Journal
JOURNAL OF NEUROPHYSIOLOGY
Volume 113, Issue 10, Pages 3490-3498Publisher
AMER PHYSIOLOGICAL SOC
DOI: 10.1152/jn.00787.2014
Keywords
Bayesian; decision making; multisensory; numerosity; vision
Categories
Funding
- National Science Foundation (NSF) [NSF1111197, NSF1109366]
- Direct For Education and Human Resources
- Division Of Research On Learning [1109366] Funding Source: National Science Foundation
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A large body of evidence suggests that an approximate number sense allows humans to estimate numerosity in sensory scenes. This ability is widely observed in humans, including those without formal mathematical training. Despite this, many outstanding questions remain about the nature of the numerosity representation in the brain. Specifically, it is not known whether approximate numbers are represented as scalar estimates of numerosity or, alternatively, as probability distributions over numerosity. In the present study, we used a multisensory decision task to distinguish these possibilities. We trained human subjects to decide whether a test stimulus had a larger or smaller numerosity compared with a fixed reference. Depending on the trial, the numerosity was presented as either a sequence of visual flashes or a sequence of auditory tones, or both. To test for a probabilistic representation, we varied the reliability of the stimulus by adding noise to the visual stimuli. In accordance with a probabilistic representation, we observed a significant improvement in multisensory compared with unisensory trials. Furthermore, a trial-by-trial analysis revealed that although individual subjects showed strategic differences in how they leveraged auditory and visual information, all subjects exploited the reliability of unisensory cues. An alternative, nonprobabilistic model, in which subjects combined cues without regard for reliability, was not able to account for these trial-by-trial choices. These findings provide evidence that the brain relies on a probabilistic representation for numerosity decisions.
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