Evidence map›Paper›PMID 26266096›Full record

ArticleNeuroImage. Clinical2015

Individual classification of ADHD children by right prefrontal hemodynamic responses during a go/no-go task as assessed by fNIRS.

Yukifumi Monden, Ippeita Dan, Masako Nagashima, Haruka Dan, Minako Uga, Takahiro Ikeda, Daisuke Tsuzuki, Yasushi Kyutoku, Yuji Gunji, Daisuke Hirano and 4 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 2 pooled it
5.3field-weighted citation impact, top 4% 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

62 citing papers in PubMed, 2 syntheses or guidelines pooled it, 113 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Review

2 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

14 authors at 3 institutions in 1 country.

Yukifumi MondenDepartment of Pediatrics, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan.
Ippeita DanFunctional Brain Science Laboratory, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan ; Applied Cognitive Neuroscience Laboratory, Chuo University, 1-13-27 Kasuga, Bunkyo, Tokyo 112-8551, Japan.
Masako NagashimaDepartment of Pediatrics, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan.
Haruka DanFunctional Brain Science Laboratory, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan ; Applied Cognitive Neuroscience Laboratory, Chuo University, 1-13-27 Kasuga, Bunkyo, Tokyo 112-8551, Japan.
Minako UgaFunctional Brain Science Laboratory, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan ; Applied Cognitive Neuroscience Laboratory, Chuo University, 1-13-27 Kasuga, Bunkyo, Tokyo 112-8551, Japan.
Takahiro IkedaDepartment of Pediatrics, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan.
Daisuke TsuzukiApplied Cognitive Neuroscience Laboratory, Chuo University, 1-13-27 Kasuga, Bunkyo, Tokyo 112-8551, Japan.
Yasushi KyutokuApplied Cognitive Neuroscience Laboratory, Chuo University, 1-13-27 Kasuga, Bunkyo, Tokyo 112-8551, Japan.
Yuji GunjiDepartment of Pediatrics, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan ; Department of Pediatrics, International University of Health and Welfare, 537-3 Iguchi, Nasushiobara, Tochigi 329-2763, Japan.
Daisuke HiranoInternational University of Health and Welfare, Otawara, Tochigi, Japan.
Takamichi TaniguchiInternational University of Health and Welfare, Otawara, Tochigi, Japan.
Hideo ShimoizumiRehabilitation Center, International University of Health and Welfare, 2600-1 Kitakanemaru, Otawara, Tochigi 324-8501, Japan.
Eiju WatanabeDepartment of Neurosurgery, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan.
Takanori YamagataDepartment of Pediatrics, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498, Japan.
Jichi Medical University · JPInternational University of Health and Welfare · JPChuo University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While a growing body of neurocognitive research has explored the neural substrates associated with attention deficit hyperactive disorder (ADHD), an objective biomarker for diagnosis has not been established. The advent of functional near-infrared spectroscopy (fNIRS), which is a noninvasive and unrestrictive method of functional neuroimaging, raised the possibility of introducing functional neuroimaging diagnosis in young ADHD children. Previously, our fNIRS-based measurements successfully visualized the hypoactivation pattern in the right prefrontal cortex during a go/no-go task in ADHD children compared with typically developing control children at a group level. The current study aimed to explore a method of individual differentiation between ADHD and typically developing control children using multichannel fNIRS, emphasizing how spatial distribution and amplitude of hemodynamic response are associated with inhibition-related right prefrontal dysfunction. Thirty ADHD and thirty typically developing control children underwent a go/no-go task, and their cortical hemodynamics were assessed using fNIRS. We explored specific regions of interest (ROIs) and cut-off amplitudes for cortical activation to distinguish ADHD children from control children. The ROI located on the border of inferior and middle frontal gyri yielded the most accurate discrimination. Furthermore, we adapted well-formed formulae for the constituent channels of the optimized ROI, leading to improved classification accuracy with an area under the curve value of 85% and with 90% sensitivity. Thus, the right prefrontal hypoactivation assessed by fNIRS would serve as a potentially effective biomarker for classifying ADHD children at the individual level.

Indexed as

Functional LateralityInhibition, PsychologicalAdolescentAttention Deficit Disorder with HyperactivityBiomarkersBrain MappingChildFemaleHumansMalePrefrontal CortexROC CurveSpectroscopy, Near-InfraredBiomarkersDevelopmental syndromesDiscrimination analysisEndophenotypeOptical topographyResponse inhibition

Identifiers

PMID26266096
PMCPMC4528046
OpenAlexW812004106

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.