Compressive temporal summation in human visual cortex

Jingyang Zhou, Noah C. Benson, Kendrick N. Kay, Jonathan Winawer

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Combining sensory inputs over space and time is fundamental to vision. Population receptive field models have been successful in characterizing spatial encoding throughout the human visual pathways. A parallel question, how visual areas in the human brain process information distributed over time, has received less attention. One challenge is that the most widely used neuroimaging method, fMRI, has coarse temporal resolution compared with the time-scale of neural dynamics. Here, via carefully controlled temporally modulated stimuli, we show that information about temporal processing can be readily derived from fMRI signal amplitudes in male and female subjects. We find that all visual areas exhibit subadditive summation, whereby responses to longer stimuli are less than the linear prediction from briefer stimuli. We also find fMRI evidence that the neural response to two stimuli is reduced for brief interstimulus intervals (indicating adaptation). These effects are more pronounced in visual areas anterior to V1-V3. Finally, we develop a general model that shows how these effects can be captured with two simple operations: temporal summation followed by a compressive nonlinearity. This model operates for arbitrary temporal stimulation patterns and provides a simple and interpretable set of computations that can be used to characterize neural response properties across the visual hierarchy. Importantly, compressive temporal summation directly parallels earlier findings of compressive spatial summation in visual cortex describing responses to stimuli distributed across space. This indicates that, for space and time, cortex uses a similar processing strategy to achieve higher-level and increasingly invariant representations of the visual world.

Original languageEnglish (US)
Pages (from-to)691-709
Number of pages19
JournalJournal of Neuroscience
Issue number3
StatePublished - Jan 17 2018

Bibliographical note

Funding Information:
Received June 20, 2017; revised Oct. 23, 2017; accepted Nov. 17, 2017. Author contributions: J.Z., N.C.B., K.N.K., and J.W. designed research; J.Z. and J.W. performed research; J.Z., N.C.B., K.N.K., and J.W. analyzed data; J.Z. and J.W. wrote the paper. This work was supported by National Institutes of Health Grants R00-EY022116 and R01-MH111417 to J.W. We thankDavidHeeger,BrianWandell,andMikeLandyforcommentsonanearlierdraftofthismanuscript;andBosco Tjan,DavidHeeger,X.J.Wang,DenisPelli,andRachelDenisonforhelpfuldiscussionsandfeedbackaswedeveloped our models and analyses. The authors declare no competing financial interests. Correspondence should be addressed to Jingyang Zhou, Department of Psychology, New York University, 6 Washington Place, New York, NY 10003. E-mail: DOI:10.1523/JNEUROSCI.1724-17.2017 Copyright © 2018 the authors 0270-6474/18/380691-19$15.00/0


  • Adaptation
  • Population receptive fields
  • Temporal summation
  • Visual cortex
  • Visual hierarchy
  • fMRI

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