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).

Musical competence may confer cognitive advantages that extend beyond processing of familiar musical sounds. Behavioural evidence indicates a general enhancement of both working memory and attention in musicians. It is possible that musicians, due to their training, are better able to maintain focus on task-relevant stimuli, a skill which is crucial to working memory. We measured the blood oxygenation-level dependent (BOLD) activation signal in musicians and non-musicians during working memory of musical sounds to determine the relation among performance, musical competence and generally enhanced cognition. All participants easily distinguished the stimuli. We tested the hypothesis that musicians nonetheless would perform better, and that differential brain activity would mainly be present in cortical areas involved in cognitive control such as the lateral prefrontal cortex. The musicians performed better as reflected in reaction times and error rates. Musicians also had larger BOLD responses than non-musicians in neuronal networks that sustain attention and cognitive control, including regions of the lateral prefrontal cortex, lateral parietal cortex, insula, and putamen in the right hemisphere, and bilaterally in the posterior dorsal prefrontal cortex and anterior cingulate gyrus. The relationship between the task performance and the magnitude of the BOLD response was more positive in musicians than in non-musicians, particularly during the most difficult working memory task. The results confirm previous findings that neural activity increases during enhanced working memory performance. The results also suggest that superior working memory task performance in musicians rely on an enhanced ability to exert sustained cognitive control. This cognitive benefit in musicians may be a consequence of focused musical training.

We applied fMRI and diffusion-weighted MRI to study the segregation of cognitive and motor functions in the human cerebro-cerebellar system. Our fMRI results show that a load increase in a nonverbal auditory working memory task is associated with enhanced brain activity in the parietal, dorsal premotor, and lateral prefrontal cortices and in lobules VII-VIII of the posterior cerebellum, whereas a sensory-motor control task activated the motor/somatosensory, medial prefrontal, and posterior cingulate cortices and lobules V/VI of the anterior cerebellum. The load-dependent activity in the crus I/II had a specific relationship with cognitive performance: This activity correlated negatively with load-dependent increase in RTs. This correlation between brain activity and RTs was not observed in the sensory-motor task in the activated cerebellar regions. Furthermore, probabilistic tractography analysis of the diffusion-weighted MRI data suggests that the tracts between the cerebral and the cerebellar areas exhibiting cognitive load-dependent and sensory-motor activity are mainly projected via separated pontine (feed-forward tracts) and thalamic (feedback tracts) nuclei. The tractography results also indicate that the crus I/II in the posterior cerebellum is linked with the lateral prefrontal areas activated by cognitive load increase, whereas the anterior cerebellar lobe is not. The current results support the view that cognitive and motor functions are segregated in the cerebellum. On the basis of these results and theories of the function of the cerebellum, we suggest that the posterior cerebellar activity during a demanding cognitive task is involved with optimization of the response speed.

A sudden change in the direction of motion is a particularly salient and relevant feature of visual information. Extensive research has identified cortical areas responsive to visual motion and characterized their sensitivity to different features of motion, such as directional specificity. However, relatively little is known about responses to sudden changes in direction. Electrophysiological data from animals and functional imaging data from humans suggest a number of brain areas responsive to motion, presumably working as a network. Temporal patterns of activity allow the same network to process information in different ways. The present study in humans sought to determine which motion-sensitive areas are involved in processing changes in the direction of motion and to characterize the temporal patterns of processing within this network of brain regions. To accomplish this, we used both magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). The fMRI data were used as supplementary information in the localization of MEG sources. The change in the direction of visual motion was found to activate a number of areas, each displaying a different temporal behavior. The fMRI revealed motion-related activity in areas MT+ (the human homologue of monkey middle temporal area and possibly also other motion sensitive areas next to MT), a region near the posterior end of the superior temporal sulcus (pSTS), V3A, and V1/V2. The MEG data suggested additional frontal sources. An equivalent dipole model for the generators of MEG signals indicated activity in MT+, starting at 130 ms and peaking at 170 ms after the reversal of the direction of motion, and then again at approximately 260 ms. Frontal activity began 0-20 ms later than in MT+, and peaked approximately 180 ms. Both pSTS and FEF+ showed long-duration activity continuing over the latency range of 200-400 ms. MEG responses in the region of V3A and V1/V2 were relatively small, and peaked at longer latencies than the initial peak in MT+. These data revealed characteristic patterns of activity in this cortical network for processing sudden changes in the direction of visual motion.