Response inhibition plays a major role in cognitive control. Understanding these mechanisms is essential because their dysfunctions may cause symptoms in many psychiatric and neurological diseases. The relationship between brain activity and behavior are particularly difficult to understand because the function of interest is specifically intended to prevent any observable behavior… In the first part, we propose a review of issues highlighting the need for a new theoretical model and adapted psychophysical methods. We also provide systematic analysis of studies using electroencephalography, widely preferred method for probing the dynamics of inhibitory mechanisms. Convergently, the review calls for revisiting both acquisition methods and processing methods of EEG signal used in conventional studies. In the second part, we implement these proposals by combining advanced treatment methods of EEG signal (blind source separation, analysis test by test, spectral analysis in the sources, location) and comparing these results with the fMRI data. We reveal the involvement of automatic and nonselective inhibitory mechanisms, when the context is uncertain. A large medial frontoparietal network would ensure the implementation. The involvement of an automatic behavior (when the environment becomes predictable) would require a top-down control that deactivates in advance the excitability of the self-inhibitory circuitry of the SMC. In the third and fourth sections, we show the key role of this function in other cognitive processes and illustrate the clinical consequences of its dysfunction. We show in particular that the difficulty in initiating an action (akinesia) would, in Parkinson’s disease, a direct consequence of this dysfunction. The involvement of the noradrenergic system and the activity of the subthalamic nucleus in the occurrence of the disorder are suggested, and therapeutic perspectives discussed

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   |wiki=    Wicri/Sante
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   |texte=   Inhibitory control and action initiation : an alternative theoretical model and advanced EEG methods for clinical perspectives in Parkinson's disease
}}