A two-stage process model of sensory discrimination: An alternative to drift-diffusion

Peng Sun, Michael Landy

Research output: Contribution to journalArticle

Abstract

Discrimination of the direction of motion of a noisy stimulus is an example of sensory discrimination under uncertainty. For stimuli that are extended in time, reaction time is quicker for larger signal values (e.g., discrimination of opposite directions of motion compared with neighboring orientations) and larger signal strength (e.g., stimuli with higher contrast or motion coherence, that is, lower noise). The standard model of neural responses (e.g., in lateral intraparietal cortex) and reaction time for discrimination is drift-diffusion. This model makes two clear predictions. (1) The effects of signal strength and value on reaction time should interact multiplicatively because the diffusion process depends on the signal-to-noise ratio. (2) If the diffusion process is interrupted, as in a cued-response task, the time to decision after the cue should be independent of the strength of accumulated sensory evidence. In two experiments with human participants, we show that neither prediction holds. A simple alternative model is developed that is consistent with the results. In this estimate-then-decide model, evidence is accumulated until estimation precision reaches a threshold value. Then, a decision is made with duration that depends on the signal-to-noise ratio achieved by the first stage.

Original languageEnglish (US)
Pages (from-to)11259-11274
Number of pages16
JournalJournal of Neuroscience
Volume36
Issue number44
DOIs
StatePublished - Nov 2 2016

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Reaction Time
Signal-To-Noise Ratio
Uncertainty
Cues
Noise
Discrimination (Psychology)
Direction compound

Keywords

  • Discrimination
  • Drift-diffusion
  • Motion
  • Orientation
  • Psychophysics
  • Reaction time

ASJC Scopus subject areas

  • Neuroscience(all)

Cite this

A two-stage process model of sensory discrimination : An alternative to drift-diffusion. / Sun, Peng; Landy, Michael.

In: Journal of Neuroscience, Vol. 36, No. 44, 02.11.2016, p. 11259-11274.

Research output: Contribution to journalArticle

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