Evidence map›Paper›PMID 26955514›Full record

ArticleNeuroImage. Clinical2016

Emerging hubs in phantom perception connectomics.

Anusha Mohan, Dirk De Ridder, Sven Vanneste

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 13% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. 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

3 authors at 2 institutions in 2 countries.

Anusha MohanLab for Clinical & Integrative Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, USA.
Dirk De RidderDepartment of Surgical Sciences, Section of Neurosurgery, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
Sven VannesteLab for Clinical & Integrative Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, USA. Electronic address: sven.vanneste@utdallas.edu.
The University of Texas at Dallas · USUniversity of Otago · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain networks are small-world networks typically characterized by the presence of hubs, i.e. nodes that have significantly greater number of links in comparison to other nodes in the network. These hubs act as short cuts in the network and promote long-distance connectivity. Long-distance connections increase the efficiency of information transfer but also increase the cost of the network. Brain disorders are associated with an altered brain connectome which reflects either as a complete change in the network topology, as in, the replacement of hubs or as an alteration in the connectivity between the hubs while retaining network structure. The current study compares the network topology of binary and weighted networks in tinnitus patients and healthy controls by studying the hubs of the two networks in different oscillatory bands. The EEG of 311 tinnitus patients and 256 control subjects are recorded, pre-processed and source-localized using sLORETA. The hubs of the different binary and weighted networks are identified using different measures of network centrality. The results suggest that the tinnitus and control networks are distinct in all the frequency bands but substantially overlap in the gamma frequency band. The differences in network topology in the tinnitus and control groups in the delta, theta and the higher beta bands are driven by a change in hubs as well as network connectivity; in the alpha band by changes in hubs alone and in the gamma band by changes in network connectivity. Thus the brain seems to employ different frequency band-dependent adaptive mechanisms trying to compensate for auditory deafferentation.

Indexed as

Brain MappingConnectomeAgedBrainElectroencephalographyFemaleHumansMaleMiddle AgedNeural PathwaysPhantom LimbTinnitusFunctional connectivityNetwork topologysLORETATinnitus

Identifiers

PMID26955514
PMCPMC4761655
OpenAlexW2252805869

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.