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eeglab function runica (InfoMax Inc)

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InfoMax Inc eeglab function runica
Eeglab Function Runica, 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/eeglab+function+in/eeglab+function+runica/pm40409165-96-10-1
Average 90 stars, based on 1 article reviews

eeglab function runica - by Bioz Stars, 2026-10

90/100 stars

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Article Title: Effects of chiropractic spinal manipulation on laser-evoked pain and brain activity
Article Snippet: After, an Infomax-independent component analysis (ICA) was applied using the in-built EEGLAB function Runica to identify and remove components associated with noise (e.g., eye movement, eye blinks, cardiac, and muscle artifacts).

Article Title: Young adults who improve performance during dual-task walking show more flexible reallocation of cognitive resources: a mobile brain-body imaging (MoBI) study
Article Snippet: In order to both achieve a high-quality ICA decomposition and retain as much low-frequency (< 1 Hz) neural activity as possible, after running Infomax ICA (“runica” function in EEGLAB, the number of retained principal components matched the rank of the EEG data) on 1–45 Hz bandpass-filtered data and obtaining the decomposition matrices (weight and sphere matrices), these matrices were transferred and applied to 45-Hz lowpass-filtered data.

Article Title: Disruption of working memory and contralateral delay activity by nociceptive stimuli is modulated by task demands.
Article Snippet: Next, an Infomax independent component analysis (ICA) was applied using the in-built EEGLAB function Runica to identify and remove components associated with noise (e.g., eye movements and blinks, and cardiac and muscle artifacts).

Article Title: Pupil dilation evoked by painful electrical stimulation is abolished during pain inhibition by distraction.
Article Snippet: An Infomax independent component analysis was applied using the in-built EEGLAB function Runica to identify and remove components associated with noise.

Article Title: Extensive sensorimotor training enhances nociceptive cortical responses in healthy individuals.
Article Snippet: Data were band- pass filtered (0.5– 40 Hz), followed by an Infomax independent component analysis using the in- built EEGLAB function runica to identify and remove components associated with noise (e.g. eye movement, eye blinks, cardiac, muscle artefacts; Jung et al., 2000).

Article Title: Free-Field Cortical Steady-State Evoked Potentials in Cochlear Implant Users.
Article Snippet: Auditory steady-state evoked potentials (SS-EPs) are phase-locked neural responses to periodic stimuli, believed to reflect specific neural generators.. As an objective measure, steady-state responses have been used in different clinical settings, including measuring hearing thresholds of normal and hearing-impaired subjects.. Recent studies are in favor of recording these responses as a part of the cochlear implant (CI) device-fitting procedure.

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Article Title: Paradoxical improvement of cognitive control in older adults under dual-task walking conditions is associated with more flexible reallocation of neural resources: A Mobile Brain-Body Imaging (MoBI) study.
Article Snippet: .. In order to both achieve a high-quality ICA decompoition and retain as much low-frequency ( < 1 Hz) neural activity as ossible, after running Infomax ICA ( runica function in EEGLAB, the umber of retained principal components matched the rank of the EEG ata) on 1–45 Hz bandpass-filtered data and obtaining the decomposiion matrices (weight and sphere matrices), these matrices were transerred and applied to 0.01–45 Hz bandpass-filtered data. ..

Article Title: Maintaining Task Performance Levels Under Cognitive Load While Walking Requires Widespread Reallocation of Neural Resources.
Article Snippet: .. In order to both achieve a high-quality ICA decomposition and retain as much low-frequency (<1 Hz) neural activity as possible, after running Infomax ICA (runica function in EEGLAB, the number of retained principal components matched the rank of the EEG data) on 1–45 Hz bandpass-filtered data and obtaining the decomposition matrices (weight and sphere matrices), these matrices were transferred and applied to 0.01–45 Hz bandpassfiltered data. ..

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