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Caravati E, Barbeni F, Chiarion G, Raggi M, Mesin L. Closed-Loop Transcranial Electrical Neurostimulation for Sustained Attention Enhancement: A Pilot Study towards Personalized Intervention Strategies. Bioengineering (Basel) 2024; 11:467. [PMID: 38790334 PMCID: PMC11118513 DOI: 10.3390/bioengineering11050467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Revised: 05/03/2024] [Accepted: 05/06/2024] [Indexed: 05/26/2024] Open
Abstract
Sustained attention is pivotal for tasks like studying and working for which focus and low distractions are necessary for peak productivity. This study explores the effectiveness of adaptive transcranial direct current stimulation (tDCS) in either the frontal or parietal region to enhance sustained attention. The research involved ten healthy university students performing the Continuous Performance Task-AX (AX-CPT) while receiving either frontal or parietal tDCS. The study comprised three phases. First, we acquired the electroencephalography (EEG) signal to identify the most suitable metrics related to attention states. Among different spectral and complexity metrics computed on 3 s epochs of EEG, the Fuzzy Entropy and Multiscale Sample Entropy Index of frontal channels were selected. Secondly, we assessed how tDCS at a fixed 1.0 mA current affects attentional performance. Finally, a real-time experiment involving continuous metric monitoring allowed personalized dynamic optimization of the current amplitude and stimulation site (frontal or parietal). The findings reveal statistically significant improvements in mean accuracy (94.04 vs. 90.82%) and reaction times (262.93 vs. 302.03 ms) with the adaptive tDCS compared to a non-stimulation condition. Average reaction times were statistically shorter during adaptive stimulation compared to a fixed current amplitude condition (262.93 vs. 283.56 ms), while mean accuracy stayed similar (94.04 vs. 93.36%, improvement not statistically significant). Despite the limited number of subjects, this work points out the promising potential of adaptive tDCS as a tailored treatment for enhancing sustained attention.
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Affiliation(s)
| | | | | | | | - Luca Mesin
- Mathematical Biology and Physiology, Department Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; (E.C.); (F.B.); (G.C.); (M.R.)
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Alipour M, Seok S, Mednick SC, Malerba P. A classification-based generative approach to selective targeting of global slow oscillations during sleep. Front Hum Neurosci 2024; 18:1342975. [PMID: 38415278 PMCID: PMC10896842 DOI: 10.3389/fnhum.2024.1342975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 01/30/2024] [Indexed: 02/29/2024] Open
Abstract
Background Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability. Objective/Hypothesis This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile. Methods We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance. Results Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization. Conclusion Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.
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Affiliation(s)
- Mahmoud Alipour
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
- The Ohio State University School of Medicine, Columbus, OH, United States
| | - SangCheol Seok
- Center for Gene Therapy, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Sara C. Mednick
- Department of Cognitive Sciences, University of California, Irvine, Irvine CA, United States
| | - Paola Malerba
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
- The Ohio State University School of Medicine, Columbus, OH, United States
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3
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Soleimani G, Nitsche MA, Bergmann TO, Towhidkhah F, Violante IR, Lorenz R, Kuplicki R, Tsuchiyagaito A, Mulyana B, Mayeli A, Ghobadi-Azbari P, Mosayebi-Samani M, Zilverstand A, Paulus MP, Bikson M, Ekhtiari H. Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments. Transl Psychiatry 2023; 13:279. [PMID: 37582922 PMCID: PMC10427701 DOI: 10.1038/s41398-023-02565-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.
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Affiliation(s)
- Ghazaleh Soleimani
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Michael A Nitsche
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
- Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, and University Clinic of Child and Adolescent Psychiatry and Psychotherapy, Bielefeld, Germany
| | - Til Ole Bergmann
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Farzad Towhidkhah
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guilford, UK
| | - Romy Lorenz
- Department of Psychology, Stanford University, Stanford, CA, USA
- MRC CBU, University of Cambridge, Cambridge, UK
- Department of Neurophysics, MPI, Leipzig, Germany
| | | | | | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
- School of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - Ahmad Mayeli
- University of Pittsburgh Medical Center, Pittsburg, PA, USA
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Mosayebi-Samani
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Hamed Ekhtiari
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
- Laureate Institute for Brain Research, Tulsa, OK, USA.
