Neuroimaging Data Analysis - 2026–2027 Connectomics Research Competition

Overview¶

Now that we have introduced the basics of neuroimaging, resting-state fMRI, and the LEMON dataset, we are ready to begin working with the data itself.

This subsection “Neuroimaging Data Analysis” focuses on analyzing the preprocessed resting-state fMRI data from the LEMON dataset (i.e., the neuroimaging component of the dataset). Although we will use the LEMON dataset throughout the competition, many of the concepts, methods, and coding techniques you learn here are transferable to other fMRI datasets, neuroimaging studies, and even other fields such as finance!

Our goal is not only to teach you how to perform analyses, but also to help you understand the reasoning behind them. As a result, this section combines:

Conceptual explanations, where we introduce the scientific ideas and principles behind each analysis step
Coding tutorials, where we demonstrate how these analyses can be performed in Python

By the end of this subsection, you will understand how researchers transform preprocessed resting-state fMRI data into meaningful measures of brain connectivity.

The following subsections explain how to access the competition codebook, tutorials, and supporting materials. After that, we will begin working through the major steps involved in resting-state fMRI analysis!

These topics will provide many of the tools needed to explore your own research questions throughout the competition.