Symposia | Invited Symposia | Poster Sessions | Data Blitz Sessions

Large-scale cortical networks are organized in structured cycles

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall
Also presenting in Data Blitz Session 3 - Saturday, April 13, 2024, 1:00 – 2:30 pm EDT, Ballroom West.

Mats W.J. van Es1 (mats.vanes@psych.ox.ac.uk), Cameron Higgins1,2, Chetan Gohil1, Andrew J. Quinn1,3, Diego Vidaurre1,4, Mark W. Woolrich1; 1University of Oxford, 2Resonait Medical Technologies Pty Ltd, 3University of Birmingham, 4Aarhus University

The brain needs to perform a diverse set of cognitive functions essential for survival, but it is unknown how it self-organizes to ensure that each of these functions is fulfilled within a reasonable period. It is a widely shared belief that they arise from dynamic switching in coherent activity within large-scale cortical networks. Here, we developed a new method to study the temporal evolution of these networks based on the long-term asymmetries in state transitions. We show that cortical networks activate in a structured manner in spontaneous brain activity. Reproduced across five independent magnetoencephalography (MEG) studies, we show that the network activations are stochastic on short time scales but self-organize into a distinct cycle that has a 300-1000 ms duration, with each network occupying a preferred location within the cycle. We further show that the cycle groups cortical networks with similar function and spectral content at specific positions within the cycle, and in turn, that the position of an individual’s brain activity within the cycle is predictive of cognition, including the spontaneous replay of memories. Moreover, we find that an individual’s cycle strength and cycle speed are heritable and predictive of individual traits; with stronger and slower cycling found in older people and males. These results suggest that cortical network activations are inherently cyclical and may provide the organisation the brain needs to spend time focusing on different cognitive functions. This occurs at time scales that have previously been shown to be the most relevant for global brain processing.

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