Early changes in corticomotor excitability underlie proactive inhibitory control of error correction

Converging evidence indicates that response inhibition may arise from the interaction of effortful proactive and reflexive reactive mechanisms. However, the distinction between the neural basis sustaining proactive and reactive inhibitory processes is still unclear. To identify reliable neural markers of proactive inhibition, we examined the behavioral and electrophysiological correlates elicited by manipulating the degree of inhibitory control in a task that involved the detection and amendment of errors. Restraining or encouraging the correction of errors did not affect the time course of the behavioral and neural correlates associated to reactive inhibition. We rather found that a bilateral and sustained decrease of corticomotor excitability was required for an effective proactive inhibitory control, whereas selective strategies were associated with defective response suppression. Our results provide behavioral and electrophysiological conclusive evidence of a comprehensive proactive inhibitory mechanism, with a distinctive underlying neural basis, governing the commission and amendment of errors. Together, these findings hint at a decisive role for changes in corticomotor excitability in determining whether an action will be successfully suppressed.

Automated SWATH Data Analysis Using Targeted Extraction of Ion Chromatograms

Targeted mass spectrometry comprises a set of methods able to quantify protein analytes in complex mixtures with high accuracy and sensitivity. These methods, e.g., Selected Reaction Monitoring (SRM) and SWATH MS, use specific mass spectrometric coordinates (assays) for reproducible detection and quantification of proteins. In this protocol, we describe how to analyze in a targeted manner data from a SWATH MS experiment aimed at monitoring thousands of proteins reproducibly over many samples. We present a standard SWATH MS analysis workflow, including manual data analysis for quality control (based on Skyline) as well as automated data analysis with appropriate control of error rates (based on the OpenSWATH workflow). We also discuss considerations to ensure maximal coverage, reproducibility and quantitative accuracy.