Less is more: Importance of long-range exceptions in brain architecture

COEX 

How brain architecture shapes function is a deep question which has occupied many researchers, from the perspective of network neuroscience (Bullmore and Sporns 2009), brain modelling (Breakspear 2017) and spectral graph theory (Atasoy, Donnelly, and Pearson 2016). Some have even suggested that geometry plays a particularly relevant role in shaping functional activity (Pang et al. 2023a), although see this ongoing discussion (Faskowitz et al. 2023; Pang et al. 2023b). Here we focus on probing the importance of the rare long-range exceptions to the exponential distance rule of brain wiring (Markov et al. 2013). New evidence using turbulence has demonstrated the fundamental role of long-range connectivity in shaping optimal brain information processing (Deco et al. 2021). Here we used Laplacian decomposition of four different graph representations of the underlying anatomy to derive anatomical brain modes: exponential-distance rule (EDR) (Ercsey-Ravasz et al. 2013) and long-range exceptions (EDR+LR), geometry-based modes (geometry) and EDR modes (EDR binary and EDR continuous) (Figure 1 A). Our results show that EDR+LR achieves significantly better reconstruction of long-range functional connectivity (FC) compared to the other mode representations. Furthermore, pertinent to time-critical information processing, we show that a small subset of modes achieves a disproportionately high reconstruction of task MRI activity. When this subset of modes is considered, EDR+LR achieves better reconstruction for the 47 HCP tasks compared to the other mode representations, suggesting that less is more for information processing in the brain.