Towards a Novel Way to Predict Deficits After a Brain Lesion: A Stroke Example Many studies have addressed the relations between different human brain regions and their role in cognitive, motor and sensory functions in patients that have suffered a brain lesion (stroke, traumatic brain injury, tissue removal). Nowadays, it is well established that the brain works as a network and the symptoms in a person are a combination of the direct impact of the lesion in a single region and its connectivity with other healthy brain regions. The aim of the present study is the development of a userfriendly desktop application to predict the induced cognitive deficits in patients who have suffered a brain lesion. The herein presented application is based on Neurosynth platform, and takes as an input a MRI mask that describes a lesion. Then our software exploits the knowledge that already exists in Neurosynth platform, so as to predict the potential deficits by grouping the Neurosynthu0027s terms that have increased Z scores with our mask. In addition, we have embedded two types of visualization methods: One to present the slices of the brain mask and another to show the 3D volume of the mask into 3D semitransparent human brain. The added value of the presented application is that it may give us a clue about which mechanisms are probably affected by a lesion in a specific region, while in the future it could provide neurosurgeons with insightful knowledge helping them in the plannification of a forthcoming surgical procedure. The proposed software was tested on 7 stroke patients, predicting accurately the 91% of the measured deficits found during a neuropsychological assessment.

Damage to the shortest structural paths between brain regions is associated with disruptions of restingstate functional connectivity after stroke Abstract   Focal brain lesions disrupt restingstate functional connectivity, but the underlying structural mechanisms are unclear. Here, we examined the direct and indirect effects of structural disconnections on restingstate functional connectivity in a large sample of subacute stroke patients with heterogeneous brain lesions. We estimated the impact of each patientu0027s lesion on the structural connectome by embedding the lesion in a diffusion MRI streamline tractography atlas constructed using data from healthy individuals. We defined direct disconnections as the loss of direct structural connections between two regions, and indirect disconnections as increases in the shortest structural path length between two regions that lack direct structural connections. We then tested the hypothesis that functional connectivity disruptions would be more severe for disconnected regions than for regions with spared connections. On average, nearly 20% of all region pairs were estimated to be either directly or indirectly disconnected by the lesions in our sample, and extensive disconnections were associated primarily with damage to deep white matter locations. Importantly, both directly and indirectly disconnected region pairs showed more severe functional connectivity disruptions than region pairs with spared direct and indirect connections, respectively, although functional connectivity disruptions tended to be most severe between region pairs that sustained direct structural disconnections. Together, these results emphasize the widespread impacts of focal brain lesions on the structural connectome and show that these impacts are reflected by disruptions of the functional connectome. Further, they indicate that in addition to direct structural disconnections, lesioninduced increases in the structural shortest path lengths between indirectly structurally connected region pairs provide information about the remote functional disruptions caused by focal brain lesions.