Who can apply to this school? Postdoctoral Fellows PhD Students Master Students Bachelor Students Medical Doctors (MD) Students residing in the Asia-Pacific, Africa, and Pan-Europe regions are eligible to apply for this school. Women and persons residing in low/low-middle income countries are particularly encouraged to apply. Applicants must be working in neuroscience or in closely related fields (e.g.: artificial intelligence, neural engineering, biomedical engineering etc.). Applicants from other fields that have strong quantitative backgrounds will also be considered. Knowing how to program in Python is essential as the school will involve intermediate level data analysis tutorials. A primer on Python and the necessary mathematics will be provided to participants ahead of the school start.
What costs are covered for participants? Travel Accommodation Meals Local transportation School fees Full funding will be available to applicants residing in low/low-middle income countries. Applicants arriving from other destinations may receive partial funding depending on available resources.
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.