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.

Learning, Inference, and Prediction in the Brain

This course is an introduction to the brain as a predictive organ. The brain learns about its environment and infers the state of that environment in order to predict it, which will help ensure its own survival.

Arduino and Microcontrollers Course

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

Introduction to Brain Computer Interface (BCI)

A BCI (Brain Computer Interface) is a system that enables communication without movement. People can communicate or control devices via thought alone. The course will give an overview of the principles, methods and applications of current BCI systems.

Cognitive Neuroscience – Outlook on Special Populations

This year Marilena Aiello and Valentina Parma will hold a course entitled Cognitive Neuroscience – Outlook on Special Populations. Such course has been thought to provide a perspective on how typical and atypical brains work and provide experimental evidence to assess these issues.

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.

Noninvasive Transcranial Brain Stimulation (NTBS)

This course will provide a general introduction on the development of NTBS approaches. This will mainly include Transcranial Magnetic Stimulation (TMS) and transcranial electric stimulation (tES)..

Introduction to EEG analysis

This course will give an introduction to the use of Electroencephalography (EEG) in cognitive neuroscience. The focus will be on basics of EEG pre-processing, statistics, and issues in experimental design. Emphasis will be on Event Related Potentials (ERPs), but Time Frequency analysis (as well as other analyses) will be also covered. The course will consist of an initial session on EEG theory and on hands-on sessions on real EEG data.

Scientific Programming

Programming is quickly becoming a necessary skill for any scientist to have, especially with regards to data collection and data analysis. This course is aimed at building a solid foundation for understanding programming, as well as developing concrete skills in the main areas of data science: collection, organization, visualization, analysis and modelling.

Scientific Writing

The aim of this course is to help improve one’s scientific writing, oral and poster 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.

Basic Principles of Magnetic Resonance Imaging

The course focuses on the analysis and characterization of neuroimaging data, including Magnetic Resonance Imaging (MRI) and functional MRI (fMRI).