Evidence map›Paper›PMID 33564031›Full record

ArticleScientific reports2021

Elucidating the complex organization of neural micro-domains in the locust Schistocerca gregaria using dMRI.

Syed Salman Shahid, Christian M Kerskens, Malcolm Burrows, Alice G Witney

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 55% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 4 institutions in 4 countries.

Syed Salman ShahidDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.ORCID http://orcid.org/0000-0002-0914-6933
Christian M KerskensTrinity College Institute of Neuroscience, Trinity Centre for Biomedical Engineering, School of Medicine, Trinity College Dublin, Dublin 2, Ireland.ORCID http://orcid.org/0000-0003-0823-4648
Malcolm BurrowsDepartment of Zoology, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0003-1386-5065
Alice G WitneyDepartment of Physiology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity Centre for Biomedical Engineering, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland. awitney@tcd.ie.ORCID http://orcid.org/0000-0002-3726-8479
Indiana University School of MedicineTrinity College · CATrinity College Dublin · IEUniversity of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To understand brain function it is necessary to characterize both the underlying structural connectivity between neurons and the physiological integrity of these connections. Previous research exploring insect brain connectivity has typically used electron microscopy techniques, but this methodology cannot be applied to living animals and so cannot be used to understand dynamic physiological processes. The relatively large brain of the desert locust, Schistercera gregaria (Forksȧl) is ideal for exploring a novel methodology; micro diffusion magnetic resonance imaging (micro-dMRI) for the characterization of neuronal connectivity in an insect brain. The diffusion-weighted imaging (DWI) data were acquired on a preclinical system using a customised multi-shell diffusion MRI scheme optimized to image the locust brain. Endogenous imaging contrasts from the averaged DWIs and Diffusion Kurtosis Imaging (DKI) scheme were applied to classify various anatomical features and diffusion patterns in neuropils, respectively. The application of micro-dMRI modelling to the locust brain provides a novel means of identifying anatomical regions and inferring connectivity of large tracts in an insect brain. Furthermore, quantitative imaging indices derived from the kurtosis model that include fractional anisotropy (FA), mean diffusivity (MD) and kurtosis anisotropy (KA) can be extracted. These metrics could, in future, be used to quantify longitudinal structural changes in the nervous system of the locust brain that occur due to environmental stressors or ageing.

Indexed as

Diffusion Tensor ImagingGrasshoppersNeuronsAnimalsFemale

Identifiers

PMID33564031
PMCPMC7873062
OpenAlexW3128914311

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.