The stop-signal paradigm is a key tool for studying response inhibition in cognitive psychology, cognitive neuroscience, and psychopathology. It involves a go task followed by a stop signal that instructs participants to inhibit their response. Successful stopping requires a fast inhibition process that prevents motor execution, interacting with slower processes that monitor and adjust performance. The stop-signal reaction time (SSRT) measures the time it takes to stop a response and is crucial for understanding cognitive control. SSRT is elevated in younger children and older adults compared to young adults, and both SSRT and go reaction time (RT) develop and decline independently. Inhibitory deficits are associated with various disorders, including ADHD, OCD, and substance abuse. ADHD is linked to impaired inhibitory control, with slower SSRT and go RT in children, and impaired SSRT but not go RT in adults. OCD is associated with reduced grey matter in the orbitofrontal and right inferior frontal regions, and impaired inhibition and performance monitoring. Substance abuse disorders also show prolonged SSRT, suggesting response inhibition deficits. Neuroimaging studies show that the right inferior frontal gyrus (IFG) and pre-SMA are involved in response inhibition, while the medial frontal regions are involved in performance monitoring. Transcranial magnetic stimulation (TMS) and lesion studies support these findings, showing that damage to the right IFG impairs stopping but not going. The basal ganglia, including the subthalamic nucleus (STN), also play a role in stopping, with STN stimulation influencing both go RT and SSRT. The stop-signal paradigm reveals that response inhibition and performance monitoring are dissociated. Behavioral and neural data suggest that monitoring and adjusting performance in the stop-signal paradigm are similar to those in paradigms without motor inhibition. Future research should focus on understanding how inhibitory processes and monitoring jointly contribute to successful stopping and how the neural substrates of these processes carry out the required computation. The development of formal models that account for both stopping and monitoring computationally and neurally is also important.The stop-signal paradigm is a key tool for studying response inhibition in cognitive psychology, cognitive neuroscience, and psychopathology. It involves a go task followed by a stop signal that instructs participants to inhibit their response. Successful stopping requires a fast inhibition process that prevents motor execution, interacting with slower processes that monitor and adjust performance. The stop-signal reaction time (SSRT) measures the time it takes to stop a response and is crucial for understanding cognitive control. SSRT is elevated in younger children and older adults compared to young adults, and both SSRT and go reaction time (RT) develop and decline independently. Inhibitory deficits are associated with various disorders, including ADHD, OCD, and substance abuse. ADHD is linked to impaired inhibitory control, with slower SSRT and go RT in children, and impaired SSRT but not go RT in adults. OCD is associated with reduced grey matter in the orbitofrontal and right inferior frontal regions, and impaired inhibition and performance monitoring. Substance abuse disorders also show prolonged SSRT, suggesting response inhibition deficits. Neuroimaging studies show that the right inferior frontal gyrus (IFG) and pre-SMA are involved in response inhibition, while the medial frontal regions are involved in performance monitoring. Transcranial magnetic stimulation (TMS) and lesion studies support these findings, showing that damage to the right IFG impairs stopping but not going. The basal ganglia, including the subthalamic nucleus (STN), also play a role in stopping, with STN stimulation influencing both go RT and SSRT. The stop-signal paradigm reveals that response inhibition and performance monitoring are dissociated. Behavioral and neural data suggest that monitoring and adjusting performance in the stop-signal paradigm are similar to those in paradigms without motor inhibition. Future research should focus on understanding how inhibitory processes and monitoring jointly contribute to successful stopping and how the neural substrates of these processes carry out the required computation. The development of formal models that account for both stopping and monitoring computationally and neurally is also important.