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statistical parametric mapping matlab toolbox  (MathWorks Inc)


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    MathWorks Inc statistical parametric mapping matlab toolbox
    Statistical Parametric Mapping Matlab Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/statistical parametric mapping matlab toolbox/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    statistical parametric mapping matlab toolbox - by Bioz Stars, 2026-03
    90/100 stars

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    The 40 warning districts on land (in green and numbered) and 12 neighbouring waterbodies (in blue with letters). The names of the warning districts (WD) and waterbodies (WB) are given in the Supplementary Information, Table . The red dots show the locations of the two validation events. The maps were generated using the Mapping Toolbox in Matlab version <t>2018b</t> ( https://www.mathworks.com/products/mapping.html ).
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    The 40 warning districts on land (in green and numbered) and 12 neighbouring waterbodies (in blue with letters). The names of the warning districts (WD) and waterbodies (WB) are given in the Supplementary Information, Table . The red dots show the locations of the two validation events. The maps were generated using the Mapping Toolbox in Matlab version <t>2018b</t> ( https://www.mathworks.com/products/mapping.html ).
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    Fig. 2. Resting-state functional connections across olfactory regions in the dog brain. Twenty-six significant connections across all 14 ROIs among all subjects, calculated by <t>CONN.</t> Calculated connections were Fisher- transformed Pearson correlation coefficients. The maximum value (8.67) is the highest correlation coefficient among found connections. The 3D brain image with ROIs and connections was created using Blender (Version 4.1, Blender Foundation, <t>2023)</t> <t>(https://www.blender.org)</t> based on a publicly available template MRI image of a dog32 (https://figshare.com/s/628cbf7d4210271ffe70).
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    Image Search Results


    The 40 warning districts on land (in green and numbered) and 12 neighbouring waterbodies (in blue with letters). The names of the warning districts (WD) and waterbodies (WB) are given in the Supplementary Information, Table . The red dots show the locations of the two validation events. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Journal: Scientific Reports

    Article Title: Weather warning archives reveal spatio-temporal hot spots of compound natural hazards

    doi: 10.1038/s41598-025-96842-6

    Figure Lengend Snippet: The 40 warning districts on land (in green and numbered) and 12 neighbouring waterbodies (in blue with letters). The names of the warning districts (WD) and waterbodies (WB) are given in the Supplementary Information, Table . The red dots show the locations of the two validation events. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Article Snippet: The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Techniques: Biomarker Discovery, Generated

    Average number of days per year and per month during 2011–2020 with warnings issued for HR ( a , b ), HQ ( c , d ) and HW ( e , f ). Note the different scales of the colour bars. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Journal: Scientific Reports

    Article Title: Weather warning archives reveal spatio-temporal hot spots of compound natural hazards

    doi: 10.1038/s41598-025-96842-6

    Figure Lengend Snippet: Average number of days per year and per month during 2011–2020 with warnings issued for HR ( a , b ), HQ ( c , d ) and HW ( e , f ). Note the different scales of the colour bars. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Article Snippet: The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Techniques: Generated

    Average number of days per year and per month during 2011–2020 with warnings issued for the combinations of HR and HQ ( a , b ), HQ and HW ( c , d ), and HR and HW ( e , f ). Note the different scales of the colour bars. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Journal: Scientific Reports

    Article Title: Weather warning archives reveal spatio-temporal hot spots of compound natural hazards

    doi: 10.1038/s41598-025-96842-6

    Figure Lengend Snippet: Average number of days per year and per month during 2011–2020 with warnings issued for the combinations of HR and HQ ( a , b ), HQ and HW ( c , d ), and HR and HW ( e , f ). Note the different scales of the colour bars. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Article Snippet: The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Techniques: Generated

    An example of a daily map of issued warnings (16 February, 2020) with corresponding values of S tc (i, j) in the table. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Journal: Scientific Reports

    Article Title: Weather warning archives reveal spatio-temporal hot spots of compound natural hazards

    doi: 10.1038/s41598-025-96842-6

    Figure Lengend Snippet: An example of a daily map of issued warnings (16 February, 2020) with corresponding values of S tc (i, j) in the table. The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Article Snippet: The maps were generated using the Mapping Toolbox in Matlab version 2018b ( https://www.mathworks.com/products/mapping.html ).

    Techniques: Generated

    Fig. 2. Resting-state functional connections across olfactory regions in the dog brain. Twenty-six significant connections across all 14 ROIs among all subjects, calculated by CONN. Calculated connections were Fisher- transformed Pearson correlation coefficients. The maximum value (8.67) is the highest correlation coefficient among found connections. The 3D brain image with ROIs and connections was created using Blender (Version 4.1, Blender Foundation, 2023) (https://www.blender.org) based on a publicly available template MRI image of a dog32 (https://figshare.com/s/628cbf7d4210271ffe70).

    Journal: Scientific reports

    Article Title: Dogs' olfactory resting-state functional connectivity is modulated by age and brain shape.

    doi: 10.1038/s41598-025-95123-6

    Figure Lengend Snippet: Fig. 2. Resting-state functional connections across olfactory regions in the dog brain. Twenty-six significant connections across all 14 ROIs among all subjects, calculated by CONN. Calculated connections were Fisher- transformed Pearson correlation coefficients. The maximum value (8.67) is the highest correlation coefficient among found connections. The 3D brain image with ROIs and connections was created using Blender (Version 4.1, Blender Foundation, 2023) (https://www.blender.org) based on a publicly available template MRI image of a dog32 (https://figshare.com/s/628cbf7d4210271ffe70).

    Article Snippet: For these processes, MATLAB (version R2023b, MathWorks, Natick, MA, USA) (for steps 6–7), Statistical Parametric Mapping 12 (SPM12) software with MATLAB (Wellcome Centre for Human Neuroimaging, UCL, London, UK) (for steps 1–5), and the CONN functional connectivity toolbox with MATLAB (version 22.a, www.nitrc.org/projects/ conn) (for steps 8–9) were applied.

    Techniques: Functional Assay, Transformation Assay