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Technical considerations of a game-theoretical approach for lesion symptom mapping

Overview of attention for article published in BMC Neuroscience, June 2016
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Title
Technical considerations of a game-theoretical approach for lesion symptom mapping
Published in
BMC Neuroscience, June 2016
DOI 10.1186/s12868-016-0275-6
Pubmed ID
Authors

Melissa Zavaglia, Nils D. Forkert, Bastian Cheng, Christian Gerloff, Götz Thomalla, Claus C. Hilgetag

Abstract

Various strategies have been used for inferring brain functions from stroke lesions. We explored a new mathematical approach based on game theory, the so-called multi-perturbation Shapley value analysis (MSA), to assess causal function localizations and interactions from multiple perturbation data. We applied MSA to a dataset composed of lesion patterns of 148 acute stroke patients and their National Institutes of Health Stroke Scale (NIHSS) scores, to systematically investigate the influence of different parameter settings on the outcomes of the approach. Specifically, we investigated aspects of MSA methodology including the choice of the predictor algorithm (typology and kernel functions), training dataset (original versus binary), as well as the influence of lesion thresholds. We assessed the suitability of MSA for processing real clinical lesion data and established the central parameters for this analysis. We derived general recommendations for the analysis of clinical datasets by MSA and showed that, for the studied dataset, the best approach was to use a linear-kernel support vector machine predictor, trained with a binary training dataset, where the binarization was implemented through a median threshold of lesion size for each region. We demonstrated that the results obtained with different MSA variants lead to almost identical results as the basic MSA. MSA is a feasible approach for the multivariate lesion analysis of clinical stroke data. Informed choices need to be made to set parameters that may affect the analysis outcome.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Unknown 42 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 23%
Student > Ph. D. Student 8 19%
Student > Master 5 12%
Student > Doctoral Student 2 5%
Lecturer 1 2%
Other 5 12%
Unknown 12 28%
Readers by discipline Count As %
Medicine and Dentistry 14 33%
Neuroscience 6 14%
Psychology 4 9%
Agricultural and Biological Sciences 2 5%
Linguistics 1 2%
Other 3 7%
Unknown 13 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 July 2016.
All research outputs
#15,379,002
of 22,879,161 outputs
Outputs from BMC Neuroscience
#708
of 1,247 outputs
Outputs of similar age
#223,005
of 352,119 outputs
Outputs of similar age from BMC Neuroscience
#16
of 36 outputs
Altmetric has tracked 22,879,161 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,247 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 352,119 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.