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BioSemi eeg data preprocessing
Eeg Data Preprocessing, supplied by BioSemi, 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/eeg+preprocessing/eeg+preprocessing+eeg+data/pm30055237-185-4-10
Average 90 stars, based on 1 article reviews
eeg data preprocessing - by Bioz Stars, 2026-09
90/100 stars

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Related Articles

Blocking Assay:

Article Title: Direct feedback and social conformity promote behavioral change via mechanisms indexed by centroparietal positivity: Electrophysiological evidence from a role-swapping ultimatum game.
Article Snippet: 1Beckman Institute for Advanced Science and Technology, University of Illinois at UrbanaChampaign, Urbana, Illinois, USA 2Department of Psychology, University of Illinois at UrbanaChampaign, Champaign, Illinois, USA 3Department of Human and Animal Physiology, Lesya Ukrainka Volyn National University, Lutsk, Ukraine 4Neuroscience Program, University of Illinois at UrbanaChampaign, Urbana, Illinois, USA

Sampling:

Article Title: Direct feedback and social conformity promote behavioral change via mechanisms indexed by centroparietal positivity: Electrophysiological evidence from a role-swapping ultimatum game.
Article Snippet: 1Beckman Institute for Advanced Science and Technology, University of Illinois at UrbanaChampaign, Urbana, Illinois, USA 2Department of Psychology, University of Illinois at UrbanaChampaign, Champaign, Illinois, USA 3Department of Human and Animal Physiology, Lesya Ukrainka Volyn National University, Lutsk, Ukraine 4Neuroscience Program, University of Illinois at UrbanaChampaign, Urbana, Illinois, USA

Software:

Article Title: Direct feedback and social conformity promote behavioral change via mechanisms indexed by centroparietal positivity: Electrophysiological evidence from a role-swapping ultimatum game.
Article Snippet: 1Beckman Institute for Advanced Science and Technology, University of Illinois at UrbanaChampaign, Urbana, Illinois, USA 2Department of Psychology, University of Illinois at UrbanaChampaign, Champaign, Illinois, USA 3Department of Human and Animal Physiology, Lesya Ukrainka Volyn National University, Lutsk, Ukraine 4Neuroscience Program, University of Illinois at UrbanaChampaign, Urbana, Illinois, USA

other:

Article Title: Contralateral delay activity does not reflect behavioral feature load in visual working memory.
Article Snippet: An ongoing debate in visual working memory research is concentrated on whether visual working memory capacity is determined solely by the number of objects to be memorized, or additionally by the number of relevant features contained within objects.. Using a novel change detection task that contained multi-feature objects we examined the effect of both object number and feature number on visual working memory capacity, change detection sensitivity, and posterior slow wave event-related brain potential (ERP) activity.. Behaviorally, working memory capacity and sensitivity were modulated as a function of both the number of objects and the number of features memorized per object.



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a , Hypnogram of the full night for a single participant. b , Time-frequency representation (spectrogram) of the <t>EEG</t> data recording (exemplary channel Pz). c , Continuously estimated 1/f spectral slope (z-scored over the full recording) from channel Pz. Aperiodic activity was estimated within a one-second sliding window (75% overlap) applied to the whole-night time series recorded from each channel (see Methods for details). Colour code indicates the simultaneously scored sleep stage shown in panel a. The dark vertical line marks the segment enlarged below. d , The inset illustrates the z-scored 1/f slope (upper trace) and <t>z-scored</t> <t>respiratory</t> signal (lower trace) across an exemplary 40-second time window.
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a , Hypnogram of the full night for a single participant. b , Time-frequency representation (spectrogram) of the <t>EEG</t> data recording (exemplary channel Pz). c , Continuously estimated 1/f spectral slope (z-scored over the full recording) from channel Pz. Aperiodic activity was estimated within a one-second sliding window (75% overlap) applied to the whole-night time series recorded from each channel (see Methods for details). Colour code indicates the simultaneously scored sleep stage shown in panel a. The dark vertical line marks the segment enlarged below. d , The inset illustrates the z-scored 1/f slope (upper trace) and <t>z-scored</t> <t>respiratory</t> signal (lower trace) across an exemplary 40-second time window.
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a , Hypnogram of the full night for a single participant. b , Time-frequency representation (spectrogram) of the EEG data recording (exemplary channel Pz). c , Continuously estimated 1/f spectral slope (z-scored over the full recording) from channel Pz. Aperiodic activity was estimated within a one-second sliding window (75% overlap) applied to the whole-night time series recorded from each channel (see Methods for details). Colour code indicates the simultaneously scored sleep stage shown in panel a. The dark vertical line marks the segment enlarged below. d , The inset illustrates the z-scored 1/f slope (upper trace) and z-scored respiratory signal (lower trace) across an exemplary 40-second time window.

