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Record W4390200559 · doi:10.1002/alz.074927

Tele‐supervised home‐based transcranial alternating current stimulation (tACS) for Alzheimer’s disease

2023· article· en· W4390200559 on OpenAlexaboutno aff
R. Hingston Fox, Tim den Boer, Wanting Yu, Nicole LaGanke, Gabriele Cattaneo, Ruben Perellón‐Alfonso, David Bartrés‐Faz, Bradley Manor, Álvaro Pascual‐Leone, Davide Cappon

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTranscranial alternating current stimulationEpisodic memoryMedicineMontreal Cognitive AssessmentCognitionPsychologyPhysical medicine and rehabilitationStimulationTranscranial magnetic stimulationCognitive impairmentInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Over 55 million people worldwide are currently diagnosed with Alzheimer’s disease (AD) and live with debilitating episodic memory deficits (World Health Organization, 2022). Current pharmacological treatments have limited efficacy. Recently, transcranial alternating current stimulation (tACS) has shown memory improvement in AD by normalizing high‐frequency neuronal activity (Benussi et al., 2022). Our goal was to assess the safety, feasibility, and preliminary effects on episodic memory of a caregiver‐led home‐based tACS approach (HB‐tACS). Method 8 participants diagnosed with AD (Table 1) underwent high‐definition HB‐tACS (40 Hz, 20‐minutes) targeting the left angular gyrus (AG), a key node of the memory network. The Acute Phase comprised 14‐weeks of HB‐tACS with at least five weekly sessions. Three participants underwent resting‐state electroencephalography (EEG) before and after. Subsequently, participants completed a 2–3‐month Hiatus Phase not receiving tACS. In the Taper Phase, participants received 2‐3 sessions per week over 3‐months. Primary outcomes were memory and global cognition, measured with the Memory Index Score (MIS) and Montreal Cognitive Assessment (MoCA), respectively, and EEG theta/gamma ratio. Results reported as mean±SD. Result All participants completed the study with, on average, 97 HB‐tACS sessions; reporting mild side effects during 25% of sessions, moderate during 5%, and severe during 1%. Acute Phase adherence was 98±6.8% and Taper Phase was 125±22.3% (from minimum of 2/week). After the Acute Phase, all participants showed memory improvement, MIS of 7.25±3.77, sustained during Hiatus 7.00±4.90 and Taper 4.63±2.39 Phases (Table 2), and decreased theta/gamma ratio in AG (Figure 1A). Conversely, participants did not show improvement in the MoCA, 1.13±3.80 after the Acute Phase, and there was modest decrease during the Hiatus ‐0.64± 3.28 and Taper ‐2.56±5.03 phases. These results suggest the specificity of the intervention for memory functioning (Figure 1B) and relate improvement to decreased theta/gamma ratio. Conclusion This pilot study shows the feasibility of a novel, remotely supervised, caregiver‐led HB‐tACS intervention for AD. Targeting the left AG, memory was noticeably improved while global cognition was relatively stable, indicating that future interventions might benefit from multifocal neuromodulation targeting multiple cognitive domains. These results are encouraging for the prospect of safe and feasible treatment within patients’ homes.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.117
GPT teacher head0.344
Teacher spread0.227 · 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 designNon-randomized trial
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

Citations1
Published2023
Admission routes1
Has abstractyes

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