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fixed-point sica  (InfoMax Inc)

 
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    InfoMax Inc fixed-point sica
    a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax <t>sICA</t> and Fixed‐Point sICA (task‐related components) at two different thresholds (P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).
    Fixed Point Sica, supplied by InfoMax 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/product/fixed-point+sica/pmc06871848-216-91-88?v=InfoMax+Inc
    Average 90 stars, based on 1 article reviews
    fixed-point sica - by Bioz Stars, 2026-07
    90/100 stars

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    1) Product Images from "Spatial independent component analysis of functional MRI time‐series: To what extent do results depend on the algorithm used?"

    Article Title: Spatial independent component analysis of functional MRI time‐series: To what extent do results depend on the algorithm used?

    Journal: Human Brain Mapping

    doi: 10.1002/hbm.10034

    a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax sICA and Fixed‐Point sICA (task‐related components) at two different thresholds (P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).
    Figure Legend Snippet: a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax sICA and Fixed‐Point sICA (task‐related components) at two different thresholds (P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).

    Techniques Used: Activation Assay, Comparison, Labeling

    a: Results from fitting a gaussian distribution to the histogram of a consistent task‐related (CTR) sICA component. Note that here the IC is positive signed and active voxels remain outside the area under the fitted gaussian density function. b: Variances of the fitted gaussian distribution (residual noise) for the CTR components generated by the two algorithms across all the case subjects (motor activation data). c: Comparison of two fitted gaussian distributions.
    Figure Legend Snippet: a: Results from fitting a gaussian distribution to the histogram of a consistent task‐related (CTR) sICA component. Note that here the IC is positive signed and active voxels remain outside the area under the fitted gaussian density function. b: Variances of the fitted gaussian distribution (residual noise) for the CTR components generated by the two algorithms across all the case subjects (motor activation data). c: Comparison of two fitted gaussian distributions.

    Techniques Used: Generated, Activation Assay, Comparison

    Cluster sizing measures for the CTR‐sICA maps and linear correlation maps. The number of active clusters (a: P = 0.01; b: P = 0.001) is plotted against the minimum cluster dimension (in number of voxels).
    Figure Legend Snippet: Cluster sizing measures for the CTR‐sICA maps and linear correlation maps. The number of active clusters (a: P = 0.01; b: P = 0.001) is plotted against the minimum cluster dimension (in number of voxels).

    Techniques Used:



    Similar Products

    fixed-point sica  (InfoMax Inc)
    90
    InfoMax Inc fixed-point sica
    a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax <t>sICA</t> and Fixed‐Point sICA (task‐related components) at two different thresholds (P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).
    Fixed Point Sica, supplied by InfoMax 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/product/fixed-point+sica/pmc06871848-216-91-88?v=InfoMax+Inc
    Average 90 stars, based on 1 article reviews
    fixed-point sica - by Bioz Stars, 2026-07
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax sICA and Fixed‐Point sICA (task‐related components) at two different thresholds (P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).

    Journal: Human Brain Mapping

    Article Title: Spatial independent component analysis of functional MRI time‐series: To what extent do results depend on the algorithm used?

    doi: 10.1002/hbm.10034

    Figure Lengend Snippet: a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax sICA and Fixed‐Point sICA (task‐related components) at two different thresholds (P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).

    Article Snippet: In particular, the supplementary motor area seems to be heavily under‐represented by the correlation analysis compared to ICA, and high contrast foci in primary motor cortex tend to reduce their spatial extension in the correlation analysis, whereas ICA maps show this “primary” activation with a spatial extension matching more closely the gyral anatomy of the Rolandic region. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 4 caption a7 a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax sICA and Fixed‐Point sICA (task‐related components) at two different thresholds ( P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).

    Techniques: Activation Assay, Comparison, Labeling

    a: Results from fitting a gaussian distribution to the histogram of a consistent task‐related (CTR) sICA component. Note that here the IC is positive signed and active voxels remain outside the area under the fitted gaussian density function. b: Variances of the fitted gaussian distribution (residual noise) for the CTR components generated by the two algorithms across all the case subjects (motor activation data). c: Comparison of two fitted gaussian distributions.

    Journal: Human Brain Mapping

    Article Title: Spatial independent component analysis of functional MRI time‐series: To what extent do results depend on the algorithm used?

    doi: 10.1002/hbm.10034

    Figure Lengend Snippet: a: Results from fitting a gaussian distribution to the histogram of a consistent task‐related (CTR) sICA component. Note that here the IC is positive signed and active voxels remain outside the area under the fitted gaussian density function. b: Variances of the fitted gaussian distribution (residual noise) for the CTR components generated by the two algorithms across all the case subjects (motor activation data). c: Comparison of two fitted gaussian distributions.

    Article Snippet: In particular, the supplementary motor area seems to be heavily under‐represented by the correlation analysis compared to ICA, and high contrast foci in primary motor cortex tend to reduce their spatial extension in the correlation analysis, whereas ICA maps show this “primary” activation with a spatial extension matching more closely the gyral anatomy of the Rolandic region. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 4 caption a7 a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax sICA and Fixed‐Point sICA (task‐related components) at two different thresholds ( P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).

    Techniques: Generated, Activation Assay, Comparison

    Cluster sizing measures for the CTR‐sICA maps and linear correlation maps. The number of active clusters (a: P = 0.01; b: P = 0.001) is plotted against the minimum cluster dimension (in number of voxels).

    Journal: Human Brain Mapping

    Article Title: Spatial independent component analysis of functional MRI time‐series: To what extent do results depend on the algorithm used?

    doi: 10.1002/hbm.10034

    Figure Lengend Snippet: Cluster sizing measures for the CTR‐sICA maps and linear correlation maps. The number of active clusters (a: P = 0.01; b: P = 0.001) is plotted against the minimum cluster dimension (in number of voxels).

    Article Snippet: In particular, the supplementary motor area seems to be heavily under‐represented by the correlation analysis compared to ICA, and high contrast foci in primary motor cortex tend to reduce their spatial extension in the correlation analysis, whereas ICA maps show this “primary” activation with a spatial extension matching more closely the gyral anatomy of the Rolandic region. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 4 caption a7 a: Activation maps from real motor activation data as obtained by linear correlation analysis, Infomax sICA and Fixed‐Point sICA (task‐related components) at two different thresholds ( P = 0.01, P = 0.001). b: Comparison of the results obtained by the two algorithms and linear correlation analysis (P=0.001). c: Averaged normalized time‐courses from area A, primary motor cortex (M1), and area B, supplementary motor area (SMA) labeled in (a).

    Techniques: