• Fabrizio Esposito, Alessandro Bertolino, Tommaso Scarabino, Valeria Latorre, Giuseppe Blasi, Teresa Popolizio, Gioacchino Tedeschi, Sossio Cirillo, Rainer Goebel, and Francesco Di Salle.
• Department of Neurological Sciences, University of Naples Federico II, II Policlinico (Nuovo Policlinico) Padiglione 17, Via S. Pansini 5, 80131 Naples, Italy. faesposi@unina.it
• Brain Res. Bull. 2006 Oct 16; 70 (4-6): 263-9.

AbstractThe "default-mode" network is an ensemble of cortical regions, which are typically deactivated during demanding cognitive tasks in functional magnetic resonance imaging (fMRI) studies. Using functional connectivity, this network can be conceptualized and studied as a "stand-alone" function or system. Regardless of the task, independent component analysis (ICA) produces a picture of the "default-mode" function even when the subject is performing a simple sensori-motor task or just resting in the scanner. This has boosted the use of default-mode fMRI for non-invasive research in brain disorders. Here, we studied the effect of cognitive load modulation of fMRI responses on the ICA-based pictures of the default-mode function. In a standard graded working memory study based on the n-back task, we used group-level ICA to explore the variability of the default-mode network related to the engagement in the task, in 10 healthy volunteers. The analysis of the default-mode components highlighted similarities and differences in the layout under three different cognitive loads. We found a load-related general increase of deactivation in the cortical network. Nonetheless, a variable recruitment of the cingulate regions was evident, with greater extension of the anterior and lesser extension of the posterior clusters when switching from lower to higher working memory loads. A co-activation of the hippocampus was only found under no working memory load. As a generalization of our results, the variability of the default-mode pattern may link the default-mode system as a whole to cognition and may more directly support use of the ICA model for evaluating cognitive decline in brain disorders.

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