Response inhibition is essential for navigating everyday life. Its derailment is considered integral to numerous neurological and psychiatric disorders, and more generally, to a wide range of behavioral and health problems. Response-inhibition efficiency furthermore correlates with treatment outcome in some of these conditions. The stop-signal task is an essential tool to determine how quickly response inhibition is implemented. Despite its apparent simplicity, there are many features (ranging from task design to data analysis) that vary across studies in ways that can easily compromise the validity of the obtained results. Our goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide 12 easy-to-implement consensus recommendations and point out the problems that can arise when they are not followed. Furthermore, we provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.

Freezing of gait is a common, debilitating feature of Parkinson's disease. We have studied gait planning in patients with freezing of gait, using motor imagery of walking in combination with functional magnetic resonance imaging. This approach exploits the large neural overlap that exists between planning and imagining a movement. In addition, it avoids confounds introduced by brain responses to altered motor performance and somatosensory feedback during actual freezing episodes. We included 24 patients with Parkinson's disease: 12 patients with freezing of gait, 12 matched patients without freezing of gait and 21 matched healthy controls. Subjects performed two previously validated tasks--motor imagery of gait and a visual imagery control task. During functional magnetic resonance imaging scanning, we quantified imagery performance by measuring the time required to imagine walking on paths of different widths and lengths. In addition, we used voxel-based morphometry to test whether between-group differences in imagery-related activity were related to structural differences. Imagery times indicated that patients with freezing of gait, patients without freezing of gait and controls engaged in motor imagery of gait, with matched task performance. During motor imagery of gait, patients with freezing of gait showed more activity than patients without freezing of gait in the mesencephalic locomotor region. Patients with freezing of gait also tended to have decreased responses in mesial frontal and posterior parietal regions. Furthermore, patients with freezing of gait had grey matter atrophy in a small portion of the mesencephalic locomotor region. The gait-related hyperactivity of the mesencephalic locomotor region correlated with clinical parameters (freezing of gait severity and disease duration), but not with the degree of atrophy. These results indicate that patients with Parkinson's disease with freezing of gait have structural and functional alterations in the mesencephalic locomotor region. We suggest that freezing of gait might emerge when altered cortical control of gait is combined with a limited ability of the mesencephalic locomotor region to react to that alteration. These limitations might become particularly evident during challenging events that require precise regulation of step length and gait timing, such as turning or initiating walking, which are known triggers for freezing of gait.

Aging is typically associated with substantial declines in motor functioning as well as robust changes in the functional organization of brain networks. Previous research has investigated the link between these 2 age-varying factors but examinations were predominantly limited to the functional organization within motor-related brain networks. Little is known about the relationship between age-related behavioral impairments and changes in functional organization at the whole brain (i.e., multiple network) level. This knowledge gap is surprising given that the decreased segregation of brain networks (i.e., increased internetwork connectivity) can be considered a hallmark of the aging process. Accordingly, we investigated the association between declines in motor performance across the adult lifespan (20-75 years) and age-related modulations of functional connectivity within and between resting state networks. Results indicated that stronger internetwork resting state connectivity observed as a function of age was significantly related to worse motor performance. Moreover, performance had a significantly stronger association with the strength of internetwork as compared with intranetwork connectivity, including connectivity within motor networks. These findings suggest that age-related declines in motor performance may be attributed to a breakdown in the functional organization of large-scale brain networks rather than simply age-related connectivity changes within motor-related networks.

Recent research on traumatic brain injury (TBI) has shown that impairments in cognitive and executive control functions are accompanied by a disrupted neural connectivity characterized by white matter damage. We constructed binary and weighted brain structural networks in 21 patients with chronic TBI and 17 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Executive function was assessed with the local global task and the trail making task, requiring inhibition, updating, and switching. The results revealed that TBI patients were less successful than controls on the executive tasks, as shown by the higher reaction times, higher switch costs, and lower accuracy rates. Moreover, both TBI patients and controls exhibited a small world topology in their white matter networks. More importantly, the TBI patients demonstrated increased shortest path length and decreased global efficiency of the structural network. These findings suggest that TBI patients have a weaker globally integrated structural brain network, resulting in a limited capacity to integrate information across brain regions. Furthermore, we showed that the white matter networks of both groups contained highly connected hub regions that were predominately located in the parietal cortex, frontal cortex, and basal ganglia. Finally, we showed significant correlations between switching performance and network property metrics within the TBI group. Specifically, lower scores on the switching tasks corresponded to a lower global efficiency. We conclude that analyzing the structural brain network connectivity provides new insights into understanding cognitive control changes following brain injury.