Josef Faller1, Jayce Doose2, Xiaoxiao Sun3, James R Mclntosh4, Golbarg T Saber5, Yida Lin6, Joshua B Teves7, Aidan Blankenship7, Sarah Huffman8, Robin I Goldman9, Mark S George10, Truman R Brown11, Paul Sajda12. 1. Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA. 2. Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, 29425, USA. 3. Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA; US DEVCOM Army Research Laboratory, Aberdeen Proving Ground, MD, 20115, USA. 4. Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA; Department of Orthopaedic Surgery, Columbia University Irving Medical Center, New York, NY, 10032, USA. 5. Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, 29425, USA; Department of Neurology, University of Chicago, Chicago, IL, 60637, USA. 6. Department of Computer Science, Columbia University, New York, NY, 10027, USA. 7. Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, 29425, USA. 8. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, 29425, USA. 9. Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, 53705, USA. 10. Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, 29425, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, 29401, USA. 11. Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, 29425, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, 29425, USA. 12. Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA; Department of Radiology, Columbia University Irving Medical Center, New York, NY, 10032, USA; Department of Electrical Engineering, Columbia University, New York, NY, 10027, USA; Data Science Institute, Columbia University, New York, NY, 10027, USA. Electronic address: psajda@columbia.edu.
Abstract
BACKGROUND: Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation modality that can treat depression, obsessive-compulsive disorder, or help smoking cessation. Research suggests that timing the delivery of TMS relative to an endogenous brain state may affect efficacy and short-term brain dynamics. OBJECTIVE: To investigate whether, for a multi-week daily treatment of repetitive TMS (rTMS), there is an effect on brain dynamics that depends on the timing of the TMS relative to individuals' prefrontal EEG quasi-alpha rhythm (between 6 and 13 Hz). METHOD: We developed a novel closed-loop system that delivers personalized EEG-triggered rTMS to patients undergoing treatment for major depressive disorder. In a double blind study, patients received daily treatments of rTMS over a period of six weeks and were randomly assigned to either a synchronized or unsynchronized treatment group, where synchronization of rTMS was to their prefrontal EEG quasi-alpha rhythm. RESULTS: When rTMS is applied over the dorsal lateral prefrontal cortex (DLPFC) and synchronized to the patient's prefrontal quasi-alpha rhythm, patients develop strong phase entrainment over a period of weeks, both over the stimulation site as well as in a subset of areas distal to the stimulation site. In addition, at the end of the course of treatment, this group's entrainment phase shifts to be closer to the phase that optimally engages the distal target, namely the anterior cingulate cortex (ACC). These entrainment effects are not observed in the group that is given rTMS without initial EEG synchronization of each TMS train. CONCLUSIONS: The entrainment effects build over the course of days/weeks, suggesting that these effects engage neuroplastic changes which may have clinical consequences in depression or other diseases.
BACKGROUND: Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation modality that can treat depression, obsessive-compulsive disorder, or help smoking cessation. Research suggests that timing the delivery of TMS relative to an endogenous brain state may affect efficacy and short-term brain dynamics. OBJECTIVE: To investigate whether, for a multi-week daily treatment of repetitive TMS (rTMS), there is an effect on brain dynamics that depends on the timing of the TMS relative to individuals' prefrontal EEG quasi-alpha rhythm (between 6 and 13 Hz). METHOD: We developed a novel closed-loop system that delivers personalized EEG-triggered rTMS to patients undergoing treatment for major depressive disorder. In a double blind study, patients received daily treatments of rTMS over a period of six weeks and were randomly assigned to either a synchronized or unsynchronized treatment group, where synchronization of rTMS was to their prefrontal EEG quasi-alpha rhythm. RESULTS: When rTMS is applied over the dorsal lateral prefrontal cortex (DLPFC) and synchronized to the patient's prefrontal quasi-alpha rhythm, patients develop strong phase entrainment over a period of weeks, both over the stimulation site as well as in a subset of areas distal to the stimulation site. In addition, at the end of the course of treatment, this group's entrainment phase shifts to be closer to the phase that optimally engages the distal target, namely the anterior cingulate cortex (ACC). These entrainment effects are not observed in the group that is given rTMS without initial EEG synchronization of each TMS train. CONCLUSIONS: The entrainment effects build over the course of days/weeks, suggesting that these effects engage neuroplastic changes which may have clinical consequences in depression or other diseases.
Authors: Leighton B N Hinkley; Sophia Vinogradov; Adrian G Guggisberg; Melissa Fisher; Anne M Findlay; Srikantan S Nagarajan Journal: Biol Psychiatry Date: 2011-09-08 Impact factor: 13.382
Authors: Julian Caspers; Christian Mathys; Felix Hoffstaedter; Martin Südmeyer; Edna C Cieslik; Christian Rubbert; Christian J Hartmann; Claudia R Eickhoff; Kathrin Reetz; Christian Grefkes; Jochen Michely; Bernd Turowski; Alfons Schnitzler; Simon B Eickhoff Journal: Front Hum Neurosci Date: 2017-05-30 Impact factor: 3.169