Suchergebnisse

Recently introduced effective connectivity methods allow for the in-vivo investigation of large-scale functional interactions between brain regions. However, dynamic causal modeling, the most widely used technique to date, typically captures only a few predefined regions of interest. In this study, we present an alternative computational approach to infer effective connectivity within the entire connectome and show its performance on a developmental cohort with emerging language capacities. The novel approach provides new opportunities to quantify effective connectivity changes in the human brain. ; G.D. was supported by the ERC Advanced Grant DYSTRUCTURE (n. 295129), the Spanish Research Project PSI2013-42091-P and the FP7-ICT BrainScales (n. 269921). D.M. was supported by a Sir Henry Dale Fellowship of the Wellcome Trust and the Royal Society (n. 101253/Z/13/Z), a Marie Curie Integration Grant of the European Commission (n. 2012-334039), the KU Leuven Special Research Fund (grant C16/15/070), and the Research Foundation Flanders (Pegasus incoming fellowship 12G9417N to MG). MG received funding from the FWO and European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie action (grant 665501). G.D., G.H and A.D. received support from the flagship Human Brain Project (n.604102). A.D was also supported by CNRS, UNIC, the foundation "Voir et Entendre" and Idex (NeuroSaclay). A.D.F. was funded by a grant from the European Research Council (ERC-2010-AdG 20100407, NEUROSYNTAX).

During the sleep-wake cycle, the brain undergoes profound dynamical changes, which manifest subjectively as transitions between conscious experience and unconsciousness. Yet, neurophysiological signatures that can objectively distinguish different consciousness states based are scarce. Here, we show that differences in the level of brain-wide signals can reliably distinguish different stages of sleep and anesthesia from the awake state in human and monkey fMRI resting state data. Moreover, a whole-brain computational model can faithfully reproduce changes in global synchronization and other metrics such as functional connectivity, structure-function relationship, integration and segregation across vigilance states. We demonstrate that the awake brain is close to a Hopf bifurcation, which naturally coincides with the emergence of globally correlated fMRI signals. Furthermore, simulating lesions of individual brain areas highlights the importance of connectivity hubs in the posterior brain and subcortical nuclei for maintaining the model in the awake state, as predicted by graph-theoretical analyses of structural data. ; G.D. was supported by the Spanish Research Project AWAKENING: using whole-brain models perturbational approaches for predicting external stimulation to force transitions between different brain states, ref. PID2019-105772GB-I00 /AEI/10.13039/501100011033, financed by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI), and by the Catalan AGAUR program 2017 SGR 1545. G.D., G.H. and G.Z. received support from the European Union's Horizon 2020 research and innovation program under Grant Agreement No. 720270 (Human Brain Project SGA1), No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3). G.H. was funded by the grant CONSCBRAIN (n. 661583) of the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie action. G.D. and G.H. received funding from the German Research Council (DFG, No. KN 588/7 – 1) within the priority program Computational Connectomics (SPP 2041). E.T. and H.L. were supported by the Bundesministerium für Bildung und Forschung (grant number 01 EV 0703) and the LOEWE Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). M.L.K. is supported by the ERC Consolidator Grant: CAREGIVING (n. 615539), Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117), and centre for Eudaimonia and Human Flourishing funded by the Pettit and Carlsberg Foundations.

Recent research has found that the human sleep cycle is characterised by changes in spatiotemporal patterns of brain activity. Yet, we are still missing a mechanistic explanation of the local neuronal dynamics underlying these changes. We used whole-brain computational modelling to study the differences in global brain functional connectivity and synchrony of fMRI activity in healthy humans during wakefulness and slow-wave sleep. We applied a whole-brain model based on the normal form of a supercritical Hopf bifurcation and studied the dynamical changes when adapting the bifurcation parameter for all brain nodes to best match wakefulness and slow-wave sleep. Furthermore, we analysed differences in effective connectivity between the two states. In addition to significant changes in functional connectivity, synchrony and metastability, this analysis revealed a significant shift of the global dynamic working point of brain dynamics, from the edge of the transition between damped to sustained oscillations during wakefulness, to a stable focus during slow-wave sleep. Moreover, we identified a significant global decrease in effective interactions during slow-wave sleep. These results suggest a mechanism for the empirical functional changes observed during slow-wave sleep, namely a global shift of the brain's dynamic working point leading to increased stability and decreased effective connectivity. ; BMJ, RH, GH, APA and GD were funded by the European Research Council (ERC) Advanced Grant DYSTRUCTURE (n. 295129), European Union's Horizon 2020 research and innovation programme under grant agreement No. 720270 (HBP SGA1) and No. 661583 (CONSBRAIN), by the Programa Estatal de Investigación Cientifica y Tecnica de Excelencia MINECO (PSI2013-42091, PSI2016-75688-P (AEI/FEDER, EU) and PCIN-2013-026), Juan de la Cierva fellowship (IJCI-2014-21066) and by the Catalan Agency for Management of University and Research Grants, AGAUR (2014SGR856). ET and HL were supported by the Bundesministerium für Bildung und Forschung (grantnumber 01 EV 0703) and the LOEWE Neuronale Koordination Forschungsschwerpunkt Frankfurt (NeFF). ET was further funded by a postdoctoral grant of the AXA foundation. MLK was supported by the ERC Consolidator Grant CAREGIVING (n. 615539).