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4
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Closed-Loop tACS Delivered during Slow-Wave Sleep Reduces Retroactive Interference on a Paired-Associates Learning Task. Brain Sci 2023; 13:brainsci13030468. [PMID: 36979277 PMCID: PMC10046133 DOI: 10.3390/brainsci13030468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/03/2023] [Accepted: 03/06/2023] [Indexed: 03/12/2023] Open
Abstract
Previous studies have found a benefit of closed-loop transcranial alternating current stimulation (CL-tACS) matched to ongoing slow-wave oscillations (SWO) during sleep on memory consolidation for words in a paired associates task (PAT). Here, we examined the effects of CL-tACS in a retroactive interference PAT (ri-PAT) paradigm, where additional stimuli were presented to increase interference and reduce memory performance. Thirty-one participants were tested on a PAT before sleep, and CL-tACS was applied over the right and left DLPFC (F3 and F4) vs. mastoids for five cycles after detection of the onset of each discrete event of SWO during sleep. Participants were awoken the following morning, learned a new PAT list, and then were tested on the original list. There was a significant effect of stimulation condition (p = 0.04297; Cohen’s d = 0.768), where verum stimulation resulted in reduced retroactive interference compared with sham and a significant interaction of encoding strength and stimulation condition (p = 0.03591). Planned simple effects testing within levels of encoding revealed a significant effect of stimulation only for low-encoders (p = 0.0066; Cohen’s d = 1.075) but not high-encoders. We demonstrate here for the first time that CL-tACS during sleep can enhance the protective benefits on retroactive interference in participants who have lower encoding aptitude.
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Antal A, Luber B, Brem AK, Bikson M, Brunoni AR, Cohen Kadosh R, Dubljević V, Fecteau S, Ferreri F, Flöel A, Hallett M, Hamilton RH, Herrmann CS, Lavidor M, Loo C, Lustenberger C, Machado S, Miniussi C, Moliadze V, Nitsche MA, Rossi S, Rossini PM, Santarnecchi E, Seeck M, Thut G, Turi Z, Ugawa Y, Venkatasubramanian G, Wenderoth N, Wexler A, Ziemann U, Paulus W. Non-invasive brain stimulation and neuroenhancement. Clin Neurophysiol Pract 2022; 7:146-165. [PMID: 35734582 PMCID: PMC9207555 DOI: 10.1016/j.cnp.2022.05.002] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/19/2022] [Accepted: 05/18/2022] [Indexed: 12/15/2022] Open
Abstract
The available data frame with a wide parameter space of tES does not allow an overarching protocol recommendation. Established engineering risk-management procedures with regard to manufacturing should be followed. Consensus among experts is that tES for neuroenhancement is safe as long as tested protocols are followed.
Attempts to enhance human memory and learning ability have a long tradition in science. This topic has recently gained substantial attention because of the increasing percentage of older individuals worldwide and the predicted rise of age-associated cognitive decline in brain functions. Transcranial brain stimulation methods, such as transcranial magnetic (TMS) and transcranial electric (tES) stimulation, have been extensively used in an effort to improve cognitive functions in humans. Here we summarize the available data on low-intensity tES for this purpose, in comparison to repetitive TMS and some pharmacological agents, such as caffeine and nicotine. There is no single area in the brain stimulation field in which only positive outcomes have been reported. For self-directed tES devices, how to restrict variability with regard to efficacy is an essential aspect of device design and function. As with any technique, reproducible outcomes depend on the equipment and how well this is matched to the experience and skill of the operator. For self-administered non-invasive brain stimulation, this requires device designs that rigorously incorporate human operator factors. The wide parameter space of non-invasive brain stimulation, including dose (e.g., duration, intensity (current density), number of repetitions), inclusion/exclusion (e.g., subject’s age), and homeostatic effects, administration of tasks before and during stimulation, and, most importantly, placebo or nocebo effects, have to be taken into account. The outcomes of stimulation are expected to depend on these parameters and should be strictly controlled. The consensus among experts is that low-intensity tES is safe as long as tested and accepted protocols (including, for example, dose, inclusion/exclusion) are followed and devices are used which follow established engineering risk-management procedures. Devices and protocols that allow stimulation outside these parameters cannot claim to be “safe” where they are applying stimulation beyond that examined in published studies that also investigated potential side effects. Brain stimulation devices marketed for consumer use are distinct from medical devices because they do not make medical claims and are therefore not necessarily subject to the same level of regulation as medical devices (i.e., by government agencies tasked with regulating medical devices). Manufacturers must follow ethical and best practices in marketing tES stimulators, including not misleading users by referencing effects from human trials using devices and protocols not similar to theirs.
