Applications of diffusion map embedding to understanding gradients of cortical organization

Brisbane Convention & Exhibition Centre 

The human cortex is intricately organized along multiple overlapping spatial axes, which can be revealed using advanced dimensionality reduction techniques like PCA and diffusion map embedding. These methods enable us to uncover spatial patterns from in vivo structural and functional connectomes and explore how they relate to other brain features, such as microstructure and functional mapping. While these approaches provide a compelling framework to understand the brain's spatial organization, significant questions remain, particularly regarding individual differences. For instance: How do these gradients vary from person to person? What is the relationship between structural and functional gradients? And what practical insights can we gain by conceptualizing the brain through its gradient organization? Answering these questions requires integrating theory-driven research with diverse datasets and innovative methodologies. By investigating the unique ways these spatial axes appear in individuals, we can better understand their roles in health and disease.

This educational session will introduce participants to cutting-edge approaches for studying individual variability in brain axes, drawing on examples ranging from biophysical modeling to the influence of the menstrual cycle. Through real-world data demonstrations, attendees will learn how to identify, interpret, and apply gradients in the context of individual differences. The session emphasizes a multimodal perspective to uncover variability while highlighting critical caveats in interpreting findings. Key theoretical frameworks, such as the dual origin theory and structural model, will be explored to provide a deeper understanding of brain gradients.

Participants will also have the opportunity to engage in hands-on learning through a guided tutorial, where they will create and interpret gradients using their own data. In addition, the session will provide access to an online resource, including a dedicated website containing tutorials, best practices, and additional information on gradient analysis. These resources aim to support participants in applying what they’ve learned long after the session ends.

The session will underscore best practices for statistical evaluation across individuals and modalities, offering practical workflows to investigate relationships and test hypotheses. Interactive components will enable participants to apply these methods directly to their research questions, ensuring relevance and actionable insights.

The goal is to equip attendees with both the conceptual framework and practical expertise to integrate gradient analysis into their work. This session is designed to make these advanced methods accessible to a wide audience, regardless of formal training in mathematics or neuroscience. Emphasis will be placed on balancing theoretical depth with practical application, making the content approachable for OHBM attendees from diverse backgrounds.

We will conclude with an open discussion, addressing common pitfalls, practical challenges, and open questions in the field. By fostering a collaborative environment and providing long-term resources like tutorials and the website, we aim to advance best practices that are both statistically sound and biologically meaningful, ultimately enabling a broader adoption of gradient-based approaches in neuroscience research.

Summary of learning goals:
- Gain a clear understanding of the spatial axes (gradients) underlying cortical organization and their relevance to structural and functional brain connectivity.
- Learn how gradients vary across individuals and how these differences relate to factors such as brain microstructure, functional mappings, and external variables (e.g., menstrual cycle).
- Acquire practical experience in creating and interpreting gradients using real data, including guidance on statistical evaluation and visualization.
- Explore key theories such as the dual origin theory and structural model to deepen understanding of gradient-based brain organization.
- Engage with peers in interactive discussions to address challenges, brainstorm applications, and refine understanding of the method.