Loss of reliable temporal structure in event-related averaging of naturalistic stimuli

Aya Ben-Yakov, Christopher J. Honey, Yulia Lerner, Uri Hasson*

*Corresponding author for this work

Research output: Contribution to journalComment/debate

35 Scopus citations


To separate neural signals from noise, brain responses measured in neuroimaging are routinely averaged across space and time. However, such procedures may obscure some properties of neural activity. Recently, multi-voxel pattern analysis methods have demonstrated that patterns of activity across voxels contain valuable information that is concealed by spatial averaging. Here we show that temporal patterns of neural activity contain information that can discriminate different stimuli, even within brain regions that show no net activation to that stimulus class. Furthermore, we find that in many brain regions, responses to natural stimuli are highly context dependent. In such cases, prototypical event-related responses do not even exist for individual stimuli, so that averaging responses to the same stimulus within different contexts may worsen the effective signal-to-noise. As a result, analysis of the temporal structures of single events can reveal aspects of neural dynamics which cannot be detected using standard event-related averaging methods.

Original languageAmerican English
Pages (from-to)501-506
Number of pages6
Issue number1
StatePublished - 15 Oct 2012
Externally publishedYes

Bibliographical note

Funding Information:
We thank Michael Arcaro, Nicholas Turk-Browne, David Poeppel and Ralf Schmaelzle for their helpful comments on the manuscript. UH and CJH were supported by the National Institute of Mental Health award R01MH094480 and the R21-DA024423 .


  • Event-related averaging
  • Inter-subject correlation
  • Natural stimuli
  • Signal reliability


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