Cloud-Based Functional Magnetic Resonance Imaging Neurofeedback to Reduce the Negative Attentional Bias in Depression: A Proof-of-Concept Study

Anne C. Mennen, Nicholas B. Turk-Browne, Grant Wallace, Darsol Seok, Adna Jaganjac, Janet Stock, Megan T. deBettencourt, Jonathan D. Cohen, Kenneth A. Norman, Yvette I. Sheline

Research output: Contribution to journalArticlepeer-review

Abstract

Individuals with depression show an attentional bias toward negatively valenced stimuli and thoughts. In this proof-of-concept study, we present a novel closed-loop neurofeedback procedure intended to remediate this bias. Internal attentional states were detected in real time by applying machine learning techniques to functional magnetic resonance imaging data on a cloud server; these attentional states were externalized using a visual stimulus that the participant could learn to control. We trained 15 participants with major depressive disorder and 12 healthy control participants over 3 functional magnetic resonance imaging sessions. Exploratory analysis showed that participants with major depressive disorder were initially more likely than healthy control participants to get stuck in negative attentional states, but this diminished with neurofeedback training relative to controls. Depression severity also decreased from pre- to posttraining. These results demonstrate that our method is sensitive to the negative attentional bias in major depressive disorder and showcase the potential of this novel technique as a treatment that can be evaluated in future clinical trials.

Original languageEnglish (US)
Pages (from-to)490-497
Number of pages8
JournalBiological Psychiatry: Cognitive Neuroscience and Neuroimaging
Volume6
Issue number4
DOIs
StatePublished - Apr 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Cognitive Neuroscience
  • Clinical Neurology
  • Biological Psychiatry

Keywords

  • Attentional bias
  • Brain-machine interface
  • Cloud computing
  • Cognitive training
  • Depression
  • Real-time fMRI

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