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00925njm 22002777a 4500 dc Clusella Coberó, Pau author Deco, Gustavo author Kringelbach, Morten L. author Ruffini, Giulio author García Ojalvo, Jordi author 2023-04-12 Spatiotemporal oscillations underlie all cognitive brain functions. Large-scale brain models, constrained by neuroimaging data, aim to trace the principles underlying such macroscopic neural activity from the intricate and multi-scale structure of the brain. Despite substantial progress in the field, many aspects about the mechanisms behind the onset of spatiotemporal neural dynamics are still unknown. In this work we establish a simple framework for the emergence of complex brain dynamics, including high-dimensional chaos and travelling waves. The model consists of a complex network of 90 brain regions, whose structural connectivity is obtained from tractography data. The activity of each brain area is governed by a Jansen neural mass model and we normalize the total input received by each node so it amounts the same across all brain areas. This assumption allows for the existence of an homogeneous invariant manifold, i.e., a set of different stationary and oscillatory states in which all nodes behave identically. Stability analysis of these homogeneous solutions unveils a transverse instability of the synchronized state, which gives rise to different types of spatiotemporal dynamics, such as chaotic alpha activity. Additionally, we illustrate the ubiquity of this route towards complex spatiotemporal activity in a network of next generation neural mass models. Altogehter, our results unveil the bifurcation landscape that underlies the emergence of function from structure in the brain. PC, GD, GR, and JGO have received funding from the Future and Emerging Technologies Programme (FET) of the European Union’s Horizon 2020 research and innovation programme (project NEUROTWIN, grant agreement No 101017716). JGO also acknowledges financial support from the Spanish Ministry of Science and Innovation and FEDER (grant PID2021-127311NB-I00), by the “Maria de Maeztu” Programme for Units of Excellence in R&D (grant CEX2018-000792-M), and by the Generalitat de Catalunya (ICREA Academia programme). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Peer Reviewed Postprint (published version) Àrees temàtiques de la UPC::Enginyeria biomèdica Brain -- Models Neural networks (Neurobiology) Computational neuroscience Cervell -- Models Xarxes neuronals (Neurobiologia) Neurociència computacional Complex spatiotemporal oscillations emerge from transverse instabilities in large-scale brain networks