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loreta algorithm  (BESA GmbH)

 
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    BESA GmbH loreta algorithm
    Loreta Algorithm, supplied by BESA GmbH, 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/loreta algorithm/product/BESA GmbH
    Average 90 stars, based on 1 article reviews
    loreta algorithm - by Bioz Stars, 2026-04
    90/100 stars

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    Image Search Results


    Schematic illustration of the LORETA source localization approach. a.) individual MRI image with intracranial electrodes; b.) position of intracranial electrodes derived from the MRI in 3-dimensional virtual space; c.) segmentation of the cortical surface derived from MRI; d.) grid electrodes superimposed on 3-dimentional reconstruction of individual cortex; e.) Evoked Potentials (EP) recorded from grid electrodes; f.) topographical map of recorded EP superimposed on reconstructed cortex; g) LORETA solutions superimposed on the anatomical cortical reconstruction for an individual brain.

    Journal:

    Article Title: Generators of the intracranial P50 response in auditory sensory gating

    doi: 10.1016/j.neuroimage.2006.12.011

    Figure Lengend Snippet: Schematic illustration of the LORETA source localization approach. a.) individual MRI image with intracranial electrodes; b.) position of intracranial electrodes derived from the MRI in 3-dimensional virtual space; c.) segmentation of the cortical surface derived from MRI; d.) grid electrodes superimposed on 3-dimentional reconstruction of individual cortex; e.) Evoked Potentials (EP) recorded from grid electrodes; f.) topographical map of recorded EP superimposed on reconstructed cortex; g) LORETA solutions superimposed on the anatomical cortical reconstruction for an individual brain.

    Article Snippet: To localize sources of our intracranial P50 data, we used the LORETA algorithm ( Pascual-Marqui, 1999 as implemented by the CURRY software package, Neuroscan, Compumedics Ltd.) because it allows many distributed sources to be concurrently active in the current density reconstructions, without assuming a limited number of dipolar sources (for reviews on source reconstruction methods, see ( Fuchs et al., 1999 ; Yao and Dewald, 2005 ).

    Techniques: Derivative Assay

    Left panel: LORETA results for the P50 source localization. Right panel: Localization results for the Gating Difference Wave source, also calculated with LORETA.

    Journal:

    Article Title: Generators of the intracranial P50 response in auditory sensory gating

    doi: 10.1016/j.neuroimage.2006.12.011

    Figure Lengend Snippet: Left panel: LORETA results for the P50 source localization. Right panel: Localization results for the Gating Difference Wave source, also calculated with LORETA.

    Article Snippet: To localize sources of our intracranial P50 data, we used the LORETA algorithm ( Pascual-Marqui, 1999 as implemented by the CURRY software package, Neuroscan, Compumedics Ltd.) because it allows many distributed sources to be concurrently active in the current density reconstructions, without assuming a limited number of dipolar sources (for reviews on source reconstruction methods, see ( Fuchs et al., 1999 ; Yao and Dewald, 2005 ).

    Techniques:

    Left panel: LORETA results for the P50 source localization. Right panel: Localization results for the Gating Difference Wave source, also calculated with LORETA

    Journal:

    Article Title: Generators of the intracranial P50 response in auditory sensory gating

    doi: 10.1016/j.neuroimage.2006.12.011

    Figure Lengend Snippet: Left panel: LORETA results for the P50 source localization. Right panel: Localization results for the Gating Difference Wave source, also calculated with LORETA

    Article Snippet: To localize sources of our intracranial P50 data, we used the LORETA algorithm ( Pascual-Marqui, 1999 as implemented by the CURRY software package, Neuroscan, Compumedics Ltd.) because it allows many distributed sources to be concurrently active in the current density reconstructions, without assuming a limited number of dipolar sources (for reviews on source reconstruction methods, see ( Fuchs et al., 1999 ; Yao and Dewald, 2005 ).

    Techniques: