Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from magnetic resonance imaging (MRI) volumes are intensely researched, but the reported results are largely incomparable due to different datasets and evaluation schemes. We approached this urgent problem of comparability with the Ischemic Stroke Lesion Segmentation (ISLES) challenge organized in conjunction with the MICCAI 2015 conference. In this paper we propose a common evaluation framework, describe the publicly available datasets, and present the results of the two sub-challenges: Sub-Acute Stroke Lesion Segmentation (SISS) and Stroke Perfusion Estimation (SPES). A total of 16 research groups participated with a wide range of state-of-the-art automatic segmentation algorithms. A thorough analysis of the obtained data enables a critical evaluation of the current state-of-the-art, recommendations for further developments, and the identification of remaining challenges. The segmentation of acute perfusion lesions addressed in SPES was found to be feasible. However, algorithms applied to sub-acute lesion segmentation in SISS still lack accuracy. Overall, no algorithmic characteristic of any method was found to perform superior to the others. Instead, the characteristics of stroke lesion appearances, their evolution, and the observed challenges should be studied in detail. The annotated ISLES image datasets continue to be publicly available through an online evaluation system to serve as an ongoing benchmarking resource (www.isles-challenge.org).

Proactive motor inhibition refers to endogenous preparatory mechanisms facilitating action inhibition, whereas reactive motor inhibition is considered to be a sudden stopping process triggered by external signals. Previous studies were inconclusive about the temporal dynamics of involved neurocognitive processes during proactive and reactive motor control. Using electroencephalography (EEG), we investigated the time-course of proactive and reactive inhibition, measuring event-related oscillations and event-related potentials (ERPs). Participants performed in a cued go/nogo paradigm with cues indicating whether the motor response might or might not have to be inhibited. Based on the dual mechanisms of control (DMC) framework by Braver, we investigated the role of attentional effects, motor preparation in the sensorimotor cortex and prefrontal cognitive control mechanisms, separating effects before and after target onset. In the cue-target interval, proactive motor inhibition was associated with increased attention, reflected in reduced visual alpha power and an increased contingent negative variation (CNV). At the same time, motor inhibition was modulated by reduced sensorimotor beta power. After target onset, proactive inhibition resulted in an increased N1, indicating allocation of attention towards relevant stimuli, increased prefrontal beta power and a modulation of sensorimotor mu activity. As in previous studies, reactive stopping of motor actions was associated with increased prefrontal beta power and increased sensorimotor beta activity. The results stress the relevance of attentional mechanisms for proactive inhibition and speak for different neurocognitive mechanisms being involved in the early preparation for and in later implementation of motor inhibition.

Proactive motor control is a preparatory mechanism facilitating upcoming action inhibition or adaptation. Previous studies investigating proactive motor control mostly focused on response inhibition, as in the classical go-nogo or stop-signal tasks. However, everyday life rarely calls for the complete suppression of actions without subsequent behavioral adjustment. Therefore, we conducted a modified cued go-nogo-change task, in which cues indicated whether participants might have to change to an alternative action or inhibit the response to an upcoming target. Based on the dual-mechanisms of control framework and using electroencephalography (EEG), we investigated the role of the sensorimotor cortex and of prefrontal regions in preparing to change and cancel motor responses. We focused on mu and beta power over sensorimotor cortex ipsi- and contralateral to an automatic motor response and on prefrontal beta power. Over ipsilateral sensorimotor cortex, mu and beta power was relatively decreased when anticipating to change or inhibit the automatic motor behavior. Moreover, alpha phase coupling between ipsilateral motor cortex and prefrontal areas decreased when preparing to change, suggesting a decoupling of sensorimotor regions from prefrontal control. When the standard motor action actually had to be changed, prefrontal beta power increased, reflecting enhanced cognitive control. Our data highlight the role of the ipsilateral motor cortex in preparing to inhibit and change upcoming motor actions. Here, especially mu power and phase coupling seem to be critical to guide upcoming behavior.

No abstract

No abstract