Connectivity Concordance Mapping: A New Tool for Model-Free Analysis of fMRI Data of the Human Brain

Functional magnetic resonance data acquired in a task-absent condition (“resting state”) require new data analysis techniques that do not depend on an activation model. Here, we propose a new analysis method called Connectivity Concordance Mapping (CCM). The main idea is to assign a label to each voxel based on the reproducibility of its whole-brain pattern of connectivity. Specifically, we compute the correlations of time courses of each voxel with every other voxel for each measurement. Voxels whose correlation pattern is consistent across measurements receive high values. The result of a CCM analysis is thus a voxel-wise map of concordance values. Regions of high inter-subject concordance can be assumed to be functionally consistent, and may thus be of specific interest for further analysis. Here we present two fMRI studies to demonstrate the possible applications of the algorithm. The first is a eyes-open/eyes-closed paradigm designed to highlight the potential of the method in a relatively simple domain. The second study is a longitudinal repeated measurement of a patient following stroke. Longitudinal clinical studies such as this may represent the most interesting domain of applications for this algorithm

Clinically relevant depressive symptoms in young stroke patients - results of the sifap1 study

BACKGROUND Although post-stroke depression is widely recognized, less is known about depressive symptoms in the acute stage of stroke and especially in young stroke patients. We thus investigated depressive symptoms and their determinants in such a cohort. METHODS The Stroke in Young Fabry Patients study (sifap1) prospectively recruited a large multinational European cohort (n = 5,023) of patients with a cerebrovascular event aged 18-55. For assessing clinically relevant depressive symptoms (CRDS, defined by a BDI-score ≥18) the self-reporting Beck Depression Inventory (BDI) was obtained on inclusion in the study. Associations with baseline parameters, stroke severity (National Institutes of Health Stroke Scale, NIHSS), and brain MRI findings were analyzed. RESULTS From the 2007 patients with BDI documentation, 202 (10.1%) had CRDS. CRDS were observed more frequently in women (12.6 vs. 8.2% in men, p < 0.001). Patients with CRDS more often had arterial hypertension, diabetes mellitus, and hyperlipidemia than patients without CRDS (hypertension: 58.0 vs. 47.1%, p = 0.017; diabetes mellitus: 17.9 vs. 8.9%, p < 0.001; hyperlipidemia: 40.5 vs. 32.3%, p = 0.012). In the subgroup of patients with ischemic stroke or TIA (n = 1,832) no significant associations between CRDS and cerebral MRI findings such as the presence of acute infarcts (68.1 vs. 65.8%, p = 0.666), old infarctions (63.4 vs. 62.1%, p = 0.725) or white matter hyper-intensities (51.6 vs. 53.7%, p = 0.520) were found. CONCLUSION Depressive symptoms were present in 10.1% of young stroke patients in the acute phase, and were related to risk factors but not to imaging findings