Evidence map›Paper›PMID 38483567›Full record

ArticleExperimental brain research2024

fNIRS is capable of distinguishing laterality of lower body contractions.

Rob J MacLennan, Jesus A Hernandez-Sarabia, Shawn M Reese, JoCarol E Shields, Claire M Smith, Katharina Stute, Jordyn Collyar, Alex A Olmos, Tyler L Danielson, Demi L MacLennan and 9 more

Abstract read
PubMed Publisher
In one paragraph

Article in Experimental brain research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
  2. Article
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

19 authors at 13 institutions in 2 countries.

Rob J MacLennanUniversity of Florida, Gainesville, USA.
Jesus A Hernandez-SarabiaColorado State University, Fort Collins, USA.
Shawn M ReeseOklahoma State University, Stillwater, USA.
JoCarol E ShieldsStetson University, DeLand, USA.
Claire M SmithOklahoma State University, Stillwater, USA.
Katharina StuteChemnitz University of Technology, Chemnitz, Germany.
Jordyn CollyarOklahoma State University, Stillwater, USA.
Alex A OlmosOklahoma State University, Stillwater, USA.
Tyler L DanielsonOklahoma State University, Stillwater, USA.
Demi L MacLennanThe Ohio State University, Columbus, USA.
Jason I PaganUniversity of Central Florida, Orlando, USA.
Ryan M GirtsPfeiffer University, Misenheimer, USA.
Kylie K HarmonSyracuse University, Syracuse, USA.
Nicholas CokerSpringfield College, Springfield, USA.
Joshua C CarrTexas Christian University, Fort Worth, USA.
Xin YeUniversity of Hartford, West Hartford, USA.
Jonathan W Perry, Houston, TX, USA.
Matt S StockUniversity of Central Florida, Orlando, USA.
Jason M DeFreitasOklahoma State University, Stillwater, USA. Jason.defreitas@okstate.edu.ORCID http://orcid.org/0000-0002-5108-8079
Oklahoma State University · USUniversity of Central Florida · USChemnitz University of Technology · DEColorado State University · USPfeiffer University · USSpringfield College · USStetson University · USSyracuse University · USTexas Christian University · USThe Ohio State University · USUniversity of Florida · USUniversity of Hartford · USUniversity of Houston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of functional near-infrared spectroscopy (fNIRS) for brain imaging during human movement continues to increase. This technology measures brain activity non-invasively using near-infrared light, is highly portable, and robust to motion artifact. However, the spatial resolution of fNIRS is lower than that of other imaging modalities. It is unclear whether fNIRS has sufficient spatial resolution to differentiate nearby areas of the cortex, such as the leg areas of the motor cortex. Therefore, the purpose of this study was to determine fNIRS' ability to discern laterality of lower body contractions. Activity in the primary motor cortex was recorded in forty participants (mean = 23.4 years, SD = 4.5, female = 23, male = 17) while performing unilateral lower body contractions. Contractions were performed at 30% of maximal force against a handheld dynamometer. These contractions included knee extension, knee flexion, dorsiflexion, and plantar flexion of the left and right legs. fNIRS signals were recorded and stored for offline processing and analysis. Channels of fNIRS data were grouped into regions of interest, with five tolerance conditions ranging from strict to lenient. Four of five tolerance conditions resulted in significant differences in cortical activation between hemispheres. During right leg contractions, the left hemisphere was more active than the right hemisphere. Similarly, during left leg contractions, the right hemisphere was more active than the left hemisphere. These results suggest that fNIRS has sufficient spatial resolution to distinguish laterality of lower body contractions. This makes fNIRS an attractive technology in research and clinical applications in which laterality of brain activity is required during lower body activity.

Indexed as

Functional LateralityMotor CortexSpectroscopy, Near-InfraredAdultBrain MappingFemaleHumansMaleMuscle ContractionYoung AdultfNIRSHemoglobinLateralityMotor controlOxygen

Identifiers

PMID38483567
OpenAlexW4392817883

What OpenQuestion holds

Textmetadata
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.