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Affiliation(s)
- Andrea Antal
- Department of Neurology, University Medical Center, Göttingen, Germany
- Corresponding author at: Department of Neurology, University Medical Center, Göttingen, Robert Koch Str. 40, 37075 Göttingen, Germany.
| | - Bruce Luber
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Anna-Katharine Brem
- University Hospital of Old Age Psychiatry, University of Bern, Bern, Switzerland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Marom Bikson
- Biomedical Engineering at the City College of New York (CCNY) of the City University of New York (CUNY), NY, USA
| | - Andre R. Brunoni
- Departamento de Clínica Médica e de Psiquiatria, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Service of Interdisciplinary Neuromodulation (SIN), Laboratory of Neurosciences (LIM-27), Institute of Psychiatry, Hospital das Clínicas da Faculdade de Medicina da USP, São Paulo, Brazil
| | - Roi Cohen Kadosh
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Veljko Dubljević
- Science, Technology and Society Program, College of Humanities and Social Sciences, North Carolina State University, Raleigh, NC, USA
| | - Shirley Fecteau
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, CERVO Brain Research Centre, Centre intégré universitaire en santé et services sociaux de la Capitale-Nationale, Quebec City, Quebec, Canada
| | - Florinda Ferreri
- Unit of Neurology, Unit of Clinical Neurophysiology, Study Center of Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
- Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Agnes Flöel
- Department of Neurology, Universitätsmedizin Greifswald, 17475 Greifswald, Germany
- German Centre for Neurodegenerative Diseases (DZNE) Standort Greifswald, 17475 Greifswald, Germany
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Roy H. Hamilton
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christoph S. Herrmann
- Experimental Psychology Lab, Department of Psychology, Carl von Ossietzky Universität, Oldenburg, Germany
| | - Michal Lavidor
- Department of Psychology and the Gonda Brain Research Center, Bar Ilan University, Israel
| | - Collen Loo
- School of Psychiatry and Black Dog Institute, University of New South Wales; The George Institute; Sydney, Australia
| | - Caroline Lustenberger
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
| | - Sergio Machado
- Department of Sports Methods and Techniques, Federal University of Santa Maria, Santa Maria, Brazil
- Laboratory of Physical Activity Neuroscience, Neurodiversity Institute, Queimados-RJ, Brazil
| | - Carlo Miniussi
- Center for Mind/Brain Sciences – CIMeC and Centre for Medical Sciences - CISMed, University of Trento, Rovereto, Italy
| | - Vera Moliadze
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | - Michael A Nitsche
- Department Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors at TU, Dortmund, Germany
- Dept. Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Simone Rossi
- Siena Brain Investigation and Neuromodulation Lab (Si-BIN Lab), Unit of Neurology and Clinical Neurophysiology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Paolo M. Rossini
- Department of Neuroscience and Neurorehabilitation, Brain Connectivity Lab, IRCCS-San Raffaele-Pisana, Rome, Italy
| | - Emiliano Santarnecchi
- Precision Neuroscience and Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Margitta Seeck
- Department of Clinical Neurosciences, Hôpitaux Universitaires de Genève, Switzerland
| | - Gregor Thut
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, EEG & Epolepsy Unit, University of Glasgow, United Kingdom
| | - Zsolt Turi
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Yoshikazu Ugawa
- Department of Human Neurophysiology, Fukushima Medical University, Fukushima, Japan
| | | | - Nicole Wenderoth
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore
| | - Anna Wexler
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ulf Ziemann
- Department of Neurology and Stroke, University of Tübingen, Germany
- Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Walter Paulus
- Department of of Neurology, Ludwig Maximilians University Munich, Germany
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Farkhondeh Tale Navi F, Heysieattalab S, Ramanathan DS, Raoufy MR, Nazari MA. Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs. Neuroscience 2021; 483:104-126. [PMID: 34902494 DOI: 10.1016/j.neuroscience.2021.12.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/30/2021] [Accepted: 12/06/2021] [Indexed: 11/27/2022]
Abstract
Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. Next, we provide an overview of the application, rationale, and therapeutic aspects of CLNM for clinical purposes. Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.
