Abstract

The complete set of connections in the brain is called our connectome. Over the last 20 years we have found out more about how this network is organised and how this organisation is linked to brain function [1,2]. I will outline how characteristic network features arise during evolution, how they are linked to brain function, and how they originate during individual brain development [3]. For example, small-world features enable the brain to rapidly integrate and bind information while the modular architecture, present at different hierarchical levels, allows separate processing of various kinds of information while preventing wide-scale spreading of activation [4]. Hubs play critical roles in information processing and are involved in many brain diseases [5]. Long-distance connections are crucial to reduce the number of processing steps. Connectomes show more long-distance connections than would be expected if energy minimisation would be a primary goal of network optimisation. Indeed, both C. elegans and the macaque show non-optimal component placement [5]. In a recent paper [6], we show that this non-optimal organisation also occurs for the human connectome. Moreover, such a spatial layout has benefits in network dynamics allowing for easier switching between brain states. Therefore, there might be distinct cognitive benefits; conversely, we might expect cognitive deficits in brain network disorders to be linked to an altered spatial organisation of brain networks. Finally, I will outline how information about topological and spatial connectome changes can be a starting point for personalised interventions with non-invasive brain stimulation using focused ultrasound.

[1] Martin, Kaiser, Andras, Young. Is the Brain a Scale-free Network? SfN Abstract, 2001. [2] Sporns, Chialvo, Kaiser, Hilgetag. Trends in Cognitive Science, 2004. [3] Kaiser. Changing Connectomes. MIT Press, 2020 http://tiny.cc/connectome [4] Kaiser et al. New Journal of Physics, 2007. [5] Kaiser & Hilegtag, PLOS Computational Biology, 2006. [6] Hayward, Huo, Chen, Kaiser. Network Neuroscience, in press.