, whereas, the second one will focus on economic and financial networks, dealing with both theory and applications.

Module 1: Advanced Theory of Complex Networks
Lecture 1 Models of Evolving Networks
Lecture 2 Fitness & Relevance models
Lecture 3 The Master Equations approach
Lecture 4 Percolation
Lecture 5 Epidemic Models on Networks
Lecture 6 Advanced Topological Properties
Lecture 7 Complex Networks Randomization
Lecture 8 Exponential Random Graphs
Lecture 9 Parameter Estimation via Maximum Likelihood
Lecture 10 Applications: Bipartite, Directed and Weighted Networks.

Module 2: Economic & Financial Networks
Lecture 1 Evolutionary Network Games
Lecture 2 Heterogeneous Mean-Field Theory
Lecture 3 Financial Networks
Lecture 4 Systemic Risk
Lecture 5 DebtRank
Lecture 6 Economic Networks
Lecture 7 The WTW & COMTRADE dataset
Lecture 8 Gravity Models of Trade
Lecture 9 Early Warning Signals
Lecture 10 Network Reconstruction from Partial Information

Module 3 Social and Infrastructural Networks
Lecture 1 Introduction to Social Network Data
Lecture 2 Tecniques and Methodologies of Analysis in Social Networks
Lecture 3 Twitter data and Models
Lecture 4 Clustering and Classification of Facebook Data
Lecture 5 Automatic Topic Extraction
Lecture 6 Introduction to Infrastructural Networks
Lecture 7 Electric Grids
Lecture 8 Cascade Phenomena
Lecture 9 Modelling of infrastructural networks
Lecture 10 Smart Grids and Renewables

Prerequisites: Matrix Algebra, Introduction to Networks, Foundations of Probability & Statistical Inference
Hours:
30
Professors/Lecturers:
Guido Caldarelli (IMT Lucca)
Compulsory for:
Economics, Management and Data Science
Also available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering

Neural Bases of Consciousness

Abstract:
TBD
Hours:
16
Professors/Lecturers:
Giulio Bernardi (CHUV, Lousanne)
Compulsory for:
Cognitive, Computational and Social Neurosciences

Neural Bases of Perception

Abstract:
The course will review the physiological and anatomical bases of perception in humans and will consequently detail the neural bases of unimodal, multisensory and supramodal perception. The last part of the course will review recent observation in early and late blind individuals to understand how the (lack of) visual experience affects brain functional and structural development.
Hours:
30
Professors/Lecturers:
Emiliano Ricciardi (IMT Lucca)
Compulsory for:
Cognitive, Computational and Social Neurosciences
Also available for:
Analysis and Management of Cultural Heritage

Neurobiology of Emotion and Behavior

Abstract:
This course will provide an introduction to general themes in Affective and Social Neurosciences, particularly focusing on the neural correlates of emotion and behavior.
Hours:
12
Professors/Lecturers:
Pietro Pietrini (IMT Lucca)
Compulsory for:
Cognitive, Computational and Social Neurosciences
Also available for:
Analysis and Management of Cultural Heritage; Economics, Management and Data Science

Neuroscience in Bio-Engineering, Automation and Robotics

Abstract:
TBD
Hours:
24
Professors/Lecturers:
Andrea Leo (Centro di Ricerca "E. Piaggio"); Domenico Prattichizzo (Università degli Studi di Siena); Enzo Pasquale Scilingo (Università di Pisa)
Compulsory for:
Cognitive, Computational and Social Neurosciences
Also available for:
Computer Science and System Engineering

Numerical Methods for the Solution of Partial Differential Equations

Abstract:
The course introduces numerical methods for the approximate solution of initial and boundary value problems governed by linear partial differential equations (PDEs) ubiquitous in physics, engineering, and quantitative finance. The fundamentals of the finite difference method and of the finite element method are introduced step-by-step in reference to exemplary model problems related to heat conduction, linear elasticity, and pricing of stock options in finance. Notions on numerical differentiation, numerical integration, interpolation, and time integration schemes are provided. Special attention is given to the implementation of the numerical schemes in Matlab and in the finite element analysis program FEAP fast intensive computations.
Hours:
20
Professors/Lecturers:
Marco Paggi (IMT Lucca)
Available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Philosophical and Ethical Themes in Neuroscience

Abstract:
Since its formal establishment as a self-standing field, neuroethics has been divided into two subdefinitions: the neuroscience of ethics and the ethics of neuroscience. While the neuroscience of ethics aims at explaining the way our brain works in relation to moral judgement, the ethics of neuroscience is a further expansion of bioethics: a discipline that wants to assess the moral dilemmas specifically raised by recent biotechnological advancements. As suggested by the title, this introductory course will focus on neuroethics in this latter sense, underlining the impact that discoveries concerning our brain can, do or will have on our society. Speculating over the ethical and political acceptability of certain innovations in the light of classical philosophical questions (i.e. What is justice? What constitutes a good life?) and other key terms necessary to understand the current debate (i.e. authenticity and personal identity, autonomy, responsibility and competence) will provide the groundworks for any further neuroethical investigation envisaged.
Hours:
14
Professors/Lecturers:
Mirko Daniel Garasic
Compulsory for:
Cognitive, Computational and Social Neurosciences