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Affiliation(s)
- Farhad Farkhondeh Tale Navi
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | - Soomaayeh Heysieattalab
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | | | - Mohammad Reza Raoufy
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Mohammad Ali Nazari
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran; Department of Neuroscience, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran.
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Brunyé TT, Yau K, Okano K, Elliott G, Olenich S, Giles GE, Navarro E, Elkin-Frankston S, Young AL, Miller EL. Toward Predicting Human Performance Outcomes From Wearable Technologies: A Computational Modeling Approach. Front Physiol 2021; 12:738973. [PMID: 34566701 PMCID: PMC8458818 DOI: 10.3389/fphys.2021.738973] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 08/18/2021] [Indexed: 12/16/2022] Open
Abstract
Wearable technologies for measuring digital and chemical physiology are pervading the consumer market and hold potential to reliably classify states of relevance to human performance including stress, sleep deprivation, and physical exertion. The ability to efficiently and accurately classify physiological states based on wearable devices is improving. However, the inherent variability of human behavior within and across individuals makes it challenging to predict how identified states influence human performance outcomes of relevance to military operations and other high-stakes domains. We describe a computational modeling approach to address this challenge, seeking to translate user states obtained from a variety of sources including wearable devices into relevant and actionable insights across the cognitive and physical domains. Three status predictors were considered: stress level, sleep status, and extent of physical exertion; these independent variables were used to predict three human performance outcomes: reaction time, executive function, and perceptuo-motor control. The approach provides a complete, conditional probabilistic model of the performance variables given the status predictors. Construction of the model leverages diverse raw data sources to estimate marginal probability density functions for each of six independent and dependent variables of interest using parametric modeling and maximum likelihood estimation. The joint distributions among variables were optimized using an adaptive LASSO approach based on the strength and directionality of conditional relationships (effect sizes) derived from meta-analyses of extant research. The model optimization process converged on solutions that maintain the integrity of the original marginal distributions and the directionality and robustness of conditional relationships. The modeling framework described provides a flexible and extensible solution for human performance prediction, affording efficient expansion with additional independent and dependent variables of interest, ingestion of new raw data, and extension to two- and three-way interactions among independent variables. Continuing work includes model expansion to multiple independent and dependent variables, real-time model stimulation by wearable devices, individualized and small-group prediction, and laboratory and field validation.
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Affiliation(s)
- Tad T Brunyé
- Cognitive Science Team, US Army DEVCOM Soldier Center, Natick, MA, United States.,Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Kenny Yau
- Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Kana Okano
- Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Grace Elliott
- Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Sara Olenich
- Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Grace E Giles
- Cognitive Science Team, US Army DEVCOM Soldier Center, Natick, MA, United States.,Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Ester Navarro
- Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Seth Elkin-Frankston
- Cognitive Science Team, US Army DEVCOM Soldier Center, Natick, MA, United States.,Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States
| | - Alexander L Young
- Department of Statistics, Harvard University, Cambridge, MA, United States
| | - Eric L Miller
- Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States.,Department of Electrical and Computer Engineering, Tufts University, Medford, MA, United States
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8
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Martens G, Ibáñez-Soria D, Barra A, Soria-Frisch A, Piarulli A, Gosseries O, Salvador R, Rojas A, Nitsche MA, Kroupi E, Laureys S, Ruffini G, Thibaut A. A novel closed-loop EEG-tDCS approach to promote responsiveness of patients in minimally conscious state: A study protocol. Behav Brain Res 2021; 409:113311. [PMID: 33878429 DOI: 10.1016/j.bbr.2021.113311] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 03/10/2021] [Accepted: 04/15/2021] [Indexed: 01/28/2023]
Abstract
Transcranial direct current stimulation (tDCS) applied over the prefrontal cortex has been shown to improve behavioral responsiveness in patients with disorders of consciousness following severe brain injury, especially those in minimally conscious state (MCS). However, one potential barrier of clinical response to tDCS is the timing of stimulation with regard to the fluctuations of vigilance that characterize this population. Indeed, a previous study showed that the vigilance of MCS patients has periodic average cycles of 70 min (range 57-80 min), potentially preventing them to be in an optimal neural state to benefit from tDCS when applied randomly. To tackle this issue, we propose a new protocol to optimize the application of tDCS by selectively stimulating at high and low vigilance states. Electroencephalography (EEG) real-time spectral entropy will be used as a marker of vigilance and to trigger tDCS, in a closed-loop fashion. We will conduct a randomized controlled crossover clinical trial on 16 patients in prolonged MCS who will undergo three EEG-tDCS sessions 5 days apart (1. tDCS applied at high vigilance; 2. tDCS applied at low vigilance; 3. tDCS applied at a random moment). Behavioral effects will be assessed using the Coma Recovery Scale-Revised at baseline and right after the stimulations. EEG will be recorded throughout the session and for 30 min after the end of the stimulation. This unique and novel approach will provide patients' tailored treatment options, currently lacking in the field of disorders of consciousness.
