Evidence map›Paper›PMID 32754023›Full record

ArticleFrontiers in computational neuroscience2020

Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory.

Hao Wang, Jiahui Wang, Xin Yuan Thow, Sanghoon Lee, Wendy Yen Xian Peh, Kian Ann Ng, Tianyiyi He, Nitish V Thakor, Chengkuo Lee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in computational neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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.

Hao WangInstitute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China.
Jiahui WangDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
Xin Yuan ThowSingapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
Sanghoon LeeDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
Wendy Yen Xian PehSingapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
Kian Ann NgSingapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
Tianyiyi HeDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
Nitish V ThakorSingapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
Chengkuo LeeDepartment of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrical excitation of neural tissue has wide applications, but how electrical stimulation interacts with neural tissue remains to be elucidated. Here, we propose a new theory, named the Circuit-Probability theory, to reveal how this physical interaction happen. The relation between the electrical stimulation input and the neural response can be theoretically calculated. We show that many empirical models, including strength-duration relationship and linear-non-linear-Poisson model, can be theoretically explained, derived, and amended using our theory. Furthermore, this theory can explain the complex non-linear and resonant phenomena and fit

Indexed as

circuit-probability theorycomputational modelingelectric nerve stimulationinductor in neural circuitmathematical model

Identifiers

PMID32754023
PMCPMC7381307

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.