Tracking Perceptual and Memory Decisions by Decoding Brain Activity

van Vugt, M., Brandt, A. & Schulze-Bonhage, A., 8-Nov-2017, BIAS 2017 preproceedings. University of Groningen, p. 76-85

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Decision making is thought to involve a process of evidence accumulation, modelled as a drifting diffusion process. This modeling framework suggests that all single-stage decisions involve a similar evidence accumulation process. In this paper we use decoding by machine learning classifiers on intracranially recorded EEG (iEEG) to examine whether different kinds of decisions (perceptual vs. memory) exhibit dynamics consistent with such drift diffusion models. We observed that decisions are indeed decodable from brain activity for both perceptual and memory decisions, and that the time courses for these types of decisions appear to be quite similar. Moreover, the high spatial resolution of iEEG reveals that perceptual and memory decisions rely on slightly different brain areas. While the accuracy of decision decoding can stil be improved, these initial studies demonstrate the power of decoding analyses to examine computational models of cognition.
Original languageEnglish
Title of host publicationBIAS 2017 preproceedings
PublisherUniversity of Groningen
ISBN (Print)78-94-034-0299-4
Publication statusPublished - 8-Nov-2017
EventThe 29th Benelux Conference on Artificial Intelligence - Groningen, Netherlands
Duration: 8-Nov-20179-Nov-2017


ConferenceThe 29th Benelux Conference on Artificial Intelligence
Abbreviated titleBNAIC 2017
Internet address


The 29th Benelux Conference on Artificial Intelligence


Groningen, Netherlands

Event: Conference


  • decision making, mvpa, ECoG, brain oscillations

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