Causal roles of neural synchrony in signal transmission and cognition in the human brain

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Healthy cognition depends on our capacity to influence the processing of external sensory events from our environment by expectations, previous experience and internal goals. In the brain, this is reflected in finely tuned interactions between higher-order frontal and parietal areas that take "top-down" cognitive control over sensory processing via influencing "bottom-up"-driven lower-level sensory regions. While brain regions that underlie top-down control are well defined anatomically, it is still an open question how the bidirectional communication between these brain regions and sensory areas is organized. In animal models, temporally correlated neuronal activity, i.e., neuronal synchronization, has been proposed to coordinate anatomically distributed processing and to regulate feedback control over the feedforward flow of sensory information in different frequency channels. However, there is only scarce evidence to support this hypothesis in the human brain and there is a need for multimodal neuroimaging techniques that would allow both whole brain mapping of large-scale brain networks and studying their causal role. We will use state-of-the art multimodal neuroimaging with combined magneto/ electroencephalography (MEG-EEG) and combined transcranial magnetic stimulation/ electroencephalography (TMS-EEG) to unravel the mechanistic / causal role of network interactions in achieving the internally controlled regulation of bottom-up (visual) signalling. We will identify interactions by which the attentional frontal and parietal brain areas influence the excitability and timing of neuronal activity in visual areas for the selection of information in accordance with expectations and relevance for current behavioural goals. Our overarching aim is to study how these top-down interactions are achieved in the human brain and to develop new probes of network integrity in the human brain.Exploiting cutting-edge analyses techniques for MEG-EEG data acquired during tasks engaging top-down control, we will uncover the dynamic nature and cortical sources of the large-scale network interactions that are correlated with feedback control of visual processing, and their local consequences on visual cortex activity. Based on these individual dynamic networks obtained from MEG-EEG, we will test how activity induced by non-invasive brain stimulation with single-pulse TMS propagates through the brain as a function of areas being stimulated and its dominant frequency. To this end, we will use simultaneous EEG recordings (TMS-EEG) and the same cutting-edge analysis framework for measuring network interactions in MEG-EEG, allowing to integrate these approaches offline in the same participants (MEG-EEG-TMS). Finally, we will use rhythmic TMS at natural frequencies to emulate top-down effects. Using simultaneous EEG and by means of integration with the MEG-EEG data, we will test to what extent the TMS-emulated top-down effects depend on the importance of the targeted brain region in the network (its "hubness") and are state-dependent. Collectively, our project will reveal both whole-brain correlative (MEG-EEG) and mechanistic (TMS-EEG) insight into the functional significance of large-scale neural synchronization in implementing top-down control of feedforward signalling and visual processing. The project is also expected to demonstrate the utility of MEG/EEG-guided TMS for improving the efficacy of repetitive TMS, which is widely used in cognitive and clinical neuroscience. Revealing whether TMS efficacy depends on network parameters in individual participants has important implications for its use in experimental and clinical settings. Altogether, this project will therefore help to identify the basic electrophysiological building blocks of brain network interactions, and to advance the tools for studying and modulating these processes.