Intrinsic EEG and task-related changes in EEG affect Go/NoGo task performance

Karamacoska, Diana; Barry, Robert J.; Steiner, Genevieve Z.; Coleman, Elle P; Wilson, Emily J

doi:10.1016/j.ijpsycho.2018.01.015

Cited by 32 publications

(29 citation statements)

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“…The sequential processing schema has proven to be a reliable research tool in studies of a range of target/nontarget processes over the lifespan (Barry, De Blasio, & Borchard, ; Barry, De Blasio, & Cave, ), with pharmacological manipulation (Barry, De Blasio, & Cave, ), variable stimulus onset asynchronies (SOAs; Borchard, Barry, & De Blasio, ), brain dynamics (Barry, De Blasio, De Pascalis, & Karamacoska, ; Barry, Fogarty, De Blasio, & Karamacoska, ; Karamacoska, Barry, & Steiner, ; Karamacoska, Barry, Steiner, Coleman, & Wilson, ), and in relation to behavior (Barry & De Blasio, ; Barry et al, ; Fogarty et al, ).…”

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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Section: Introductionmentioning

confidence: 99%

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

2018

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“…Trial response time is defined as the latency of each click with respect to the digit onset. Note we do not omit trials with response time below a certain threshold as done in [8] since we are interested in analyzing these fast reactions as a natural occurrence in the response traits of our participants. Section IV-B includes a comparison of our findings on neural correlates of impulsivity with those from studies which omitted these fast responses.…”

Section: Eeg Analysis and Feature Extractionmentioning

confidence: 99%

“…Higher ratios of EO delta especially from the left frontal and temporal regions predicted faster responses as well as less variability in the reaction time in our long SART experiment. Therefore, they could be considered as the neural correlates of uniform impulsivity and point to the role of delta oscillations in improving the "Go stimulus-responses" [8] and suppression of processing the irrelevant stimuli. In a much shorter task of auditory Go/NoGo and after rejection of the extremely fast trials as well as the erroneous and posterror trials, increase in delta (1-3 Hz) during the task with respect to the pre-task EO was correlated with higher omission errors and higher RT variability -standard deviation, according to their calculations [8].…”

Section: B Roles Of Delta and Theta Ratiosmentioning

confidence: 99%

“…Therefore, they could be considered as the neural correlates of uniform impulsivity and point to the role of delta oscillations in improving the "Go stimulus-responses" [8] and suppression of processing the irrelevant stimuli. In a much shorter task of auditory Go/NoGo and after rejection of the extremely fast trials as well as the erroneous and posterror trials, increase in delta (1-3 Hz) during the task with respect to the pre-task EO was correlated with higher omission errors and higher RT variability -standard deviation, according to their calculations [8]. Their finding on associations between frontal delta with higher RT variability should not be interpreted as being different from our prediction results as we did not eliminate the extremely fast trials and wanted to account for such impulsivities in the reaction time and cumulative vigilance scores.…”

Section: B Roles Of Delta and Theta Ratiosmentioning

confidence: 99%

“…As a first of its kind, Loo et al obtained the number of errors, response time, and variability of RT and task performance -without specifying how they were calculatedfrom the ADHD and control groups, and reported the task variability of ADHD patients was linearly correlated with lower levels of frontal alpha, frontal beta (17)(18), and parietal beta power (13 -14 Hz) [20]. Karamacoska et al designed two pre-task, two-minute resting state sessions followed by auditory SART blocks [8]. Their step-wise regression models showed that changes in the power of delta and alpha bands during the task with respect to the resting-state recordings could predict the task accuracy, mean response time, and standard deviation of response time with an adjusted R 2 below 0.22 for each model.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Reaction Time and Vigilance Variability From Spatio-Spectral Features of Resting-State EEG in a Long Sustained Attention Task

Torkamani-Azar

Kanik

Aydın

et al. 2020

IEEE J. Biomed. Health Inform.

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Resting-state brain networks represent the intrinsic state of the brain during the majority of cognitive and sensorimotor tasks. However, no study has yet presented concise predictors of task-induced vigilance variability from spectrospatial features of the pre-task, resting-state electroencephalograms (EEG). We asked ten healthy volunteers (6 females, 4 males) aged from 22 to 45.5 to participate in 105-minute fixed-sequence-varying-duration sessions of sustained attention to response task (SART). A novel and adaptive vigilance scoring scheme was designed based on the performance and response time in consecutive trials, and demonstrated large inter-participant variability in terms of maintaining consistent tonic performance. Multiple linear regression using feature relevance analysis obtained significant predictors of the mean cumulative vigilance score (CVS), mean response time, and variabilities of these scores from the resting-state, bandpower ratios of EEG signals, p<0. Brodmanns areas 35 and 36). Higher ratios of parietal alpha (8-12 Hz) from the Brodmann's areas 18, 19, and 37 during the eyes-open states predicted slower responses but more consistent CVS and reactions associated with the superior ability in vigilance maintenance. The proposed framework and these first findings on the most stable and significant attention predictors from the intrinsic EEG power ratios can be used to model attention variations during the calibration sessions of BCI applications and vigilance monitoring systems. Single-layer neural networks trained with cross-validation also captured different associations for the beta sub-bands. Increase in the gamma (28-48 Hz) and upper beta (24-28 Hz) ratios from the left central and temporal regions predicted slower reactions and more inconsistent vigilance as explained by the increased activation of default mode network (DMN) and differences between the high-and low-attention networks at temporal regions (

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Electroencephalographic characteristics of word finding during phonological and semantic verbal fluency tasks

Mousavi

Nazari

Babapour

et al. 2020

Neuropsychopharm Rep

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Aims Verbal Fluency is sensitive to brain damage and is employed to assess language abilities like the size of vocabulary and the semantic‐lexical networks’ integrity and executive functioning abilities particularly inhibition, working memory, and self‐monitoring. Various studies revealed oscillatory changes related to word retrieval during different tasks. However, there are not enough studies on electroencephalographic characteristics of word retrieval routes (phonological or semantic pathway) during free recall. The purpose of our study was to investigate electroencephalography power relationship with semantic and phonological word finding routes during verbal fluency. Methods In this within‐subject study, the electroencephalography of 20 healthy participants was recorded during written category and letter fluency tasks and compared with the rest state. Absolute power of the signals in delta (1‐3.5 Hz), theta (4‐7.5 Hz), alpha (8‐12 Hz), and beta (12.5‐30 Hz) was calculated in three lobes (frontal, parietal, and temporal). Results A repeated measures ANOVA showed significant interaction of condition × lobe × frequency × side (P < .001). Post hoc test for each lobe showed significant changes in the absolute power of delta, theta and beta for frontal, delta and theta for parietal, and theta and beta for temporal lobes (P‐values < .05). Conclusion Searching the words by phonological entries is associated with decreased beta and increased theta in left frontal lobe. These changes are not necessary for semantic word retrieval strategy.

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Intrinsic EEG and task-related changes in EEG affect Go/NoGo task performance

Cited by 32 publications

References 74 publications

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

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

Prediction of Reaction Time and Vigilance Variability From Spatio-Spectral Features of Resting-State EEG in a Long Sustained Attention Task

Electroencephalographic characteristics of word finding during phonological and semantic verbal fluency tasks

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