September 2015
Volume 15, Issue 12
Free
Vision Sciences Society Annual Meeting Abstract  |   September 2015
Manipulating Perceptual Decisions Using Input From Others
Author Affiliations
  • Koel Das
    Indian Institute of Science Education and Research, Kolkata
  • Bapun Giri
    Indian Institute of Science Education and Research, Kolkata
  • Arpita Chowdhury
    Indian Institute of Science Education and Research, Kolkata
  • Sucheta Chakravarty
    Indian Institute of Science Education and Research, Kolkata
Journal of Vision September 2015, Vol.15, 621. doi:10.1167/15.12.621
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      Koel Das, Bapun Giri, Arpita Chowdhury, Sucheta Chakravarty; Manipulating Perceptual Decisions Using Input From Others. Journal of Vision 2015;15(12):621. doi: 10.1167/15.12.621.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

How prior expectation modulates perceptual decision making(Summerfield and de Lange, Puri and Wojciulik) is a topic of active research. But it is not clear how our decision making is influenced by decisions of others. Here we systematically manipulate cues to explore how input from observers affect perceptual decisions. Seventeen naive observers perceptually categorized briefly (50 ms) presented images of cars (C) and faces (F) embedded in filtered noise while their EEG activity was recorded for 1000 trials. Observers were rapidly (100 ms) presented with prior cues(FF,CC,FC,CF) in the guise of decisions of previous observers. Cues were randomly generated so that equal number of images have positive cues(e.g.:FF followed by Face image), negative cues, neutral cues and no cues. Observers reported their decision (face/car) using a 10-point confidence rating. A multivariate pattern classifier was used to predict the object (face/car). Classifier performance identifying Face/Car from single trial EEG activity averaged across observers increased significantly (69.1%± 0.02) in presence of positive cues and decreased (66.5%± 0.02) with negative cues. Behavioral performance was consistent with the neural results. The neural decision variables extracted from the classifier correlated with observer's decision confidence showing highest positive correlation(r=0.76) with positive cues and lowest (r=0.605) with negative cues. Classifier performance for positive cues increased significantly reaching the highest accuracy(64.8% ± 0.02) during the time-interval of 240-280 ms. Classifier accuracy monotonically decreased till 400 ms and increased to 63%± 0.02 during a later epoch(500-550 ms.). Our findings suggest that perceptual decisions can be reliably manipulated using non-informative cues. The identified neural mechanisms predicting the object when positive cues are presented seem to be distinct from those with negative cues. The temporally localized nature of the neural activity suggests that input from others influence an observer's decision significantly in the visually evoked epoch and later post-stimulus intervals.

Meeting abstract presented at VSS 2015

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