Global connectivity and local excitability changes underlie antidepressant effects of repetitive transcranial magnetic stimulation
Repetitive transcranial magnetic stimulation (rTMS) is a commonly- used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinic...
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| Veröffentlicht in: | Neuropsychopharmacology (New York, N.Y.) Jg. 45; H. 6; S. 1018 - 1025 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Nature Publishing Group
01.05.2020
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| ISSN: | 0893-133X, 1740-634X, 1740-634X |
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| Abstract | Repetitive transcranial magnetic stimulation (rTMS) is a commonly- used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinical outcome. Such signals would allow for treatment stratification and optimization. Here, we performed a randomized, sham-controlled clinical trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS. Patients (N = 36) were randomized to receive either active or sham rTMS to the left dorsolateral prefrontal cortex (dlPFC) for 20 consecutive weekdays. To capture the rTMS-driven changes in connectivity and causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment. Baseline causal connectivity differences between depressed patients and healthy controls were also evaluated with concurrent TMS/fMRI. We found that active, but not sham rTMS elicited (1) an increase in dlPFC global connectivity, (2) induction of negative dlPFC-amygdala connectivity, and (3) local and distributed changes in TMS/EEG potentials. Global connectivity changes predicted clinical outcome, while both global connectivity and TMS/EEG changes tracked clinical outcome. In patients but not healthy participants, we observed a perturbed inhibitory effect of the dlPFC on the amygdala. Taken together, rTMS induced lasting connectivity and excitability changes from the site of stimulation, such that after active treatment, the dlPFC appeared better able to engage in top-down control of the amygdala. These measures of network functioning both predicted and tracked clinical outcome, potentially opening the door to treatment optimization. |
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| AbstractList | Repetitive transcranial magnetic stimulation (rTMS) is a commonly- used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinical outcome. Such signals would allow for treatment stratification and optimization. Here, we performed a randomized, sham-controlled clinical trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS. Patients (N = 36) were randomized to receive either active or sham rTMS to the left dorsolateral prefrontal cortex (dlPFC) for 20 consecutive weekdays. To capture the rTMS-driven changes in connectivity and causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment. Baseline causal connectivity differences between depressed patients and healthy controls were also evaluated with concurrent TMS/fMRI. We found that active, but not sham rTMS elicited (1) an increase in dlPFC global connectivity, (2) induction of negative dlPFC-amygdala connectivity, and (3) local and distributed changes in TMS/EEG potentials. Global connectivity changes predicted clinical outcome, while both global connectivity and TMS/EEG changes tracked clinical outcome. In patients but not healthy participants, we observed a perturbed inhibitory effect of the dlPFC on the amygdala. Taken together, rTMS induced lasting connectivity and excitability changes from the site of stimulation, such that after active treatment, the dlPFC appeared better able to engage in top-down control of the amygdala. These measures of network functioning both predicted and tracked clinical outcome, potentially opening the door to treatment optimization.Repetitive transcranial magnetic stimulation (rTMS) is a commonly- used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinical outcome. Such signals would allow for treatment stratification and optimization. Here, we performed a randomized, sham-controlled clinical trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS. Patients (N = 36) were randomized to receive either active or sham rTMS to the left dorsolateral prefrontal cortex (dlPFC) for 20 consecutive weekdays. To capture the rTMS-driven changes in connectivity and causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment. Baseline causal connectivity differences between depressed patients and healthy controls were also evaluated with concurrent TMS/fMRI. We found that active, but not sham rTMS elicited (1) an increase in dlPFC global connectivity, (2) induction of negative dlPFC-amygdala connectivity, and (3) local and distributed changes in TMS/EEG potentials. Global connectivity changes predicted clinical outcome, while both global connectivity and TMS/EEG changes tracked clinical outcome. In patients but not healthy participants, we observed a perturbed inhibitory effect of the dlPFC on the