2016
DOI: 10.1016/j.neuroimage.2016.07.024
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Visual deviant stimuli produce mismatch responses in the amplitude dynamics of neuronal oscillations

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Cited by 10 publications
(10 citation statements)
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References 49 publications
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“…In the following window of 300–450 ms, all the stimuli elicited alpha power decrease. Alpha power decrease has been reported in previous vMMN studies focusing on elementary visual feature detection (Stothart and Kazanina, 2013; Tugin et al, 2016). It has been suggested that while alpha power increase reflects task-related inhibition within a cortical area (Palva and Palva, 2007; Jensen et al, 2014), a decrease in the oscillatory amplitude suggests active neuronal processing (Pfurtscheller and Da Silva, 1999; Thut et al, 2012) and the enhanced attentional demands of processing (Klimesch, 1999; Bastiaansen et al, 2002; Stothart and Kazanina, 2013; Wang and Bastiaansen, 2014).…”
Section: Discussionsupporting
confidence: 64%
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“…In the following window of 300–450 ms, all the stimuli elicited alpha power decrease. Alpha power decrease has been reported in previous vMMN studies focusing on elementary visual feature detection (Stothart and Kazanina, 2013; Tugin et al, 2016). It has been suggested that while alpha power increase reflects task-related inhibition within a cortical area (Palva and Palva, 2007; Jensen et al, 2014), a decrease in the oscillatory amplitude suggests active neuronal processing (Pfurtscheller and Da Silva, 1999; Thut et al, 2012) and the enhanced attentional demands of processing (Klimesch, 1999; Bastiaansen et al, 2002; Stothart and Kazanina, 2013; Wang and Bastiaansen, 2014).…”
Section: Discussionsupporting
confidence: 64%
“…While no difference in alpha band power between deviant and standard stimuli has been reported in auditory MMN studies (e.g., Hsiao et al, 2009; Ko et al, 2012), two studies in the visual modality have indeed found such a difference. Stothart and Kazanina (2013) and Tugin et al (2016) both described stronger alpha power decrease induced by deviants than standards. Tugin et al (2016) also reported a larger increase of alpha band to deviant than standard items, despite an absence of vMMN in their study.…”
Section: Introductionmentioning
confidence: 90%
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“…To our knowledge, we are the first to utilize CSP filtering for the analysis of tACS effects and thus to obtain neural activity selectively tuned to show a decrease or an increase of alpha oscillations following tACS. Although CSP is mainly applied in BCI paradigms to differentiate particular activation patterns, which usually correspond to different anatomical regions (e.g., left or right motor imaginary corresponding to the activation of the right or left motor cortex), this method also can be useful for discriminating between activity in the same spatial region, which was previously shown for alpha oscillations with standard and deviant visual stimuli (Tugin et al, 2016 ). In our study, CSP was used to provide spatial filters maximally discriminating activity between the periods with and without stimulation.…”
Section: Discussionmentioning
confidence: 99%
“…One of the established and efficient methods for extraction of modulated brain activity is the Common Spatial Patterns (CSP) approach, which was introduced in (Blankertz et al, 2008) for single-trial analysis and is commonly used in brain-computer interface (BCI) applications to differentiate between classes of brain activation. Moreover, CSP has been successfully applied previously for the extraction of alpha band activity sensitive to the processing and discrimination of standard and deviant visual stimuli (Tugin et al, 2016). We utilized CSP to obtain data from parietal-occipital regions to investigate possible differences between pre-and post-stimulation activity for alpha band oscillations in visuo-occipital components.…”
Section: Common Spatial Patternsmentioning
confidence: 99%