The teaching offer in the Cognitive Neuroscience PhD at SISSA consists of theoretical and methodological courses. The former are taught by our Faculty, and cover advanced topics in the fields that are investigated in the group (tactile, visual and time perception, language and reading, social and food neuroscience, and neural computation). The latter are taught by our Faculty, external experts and, occasionally, postdocs in the group; and are designed to introduce the students to the tools that they may use during their PhD (coding, information theory, TMS, fMRI, eye tracking, EEG, and scientific writing).

The courses are primarily directed to 1st year students, who must pass all the theoretical exams and the coding, information theory and scientific writing courses in order to be admitted to the second year. Senior students are also more than welcome to attend any of the courses, and take part into the exams if they wish so. The TMS, fMRI, eye tracking and EEG courses will all start with a couple of introductory meetings, which are designed the illustrate the main features of the tool at hand, so that everyone can decide whether they’re interested in attending the remaining classes.

To explore the course list for 2016-2017, please use the menu on the right.

Scientific Dissemination

Course Overview:

The aim of the course is to help improve one’s scientific dissemination abilities, including writing, poster presentations, and oral presentations, by introducing rules of style to communicate in a concise, clear, and convincing way and rules for effective slide and poster preparation and speech delivery. The course is based on similar ones by Peter Kramer, Stuart Anstis, and Ed Hubbard and incorporates advice by Philip Bourne.

Bayesian Modeling and Information Theory for neuroscience and cognitive science

In this course we will explore Bayesian modeling and information theory as model-building tools in the study of the mind and the brain.

The course will take place in room 139

Scientific programming: A crash course

Basic coding skills are essential in science, but, unfortunately, many students do not receive formal training in programming and are often left to figure things out for themselves. The aim of this short crash course is cover enough of the core principles that you can feel confident in continuing your coding journey through self-directed learning and discovery. By the end of the course, you should be able to script a basic experiment, handle data, and plot graphs.

How the Brain Tells Time

This course will offer an overview of the state of the art of the neuroscience of time, from theoretical models to empirical data. Particular emphasis will be given to the perception of time. 

The course will take place in room 139

Cognitive Neuroscience - Intelligence

Cognitive and non-cognitive factors influencing academic and life outcomes, and normal and pathological aging and the role of intelligence

Raffaella I. Rumiati, SISSA office 341,,

The course will take place in room 139

Lecture 1. Introduction to Intelligence

Data Modelling

In this course we will explore the data analysis process from the beginning —the moment a set of data comes out of a subject's brain and/or behaviour— to the end —the moment we make an inference about how the brain and/or cognition works. In doing this, we wil cover data treatment and management (e.g., tidy datasets), graphical data exploration, data manipulation (e.g., standardisation, centering) and, of course, data modelling. We will focus on mixed-effect models as our main statistical tool, which is a very general approach that covers essentially all kind of datasets a neuroscientist might ever want to tackle -- from cell biology, to system neuroscience, to psychophysics.  

Arduino and Microcontrollers Course

This course is intended as an introduction to using arduino and microcontrollers.

Introduction to Electronics

Along this course you will be guided through a rational pathway touching different topics in the field of electronics. By following a theoretical approach with practical examples connected to the scientific laboratory environment, the course is open to everybody who aims to understand and take advantage of electronics as a tool for their research.

Introduction to Systems and Computational Neuroscience: Evolution of Neural Computation

The course delineates the evolution of the vertebrate nervous systems, with a particular focus on mammals and among them on the human lineage.

The course will take place in room 004.