The research in this area is focused on understanding the neural substrates of numerical cognition. In particular, we are interested in investigating the neural networks involved in subitizing and estimation. In visual enumeration tasks, participants are required to determine the numerosity of a set of items; in this domain, one intriguing phenomenon is the rapid, precise and confident judgment of the numerosity of small sets, known as subitizing (Kaufman, Lord, Reese, & Volkmann, 1949). Subitizing can be usually observed only up to four items (Trick & Pylyshyn, 1994): enumeration within this range is apparently effortless and item numerosity has a close-to-nil effect on reaction times (RTs) and errors. When such limit is exceeded and serial counting is precluded, OTS gives way to another pre-verbal system that supports numerosity estimation, the Approximate Number System (ANS) (Feigenson, Dehaene, & Spelke, 2004; Piazza, 2010; Stoianov & Zorzi, 2012). ANS computes an approximate representation of numerosity with a characteristic variability signature that obeys Weber’s law. Neuroimaging data suggests that the core region of numerical processing is located in the intraparietal sulcus.