Literature DB >> 25744886

Multisensory decisions provide support for probabilistic number representations.

Ingmar Kanitscheider1, Amanda Brown2, Alexandre Pouget3, Anne K Churchland4.   

Abstract

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.
Copyright © 2015 the American Physiological Society.

Entities:  

Keywords:  Bayesian; decision making; multisensory; numerosity; vision

Mesh:

Year:  2015        PMID: 25744886      PMCID: PMC4455484          DOI: 10.1152/jn.00787.2014

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  52 in total

1.  A model of the neural basis of the rat's sense of direction.

Authors:  W E Skaggs; J J Knierim; H S Kudrimoti; B L McNaughton
Journal:  Adv Neural Inf Process Syst       Date:  1995

2.  Numerosity discrimination in infants: evidence for two systems of representations.

Authors:  Fei Xu
Journal:  Cognition       Date:  2003-08

3.  Supramodal numerosity selectivity of neurons in primate prefrontal and posterior parietal cortices.

Authors:  Andreas Nieder
Journal:  Proc Natl Acad Sci U S A       Date:  2012-07-03       Impact factor: 11.205

4.  Bayesian inference with probabilistic population codes.

Authors:  Wei Ji Ma; Jeffrey M Beck; Peter E Latham; Alexandre Pouget
Journal:  Nat Neurosci       Date:  2006-10-22       Impact factor: 24.884

5.  Cue combination and the effect of horizontal disparity and perspective on stereoacuity.

Authors:  Anna M Zalevski; G Bruce Henning; N Jeremy Hill
Journal:  Spat Vis       Date:  2007

Review 6.  Probabilistic brains: knowns and unknowns.

Authors:  Alexandre Pouget; Jeffrey M Beck; Wei Ji Ma; Peter E Latham
Journal:  Nat Neurosci       Date:  2013-08-18       Impact factor: 24.884

7.  Development of elementary numerical abilities: a neuronal model.

Authors:  S Dehaene; J P Changeux
Journal:  J Cogn Neurosci       Date:  1993       Impact factor: 3.225

8.  Nonverbal arithmetic in humans: light from noise.

Authors:  Sara Cordes; C R Gallistel; Rochel Gelman; Peter Latham
Journal:  Percept Psychophys       Date:  2007-10

9.  Young children bet on their numerical skills: metacognition in the numerical domain.

Authors:  Vy A Vo; Rosa Li; Nate Kornell; Alexandre Pouget; Jessica F Cantlon
Journal:  Psychol Sci       Date:  2014-06-27

10.  Monotonic coding of numerosity in macaque lateral intraparietal area.

Authors:  Jamie D Roitman; Elizabeth M Brannon; Michael L Platt
Journal:  PLoS Biol       Date:  2007-08       Impact factor: 8.029

View more
  5 in total

1.  Three challenges for connecting model to mechanism in decision-making.

Authors:  A K Churchland; R Kiani
Journal:  Curr Opin Behav Sci       Date:  2016-10

2.  Integration of visual and whisker signals in rat superior colliculus.

Authors:  Saba Gharaei; Ehsan Arabzadeh; Samuel G Solomon
Journal:  Sci Rep       Date:  2018-11-06       Impact factor: 4.379

3.  Stimulus Reliability Automatically Biases Temporal Integration of Discrete Perceptual Targets in the Human Brain.

Authors:  Dragan Rangelov; Rebecca West; Jason B Mattingley
Journal:  J Neurosci       Date:  2021-07-29       Impact factor: 6.167

4.  Fast and Accurate Learning When Making Discrete Numerical Estimates.

Authors:  Adam N Sanborn; Ulrik R Beierholm
Journal:  PLoS Comput Biol       Date:  2016-04-12       Impact factor: 4.475

5.  Sources of noise during accumulation of evidence in unrestrained and voluntarily head-restrained rats.

Authors:  Benjamin B Scott; Christine M Constantinople; Jeffrey C Erlich; David W Tank; Carlos D Brody
Journal:  Elife       Date:  2015-12-17       Impact factor: 8.140

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.