fnint-06-00025.pdf (769.44 kB)
Download file

Representation of numerosity in posterior parietal cortex

Download (769.44 kB)
journal contribution
posted on 01.11.2013, 00:00 by Jamie D. Roitman, Elizabeth M. Brannon, Michael L. Platt
Humans and animals appear to share a similar representation of number as an analog magnitude on an internal, subjective scale. Neurological and neurophysiological data suggest that posterior parietal cortex (PPC) is a critical component of the circuits that form the basis of numerical abilities in humans. Patients with parietal lesions are impaired in their ability to access the deep meaning of numbers. Acalculiac patients with inferior parietal damage often have difficulty performing arithmetic (2 + 4?) or number bisection (what is between 3 and 5?) tasks, but are able to recite multiplication tables and read or write numerals. Functional imaging studies of neurologically intact humans performing subtraction, number comparison, and non-verbal magnitude comparison tasks show activity in areas within the intraparietal sulcus (IPS). Taken together, clinical cases and imaging studies support a critical role for parietal cortex in the mental manipulation of numerical quantities. Further, responses of single PPC neurons in non-human primates are sensitive to the numerosity of visual stimuli independent of low-level stimulus qualities. When monkeys are trained to make explicit judgments about the numerical value of such stimuli, PPC neurons encode their cardinal numerical value; without such training PPC neurons appear to encode numerical magnitude in an analog fashion. Here we suggest that the spatial and integrative properties of PPC neurons contribute to their critical role in numerical cognition.


Publisher Statement

This Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission. © 2012 by Frontiers Research Foundation , Frontiers in Integrative Neuroscience.


Frontiers Research Foundation





Issue date


Usage metrics