Learning to predict : exposure to temporal sequences facilitates prediction of future events

Rosalind Baker, Matthew Dexter, Tom E. Hardwicke, Aimee Goldstone, Zoe Kourtzi

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
211 Downloads (Pure)


Previous experience is thought to facilitate our ability to extract spatial and temporal regularities from cluttered scenes. However, little is known about how we may use this knowledge to predict future events. Here we test whether exposure to temporal sequences facilitates the visual recognition of upcoming stimuli. We presented observers with a sequence of leftwards and rightwards oriented gratings that was interrupted by a test stimulus. Observers were asked to indicate whether the orientation of the test stimulus matched their expectation based on the preceding sequence. Our results demonstrate that exposure to temporal sequences without feedback facilitates our ability to predict an upcoming stimulus. In particular, observers’ performance improved following exposure to structured but not random sequences. Improved performance lasted for a prolonged period and generalized to untrained stimulus orientations rather than sequences of different global structure, suggesting that observers acquire knowledge of the sequence structure rather than its items. Further, this learning was compromised when observers performed a dual task resulting in increased attentional load. These findings suggest that exposure to temporal regularities in a scene allows us to accumulate knowledge about its global structure and predict future events.
Original languageEnglish
Pages (from-to)124-133
JournalVision Research
Early online date11 Nov 2013
Publication statusPublished - Jun 2014


  • Visual learning
  • Transfer
  • Perception
  • Prediction
  • Attention


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