amygdala. Taken together, rTMS induced lasting connectivity and excitability changes from the site of stimulation, such that after active treatment, the dlPFC appeared better able to engage in top-down control of the amygdala. These measures of network functioning both predicted and tracked clinical outcome, potentially opening the door to treatment optimization. Repetitive transcranial magnetic stimulation (rTMS) is a commonly- used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinical outcome. Such signals would allow for treatment stratification and optimization. Here, we performed a randomized, sham-controlled clinical trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS. Patients (N = 36) were randomized to receive either active or sham rTMS to the left dorsolateral prefrontal cortex (dlPFC) for 20 consecutive weekdays. To capture the rTMS-driven changes in connectivity and causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment. Baseline causal connectivity differences between depressed patients and healthy controls were also evaluated with concurrent TMS/fMRI. We found that active, but not sham rTMS elicited (1) an increase in dlPFC global connectivity, (2) induction of negative dlPFC-amygdala connectivity, and (3) local and distributed changes in TMS/EEG potentials. Global connectivity changes predicted clinical outcome, while both global connectivity and TMS/EEG changes tracked clinical outcome. In patients but not healthy participants, we observed a perturbed inhibitory effect of the dlPFC on the amygdala. Taken together, rTMS induced lasting connectivity and excitability changes from the site of stimulation, such that after active treatment, the dlPFC appeared better able to engage in top-down control of the amygdala. These measures of network functioning both predicted and tracked clinical outcome, potentially opening the door to treatment optimization. |
| Author | Jiang, Jing Ichikawa, Naho McTeague, Lisa Yee, Andrew Huemer, Julia Wu, Wei Etkin, Amit Fonzo, Gregory A Keller, Corey J Wong, Melinda Eshel, Neir Wright, Rachael Guo, Yi Maron-Katz, Adi Mills-Finnerty, Colleen Shpigel, Emmanuel Carreon, David |
| Author_xml | – sequence: 1 givenname: Neir surname: Eshel fullname: Eshel, Neir organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 2 givenname: Corey J surname: Keller fullname: Keller, Corey J organization: Alto Neuroscience, Los Altos, CA, USA – sequence: 3 givenname: Wei surname: Wu fullname: Wu, Wei organization: School of Automation Science and Engineering, South China University of Technology, 510640, Guangzhou, Guangdong, China – sequence: 4 givenname: Jing surname: Jiang fullname: Jiang, Jing organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 5 givenname: Colleen surname: Mills-Finnerty fullname: Mills-Finnerty, Colleen organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 6 givenname: Julia surname: Huemer fullname: Huemer, Julia organization: Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria – sequence: 7 givenname: Rachael surname: Wright fullname: Wright, Rachael organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 8 givenname: Gregory A surname: Fonzo fullname: Fonzo, Gregory A organization: Department of Psychiatry, Dell Medical School, University of Texas at Austin, Austin, TX, USA – sequence: 9 givenname: Naho surname: Ichikawa fullname: Ichikawa, Naho organization: Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan – sequence: 10 givenname: David orcidid: 0000-0002-3260-4111 surname: Carreon fullname: Carreon, David organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 11 givenname: Melinda surname: Wong fullname: Wong, Melinda organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 12 givenname: Andrew surname: Yee fullname: Yee, Andrew organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 13 givenname: Emmanuel surname: Shpigel fullname: Shpigel, Emmanuel organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 14 givenname: Yi surname: Guo fullname: Guo, Yi organization: 2nd Clinical Medical College of Jinan University, Shenzhen, China – sequence: 15 givenname: Lisa surname: McTeague fullname: McTeague, Lisa organization: Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA – sequence: 16 givenname: Adi surname: Maron-Katz fullname: Maron-Katz, Adi organization: Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA – sequence: 17 givenname: Amit orcidid: 0000-0001-8259-3521 surname: Etkin fullname: Etkin, Amit email: amitetkin@stanford.edu, amitetkin@stanford.edu, amitetkin@stanford.edu organization: Alto Neuroscience, Los Altos, CA, USA. amitetkin@stanford.edu |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32053828$$D View this record in MEDLINE/PubMed |
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| Title | Global connectivity and local excitability changes underlie antidepressant effects of repetitive transcranial magnetic stimulation |
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