Philosophy and Neuroscience in Moral Reasoning

Abstract:
TBD
Hours:
12
Available for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences

Philosophy of Science (long seminar without exam)

Abstract:
We know a lot of things – or, at least, we think we do. Epistemology is the branch of philosophy that
studies knowledge: its main features, the dynamics of its growth, as well as its claims for truth, validity, and progress. In this course – which is designed as a series of seminars held by the students, preceded by a few introductory lectures – we will consider some of the key contributions to the philosophical debate about the growth of scientific knowledge in the twentieth century, from Logical Positivism to Karl Popper, from Thomas Kuhn to Paul Feyerabend. We shall read some of their (as well as others’) works, and critically consider the content and limits of the different methodologies they advanced. Finally, we will reflect on the extent to which such debates affected the methodology of the social sciences, and consider in what ways hard and social sciences differ: as to their inner nature, the context in which they operate, the data they employ and rely upon, and the prescriptive methodology they more or less explicitly adopt.
Hours:
10
Professors/Lecturers:
Stefano Gattei (Chemical Heritage Foundation, Philadelphia)
Available for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Principles of Brain Anatomy and Physiology

Abstract:
The course aims at introducing the fundamentals of brain anatomy and physiology. In the first part of the course we will revise the basics of neuron structure and function, as well as synaptic mechanisms and cytoarchitectonic properties of the cortical mantle, with particular regards to visual, auditory, somatosensory and motor systems. Moving from this fine-grained description of the human brain, we will focus on gross neuroanatomy: through the use of in-vivo state-of-the-art techniques, such as structural MRI and diffusion weighted imaging, we will review gyri and sulci of the cortex, subcortical structures, brainstem nuclei and major white matter fasciculi. The second part of the course will be devoted to the study of functional neuroanatomy, with insights on the relationship between specific brain structures and human cognition, collected using functional, metabolic and receptors mapping, as well as lesion studies. In particular, the the following topics will be covered: central and peripheral nervous systems, occipital parietal frontal temporal and limbic areas, subcortical nuclei and white matter fasciculi, cerebellum, methodologies of structural brain imaging: VBM, cortical thickness and folding, VLSM, Diffusion Weighted Imaging and Tractography (theory and methodologies of data processing, hands-on sessions). The last part of the course will instead cover topics related to peripheral and autonomous nervous system.
Hours:
38
Professors/Lecturers:
Luca Cecchetti (IMT Lucca); Michele Emdin (Scuola Superiore Sant'Anna Pisa)
Compulsory for:
Cognitive, Computational and Social Neurosciences

Scientific Writing, Dissemination and Evaluation (long seminar without exam)

Abstract:
In order to ensure their widest possible dissemination, research results need to be presented in academic publications and in talks. The first goal of this course is to introduce students to basic principles of academic writing and on basic techniques to plan and deliver good academic talks. In addition, the course discusses the key principles of peer review, which is what makes science reliable knowledge. In particular, the course focuses on how to write a professional referee report.
Hours:
8
Professors/Lecturers:
Luca Aceto (Reykjavik University)
Available for:
Analysis and Management of Cultural Heritage; Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering; Economics, Management and Data Science

Stochastic Processes and Stochastic Calculus

Abstract:
This course aims at introducing some important stochastic processes and Ito stochastic calculus. Some proofs are sketched or omitted in order to have more time for examples, applications and exercises.
In particular, the course deals with the following topics:

- Markov chains (definitions and basic properties, classification of states, invariant measure, stationary distribution, some convergence results and applications, passage problems, random walks, urn models, introduction to the Markov chain Monte Carlo method),
- conditional expectation and conditional variance,
- martingales (definitions and basic properties, Burkholder transform, stopping theorem and some applications, predictable compensator and Doob decomposition, some convergence results, game theory, random walks, urn models),
- Poisson process, Birth-Death processes,
- Wiener process (definitions, some properties, Donsker theorem, Kolmogorov-Smirnov test) and Ito calculus (Ito stochastic integral, Ito processes and stochastic differential, Ito formula, stochastic differential equations, Ornstein-Uhlenbeck process, Geometric Brownian motion, Feynman-Kac representation formula).

Prerequisites: Matrix Algebra + Foundations of Probability and Statistical Inference
Hours:
30
Professors/Lecturers:
Irene Crimaldi (IMT Lucca)
Specializing course for:
Economics, Management and Data Science
Also available for:
Cognitive, Computational and Social Neurosciences; Computer Science and System Engineering

Topics in Visual Arts

Abstract:
TBD
Hours:
12
Professors/Lecturers:
Emanuele Pellegrini (IMT Lucca); Maria Luisa Catoni (IMT Lucca); Linda Bertelli (IMT Lucca)
Compulsory for:
Cognitive, Computational and Social Neurosciences
Also available for:
Analysis and Management of Cultural Heritage