Evidence map›Paper›PMID 32289695›Full record

ArticleBrain stimulation

Modeling transcranial electrical stimulation in the aging brain.

Aprinda Indahlastari, Alejandro Albizu, Andrew O'Shea, Megan A Forbes, Nicole R Nissim, Jessica N Kraft, Nicole D Evangelista, Hanna K Hausman, Adam J Woods, Alzheimer’s Disease Neuroimaging Initiative

Open access · goldAbstract read
In one paragraph

Article in Brain stimulation. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

66 citing papers in PubMed, 1 synthesis or guideline pooled it, 111 citations in OpenAlex.

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  15. 2 mA is NOT 2 mA: Electric field variability in high-definition tDCS and its implications for precision neuromodulation in aging.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2026
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6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Aprinda IndahlastariDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA. Electronic address: aprinda.indahlas@phhp.ufl.edu.
Alejandro AlbizuDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Andrew O'SheaDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Megan A ForbesDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Nicole R NissimDepartment of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Jessica N KraftDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Nicole D EvangelistaDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Hanna K HausmanDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Adam J WoodsDepartment of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Alzheimer’s Disease Neuroimaging Initiative
University of Florida · USAllen Institute for Brain Science · USUniversity of Pennsylvania · US

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MICHAEL W WEINER · 2016 to 2026
$226.7M
Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
TRD4 - Ultrahigh Field Engineering and SafetyP41EB027061 · NIBIB · UNIVERSITY OF MINNESOTA · PI Mehmet Akcakaya · 2019 to 2026
$11.7M
Augmenting Cognitive Training in Older Adults - The ACT GrantR01AG054077 · NIA · UNIVERSITY OF FLORIDA · PI COHEN, RONALD A, MARSISKE, MICHAEL · 2016 to 2020
$6.9M
Research Training in Non-Pharmacological Interventions for Cognition in Aging, MCI, and Alzheimer's DiseaseT32AG020499 · NIA · UNIVERSITY OF FLORIDA · PI MARSISKE, MICHAEL, SMITH, GLENN E. · 2003 to 2024
$3.7M
Advanced 3T for Structural and Functional Imaging at University of FloridaS10OD021726 · OD · UNIVERSITY OF FLORIDA · PI LONG, JOANNA R · 2017 to 2017
$2.0M
Neuromodulation of Cognition in Older AdultsK01AG050707 · NIA · UNIVERSITY OF FLORIDA · PI WOODS, ADAM J. · 2016 to 2020
$613k
NIA NIH HHS K01 AG050707NIA NIH HHS R01 AG054077NIA NIH HHS T32 AG020499NIA NIH HHS U01 AG024904NIA NIH HHS U19 AG024904NIBIB NIH HHS P41 EB027061NIH HHS S10 OD021726NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

backgroundVarying treatment outcomes in transcranial electrical stimulation (tES) recipients may depend on the amount of current reaching the brain. Brain atrophy associated with normal aging may affect tES current delivery to the brain. Computational models have been employed to compute predicted tES current inside the brain. This study is the largest study that uses computational models to investigate tES field distribution in healthy older adults.

methodsIndividualized head models from 587 healthy older adults (mean = 73.9years, 51-95 years) were constructed to create field maps. Two electrode montages (F3-F4, M1-SO) with 2 mA input current were modeled using ROAST with modified codes. A customized template of healthy older adults, the UFAB-587, was created from the same dataset and used to warp individual brains into the same space. Warped models were analyzed to determine the relationship between computed field measures, brain atrophy and age. MAIN

resultsComputed field measures were inversely correlated with brain atrophy (R

conclusionsComputed field measures showed decreasing amount of tES current reaching the brain with increasing atrophy. Therefore, adjusting current dose by modifying tES stimulation parameters in older adults based on degree of atrophy may be necessary to achieve desired stimulation benefits. Results from this study may inform future tES application in healthy older adults.

Indexed as

Computer SimulationAgedAged, 80 and overAgingBrainFinite Element AnalysisHumansImaging, Three-DimensionalMagnetic Resonance ImagingMaleMiddle AgedTranscranial Direct Current StimulationAgingBrain atrophyFinite element modeltDCStES

Identifiers

PMID32289695
PMCPMC7196025
OpenAlexW3004493719

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.