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Grosshagauer S, Woletz M, Vasileiadi M, Linhardt D, Nohava L, Schuler AL, Windischberger C, Williams N, Tik M. Chronometric TMS-fMRI of personalized left dorsolateral prefrontal target reveals state-dependency of subgenual anterior cingulate cortex effects. Mol Psychiatry 2024; 29:2678-2688. [PMID: 38532009 PMCID: PMC11420068 DOI: 10.1038/s41380-024-02535-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 03/12/2024] [Accepted: 03/14/2024] [Indexed: 03/28/2024]
Abstract
Transcranial magnetic stimulation (TMS) applied to a left dorsolateral prefrontal cortex (DLPFC) area with a specific connectivity profile to the subgenual anterior cingulate cortex (sgACC) has emerged as a highly effective non-invasive treatment option for depression. However, antidepressant outcomes demonstrate significant variability among therapy plans and individuals. One overlooked contributing factor is the individual brain state at the time of treatment. In this study we used interleaved TMS-fMRI to investigate the influence of brain state on acute TMS effects, both locally and remotely. TMS was performed during rest and during different phases of cognitive task processing. Twenty healthy participants were included in this study. In the first session, imaging data for TMS targeting were acquired, allowing for identification of individualized targets in the left DLPFC based on highest anti-correlation with the sgACC. The second session involved chronometric interleaved TMS-fMRI measurements, with 10 Hz triplets of TMS administered during rest and at distinct timings during an N-back task. Consistent with prior findings, interleaved TMS-fMRI revealed significant BOLD activation changes in the targeted network. The precise timing of TMS relative to the cognitive states during the task demonstrated distinct BOLD response in clinically relevant brain regions, including the sgACC. Employing a standardized timing approach for TMS using a task revealed more consistent modulation of the sgACC at the group level compared to stimulation during rest. In conclusion, our findings strongly suggest that acute local and remote effects of TMS are influenced by brain state during stimulation. This study establishes a basis for considering brain state as a significant factor in designing treatment protocols, possibly improving TMS treatment outcomes.
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Affiliation(s)
- Sarah Grosshagauer
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Michael Woletz
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Maria Vasileiadi
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - David Linhardt
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Lena Nohava
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Anna-Lisa Schuler
- Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christian Windischberger
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Nolan Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Martin Tik
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
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2
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Liufu M, Leveroni ZM, Shridhar S, Zhou N, Yu JY. Optimizing real-time phase detection in diverse rhythmic biological signals for phase-specific neuromodulation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.24.609522. [PMID: 39253473 PMCID: PMC11383035 DOI: 10.1101/2024.08.24.609522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/11/2024]
Abstract
Closed-loop, phase-specific neurostimulation is a powerful method to modulate ongoing brain activity for clinical and research applications. Phase-specific stimulation relies on estimating the phase of an ongoing oscillation in real time and issuing a control command at a target phase. Phase detection algorithms based on Fast Fourier transform (FFT) are widely used due to their computational efficiency and robustness. However, it is unclear how algorithm performance depends on the spectral properties of the input signal and how algorithm parameters can be optimized. We used offline simulation to evaluate the performance of three algorithms (endpoint-corrected Hilbert Transform, Hilbert Transform and phase mapping) on three rhythmic biological signals with distinct spectral properties (rodent hippocampal theta potential, human EEG alpha and human essential tremor). First, we found that algorithm performance was more strongly influenced by signal amplitude and frequency variation compared with signal to noise ratio. Second, our simulations showed that the size of the data window for phase estimation was critical for the performance of FFT-based algorithms, where the optimal data window corresponds to the period of the oscillation. We validated this prediction with real time phase detection of hippocampal theta oscillations in freely behaving rats performing spatial navigation. Our findings define the relationship between signal properties and algorithm performance and provide a convenient method for optimizing FFT-based phase detection algorithms.
