Cloud-Based Functional Magnetic Resonance Imaging Neurofeedback to Reduce the Negative Attentional Bias in Depression: A Proof-of-Concept Study
| Autor: | Nicholas B. Turk-Browne, Janet Stock, Megan T. deBettencourt, Kenneth A. Norman, Jonathan D. Cohen, Grant Wallace, Yvette I. Sheline, Anne C. Mennen, Darsol Seok, Adna Jaganjac |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
medicine.diagnostic_test Cognitive Neuroscience 05 social sciences Attentional bias Stimulus (physiology) Audiology medicine.disease 050105 experimental psychology Cognitive training 03 medical and health sciences 0302 clinical medicine Proof of concept medicine Major depressive disorder 0501 psychology and cognitive sciences Radiology Nuclear Medicine and imaging Neurology (clinical) Neurofeedback Functional magnetic resonance imaging Psychology 030217 neurology & neurosurgery Biological Psychiatry Brain–computer interface |
| Zdroj: | Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. 6:490-497 |
| ISSN: | 2451-9022 |
| DOI: | 10.1016/j.bpsc.2020.10.006 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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