Substance Withdrawal Syndrome
Substance Withdrawal Syndrome affects brain function in measurable ways that QEEG brain mapping can identify. At Peak Brain Institute, we use quantitative EEG to assess individual patterns related to substance withdrawal syndrome, then design personalized neurofeedback protocols targeting those specific signatures. Explore our 2 research papers covering this topic.
Research Papers
Brain pathways to recovery from alcohol dependence
This article highlights the research presentations at the satellite symposium on "Brain Pathways to Recovery from Alcohol Dependence" held at the 2013 Society for Neuroscience Annual Meeting. The purpose of this symposium was to provide an up to date overview of research efforts focusing on understanding brain mechanisms that contribute to recovery from alcohol dependence. A panel of scientists from the alcohol and addiction research field presented their insights and perspectives on brain mechanisms that may underlie both recovery and lack of recovery from alcohol dependence. The four sessions of the symposium encompassed multilevel studies exploring mechanisms underlying relapse and craving associated with sustained alcohol abstinence, cognitive function deficit and recovery, and translational studies on preventing relapse and promoting recovery. Gaps in our knowledge and research opportunities were also discussed.
View Full Paper →Real-time fMRI in the treatment of nicotine dependence: a conceptual review and pilot studies
Technical advances allowing for the analysis of functional MRI (fMRI) results in real time have led to studies exploring the ability of individuals to use neural feedback signals to modify behavior and regional brain activation. The use of real-time fMRI (rtfMRI) feedback has been explored for therapeutic benefit in a number of disease states, but to our knowledge, the potential therapeutic benefit of rtfMRI feedback in the treatment of addictive disorders has not been explored. This article will provide an overview of the development of rtfMRI and discussion of its potential uses in the treatment of addictions. We also describe a series of pilot studies that highlight some of the technical challenges in developing a rtfMRI feedback paradigm for use in addictions, specifically in nicotine dependence. Because the use of rtfMRI feedback is in its infancy, the work described is focused on establishing some of the basic parameters in optimizing the rtfMRI feedback, such as the type of feedback signal, region of interest for feedback and predicting which subjects are most likely to respond well to training. While rtfMRI feedback remains an intriguing possibility for the treatment of addictions, much work remains to be done in establishing its efficacy.
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