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Affiliation(s)
- Géraldine Martens
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du cerveau², University Hospital of Liège, Liège, Belgium.
| | | | - Alice Barra
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du cerveau², University Hospital of Liège, Liège, Belgium
| | | | - Andrea Piarulli
- Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Italy
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du cerveau², University Hospital of Liège, Liège, Belgium
| | | | | | - Michael A Nitsche
- Dept. Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany; Dept. Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | | | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du cerveau², University Hospital of Liège, Liège, Belgium
| | | | - Aurore Thibaut
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium; Centre du cerveau², University Hospital of Liège, Liège, Belgium
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9
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Frohlich F, Townsend L. Closed-Loop Transcranial Alternating Current Stimulation: Towards Personalized Non-invasive Brain Stimulation for the Treatment of Psychiatric Illnesses. Curr Behav Neurosci Rep 2021. [DOI: 10.1007/s40473-021-00227-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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10
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The effects of non-invasive brain stimulation on sleep disturbances among different neurological and neuropsychiatric conditions: A systematic review. Sleep Med Rev 2021; 55:101381. [DOI: 10.1016/j.smrv.2020.101381] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 04/17/2020] [Accepted: 06/09/2020] [Indexed: 12/11/2022]
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11
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Dondé C, Brunelin J, Micoulaud-Franchi JA, Maruani J, Lejoyeux M, Polosan M, Geoffroy PA. The Effects of Transcranial Electrical Stimulation of the Brain on Sleep: A Systematic Review. Front Psychiatry 2021; 12:646569. [PMID: 34163380 PMCID: PMC8215269 DOI: 10.3389/fpsyt.2021.646569] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 04/19/2021] [Indexed: 01/23/2023] Open
Abstract
Transcranial Electrical Stimulation (tES) is a promising non-invasive brain modulation tool. Over the past years, there have been several attempts to modulate sleep with tES-based approaches in both the healthy and pathological brains. However, data about the impact on measurable aspects of sleep remain scattered between studies, which prevent us from drawing firm conclusions. We conducted a systematic review of studies that explored the impact of tES on neurophysiological sleep oscillations, sleep patterns measured objectively with polysomnography, and subjective psychometric assessments of sleep in both healthy and clinical samples. We searched four main electronic databases to identify studies until February 2020. Forty studies were selected including 511 healthy participants and 452 patients. tES can modify endogenous brain oscillations during sleep. Results concerning changes in sleep patterns are conflicting, whereas subjective assessments show clear improvements after tES. Possible stimulation-induced mechanisms within specific cortico-subcortical sleep structures and networks are discussed. Although these findings cannot be directly transferred to the clinical practice and sleep-enhancing devices development for healthy populations, they might help to pave the way for future researches in these areas. PROSPERO registration number 178910.
