Learning from default mode network: the predictive value of resting state in traumatic brain injury

In the 1880s, the Italian physiologist Angelo Mosso hypothesized that an attentional or cognitive task increases cerebral blood flow (Mosso, 1884). Lacking current technology, he tried to measure the blood flow of a supine live subject with a “delicately balanced table which could tip downward either at the head or the foot if the weight of either end were increased” (James, 1890). In resting conditions, the subject was in perfect equilibrium, whereas during emotional or intellectual tasks the head-end of the table inclined downward (Fig. 1). This incredibly simple but revolutionary balance can be considered the first ante litteram “neuroimaging” technique, one that anticipated the physical principles of functional magnetic resonance imaging (fMRI) and positron emission tomography by numerous decades. These techniques are now becoming essential, both in physiological and pathological conditions, since they enable the imaging and quantification of organized active neural systems in working and resting states.