A temporal basis for weber’s law in value perception

Vijay Mohan K. Namboodiri, Stefan Mihalas, Marshall G. Hussain Shuler

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


Weber’s law—the observation that the ability to perceive changes in magnitudes of stimuli is proportional to the magnitude—is a widely observed psychophysical phenomenon. It is also believed to underlie the perception of reward magnitudes and the passage of time. Since many ecological theories state that animals attempt to maximize reward rates, errors in the perception of reward magnitudes and delays must affect decision-making. Using an ecological theory of decision-making (TIMERR), we analyze the effect of multiple sources of noise (sensory noise, time estimation noise, and integration noise) on reward magnitude and subjective value perception. We show that the precision of reward magnitude perception is correlated with the precision of time perception and that Weber’s law in time estimation can lead to Weber’s law in value perception. The strength of this correlation is predicted to depend on the reward history of the animal. Subsequently, we show that sensory integration noise (either alone or in combination with time estimation noise) also leads to Weber’s law in reward magnitude perception in an accumulator model, if it has balanced Poisson feedback. We then demonstrate that the noise in subjective value of a delayed reward, due to the combined effect of noise in both the perception of reward magnitude and delay, also abides by Weber’s law. Thus, in our theory we prove analytically that the perception of reward magnitude, time, and subjective value change all approximately obey Weber’s law.

Original languageEnglish (US)
Article number79
JournalFrontiers in Integrative Neuroscience
Issue numberOCT
StatePublished - Oct 14 2014


  • Decision making
  • Reward
  • Scalar timing
  • Subjective value
  • Uncertainty
  • Weber’s law

ASJC Scopus subject areas

  • Sensory Systems
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience


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