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Affiliation(s)
- Clément Dondé
- University Grenoble Alpes, Grenoble, France.,U1216 INSERM, Grenoble Institut of Neuroscience, La Tronche, France.,Psychiatry Department, CHU Grenoble Alpes, Grenoble, France
| | - Jerome Brunelin
- INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center, PSY-R2 Team, Lyon, France.,Lyon University, Lyon, France.,Centre Hospitalier le Vinatier, Batiment 416, Bron, France
| | - Jean-Arthur Micoulaud-Franchi
- University Sleep Clinic, Services of Functional Exploration of the Nervous System, University Hospital of Bordeaux, Bordeaux, France.,USR CNRS 3413 SANPSY, University Hospital Pellegrin, University of Bordeaux, Bordeaux, France
| | - Julia Maruani
- Département de Psychiatrie et de Médecine Addictologique, Hôpital Fernand Widal, Assistance Publique des Hôpitaux de Paris (APHP), Paris, France.,Université de Paris, Paris, France.,INSERM U1144, Optimisation Thérapeutique en Neuropsychopharmacologie, Paris, France
| | - Michel Lejoyeux
- Paris Diderot University-Paris VII, 5 Rue Thomas Mann, Paris, France.,University Hospital Bichat-Claude Bernard, 46 rue Henri Huchard, Paris, France
| | - Mircea Polosan
- University Grenoble Alpes, Grenoble, France.,U1216 INSERM, Grenoble Institut of Neuroscience, La Tronche, France.,Psychiatry Department, CHU Grenoble Alpes, Grenoble, France
| | - Pierre A Geoffroy
- Paris Diderot University-Paris VII, 5 Rue Thomas Mann, Paris, France.,University Hospital Bichat-Claude Bernard, 46 rue Henri Huchard, Paris, France.,Université de Paris, NeuroDiderot, Inserm, Paris, France
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12
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Romanella SM, Roe D, Tatti E, Cappon D, Paciorek R, Testani E, Rossi A, Rossi S, Santarnecchi E. The Sleep Side of Aging and Alzheimer's Disease. Sleep Med 2021; 77:209-225. [PMID: 32912799 PMCID: PMC8364256 DOI: 10.1016/j.sleep.2020.05.029] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/13/2020] [Accepted: 05/19/2020] [Indexed: 01/23/2023]
Abstract
As we age, sleep patterns undergo significant modifications in micro and macrostructure, worsening cognition and quality of life. These are associated with remarkable brain changes, like deterioration in synaptic plasticity, gray and white matter, and significant modifications in hormone levels. Sleep alterations are also a core component of mild cognitive impairment (MCI) and Alzheimer's Disease (AD). AD night time is characterized by a gradual decrease in slow-wave activity and a substantial reduction of REM sleep. Sleep abnormalities can accelerate AD pathophysiology, promoting the accumulation of amyloid-β (Aβ) and phosphorylated tau. Thus, interventions that target sleep disturbances in elderly people and MCI patients have been suggested as a possible strategy to prevent or decelerate conversion to dementia. Although cognitive-behavioral therapy and pharmacological medications are still first-line treatments, despite being scarcely effective, new interventions have been proposed, such as sensory stimulation and Noninvasive Brain Stimulation (NiBS). The present review outlines the current state of the art of the relationship between sleep modifications in healthy aging and the neurobiological mechanisms underlying age-related changes. Furthermore, we provide a critical analysis showing how sleep abnormalities influence the prognosis of AD pathology by intensifying Aβ and tau protein accumulation. We discuss potential therapeutic strategies to target sleep disruptions and conclude that there is an urgent need for testing new therapeutic sleep interventions.
