Towards Using Microstate-Neurofeedback for the Treatment of Psychotic Symptoms in Schizophrenia. A Feasibility Study in Healthy Participants

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• 作者：Laura Diaz Hernandez ; Kathryn Rieger ; Anja Baenninger ; Daniel Brandeis…
• 关键词：EEG ; Neurofeedback ; Resting state ; Microstates ; Modelling ; Schizophrenia
• 刊名：Brain Topography
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：29
• 期：2
• 页码：308-321
• 全文大小：1,658 KB
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• 作者单位：Laura Diaz Hernandez (1)
  Kathryn Rieger (1) (2)
  Anja Baenninger (1)
  Daniel Brandeis (3) (4) (5) (6)
  Thomas Koenig (1) (2)
  
  1. Translational Research Center, University Hospital of Psychiatry, University of Bern, Bolligenstrasse 111, 3000, Bern 60, Switzerland
  2. Center for Cognition, Learning and Memory, University of Bern, Fabrikstrasse 8, 3012, Bern, Switzerland
  3. Department of Child and Adolescent Psychiatry, University of Zürich, Neumünsterallee 9/Fach, 8032, Zurich, Switzerland
  4. Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159, Mannheim, Germany
  5. Zurich Center for Integrative Human Physiology, University of Zürich, Zurich, Switzerland
  6. Neuroscience Center Zurich, University and ETH Zürich, Zurich, Switzerland
  
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Biomedicine
  Neurosciences
  Psychiatry
  Neurology
  
• 出版者：Springer New York
• ISSN：1573-6792

文摘

Spontaneous EEG signal can be parsed into sub-second periods of stable functional states (microstates) that assumingly correspond to brief large scale synchronization events. In schizophrenia, a specific class of microstate (class “D”) has been found to be shorter than in healthy controls and to be correlated with positive symptoms. To explore potential new treatment options in schizophrenia, we tested in healthy controls if neurofeedback training to self-regulate microstate D presence is feasible and what learning patterns are observed. Twenty subjects underwent EEG-neurofeedback training to up-regulate microstate D presence. The protocol included 20 training sessions, consisting of baseline trials (resting state), regulation trials with auditory feedback contingent on microstate D presence, and a transfer trial. Response to neurofeedback was assessed with mixed effects modelling. All participants increased the percentage of time spent producing microstate D in at least one of the three conditions (p < 0.05). Significant between-subjects across-sessions results showed an increase of 0.42 % of time spent producing microstate D in baseline (reflecting a sustained change in the resting state), 1.93 % of increase during regulation and 1.83 % during transfer. Within-session analysis (performed in baseline and regulation trials only) showed a significant 1.65 % increase in baseline and 0.53 % increase in regulation. These values are in a range that is expected to have an impact upon psychotic experiences. Additionally, we found a negative correlation between alpha power and microstate D contribution during neurofeedback training. Given that microstate D has been related to attentional processes, this result provides further evidence that the training was to some degree specific for the attentional network. We conclude that microstate-neurofeedback training proved feasible in healthy subjects. The implementation of the same protocol in schizophrenia patients may promote skills useful to reduce positive symptoms by means of EEG-neurofeedback.