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Introduction: Patients with carotid stenosis, without history of stroke or transient ischemic attack are considered to be asymptomatic. However, many of those patients might have some degree of cognitive decline, changes in perfusion and functional connectivity that may precede clinical events suggesting a high risk for stroke. In this study, we aimed to evaluate the frequency and severity of cerebral blood flow (CBF), functional connectivity (FC) and cognitive performance abnormalities in patients with severe “asymptomatic” carotid artery stenosis (aCAS).Methods: Fifteen patients with aCAS >70% and 15 controls were evaluated with 3T MRI, including BOLD-FMRI, Pseudo-continuous Arterial Spin Labeling and Resting-State Brain Networks. The cognitive assessment included tests for executive function, psychomotor speed, attention and memory. We used Mann-Whitney U Test to compare cognition and CBF between groups; Wilcoxon test for intragroup CBF differences; Spearman Correlation Coefficient for associations between CBF, FC and cognition.Results: CBF maps in patients with aCAS revealed reduction in blood flow in the gray matter of temporal lobes and internal structures when compared to controls (p<0.05). The cognitive performance of patients with aCAS was lower than the control group for all measures, with significant differences in attention, mnemonic process and executive functions (p<0.05). Patients presented decreased connectivity for the fronto-temporal, salience and dorsal attentional networks (p-FDR<0.01). Additionally, we observed significant correlations (p<0.01) between salience network and the cognitive measures performed in this study.Conclusions: Subjects with aCAS showed less expressive networks and significantly lower cognitive performance, indicating deficits in fundamental networks for the identification of relevant stimuli, neural resource coordination, and information processing. We identified preclinical abnormalities in CBF, FC and cognitive performance of patients with aCAS, suggesting that neuroimaging markers in MRI, combined with cognitive assessment, have a great potential to identify the profile of patients with high risk of stroke and cognitive decline.