Time–frequency analysis of the event-related potentials associated with the Stroop test

Ergen, Mehmet; Saban, Sara; Kirmizi-Alsan, Elif; Uslu, Atilla; Keskin-Ergen, Yasemin; Demiralp, Tamer

doi:10.1016/j.ijpsycho.2014.08.177

Cited by 57 publications

(54 citation statements)

References 68 publications

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“…But the amplitudes of the P300 waves reported differed between studies. Also, a prolonged negativity was reported by some authors [20,22,24,25]. …”

Section: Resultsmentioning

confidence: 77%

“…Ergen et al [25] used the Turkish equivalents of the words red, green and blue as stimuli and the participant were required to give a key-press type of response and their ERPs were recorded from 30 electrode sites according to the extended 10-20 system. Their behavioral data displayed that RTs to incongruent stimuli was longer compared to the results of the congruent.…”

Section: Event-related Potential Studiesmentioning

confidence: 99%

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Event-Related Potentials and the Stroop Effect

Şahinoğlu¹,

Dogan²

2016

Eurasian J Med

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“…But the amplitudes of the P300 waves reported differed between studies. Also, a prolonged negativity was reported by some authors [20,22,24,25]. …”

Section: Resultsmentioning

confidence: 77%

Section: Event-related Potential Studiesmentioning

confidence: 99%

Event-Related Potentials and the Stroop Effect

Şahinoğlu¹,

Dogan²

2016

Eurasian J Med

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“…3 and 4 (B) the associated TFR distribution of the mixedsignal). This can be also confirmed in the actual ERP signals (Barry, 2009;Ergen et al, 2014;Jones et al, 2006). In their studies, the number of visible evoked EROs identified from the grand averaged TFR was smaller than those of the analyzed ERPs.…”

Section: Introductionmentioning

confidence: 61%

“…The conventional rectangle method was a widely used-way to mark the region of evoked ERO (Ergen et al, 2014;Lally et al, 2014;Jones et al, 2006;Sandre & Weinberg, 2019;Zhang et al, 2019;Her et al, 2019). As the demonstration in Section 3.2.1, different statistical results were displayed because it was a subjective method to determine the region.…”

Section: Objectively Determining the Region Of Eros Via Edge Detectiomentioning

confidence: 99%

“…TFA can overcome this obstacle, allowing examination of EROs in temporal and spectral domains simultaneously. The regions of evoked EROs of interest were usually determined by a certain time window and a frequency range according to the previous studies and the visual inspection of grand averaged time-frequency representation (TFR) distributions -in other words, they were subjectively chosen by experimenters (Ergen et al, 2014;Lally et al, 2014;Jones et al, 2006;Sandre & Weinberg, 2019;Zhang et al, 2019;Her et al, 2019). This technique is called as conventional rectangle method in this study due to the rectangle-like shape of this certain region.…”

Section: Introductionmentioning

confidence: 99%

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Objective Extraction of Evoked Event-related Oscillations from Time-frequency Representation of Event-related Potentials

Zhang

Ristaniemi

Cong

2020

Preprint

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Evoked event-related oscillations (EROs) have been widely used to explore the mechanisms of brain activities for both normal people and neuropsychiatric disease patients. The selection of regions of evoked EROs tends to be subjectively based on the previous studies and the visual inspection of grand averaged time-frequency representations (TFRs) which causes some missing or redundant information. Meanwhile, the evoked EROs cannot be fully extracted via the conventional time-frequency analysis (TFA) method because they are sometimes overlapped with each other or with artifacts in time, frequency, and space domains to some extent. Hence, these shortcomings may pose some challenges to investigate the related neuronal processes. A data-driven approach was introduced to fill the gaps as below: extracting the temporal and spatial components of interest simultaneously by principal component analysis and Promax rotation and projecting them to the electrode field to correct their variance and polarity indeterminacy, calculating the TFRs of the back-projected components, and determining the regions of interest objectively using the edge detection algorithm. We performed this novel approach and the conventional TFA method in analyzing both a synthetic dataset and an actual ERP dataset in a two-factor simple gambling paradigm of waiting time (short/long) and feedback (loss/gain) separately. Synthetic dataset results indicated that N2-theta and P3-delta oscillations were detected using the proposed approach, but, by comparison, only one oscillation was obtained via the conventional TFA method. Furthermore, the actual ERP dataset results of P3-delta for our approach revealed that it was sensitive to the waiting time (which also was found in the previous reports) but not for that of the conventional TFA method. This study manifested that the proposed approach can objectively extract evoked EROs, which allows a better understanding of the modulations of the oscillatory responses.

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A study of alpha desynchronization, heart rate, and MRI during stroop testing unmasks pre‐symptomatic Alzheimer’s disease

Arakaki

Hung

Wei

et al. 2020

Alzheimer's & Dementia

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Background Alzheimer’s disease (AD) studies suggested the need to detect pre‐symptomatic stage, when cognitive challenges reveal changes of alpha power (brain hyperactivity). Heart rate (HR) regulates brain oxygen supply, is regulated by the brain (eg. hippocampus and amygdala), and correlated with resting state alpha power. We aimed to compare alpha power, HR, and hippocampal and amygdala volume between pre‐symptomatic AD and normal, aging individuals. Method We employed quantitative electroencephalography (qEEG) to monitor brain activity during resting and during Stroop interference testing. Cognitively healthy (CH) study participants (demographically matched) were recruited from the local community, consisting of two subgroups based on cerebrospinal fluid (CSF) proteins: with normal amyloid/tau ratio (CH‐NAT, n=20) or pathological amyloid/tau ratio (CH‐PAT, equals pre‐symptomatic AD, n=21). Cognition was assessed using Montreal Cognitive Assessment (MoCA) and Mini‐Mental State Examination‐7 (MMSE‐7). Participants were presented a series of colored words and asked to respond to each word for the color of the ink, including low load (congruent trials, when color matches the word) and high load (incongruent trials, when color does not match the word). Comparisons between two groups include: alpha desynchronization and alpha spectral entropy (SE), as well as the relationships of alpha desynchronization, HR after Stroop testing, and hippocampal and amygdala volumes (1.5T MRI, demographically balanced subgroups). Result No alpha differences were found during the resting state. Occipital alpha desynchronization of CH‐PATs was more negative than in that of CH‐NATs (p=0.024) during the congruent trials (Figure 1), indicating hyperactivity during low load. CH‐PATs had higher alpha SE during congruent trials (p=0.042 frontal, p=0.039 occipital), and lower frontal SE change from congruent to incongruent trials (p=0.012) (Figure 2), supporting reduced functional reserve. Alpha desynchronization positively correlated with HR in CH‐PATs but not CH‐NATs; alpha desynchronization correlated with hippocampal or amygdala differently between CH‐NATs and CH‐PATs (Figure 4). Multiple spectral frequencies revealed correlations in MMSE‐7 & MoCA that differed between CH‐NATs and CH‐PATs. Conclusion These results suggest that hyper‐excitability during low load challenge and limited brain reserve is manifest with increasing interference load in pre‐symptomatic AD. We also find brain‐heart coupling is altered in pre‐symptomatic AD.

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Time–frequency analysis of the event-related potentials associated with the Stroop test

Cited by 57 publications

References 68 publications

Event-Related Potentials and the Stroop Effect

Event-Related Potentials and the Stroop Effect

Objective Extraction of Evoked Event-related Oscillations from Time-frequency Representation of Event-related Potentials

A study of alpha desynchronization, heart rate, and MRI during stroop testing unmasks pre‐symptomatic Alzheimer’s disease

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