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Related Experiment Video

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Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
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Revealing hidden states in visual working memory using electroencephalography.

Michael J Wolff1, Jacqueline Ding2, Nicholas E Myers3

  • 1Department of Experimental Psychology, University of Groningen Groningen, Netherlands ; Oxford Centre for Human Brain Activity, University of Oxford Oxford, UK.

Frontiers in Systems Neuroscience
|September 22, 2015
PubMed
Summary
This summary is machine-generated.

Information in visual working memory (vWM) may be stored silently. A novel echolocation-like method using EEG successfully decoded silent vWM content by probing brain responses to a visual stimulus.

Keywords:
EEGdynamic codinghidden statemultivariate pattern analysisvisual working memory

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Area of Science:

  • Cognitive Neuroscience
  • Neuroscience
  • Psychology

Background:

  • Visual working memory (vWM) is traditionally thought to rely on persistent neural activity.
  • Emerging evidence suggests vWM information may be maintained in an

Purpose of the Study:

  • To investigate the possibility of

Main Methods:

  • Electroencephalography (EEG) was used to record brain activity.
  • Participants performed a vWM task, remembering a randomly oriented grating.
  • A high-contrast, task-irrelevant stimulus was presented during the maintenance period in half the trials to probe brain responses.

Main Results:

  • Decoding of grating orientation from EEG data was successful during and immediately after stimulus presentation.
  • Decoding accuracy decreased to baseline levels during the delay period.
  • The visual evoked response to the task-irrelevant stimulus led to a significant re-emergence of decodability, indicating retrieval of vWM content.

Conclusions:

  • This study provides proof-of-concept for a novel method to detect "activity-silent" vWM.
  • The proposed echolocation-like approach using EEG is a promising and relatively simple technique for studying silent neural states.