Predicting what you remember from brain activity: EEG-based decoding of long-term memory formation

Taeho Kang, Yiyu Chen, Siamac Fazli, Christian Wallraven

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The use of EEG to enhance learning experience in learning environments can contribute to furthering symbiotic relationship between the user and the system. This study examines whether it is possible to predict successful memorization of previously-learned words in a language learning context from brain activity alone. Participants are tasked with learning German-Korean word association pairs, and their retention performance is tested on the day of and the after learning. We perform statistical analysis as well as single-trial classification to investigate whether brain activity as recorded via multi-channel EEG is able to predict whether a word is remembered or not. Our preliminary results confirm above-chance prediction of successful word learning.

Original languageEnglish
Title of host publicationSymbiotic Interaction - 6th International Workshop, Symbiotic 2017, Revised Selected Papers
EditorsBenjamin Blankertz, Anna Spagnolli, Luciano Gamberini, Giulio Jacucci, Jaap Ham
PublisherSpringer Verlag
Pages63-73
Number of pages11
ISBN (Print)9783319915920
DOIs
Publication statusPublished - Jan 1 2018
Externally publishedYes
Event6th International Workshop on Symbiotic Interaction, SYMBIOTIC 2017 - Eindhoven, Netherlands
Duration: Dec 18 2017Dec 19 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10727 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Workshop on Symbiotic Interaction, SYMBIOTIC 2017
Country/TerritoryNetherlands
CityEindhoven
Period12/18/1712/19/17

Keywords

  • BCI
  • Education
  • EEG
  • Language learning
  • Memory

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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