Evidence map›Paper›PMID 37287801›Full record

ArticleFrontiers in neuroscience2023

Estimation of brain tissue response by electrical stimulation in a subject-specific model implemented by conductivity tensor imaging.

Nitish Katoch, Youngsung Kim, Bup Kyung Choi, Sang Woo Ha, Tae Hoon Kim, Eun Ju Yoon, Sang Gook Song, Jin Woong Kim, Hyung Joong Kim

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Nitish KatochDepartment of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea.
Youngsung KimOffice of Strategic R&D Planning (MOTIE), Seoul, Republic of Korea.
Bup Kyung ChoiDepartment of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea.
Sang Woo HaDepartment of Neurosurgery, Chosun University Hospital and Chosun University College of Medicine, Gwangju, Republic of Korea.
Tae Hoon KimMedical Convergence Research Center, Wonkwang University Hospital, Iksan, Republic of Korea.
Eun Ju YoonDepartment of Radiology, Chosun University Hospital and Chosun University College of Medicine, Gwangju, Republic of Korea.
Sang Gook SongDepartment of Radiology, Chosun University Hospital and Chosun University College of Medicine, Gwangju, Republic of Korea.
Jin Woong KimDepartment of Radiology, Chosun University Hospital and Chosun University College of Medicine, Gwangju, Republic of Korea.
Hyung Joong KimDepartment of Biomedical Engineering, Kyung Hee University, Seoul, Republic of Korea.
Chosun University Hospital · KRKyung Hee University · KRKorea Institute of Science & Technology Evaluation and Planning · KRWonkwang University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrical stimulation such as transcranial direct current stimulation (tDCS) is widely used to treat neuropsychiatric diseases and neurological disorders. Computational modeling is an important approach to understand the mechanisms underlying tDCS and optimize treatment planning. When applying computational modeling to treatment planning, uncertainties exist due to insufficient conductivity information inside the brain. In this feasibility study, we performed

Indexed as

conductivity tensorcurrent densityelectrical stimulationelectric fieldmagnetic resonance imagingtranscranial direct current stimulation

Identifiers

PMID37287801
PMCPMC10242016
OpenAlexW4378084500

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.