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Record W4281486035 · doi:10.1016/j.cnp.2022.05.002

Non-invasive brain stimulation and neuroenhancement

2022· review· en· W4281486035 on OpenAlexaff
Andrea Antal, Bruce Luber, Anna‐Katharine Brem, Marom Bikson, André R. Brunoni, Roi Cohen Kadosh, Veljko Dubljević, Shirley Fecteau, Florinda Ferreri, Agnes Flöel, Mark Hallett, Roy H. Hamilton, Christoph S. Herrmann, Michal Lavidor, Collen Loo, Caroline Lustenberger, Sérgio Machado, Carlo Miniussi, Vera Moliadze, Michael A. Nitsche, Símone Rossi, Paolo Maria Rossini, Emiliano Santarnecchi, Margitta Seeck, Gregor Thut, Zsolt Turi, Yoshikazu Ugawa, Ganesan Venkatasubramanian, Nicole Wenderoth, Anna Wexler, Ulf Ziemann, Walter Paulus

Bibliographic record

VenueClinical Neurophysiology Practice · 2022
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversité Laval
FundersMedical Research CouncilBayer VitalEuropean Research CouncilThe Wellcome Trust DBT India AllianceFaculdade de Medicina da Universidade de São PauloBundesministerium für Bildung und ForschungNational Health and Medical Research CouncilAllerganUniversidade de São PauloFundação de Amparo à Pesquisa do Estado de São PauloAlexion PharmaceuticalsSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMinistry of Education, Culture, Sports, Science and TechnologyNational Institutes of HealthVolkswagen FoundationNational Science FoundationDepartment of Biotechnology, Ministry of Science and Technology, IndiaNational Institute of Neurological Disorders and StrokeUniversity of CambridgeNational Research Foundation SingaporeCorTecNational Research FoundationUniversity of OxfordJanssen PharmaceuticalsBrainsWayEU Joint Programme – Neurodegenerative Disease ResearchCity University of New YorkDeutsche ForschungsgemeinschaftConselho Nacional de Desenvolvimento Científico e TecnológicoGlaxoSmithKlineEuropean CommissionU.S. Department of DefenseWellcome TrustNational Institute of Mental HealthHorizon 2020 Framework ProgrammeTakeda Pharmaceuticals U.S.A.PfizerAcademy of Medical SciencesBoston Scientific Corporation
KeywordsStimulationTranscranial direct-current stimulationBrain stimulationTranscranial magnetic stimulationNeuroscienceHuman brainCognitionPsychologyEffects of sleep deprivation on cognitive performanceMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.231
GPT teacher head0.468
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations211
Published2022
Admission routes1
Has abstractyes

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