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3
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Xia AWL, Jin M, Qin PPI, Kan RLD, Zhang BBB, Giron CG, Lin TTZ, Li ASM, Kranz GS. Instantaneous effects of prefrontal transcranial magnetic stimulation on brain oxygenation: A systematic review. Neuroimage 2024; 293:120618. [PMID: 38636640 DOI: 10.1016/j.neuroimage.2024.120618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 04/20/2024] Open
Abstract
This systematic review investigates how prefrontal transcranial magnetic stimulation (TMS) immediately influences neuronal excitability based on oxygenation changes measured by functional magnetic resonance imaging (fMRI) or functional near-infrared spectroscopy (fNIRS). A thorough understanding of TMS-induced excitability changes may enable clinicians to adjust TMS parameters and optimize treatment plans proactively. Five databases were searched for human studies evaluating brain excitability using concurrent TMS/fMRI or TMS/fNIRS. Thirty-seven studies (13 concurrent TMS/fNIRS studies, 24 concurrent TMS/fMRI studies) were included in a qualitative synthesis. Despite methodological inconsistencies, a distinct pattern of activated nodes in the frontoparietal central executive network, the cingulo-opercular salience network, and the default-mode network emerged. The activated nodes included the prefrontal cortex (particularly dorsolateral prefrontal cortex), insula cortex, striatal regions (especially caudate, putamen), anterior cingulate cortex, and thalamus. High-frequency repetitive TMS most consistently induced expected facilitatory effects in these brain regions. However, varied stimulation parameters (e.g., intensity, coil orientation, target sites) and the inter- and intra-individual variability of brain state contribute to the observed heterogeneity of target excitability and co-activated regions. Given the considerable methodological and individual variability across the limited evidence, conclusions should be drawn with caution.
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Affiliation(s)
- Adam W L Xia
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Minxia Jin
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China; Shanghai YangZhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China
| | - Penny P I Qin
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Rebecca L D Kan
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Bella B B Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Cristian G Giron
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Tim T Z Lin
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Ami S M Li
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Georg S Kranz
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China; Mental Health Research Center (MHRC), The Hong Kong Polytechnic University, Hong Kong, China; Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
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4
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Sack AT, Paneva J, Küthe T, Dijkstra E, Zwienenberg L, Arns M, Schuhmann T. Target Engagement and Brain State Dependence of Transcranial Magnetic Stimulation: Implications for Clinical Practice. Biol Psychiatry 2024; 95:536-544. [PMID: 37739330 DOI: 10.1016/j.biopsych.2023.09.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 08/31/2023] [Accepted: 09/12/2023] [Indexed: 09/24/2023]
Abstract
Transcranial magnetic stimulation (TMS) is capable of noninvasively inducing lasting neuroplastic changes when applied repetitively across multiple treatment sessions. In recent years, repetitive TMS has developed into an established evidence-based treatment for various neuropsychiatric disorders such as depression. Despite significant advancements in our understanding of the mechanisms of action of TMS, there is still much to learn about how these mechanisms relate to the clinical effects observed in patients. If there is one thing about TMS that we know for sure, it is that TMS effects are state dependent. In this review, we describe how the effects of TMS on brain networks depend on various factors, including cognitive brain state, oscillatory brain state, and recent brain state history. These states play a crucial role in determining the effects of TMS at the moment of stimulation and are therefore directly linked to what is referred to as target engagement in TMS therapy. There is no control over target engagement without considering the different brain state dependencies of our TMS intervention. Clinical TMS protocols are largely ignoring this fundamental principle, which may explain the large variability and often still limited efficacy of TMS treatments. We propose that after almost 30 years of research on state dependency of TMS, it is time to change standard clinical practice by taking advantage of this fundamental principle. Rather than ignoring TMS state dependency, we can use it to our clinical advantage to improve the effectiveness of TMS treatments.
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Affiliation(s)
- Alexander T Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Brain + Nerve Center, Maastricht University Medical Center, Maastricht, the Netherlands.
| | - Jasmina Paneva
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Tara Küthe
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Eva Dijkstra
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Heart and Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands; Neurowave, Amsterdam, the Netherlands
| | - Lauren Zwienenberg
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Heart and Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands; Synaeda Psycho Medisch Centrum, Leeuwarden, the Netherlands
| | - Martijn Arns
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Brain + Nerve Center, Maastricht University Medical Center, Maastricht, the Netherlands; Heart and Brain Group, Brainclinics Foundation, Nijmegen, the Netherlands
| | - Teresa Schuhmann
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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Sinisalo H, Rissanen I, Kahilakoski OP, Souza VH, Tommila T, Laine M, Nyrhinen M, Ukharova E, Granö I, Soto AM, Matsuda RH, Rantala R, Guidotti R, Kičić D, Lioumis P, Mutanen T, Pizzella V, Marzetti L, Roine T, Stenroos M, Ziemann U, Romani GL, Ilmoniemi RJ. Modulating brain networks in space and time: Multi-locus transcranial magnetic stimulation. Clin Neurophysiol 2024; 158:218-224. [PMID: 38184469 DOI: 10.1016/j.clinph.2023.12.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/17/2023] [Accepted: 12/15/2023] [Indexed: 01/08/2024]
Affiliation(s)
- Heikki Sinisalo
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.
