Connectome modes to reveal and model neuromodulatory control of primate brain dynamics

Brain activity unfolds over an intricately connected network of white matter fibers – the structural connectome. By generalising the well-known Fourier transform to the network structure of the connectome, the mathematics of structural eigenmode decomposition allows us to predict expected patterns of brain activity. Structural eigenmodes are distributed patterns of brain activity, each associated with a specific spatial frequency, from coarse- to fine-grained. Although this approach tells us how the spatial organisation of brain activity arises from the connectome, a, a puzzle remains: How does this static network give rise to the rich dynamics that characterise the living brain? What governs the relative prevalence of structural eigenmodes at different points in time? The answer comes from neuromodulation. Neurons express a wide array of neurotransmitter receptors, which control cellular and ultimately regional excitability and receptivity to incoming inputs, according to macroscopic gradients.

This educational session introduces the combined use of structural eigenmodes and pharmacological-fMRI as a means of interrogating the relationship between brain structure and dynamics. Through specific examples with real data, attendees will learn how to extract and interpret structural eigenmodes’ contribution to brain dynamics, and their relative change under different pharmacological perturbations. We will place emphasis on using structural eigenmodes to disentangle how different perturbations can induce convergent effects on dynamics, which are obscured by traditional approaches to neuroimaging data analysis. We will also show how using the same decomposition (eigenmodes of the structural connectome) and imaging modality (functional MRI) provides a ‘common currency’ to compare brain dynamics and their perturbations in different species. Finally, we will guide attendees on how to combine structural eigenmodes with publicly available PET maps of receptor density and meta-analytic maps of task-related activity in the human brain, to model transitions between different activity patterns of interest. Throughout, we will emphasise how practitioners can identify and use appropriate null models to test neurobiological hypotheses using structural eigenmodes. An interactive session will demonstrate this principle on concrete hypotheses provided by session participants, to ensure relevance for their own work.

The goal of this session is to enable participants with the conceptual tools and practical know-how to integrate the method of structural eigenmodes into their own work. We intend to ensure that the field can converge towards best practices that are statistically rigorous and biologically meaningful. To lower barriers to adoption and ensure broad accessibility across the diverse backgrounds of OHBM attendees, the session will be self-contained, without requiring formal training in mathematics. Rather, emphasis will be placed on balancing rigour and intuitive understanding with practical relevance. We will conclude by addressing conceptual pitfalls, practical caveats and open challenges of this approach in an open discussion.