Cognitive, Computational and Social Neurosciences

Critical Thinking (long seminar without exam)

Constructing and evaluating arguments is fundamental in all branches of science, as well as in everyday life. The course provides the basic skills and tools to recognize correct forms of inference and reasoning, detect the unsound or fallacious ones, and assess the strength of various kinds of argument. The toolbox includes elementary deductive logic, patterns of inductive and abductive inference, the basics of statistical and probabilistic reasoning, and the analysis of heuristics and biases in cognitive psychology.

Business Model for Emerging Markets

Teaching contents:

1. The economy of the intangibles
2. Manufacturing and robot
3. Strategy and business model
4. How to model a business
5. How to model a business in a complex scenario
6. What make market emerging? Not only new lands.
7. The Blockchain technology and the future
8. Initial Coins Offering (ICO) compressed between Business plan and White paper
9. Possible value of Blockchain technology for Small and medium Italian sized business
10. A global value chain approach to protect and foster strategic identity

Behavioral and Cognitive Neuroscience of Perception

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.

Basic Neuro-Linguistics

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.

Advanced Topics in Network Theory: Statistical Mechanics of Networks

Information theory, Exponential Random Graphs.
Hypothesis testing on networks
Reconstruction of networks.

Lecture 1: Basics of Information Theory
Lecture 2: Complex Networks Randomization
Lecture 3: Exponential Random Graphs
Lecture 4: maximum Likelihood Estimation
Lecture 5: Hypothesis testing on networks
Lecture 6: Early warnings in economic and financial networks
Lecture 7: Gravity Models of Trade
Lecture 8: Reconstruction algorithms I
Lecture 9: Reconstruction algorithms II