| | - Ilkka Rissanen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | | | - Victor H Souza
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University, and Helsinki University Hospital, Helsinki, Finland; Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Timo Tommila
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Mikael Laine
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Mikko Nyrhinen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; AMI Centre, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland
| | - Elena Ukharova
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Ida Granö
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Ana M Soto
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Renan H Matsuda
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Robin Rantala
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Roberto Guidotti
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Dubravko Kičić
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University, and Helsinki University Hospital, Helsinki, Finland
| | - Tuomas Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Vittorio Pizzella
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies (ITAB), University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Laura Marzetti
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies (ITAB), University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Timo Roine
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Tübingen, Germany
| | - Gian Luca Romani
- Institute for Advanced Biomedical Technologies (ITAB), University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
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Lefaucheur JP. It is time to personalize rTMS targeting for the treatment of pain. Neurophysiol Clin 2024; 54:102950. [PMID: 38382139 DOI: 10.1016/j.neucli.2024.102950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 01/30/2024] [Indexed: 02/23/2024] Open
Affiliation(s)
- Jean-Pascal Lefaucheur
- Unité de Neurophysiologie Clinique, Hôpital Henri Mondor, AP-HP, Créteil, France; UR ENT (EA4391), Faculté de Santé, Université Paris Est Créteil, Créteil, France.
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George MS, Huffman S, Doose J, Sun X, Dancy M, Faller J, Li X, Yuan H, Goldman RI, Sajda P, Brown TR. EEG synchronized left prefrontal transcranial magnetic stimulation (TMS) for treatment resistant depression is feasible and produces an entrainment dependent clinical response: A randomized controlled double blind clinical trial. Brain Stimul 2023; 16:1753-1763. [PMID: 38043646 PMCID: PMC10872322 DOI: 10.1016/j.brs.2023.11.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 10/19/2023] [Accepted: 11/19/2023] [Indexed: 12/05/2023] Open
Abstract
BACKGROUND Synchronizing a TMS pulse with a person's underlying EEG rhythm can modify the brain's response. It is unclear if synchronizing rTMS trains might boost the antidepressant effect of TMS. In this first-in-human trial, we demonstrated that a single TMS pulse over the prefrontal cortex produces larger effects in the anterior cingulate depending on when it is fired relative to the individual's EEG alpha phase. OBJECTIVE/HYPOTHESES We had three hypotheses. 1) It is feasible to synchronize repetitive TMS (rTMS) delivery to a person's preferred prefrontal alpha phase in each train of every session during a 30-visit TMS depression treatment course. 2) EEG-synchronized rTMS would produce progressive entrainment greater than unsynchronized (UNSYNC) rTMS. And 3) SYNC TMS would have better antidepressant effects than UNSYNC (remission, final Hamilton Depression Rating <10). METHODS We enrolled (n = 34) and treated (n = 28) adults with treatment resistant depression (TRD) and randomized them to receive six weeks (30 treatments) of left prefrontal rTMS at their individual alpha frequency (IAF) (range 6-13 Hz). Prior to starting the clinical trial, all patients had an interleaved fMRI-EEG-TMS (fET) scan to determine which phase of their alpha rhythm would produce the largest BOLD response in their dorsal anterior cingulate. Our clinical EEG-rTMS system then delivered the first TMS pulse in each train time-locked to this patient-specific 'preferred phase' of each patient's left prefrontal alpha oscillation. We randomized patients (1:1) to SYNC or UNSYNC, and all were treated at their IAF. Only the SYNC patients had the first pulse of each train for all sessions synchronized to their individualized preferred alpha phase (75 trains/session ×30 sessions, 2250 synchronizations per patient over six weeks). The UNSYNC group used a random firing with respect to the alpha wave. All other TMS parameters were balanced between the two groups. The system interfaced with a MagStim Horizon air-cooled Fig. 8 TMS coil. All patients were treated at their IAF, coil in the F3 position, 120 % MT, frequency 6-13 Hz, 40 pulses per train, average 15-s inter-train interval, 3000 pulses per session. All patients, raters, and treaters were blinded. RESULTS In the intent to treat (ITT) sample, both groups had significant clinical improvement from