Evidence map›Paper›PMID 26759784›Full record

ArticleNeuroImage. Clinical2016

Cortical thinning in the anterior cingulate cortex predicts multiple sclerosis patients' fluency performance in a lateralised manner.

Olivia Geisseler, Tobias Pflugshaupt, Ladina Bezzola, Katja Reuter, David Weller, Bernhard Schuknecht, Peter Brugger, Michael Linnebank

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 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

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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

8 authors at 2 institutions in 2 countries.

Olivia GeisselerDepartment of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091 Zurich, Switzerland; Department of Psychology, University of Zurich, Binzmühlestrasse 14/1, 8050 Zürich, Switzerland.
Tobias PflugshauptDepartment of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091 Zurich, Switzerland; Neurology and Neurorehabilitation Center, Luzerner Kantonsspital, 6016 Luzern, Switzerland.
Ladina BezzolaURPP Dynamics of Healthy Aging, University of Zurich, Andreasstrasse 15/Box 2, 8050 Zurich, Switzerland.
Katja ReuterDepartment of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091 Zurich, Switzerland.
David WellerDepartment of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091 Zurich, Switzerland.
Bernhard SchuknechtMedizinisch Radiologisches Institut, Bahnhofplatz 3, 8001 Zurich, Switzerland.
Peter BruggerDepartment of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091 Zurich, Switzerland.
Michael LinnebankDepartment of Neurology, University Hospital Zurich, Frauenklinikstrasse 26, 8091 Zurich, Switzerland; Department of Neurology, Helios-Klinik Hagen-Ambrock, Ambrocker Weg 60, 58091 Hagen, Germany.
University Hospital of Zurich · CHUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cognitive impairment is as an important feature of Multiple Sclerosis (MS), and might be even more relevant to patients than mobility restrictions. Compared to the multitude of studies investigating memory deficits or basic cognitive slowing, executive dysfunction is a rarely studied cognitive domain in MS, and its neural correlates remain largely unexplored. Even rarer are topological studies on specific cognitive functions in MS. Here we used several structural MRI parameters - including cortical thinning and T2 lesion load - to investigate neural correlates of executive dysfunction, both on a global and a regional level by means of voxel- and vertex-wise analyses. Forty-eight patients with relapsing-remitting MS and 48 healthy controls participated in the study. Five executive functions were assessed, i.e. verbal and figural fluency, working memory, interference control and set shifting. Patients scored lower than controls in verbal and figural fluency only, and displayed widespread cortical thinning. On a global level, cortical thickness independently predicted verbal fluency performance, when controlling for lesion volume and central brain atrophy estimates. On a regional level, cortical thinning in the anterior cingulate region correlated with deficits in verbal and figural fluency and did so in a lateralised manner: Left-sided thinning was related to reduced verbal - but not figural - fluency, whereas the opposite pattern was observed for right-sided thinning. We conclude that executive dysfunction in MS patients can specifically affect verbal and figural fluency. The observed lateralised clinico-anatomical correlation has previously been described in brain-damaged patients with large focal lesions only, for example after stroke. Based on focal grey matter atrophy, we here show for the first time comparable lateralised findings in a white matter disease with widespread pathology.

Indexed as

Executive FunctionFunctional LateralityAdultAtrophyCerebral CortexFemaleGyrus CinguliHumansMagnetic Resonance ImagingMaleMemory, Short-TermMultiple Sclerosis, Relapsing-RemittingNeuropsychological TestsSpeech DisordersAtrophyCortical thinningEDSS, Expanded Disability Status ScaleExecutive functionFDR, false discovery rateFLAIR, fluid attenuated inversion recoveryFluencyMPRAGE, magnetization prepared rapid gradient-echo imagingMS, multiple sclerosisMultiple sclerosisTVW, third ventricle widthVLSM, voxel-lesion symptom mapping

Identifiers

PMID26759784
PMCPMC4683425
OpenAlexW2409133111

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.