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Affiliation(s)
- S M Romanella
- Siena Brain Investigation and Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy
| | - D Roe
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - E Tatti
- Department of Molecular, Cellular & Biomedical Sciences, CUNY, School of Medicine, New York, NY, USA
| | - D Cappon
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - R Paciorek
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - E Testani
- Sleep Medicine Center, Department of Neurology, Policlinico Santa Maria Le Scotte, Siena, Italy
| | - A Rossi
- Siena Brain Investigation and Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy; Human Physiology Section, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - S Rossi
- Siena Brain Investigation and Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy; Human Physiology Section, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - E Santarnecchi
- Siena Brain Investigation and Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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13
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Romanella SM, Sprugnoli G, Ruffini G, Seyedmadani K, Rossi S, Santarnecchi E. Noninvasive Brain Stimulation & Space Exploration: Opportunities and Challenges. Neurosci Biobehav Rev 2020; 119:294-319. [PMID: 32937115 PMCID: PMC8361862 DOI: 10.1016/j.neubiorev.2020.09.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 05/22/2020] [Accepted: 09/03/2020] [Indexed: 01/11/2023]
Abstract
As NASA prepares for longer space missions aiming for the Moon and Mars, astronauts' health and performance are becoming a central concern due to the threats associated with galactic cosmic radiation, unnatural gravity fields, and life in extreme environments. In space, the human brain undergoes functional and structural changes related to fluid shift and changes in intracranial pressure. Behavioral abnormalities, such as cognitive deficits, sleep disruption, and visuomotor difficulties, as well as psychological effects, are also an issue. We discuss opportunities and challenges of noninvasive brain stimulation (NiBS) methods - including transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES) - to support space exploration in several ways. NiBS includes safe and portable techniques already applied in a wide range of cognitive and motor domains, as well as therapeutically. NiBS could be used to enhance in-flight performance, supporting astronauts during pre-flight Earth-based training, as well as to identify biomarkers of post-flight brain changes for optimization of rehabilitation/compensatory strategies. We review these NiBS techniques and their effects on brain physiology, psychology, and cognition.
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Affiliation(s)
- S M Romanella
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy
| | - G Sprugnoli
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Radiology Unit, Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - G Ruffini
- Neuroelectrics Corporation, Cambridge, MA, USA
| | - K Seyedmadani
- University Space Research Association NASA Johnson Space Center, Houston, TX, USA; Ann and H.J. Smead Aerospace Engineering Sciences, University of Colorado, Boulder, CO, USA
| | - S Rossi
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy; Human Physiology Section, Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - E Santarnecchi
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy; Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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14
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Romanella SM, Roe D, Paciorek R, Cappon D, Ruffini G, Menardi A, Rossi A, Rossi S, Santarnecchi E. Sleep, Noninvasive Brain Stimulation, and the Aging Brain: Challenges and Opportunities. Ageing Res Rev 2020; 61:101067. [PMID: 32380212 DOI: 10.1016/j.arr.2020.101067] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 02/26/2020] [Accepted: 04/04/2020] [Indexed: 02/06/2023]
Abstract
As we age, sleep patterns undergo severe modifications of their micro and macrostructure, with an overall lighter and more fragmented sleep structure. In general, interventions targeting sleep represent an excellent opportunity not only to maintain life quality in the healthy aging population, but also to enhance cognitive performance and, when pathology arises, to potentially prevent/slow down conversion from e.g. Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD). Sleep abnormalities are, in fact, one of the earliest recognizable biomarkers of dementia, being also partially responsible for a cascade of cortical events that worsen dementia pathophysiology, including impaired clearance systems leading to build-up of extracellular amyloid-β (Aβ) peptide and intracellular hyperphosphorylated tau proteins. In this context, Noninvasive Brain Stimulation (NiBS) techniques, such as transcranial electrical stimulation (tES) and transcranial magnetic stimulation (TMS), may help investigate the neural substrates of sleep, identify sleep-related pathology biomarkers, and ultimately help patients and healthy elderly individuals to restore sleep quality and cognitive performance. However, brain stimulation applications during sleep have so far not been fully investigated in healthy elderly cohorts, nor tested in AD patients or other related dementias. The manuscript discusses the role of sleep in normal and pathological aging, reviewing available evidence of NiBS applications during both wakefulness and sleep in healthy elderly individuals as well as in MCI/AD patients. Rationale and details for potential future brain stimulation studies targeting sleep alterations in the aging brain are discussed, including enhancement of cognitive performance, overall quality of life as well as protein clearance.
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A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions. SENSORS 2020; 20:s20102770. [PMID: 32414060 PMCID: PMC7285770 DOI: 10.3390/s20102770] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/13/2020] [Accepted: 05/10/2020] [Indexed: 01/09/2023]
Abstract
Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms. In many fields, the effectiveness of these closed-loop protocols has proven to be better than that of the simple open-loop paradigms. Recently, sleep studies have attracted much attention as one possible application of closed-loop paradigms. To date, several studies that used closed-loop paradigms have been reported in the sleep-related literature and recommend a closed-loop feedback system to enhance specific brain activity during sleep, which leads to improvements in sleep's effects, such as memory consolidation. However, to the best of our knowledge, no report has reviewed and discussed the detailed technical issues that arise in designing sleep closed-loop paradigms. In this paper, we reviewed the most recent reports on sleep closed-loop paradigms and offered an in-depth discussion of some of their technical issues. We found 148 journal articles strongly related with 'sleep and stimulation' and reviewed 20 articles on closed-loop feedback sleep studies. We focused on human sleep studies conducting any modality of feedback stimulation. Then we introduced the main component of the closed-loop system and summarized several open-source libraries, which are widely used in closed-loop systems, with step-by-step guidelines for closed-loop system implementation for sleep. Further, we proposed future directions for sleep research with closed-loop feedback systems, which provide some insight into closed-loop feedback systems.