baseline with no significant between-group differences, with the USYNC group having mathematically more remitters but fewer responders. (ITT -15 SYNC; 13 UNSYNC, response 5 (33 %), 1 (7 %), remission 2 (13 %), 6 (46 %). The same was true with the completer sample - 12 SYNC; 12 UNSYNC, response 4, 4 (both 30 %), remission 2 (17 %), 3 (25 %)). The clinical EEG phase synchronization system performed well with no failures. The average treatment session was approximately 90 min, with 30 min for placing the EEG cap and the actual TMS treatment for 45 min (which included gathering 10 min of resting EEG). Four subjects (1 SYNC) withdrew before six weeks of treatment. All 24 completer patients were treated for six weeks despite the trial occurring during the COVID pandemic. SYNC patients exhibited increased post-stimulation EEG entrainment over the six weeks. A detailed secondary analysis of entrainment data in the SYNC group showed that responders and non-responders in this group could be cleanly separated based on the total number of sessions with entrainment and the session-to-session precision of the entrained phase. For the SYNC group only, depression improvement was greater when more sessions were entrained at similar phases. CONCLUSIONS Synchronizing prefrontal TMS with a patient's prefrontal alpha frequency in a blinded clinical trial is possible and produces progressive EEG entrainment in synchronized patients only. There was no difference in overall clinical response in this small clinical trial. A secondary analysis showed that the consistency of the entrained phase across sessions was significantly associated with response outcome only in the SYNC group. These effects may not simply be due to how the stimulation is delivered but also whether the patient's brain can reliably entrain to a precise phase. EEG-synchronized clinical delivery of TMS is feasible and requires further study to determine the best method for determining the phase for synchronization.
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Affiliation(s)
- Mark S George
- Brain Stimulation Division, Psychiatry, MUSC, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston SC, USA.
| | - Sarah Huffman
- Brain Stimulation Division, Psychiatry, MUSC, Charleston, SC, USA
| | - Jayce Doose
- Department of Radiology, MUSC, Charleston, SC, USA
| | - Xiaoxiao Sun
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Morgan Dancy
- Brain Stimulation Division, Psychiatry, MUSC, Charleston, SC, USA
| | - Josef Faller
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Xingbao Li
- Brain Stimulation Division, Psychiatry, MUSC, Charleston, SC, USA
| | - Han Yuan
- Bioengineering Dept, University of Oklahoma, Norman, OK, USA
| | | | - Paul Sajda
- Department of Biomedical Engineering, Columbia University, New York, NY, USA; Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA
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Sun X, Doose J, Faller J, McIntosh JR, Saber GT, Huffman S, Pantazatos SP, Yuan H, Goldman RI, Brown TR, George MS, Sajda P. Increased entrainment and decreased excitability predict efficacious treatment of closed-loop phase-locked rTMS for treatment-resistant depression. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.09.23296751. [PMID: 37873424 PMCID: PMC10593047 DOI: 10.1101/2023.10.09.23296751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Transcranial magnetic stimulation (TMS) is an FDA-approved therapy for major depressive disorder (MDD), specifically for patients who have treatment-resistant depression (TRD). However, TMS produces response or remission in about 50% of patients but is ineffective for the other 50%. Limits on efficacy may be due to individual patient variability, but to date, there are no good biomarkers or measures of target engagement. In addition, TMS efficacy is typically not assessed until a six-week treatment ends, precluding the evaluation of intermediate improvements during the treatment duration. Here, we report on results using a closed-loop phase-locked repetitive TMS (rTMS) treatment that synchronizes the delivery of rTMS based on the timing of the pulses relative to a patient's individual electroencephalographic (EEG) prefrontal alpha oscillation informed by functional magnetic resonance imaging (fMRI). We find that, in responders, synchronized delivery of rTMS produces two systematic changes in brain dynamics. The first change is a decrease in global cortical excitability, and the second is an increase in the phase entrainment of cortical dynamics. These two effects predict clinical outcomes in the synchronized treatment group but not in an active-treatment unsynchronized control group. The systematic decrease in excitability and increase in entrainment correlated with treatment efficacy at the endpoint and intermediate weeks during the synchronized treatment. Specifically, we show that weekly tracking of these biomarkers allows for efficacy prediction and potential of dynamic adjustments through a treatment course, improving the overall response rates.
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