ERP Go/NoGo condition effects are better detected with separate PCAs

Barry, Robert J.; Blasio, Frances M. De; Fogarty, Jack S.; Karamacoska, Diana

doi:10.1016/j.ijpsycho.2016.06.003

Cited by 43 publications

(61 citation statements)

References 25 publications

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“…The limitations to these methods are recognized with both the temporal PCA of ERP data and the grouping of band activity according to traditionally defined frequency limits, restricting the electrophysiological information available for analysis. Temporal PCA, however, has been reliably applied in studies of sequential ERP response activity for its ability to separate overlapping components that spatial PCAs cannot (Barry & De Blasio, ; Barry, De Blasio, Fogarty, & Karamacoska, ; Karamacoska, Barry, Steiner, & De Blasio, ; Kayser & Tenke, ; Kayser et al, ). Furthermore, the utility of spatial PCA holds value when assessing specified components (markedly the P3b) within large electrode arrays, and as the present study had several components of interest, this was not pursued for component extraction.…”

Section: Discussionmentioning

confidence: 99%

“…Following rotation, PCA factors that contributed ≥ 3% of the variance were selected for identification as ERP components according to their latency, topography, polarity, and sequence within the expected processing schema (Barry, De Blasio, & Cave, ). The selected components were extracted using Dien's PCA output procedure that retains comparability with the original ERP data (Dien & Frishkoff, ; see also Barry, De Blasio, Fogarty, & Karamacoska, ). Guided by the component topographies reported by Borchard et al (), amplitudes were analyzed at their region of maximal activity (pooled across three sites).…”

Section: Methodsmentioning

confidence: 99%

“…The equiprobable go/no‐go task is an optimal paradigm in which these cognitive operations have been studied to assess the electrophysiology of neurotypical functioning across the lifespan (Barry & De Blasio, ; Barry, De Blasio, & Borchard, ; Barry, De Blasio, & Cave, ). The work of Barry and colleagues has reliably mapped the ERP sequence of go/no‐go stimulus‐response processes using temporal principal components analysis (PCA), a technique that extracts the major factors, or peaks, contributing to ERP time‐series variability (Barry, De Blasio, Fogarty, & Karamacoska, ; Borchard, Barry, & De Blasio, ; for a PCA tutorial, see Dien, ). This processing schema links stimulus appraisal to the P1 and the N1 subcomponents, with stimulus categorization and response selections indexed by the following central P2.…”

Section: Erp Correlates Of Response Processesmentioning

confidence: 99%

“…Adequate no‐go performance requires a degree of cognitive control to maintain accuracy and avoid responding. The frontal N2b and central P3a components are typically elicited when exercising inhibition to no‐go (Folstein & Van Petten, ; Larson & Clayson, ; Smith, Johnstone, & Barry, ); however, neurotypical adult no‐go performance in the equiprobable task tends to show a weak N2b (Barry & De Blasio, ; Barry, De Blasio, & Cave, ; Barry, De Blasio, Fogarty, & Karamacoska, ). This was especially apparent when a varied stimulus‐onset asynchrony (SOA) was employed (Borchard et al, ), suggesting that inhibition is required to a lesser extent for this cohort.…”

Section: Erp Correlates Of Response Processesmentioning

confidence: 99%

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Resting state intrinsic EEG impacts on go stimulus‐response processes

2017

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Neuropsychological research and practice rely on cognitive task performance measures as indicators of brain functioning. The neural activity underlying stimulus-response processes can be assessed with ERPs, but the relations between these cognitive processes and the brain's intrinsic resting state EEG activity are less understood. This study focused on the neurocognitive functioning of 20 healthy young adults in an equiprobable go/no-go task to map the ERP correlates of behavioral responses and examine contributions of the resting state intrinsic EEG to task-related outcomes. Continuous EEG was recorded during pretask eyes-closed (EC) and eyes-open (EO) conditions, and in the subsequent task. Delta, theta, alpha, and beta band amplitudes were assessed for the EC state and also for the reactive change to EO. Go/no-go ERPs were submitted to temporal principal components analysis, where the P2, N2, P3, and slow wave components of interest were extracted. The performance measure of reaction time (RT) variability was positively correlated with no-go and go errors, and also with go P2 amplitude, linking these to stimulus discrimination efforts involved in appropriate response selection. An N2c-P3b pairing was enhanced for shorter mean RTs, supporting their involvement in the decision to execute a response. A stepwise regression model identified EC midline delta as a predictor of P3b positivity, highlighting the relevance of delta in the neural mechanisms of attentional processes. These findings clarify the electrophysiology underlying decision-making processes in executive function, and provide a platform for further research assessing performance outcomes in larger samples and in developmental/clinical contexts.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Erp Correlates Of Response Processesmentioning

confidence: 99%

Section: Erp Correlates Of Response Processesmentioning

confidence: 99%

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Resting state intrinsic EEG impacts on go stimulus‐response processes

2017

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“…Following several conceptual and methodological advancements (e.g., Barry, De Blasio, Fogarty, & Karamacoska, ), Barry and colleagues have produced updated versions of the schema for children (Barry, De Blasio, & Fogarty, ) and for young adults (Fogarty, Barry, De Blasio, & Steiner, ). The young adult schema in Fogarty et al () starts with the auditory P1 and N1‐3 components, representing early sensory and attentional mechanisms involved in stimulus detection (Figure ); however, these components are not always identified using PCA, given that they account for such a small proportion of ERP variance (typically < 1%; Barry & De Blasio, ).…”

Section: Introductionmentioning

confidence: 99%

Sequential processing in the classic oddball task: ERP components, probability, and behavior

2018

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This study compared the ERP components and behavior associated with the auditory equiprobable and classic oddball tasks, to relate the cognitive processing stages in those paradigms and continue the development of the sequential processing schema. Target and nontarget ERP data were acquired from 66 healthy young adults (Mage = 20.1, SD = 2.4 years, 14 male) who completed both equiprobable (target p = 0.5) and oddball tasks (target p = 0.3). Separate temporal PCAs were used to decompose the ERP data in each task and condition, and the similarity of the components identified in each condition was examined between tasks. Probability effects on component amplitudes and behavior were also analyzed to identify task differences in cognitive demands. A highly similar series of components was identified in each task, closely matching the schema: targets elicited N1‐3, N1‐1, PN, N2c, P3b, SW1, SW2; whereas nontargets elicited N1‐3, N1‐1, PN, N2b, P3a, SW1, SW2. N1‐1 and PN amplitudes increased as stimulus probability decreased, irrespective of the condition. N2b, P3b, SW1, and SW2 amplitudes also varied between tasks, illustrating task‐specific demands on those processing stages. These findings complemented the behavioral outcomes, which demonstrated greater accuracy and control in the classic oddball task. Overall, this study demonstrated comparable processing in the auditory equiprobable and classic oddball tasks, extending the generalizability of the schema and enabling further integration of the ERP theory associated with these tasks. This study also clarifies stimulus probability effects on the schema, providing important insight into the functionality of common ERP components.

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The fronto-central N2 but not parietal P3 reflects response inhibition in the count/no-count task

Jing

Zhang

et al. 2021

Psychological Research

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ERP Go/NoGo condition effects are better detected with separate PCAs

Cited by 43 publications

References 25 publications

Resting state intrinsic EEG impacts on go stimulus‐response processes

Resting state intrinsic EEG impacts on go stimulus‐response processes

Sequential processing in the classic oddball task: ERP components, probability, and behavior

The fronto-central N2 but not parietal P3 reflects response inhibition in the count/no-count task

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