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16
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Wang H, Zhang W, Zhao W, Wang K, Wang Z, Wang L, Peng M, Xue Q, Leng H, Ding W, Liu Y, Li N, Dong K, Zhang Q, Huang X, Xie Y, Chu C, Xue S, Huang L, Yao H, Ding J, Zhan S, Min B, Fan C, Zhou A, Sun Z, Yin L, Ma Q, Baskys A, Jorge RE, Song H. The efficacy of transcranial alternating current stimulation for treating post-stroke depression: Study Protocol Clinical Trial (SPIRIT Compliant). Medicine (Baltimore) 2020; 99:e19671. [PMID: 32311940 PMCID: PMC7220515 DOI: 10.1097/md.0000000000019671] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND The treatment of post-stroke depression (PSD) with anti-depressant drugs is partly practical. Transcranial alternating current stimulation (tACS) offers the potential for a novel treatment modality for adult patients with PSD. In this study, we will assess the efficacy and safety of tACS for treating PSD and explore its effect on gamma and beta-oscillations involving in emotional regulation. METHODS The prospective study is an 8-week, double-blind, randomized, placebo-controlled trial. Seventy eligible participants with mild to moderate PSD aged between 18 years and 70 years will be recruited and randomly assigned to either active tACS intervention group or sham group. Daily 40-minute, 77.5-Hz, 15-mA sessions of active or sham tACS targeting the forehead and both mastoid areas on weekdays for 4 consecutive weeks (week 4), and an additional 4-week observational period (week 8) will be followed up. The primary outcome is the proportion of participants having an improvement at week 8 according to the Hamilton Depression Rating Scale 17-Item (HAMD-17) score, including the proportion of participants having a decrease of ≥ 50% in HAMD-17 score or clinical recovery (HAMD-17 score ≤ 7). Secondary outcomes include neurological function, independence level, activities of daily living, disease severity, anxiety, and cognitive function. The exploratory outcomes are gamma and beta-oscillations assessed at baseline, week 4, and week 8. Data will be analyzed by logistical regression analyses and mixed-effects models. DISCUSSION The study will be the first randomized controlled trial to evaluate the efficacy and safety of tACS at a 77.5-Hz frequency and 15-mA current in reducing depressive severity in patients with PSD. The results of the study will present a base for future studies on the tACS in PSD and its possible mechanism. TRIAL REGISTRATION NUMBER NCT03903068, pre-results.
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Affiliation(s)
- Hongxing Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University
- Beijing Key Laboratory of Neuromodulation
- Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University
| | - Wenrui Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Wenfeng Zhao
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Kun Wang
- Department of Neurology, Beijing Puren Hospital
| | - Zu Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Li Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Mao Peng
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Qing Xue
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Haixia Leng
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Weijun Ding
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Yuan Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Ning Li
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Kai Dong
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Qian Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Xiaoqin Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Yunyan Xie
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Changbiao Chu
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Sufang Xue
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Liyuan Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Hui Yao
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Jianping Ding
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Shuqin Zhan
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Baoquan Min
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Chunqiu Fan
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Aihong Zhou
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Zhichao Sun
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Lu Yin
- Medical Research & Biometrics Centre, National Centre for Cardiovascular Diseases Cardiovascular
| | - Qingfeng Ma
- Department of Neurology, Xuanwu Hospital, Capital Medical University
| | - Andrius Baskys
- Andrius Baskys, Graduate College of Biomedical Sciences, Western University of Health Sciences, Pomona, CA
| | - Ricardo E. Jorge
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX
| | - Haiqing Song
- Department of Neurology, Xuanwu Hospital, Capital Medical University
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