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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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Chenot Q, Hamery C, Lepron E, Besson P, De Boissezon X, Perrey S, Scannella S. Performance after training in a complex cognitive task is enhanced by high-definition transcranial random noise stimulation. Sci Rep 2022; 12:4618. [PMID: 35301388 PMCID: PMC8931133 DOI: 10.1038/s41598-022-08545-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/28/2022] [Indexed: 11/10/2022] Open
Abstract
Interest for neuromodulation, and transcranial random noise stimulation (tRNS) in particular, is growing. It concerns patients rehabilitation, but also healthy people who want or need to improve their cognitive and learning abilities. However, there is no consensus yet regarding the efficacy of tRNS on learning and performing a complex task. In particular, the most effective electrode montage is yet to be determined. Here, we examined the effect of two different tRNS montages on learning rate, short- and long-term performance in a video game (Space Fortress) that engages multiple cognitive abilities. Sixty-one participants were randomly assigned to one of three groups (sham vs. simple-definition tRNS vs. high-definition tRNS) in a double-blind protocol. Their performance on the Space Fortress task was monitored during a 15-day experiment with baseline (day 1), stimulation (day 2 to 4), short- (day 5) and long-term (day 15) evaluations. Our results show that the high-definition tRNS group improved more on the long term than simple-definition tRNS group, tended to learn faster and had better performance retention compared to both simple-definition tRNS and sham groups. This study is the first to report that high-definition tRNS is more effective than conventional simple-definition tRNS to enhance performance in a complex task.
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Affiliation(s)
| | | | | | - Pierre Besson
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - Xavier De Boissezon
- Toulouse Neuroimaging Center (ToNIC), Université de Toulouse, INSERM, Toulouse, France.,Department of Physical Medicine and Rehabilitation, University Hospital of Toulouse, Toulouse, France
| | - Stéphane Perrey
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
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van Bueren NER, Reed TL, Nguyen V, Sheffield JG, van der Ven SHG, Osborne MA, Kroesbergen EH, Cohen Kadosh R. Personalized brain stimulation for effective neurointervention across participants. PLoS Comput Biol 2021; 17:e1008886. [PMID: 34499639 PMCID: PMC8454957 DOI: 10.1371/journal.pcbi.1008886] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 09/21/2021] [Accepted: 08/10/2021] [Indexed: 11/24/2022] Open
Abstract
Accumulating evidence from human-based research has highlighted that the prevalent one-size-fits-all approach for neural and behavioral interventions is inefficient. This approach can benefit one individual, but be ineffective or even detrimental for another. Studying the efficacy of the large range of different parameters for different individuals is costly, time-consuming and requires a large sample size that makes such research impractical and hinders effective interventions. Here an active machine learning technique is presented across participants-personalized Bayesian optimization (pBO)-that searches available parameter combinations to optimize an intervention as a function of an individual's ability. This novel technique was utilized to identify transcranial alternating current stimulation (tACS) frequency and current strength combinations most likely to improve arithmetic performance, based on a subject's baseline arithmetic abilities. The pBO was performed across all subjects tested, building a model of subject performance, capable of recommending parameters for future subjects based on their baseline arithmetic ability. pBO successfully searches, learns, and recommends parameters for an effective neurointervention as supported by behavioral, simulation, and neural data. The application of pBO in human-based research opens up new avenues for personalized and more effective interventions, as well as discoveries of protocols for treatment and translation to other clinical and non-clinical domains.
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Affiliation(s)
- Nienke E. R. van Bueren
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Thomas L. Reed
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Vu Nguyen
- Department of Materials, University of Oxford, Oxford, United Kingdom
- Amazon, Adelaide, Australia
| | - James G. Sheffield
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | | | - Michael A. Osborne
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Evelyn H. Kroesbergen
- Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Roi Cohen Kadosh
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
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Brambilla M, Dinkelbach L, Bigler A, Williams J, Zokaei N, Cohen Kadosh R, Brem AK. The Effect of Transcranial Random Noise Stimulation on Cognitive Training Outcome in Healthy Aging. Front Neurol 2021; 12:625359. [PMID: 33767658 PMCID: PMC7985554 DOI: 10.3389/fneur.2021.625359] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 02/09/2021] [Indexed: 12/20/2022] Open
Abstract
Background and Objective: Aging is associated with a decline in attentional and executive abilities, which are linked to physiological, structural, and functional brain changes. A variety of novel non-invasive brain stimulation methods have been probed in terms of their neuroenhancement efficacy in the last decade; one that holds significant promise is transcranial random noise stimulation (tRNS) that delivers an alternate current at random amplitude and frequency. The aim of this study was to investigate whether repeated sessions of tRNS applied as an add-on to cognitive training (CT) may induce long-term near and far transfer cognitive improvements. Methods: In this sham-controlled, randomized, double-blinded study forty-two older adults (age range 60-86 years) were randomly assigned to one of three intervention groups that received 20 min of 0.705 mA tRNS (N = 14), 1 mA tRNS (N = 14), or sham tRNS (N = 19) combined with 30 min of CT of executive functions (cognitive flexibility, inhibitory control, working memory). tRNS was applied bilaterally over the dorsolateral prefrontal cortices for five sessions. The primary outcome (non-verbal logical reasoning) and other cognitive functions (attention, memory, executive functions) were assessed before and after the intervention and at a 1-month follow-up. Results: Non-verbal logical reasoning, inhibitory control and reaction time improved significantly over time, but stimulation did not differentially affect this improvement. These changes occurred during CT, while no further improvement was observed during follow-up. Performance change in logical reasoning was significantly correlated with age in the group receiving 1 mA tRNS, indicating that older participants profited more from tRNS than younger participants. Performance change in non-verbal working memory was significantly correlated with age in the group receiving sham tRNS, indicating that in contrast to active tRNS, older participants in the sham group declined more than younger participants. Interpretation: CT induced cognitive improvements in all treatment groups, but tRNS did not modulate most of these cognitive improvements. However, the effect of tRNS depended on age in some cognitive functions. We discuss possible explanations leading to this result that can help to improve the design of future neuroenhancement studies in older populations.
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Affiliation(s)
- Michela Brambilla
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Biomedical and Clinical Sciences Department, Center for Research and Treatment on Cognitive Dysfunctions, “Luigi Sacco” Hospital, University of Milan, Milan, Italy
| | - Lars Dinkelbach
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Department of Neurology, Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Duesseldorf, Germany
| | - Annelien Bigler
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Joseph Williams
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Nahid Zokaei
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Roi Cohen Kadosh
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Anna-Katharine Brem
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- Department of Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation and Division for Cognitive Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States
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