Multisensory decisions provide support for probabilistic number representations.
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.
Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland; Center for Learning and Memory and Department of Neuroscience, The University of Texas at Austin, Austin, Texas.
Ingmar
I
Kanitscheider
Cold Spring Harbor Laboratory, Cold Spring Harbor, New York;
Amanda
A
Brown
Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York; Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland; Gatsby Computational Neuroscience Unit, London, United Kingdom; and.
Alexandre
A
Pouget
Cold Spring Harbor Laboratory, Cold Spring Harbor, New York; churchland@cshl.edu.
Anne K
AK
Churchland
D000161:Acoustic Stimulation; D000293:Adolescent; D000328:Adult; D001307:Auditory Perception / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008433:Mathematics; D008875:Middle Aged; D010775:Photic Stimulation; D011336:Probability; D011594:Psychometrics; D013663:Teaching; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult
Bayesian; decision making; multisensory; numerosity; vision