Functional neuroimaging and electrophysiological techniques, such as functional magnetic resonance imaging (fMRI) as well as electro- and magnetoencephalography (EEG/MEG), serve well to study spontaneous or task-related neuronal activity as correlates of specific cognitive functions in the human brain. However, to infer causality of brain activation for cognition, the former must be manipulated experimentally. This is possible in healthy humans with the help of non-invasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation (TMS), transcranial electric stimulation (tES), and since recently also transcranial ultrasound stimulation (TUS). Importantly, NIBS can also be combined with fMRI as well as EEG/MEG, either concurrently (online) or consecutively (offline). Online approaches, assessing the immediate neural response to stimulation, can be used to (i) quantify neuronal network properties such as excitation, inhibition, or connectivity, (ii) interfere with ongoing spontaneous or task-related activity and thus affect behavioral performance, or (iii) modulate the level and timing of neuronal activity, e.g., trying to mimic neuronal oscillations in behaviorally relevant manner. In contrast, offline approaches can be utilized to either (iv) inhibit or (v) facilitate local neuronal excitability via the induction of synaptic plasticity, assessing its subsequent effects on neuronal activity and behavior. In this talk, I will discuss the different approaches and challenges with respect to their combination with fMRI and EEG, in particular concurrent TMS-fMRI and TMS-EEG, and highlight their potential as well as the caveats for inferring causality from NIBS studies in cognitive neuroscience. I will also introduce the novel approach of brain state-dependent brain stimulation, which allows to control NIBS in real-time based on the online assessment of specific oscillatory states, providing a unique opportunity to causally interact with ongoing neuronal oscillations to study its role in information processing and synaptic plasticity.
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