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Record W4407934390 · doi:10.1016/j.brs.2024.12.405

Investigating the impact of transcranial direct current stimulation (tDCS) on prevention of cognitive decline

2025· article· en· W4407934390 on OpenAlexaff
Mina Mirjalili, Heather Brooks, Alina Lee, Clement Ma, Marom Bikson, Sanjeev Kumar, Daniel M. Blumberger, Aristotle N. Voineskos, Alastair J. Flint, Tarek K. Rajji

Bibliographic record

VenueBrain stimulation · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTranscranial direct-current stimulationPhysical medicine and rehabilitationCognitionMedicineStimulationCurrent (fluid)Brain stimulationNeurosciencePsychologyPhysics

Abstract

fetched live from OpenAlex

factors like sensory co-stimulation, a control group (N 25) received identical stimulation on the forehead.Results: Our findings revealed that working memory performance improved in a phase lag-dependent manner in participants receiving parietooccipital stimulation.Across participants, the modulation of frontoparietal alpha oscillations correlated in both amplitude and phase with the modulation of working memory performance.Notably, these effects were absent in the control group receiving frontal stimulation.Conclusions: These results highlight the potential of real-time phasetuned CLAM-tACS to modulate brain oscillations and brain function, opening up new avenues for investigating brain-behavior interactions and exploring novel therapeutic interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.387
Teacher spread0.323 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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