The parietal cortex has been implicated in a variety of numerosity and numerical cognition tasks and was proposed to encompass dedicated neural populations that are tuned for analogue magnitudes as well as for symbolic numerals. Nonetheless, it remains unknown whether the parietal cortex plays a role in approximate numerical averaging (rapid, yet coarse computation of numbers' mean)—a process that is fundamental to preference formation and decision-making. To causally investigate the role of the parietal cortex in numerical averaging, we have conducted a transcranial direct current stimulation (tDCS) study, in which participants were presented with rapid sequences of numbers and asked to convey their intuitive estimation of each sequence's average. During the task, the participants underwent anodal (excitatory) tDCS (or sham), applied either on a parietal or a frontal region. We found that, although participants exhibit above-chance accuracy in estimating the average of numerical sequences, they did so with higher precision under parietal stimulation. In a second experiment, we have replicated this finding and confirmed that the effect is number-specific rather than domain-general or attentional. We present a neurocomputational model postulating population-coding underlying rapid numerical averaging to account for our findings. According to this model, stimulation of the parietal cortex elevates neural activity in number-tuned dedicated detectors, leading to increase in the system's signal-to-noise level and thus resulting in more precise estimations.

We propose a neural model for object-oriented attention in which various visual stimuli (shapes, colors, letters, etc.) are represented by competing, mutually inhibitory, cell assemblies. The model's response to a sequence of cue and target stimuli mimics the neural responses in infero temporal (IT) visual cortex of monkeys performing a visual search task: enhanced response during the display of the stimulus, which decays but remains above a spontaneous rate after the cue disappears. When, subsequently, a display consisting of the target and several distractors is presented, the activity of all stimulus-driven cells is initially enhanced. After a short period of time, however, the activity of the cell assembly representing the cue stimulus is enhanced while the activity of the distractors decays because of mutual competition and a small top-down “expectational” input. The model fits the measured delayed activity in IT-cortex, recently reported by Chelazzi, Miller, Duncan, and Desimone (1993a), and we suggest that such a process, which is largely independent of the number of distractors, may be used by the visual system for selecting an expected target (appearing at an uncertain location) among distractors.