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independent component analysis runica logistic infomax algorithm  (InfoMax Inc)

 
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    Structured Review

    InfoMax Inc independent component analysis runica logistic infomax algorithm
    Independent Component Analysis Runica Logistic Infomax Algorithm, 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/independent+component+analysis+algorithm/independent+component+analysis+runica/pm37353108-101-14-18
    Average 90 stars, based on 1 article reviews
    independent component analysis runica logistic infomax algorithm - by Bioz Stars, 2026-11
    90/100 stars

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    Related Articles

    other:

    Article Title: Assessing the influence of latency variability on EEG classifiers - a case study of face repetition priming
    Article Snippet: Blinks and eye movements were eliminated in the first step using independent component analysis (function: runica(); algorithm: Infomax (Gradient)).

    Article Title: Watching Nature Videos Promotes Physiological Restoration: Evidence From the Modulation of Alpha Waves in Electroencephalography
    Article Snippet: EEG data was submitted to extended Infomax independent component analysis (ICA, “pop_runica.m”) to detect and afterward remove non-neural activity (eye and muscle movements).

    Article Title: Changing connectivity between premotor and motor cortex changes inter-areal communication in the human brain.
    Article Snippet: Physiological artefacts such as eye blinks and saccades were corrected by means of independent component analysis (RUNICA, logistic Infomax algorithm) as implemented in the FieldTrip toolbox.

    Article Title: Cortical interaction of bilateral inputs is similar for noxious and innocuous stimuli but leads to different perceptual effects.
    Article Snippet: The cerebral integration of somatosensory inputs from multiple sources is essential to produce adapted behaviors.. Previous studies suggest that bilateral somatosensory inputs interact differently depending on stimulus characteristics, including their noxious nature.. The aim of this study was to clarify how bilateral inputs evoked by noxious laser stimuli, noxious shocks, and innocuous shocks interact in terms of perception and brain responses.

    Article Title: Excitability changes induced in the human auditory cortex by transcranial alternating current stimulation.
    Article Snippet: Transcranial alternating current stimulation (tACS) has been widely studied for its ability to regulate motor, perceptual, and cognitive functions.. Given the unique frequency specificity of tACS, it is expected to directly target rhythmic activity in the typical electroencephalogram (EEG) range.. After tACS stimulation, changes in stimulation-induced and evoked activities can be inspected.

    Article Title: The Cortical Response Evoked by Robotic Wrist Perturbations Reflects Level of Proprioceptive Impairment After Stroke
    Article Snippet: To separate brain activity from eye blinks and remaining sources of noise Infomax independent component analysis (runica.m) was conducted ( ).

    Electroencephalography:

    Article Title: Delta-modulated cortical alpha oscillations support new knowledge generation through memory integration
    Article Snippet: .. To mitigate the potential influence of oculomotor artifacts on the oscillatory results, eye-blinks and saccades were detected and removed from the continuous EEG data using the standard runica extended Infomax independent component analysis (ICA) algorithm. ..

    Analysis:

    Article Title: Delta-modulated cortical alpha oscillations support new knowledge generation through memory integration
    Article Snippet: .. To mitigate the potential influence of oculomotor artifacts on the oscillatory results, eye-blinks and saccades were detected and removed from the continuous EEG data using the standard runica extended Infomax independent component analysis (ICA) algorithm. ..

    Activity Assay:

    Article Title: Deep learning-based auditory attention decoding in listeners with hearing impairment .
    Article Snippet: .. The following non-brain artifacts were removed: eye movements, eye blinks, muscle activity, heart beats, and single-channel noise, using independent component analysis with the runica algorithm based on InfoMax [29]. ..



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