Introduction to Neuroscience and Neurophysiology
The school's program will cover three main areas: Introduction to Neuroscience and Neurophysiology, Experimental Protocols, and Data Analysis and Modeling. In the first, students will learn about the fundamentals of neurophysiology and electrophysiology, understanding how neural signals are generated and recorded. It includes theoretical lectures and case studies that illustrate real-world applications, as well as initial hands-on sessions to familiarize students with basic EEG and fMRI equipment, focusing on understanding the technology and basic data collection techniques. An overview of the complete workflow of a neuroimaging study, from hypothesis generation to data interpretation, will also be provided.
Experimental Protocols will focus on the practical aspects of neuroscience research. Students will gain hands-on experience with live EEG setups, data acquisition sessions, and fMRI demonstrations. This area focuses on designing and implementing experimental protocols, including subject preparation, equipment setup, and troubleshooting. Practical sessions will involve specific case scenarios to illustrate common experimental protocols and challenges in neuroscience research.
In Data Analysis and Modeling, students will focus on the analysis of experimental data gathered during hands-on sessions. This area covers signal processing, neural modeling, and the application of machine learning techniques to neuroimaging data. Students will analyze the experimental data they collected, applying various analytical methods to interpret the results.
All participants are required to commit to the school for its duration.
Lectures and workshops by faculty members on the different techniques of data collection and analysis as well as the applications in neurotechnology and neuroscience.
Students will conduct hands-on tutorials on EEG data collection and analysis covering all the stages of project ideation, experimental design, data collection and analysis, and making conclusions.
Students will get the opportunity to apply what they learned in a short project which could utilize data collected onsite or already provided datasets. They will be working on their projects in the afternoon and will present them on the last day.
The social cohesion component will be focused on where the students will be having lunches together with the faculty and teaching assistants, which will give them the opportunity to socialize informally with the faculty members.