Journal: bioRxiv

Article Title: Respiratory coordination of excitability states across the human wake-sleep cycle

doi: 10.1101/2025.06.03.657770

Figure Lengend Snippet: a , Hypnogram of the full night for a single participant. b , Time-frequency representation (spectrogram) of the EEG data recording (exemplary channel Pz). c , Continuously estimated 1/f spectral slope (z-scored over the full recording) from channel Pz. Aperiodic activity was estimated within a one-second sliding window (75% overlap) applied to the whole-night time series recorded from each channel (see Methods for details). Colour code indicates the simultaneously scored sleep stage shown in panel a. The dark vertical line marks the segment enlarged below. d , The inset illustrates the z-scored 1/f slope (upper trace) and z-scored respiratory signal (lower trace) across an exemplary 40-second time window.

Article Snippet: All EEG and respiratory data preprocessing was done in Fieldtrip for Matlab [ ].

Techniques: Activity Assay

a , Group-level distribution of 1/f slope across polysomnographic stages, averaged across all k = 60 EEG channels and irrespective of respiration phase. Tukey-Kramer-corrected significance is shown relative to wakefulness; full statistical results are provided in the main text. b , Group-level distribution of respiratory rates across stages. Across all pairwise comparisons, only the difference between N1 and SWS was significant ( p = .041, Tukey-Kramer-corrected). c , Polar representation of group-level mean 1/f slope ± SEM across respiration phase per polysomnographic stage, averaged across all k = 60 channels. Coloured dashed lines indicate mean directions of the respective circular distributions. FDR-corrected significance is shown relative to wakefulness; full statistics on differences in mean direction are provided in the main text. d , Polar histograms show the circular distribution of mean directions in 1/f slope across the n = 23 participants per stage. Polar plots show individual courses of aperiodic activity over respiration phase. FDR-corrected tests against circular uniformity were highly significant for all polysomnographic stages. Statistical results are provided in the main text. e , Polar histograms show the circular distribution of group-level mean directions in 1/f slope across the k = 60 electrodes per stage. Polar plots show electrode-specific courses of aperiodic activity over respiration phase. FDR-corrected tests against circular uniformity were highly significant for all sleep stages. Statistical results are provided in the main text. f , Detailed visualisation of topographic consistency in group-level average 1/f slope across all electrodes, sorted from anterior to posterior location.

Journal: bioRxiv

Article Title: Respiratory coordination of excitability states across the human wake-sleep cycle

doi: 10.1101/2025.06.03.657770

Figure Lengend Snippet: a , Group-level distribution of 1/f slope across polysomnographic stages, averaged across all k = 60 EEG channels and irrespective of respiration phase. Tukey-Kramer-corrected significance is shown relative to wakefulness; full statistical results are provided in the main text. b , Group-level distribution of respiratory rates across stages. Across all pairwise comparisons, only the difference between N1 and SWS was significant ( p = .041, Tukey-Kramer-corrected). c , Polar representation of group-level mean 1/f slope ± SEM across respiration phase per polysomnographic stage, averaged across all k = 60 channels. Coloured dashed lines indicate mean directions of the respective circular distributions. FDR-corrected significance is shown relative to wakefulness; full statistics on differences in mean direction are provided in the main text. d , Polar histograms show the circular distribution of mean directions in 1/f slope across the n = 23 participants per stage. Polar plots show individual courses of aperiodic activity over respiration phase. FDR-corrected tests against circular uniformity were highly significant for all polysomnographic stages. Statistical results are provided in the main text. e , Polar histograms show the circular distribution of group-level mean directions in 1/f slope across the k = 60 electrodes per stage. Polar plots show electrode-specific courses of aperiodic activity over respiration phase. FDR-corrected tests against circular uniformity were highly significant for all sleep stages. Statistical results are provided in the main text. f , Detailed visualisation of topographic consistency in group-level average 1/f slope across all electrodes, sorted from anterior to posterior location.

Article Snippet: All EEG and respiratory data preprocessing was done in Fieldtrip for Matlab [ ].

Techniques: Activity Assay