Evidence map›Paper›PMID 34780490›Full record

ArticlePloS one2021

Brain structures and activity during a working memory task associated with internet addiction tendency in young adults: A large sample study.

Saeid Sadeghi, Hikaru Takeuchi, Bita Shalani, Yasuyuki Taki, Rui Nouchi, Ryoichi Yokoyama, Yuka Kotozaki, Seishu Nakagawa, Atsushi Sekiguchi, Kunio Iizuka and 10 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

20 authors.

Saeid SadeghiInstitute for Cognitive and Brain Sciences (ICBS), Shahid Beheshti University, Tehran, Iran.ORCID 0000-0002-2922-6412
Hikaru TakeuchiDivision of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Bita ShalaniDepartment of Psychology, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran.
Yasuyuki TakiDivision of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Rui NouchiCreative Interdisciplinary Research Division, Frontier Research Institute for Interdisciplinary Science, Tohoku University, Sendai, Japan.
Ryoichi YokoyamaSchool of Medicine, Kobe University, Kobe, Japan.
Yuka KotozakiDivision of Clinical research, Medical-Industry Translational Research Center, Fukushima Medical University School of Medicine, Fukushima, Japan.
Seishu NakagawaDepartment of Human Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Atsushi SekiguchiDivision of Medical Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Kunio IizukaDepartment of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan.
Sugiko HanawaDepartment of Human Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Tsuyoshi ArakiADVANTAGE Risk Management Co., Ltd., Tokyo, Japan.
Carlos Makoto MiyauchiDepartment of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Kohei SakakiDepartment of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Takayuki NozawaResearch Center for the Earth Inclusive Sensing Empathizing with Silent Voices, Tokyo Institute of Technology, Tokyo, Japan.ORCID 0000-0001-6300-4373
Shigeyuki IkedaDepartment of Ubiquitous Sensing, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Susumu YokotaDivision for Experimental Natural Science, Faculty of Arts and Science, Kyushu University, Fukuoka, Japan.
Daniele MagistroDepartment of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.ORCID 0000-0002-2554-3701
Yuko SassaDivision of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
Ryuta KawashimaDivision of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The structural and functional brain characteristics associated with the excessive use of the internet have attracted substantial research attention in the past decade. In current study, we used voxel-based morphometry (VBM) and multiple regression analysis to assess the relationship between internet addiction tendency (IAT) score and regional gray and white matter volumes (rGMVs and rWMVs) and brain activity during a WM task in a large sample of healthy young adults (n = 1,154, mean age, 20.71 ± 1.78 years). We found a significant positive correlation between IAT score and gray matter volume (GMV) of right supramarginal gyrus (rSMG) and significant negative correlations with white matter volume (WMV) of right temporal lobe (sub-gyral and superior temporal gyrus), right sublobar area (extra-nuclear and lentiform nucleus), right cerebellar anterior lobe, cerebellar tonsil, right frontal lobe (inferior frontal gyrus and sub-gyral areas), and the pons. Also, IAT was significantly and positively correlated with brain activity in the default-mode network (DMN), medial frontal gyrus, medial part of the superior frontal gyrus, and anterior cingulate cortex during a 2-back working memory (WM) task. Moreover, whole-brain analyses of rGMV showed significant effects of interaction between sex and the IAT scores in the area spreading around the left anterior insula and left lentiform. This interaction was moderated by positive correlation in women. These results indicate that IAT is associated with (a) increased GMV in rSMG, which is involved in phonological processing, (b) decreased WMV in areas of frontal, sublobar, and temporal lobes, which are involved in response inhibition, and (c) reduced task-induced deactivation of the DMN, indicative of altered attentional allocation.

Indexed as

BrainInternet Addiction DisorderMagnetic Resonance ImagingMemory, Short-TermAdolescentAdultBehavior, AddictiveBrain MappingFemaleGray MatterHumansMaleWhite MatterYoung Adult

Identifiers

PMID34780490
PMCPMC8592411

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.