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Background: The study aimed to isolate and localize mutually independent cognitive processes evoked during a word recognition task involving food-related and food-neutral words using independent component analysis (ICA) for continuously recorded EEG data. Recognition memory (old/new effect) involves cognitive subcomponents-familiarity and recollection-which may be temporally and spatially dissociated in the brain. Food words may evoke additional attentional salience which may interact with the old/new effect., Methods: Sixteen satiated female participants undertook a word recognition task consisting of an encoding phase (learning of presented words, 40 food-related and 40 food neutral) and a test phase (recognition of previously learned words and new words). Simultaneously recorded 64-channel EEG data were decomposed into mutually independent components using the Infomax algorithm in EEGLAB. The components were localized using single dipole fitting using a four-shell BESA head model. The resulting (nonartefactual) components with <15% residual variance were clustered across subjects using the kmeans algorithm resulting in five meaningful clusters localized to fronto-parietal regions. Repeated-measures anova was employed to test main effects (old/new and food relevance) and their interaction on cluster time courses., Results: Early task-relevant old/new effects were localized to the medial frontal gyrus (MFG) and later old/new effects to the right parietal regions (precuneus). Food-related (nontask-relevant) salience effects were localized to bilateral parietal regions (left precuneus and right postcentral gyrus). Food-related salience interacted with task relevance, the old/new effect in MFG being significant only for food-neutral words highlighting central the role of MFG as the converging site of endogenous and exogenous salience inputs., Conclusion: Our results indicate ICA to be a valid technique to decompose complex neurophysiological signals involving multiple cognitive processes and implicate the fronto-parietal network as an important attentional network for processing salience and task demands.