Theta power as a marker for cognitive interference

Nigbur, Roland; Ivanova, Galina; Stürmer, Birgit

doi:10.1016/j.clinph.2011.03.030

Cited by 382 publications

(378 citation statements)

References 68 publications

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“…This is also supported by the suggested distinction between alpha and theta, respectively, to correlate with semantic long-term memory performance and the ability to encode new information (Klimesch, 1999), in which case theta is associated with search processes during retrieval and updates newly activated information. Alternatively, a compatibility effect has also been observed as changes in theta power synchronization (Nigbur et al, 2011). However, since all sequences were thoroughly counterbalanced across participants, with one pair presented first in some but the other pair presented first in others, this effect has been minimized.…”

Section: Theta Power Resultsmentioning

confidence: 98%

Common and differential electrophysiological mechanisms underlying semantic object memory retrieval probed by features presented in different stimulus types

Chiang

Eroh

Spence

et al. 2016

International Journal of Psychophysiology

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Section: Theta Power Resultsmentioning

confidence: 98%

Common and differential electrophysiological mechanisms underlying semantic object memory retrieval probed by features presented in different stimulus types

Chiang

Eroh

Spence

et al. 2016

International Journal of Psychophysiology

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“…Gennady et al [48] reviewed the delta band relationship with cognitive processing and have confirmed that delta is linked with the cognitive process. Similarly, the theta rhythms are the most intensively studied in the cognitive neuroscience aimed at correlating the theta rhythms with cognitive processing [49][50][51]. Particularly, theta in the frontal regions is critical for attentional and cognitive processing in ERP tasks [50].…”

Section: Eeg Low Frequencies With Cognitive Neuroscience Perspectivementioning

confidence: 99%

Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques

Amin

Malik

Ahmad

et al. 2015

Australas Phys Eng Sci Med

269

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This paper describes a discrete wavelet transform-based feature extraction scheme for the classification of EEG signals. In this scheme, the discrete wavelet transform is applied on EEG signals and the relative wavelet energy is calculated in terms of detailed coefficients and the approximation coefficients of the last decomposition level. The extracted relative wavelet energy features are passed to classifiers for the classification purpose. The EEG dataset employed for the validation of the proposed method consisted of two classes: (1) the EEG signals recorded during the complex cognitive task--Raven's advance progressive metric test and (2) the EEG signals recorded in rest condition--eyes open. The performance of four different classifiers was evaluated with four performance measures, i.e., accuracy, sensitivity, specificity and precision values. The accuracy was achieved above 98 % by the support vector machine, multi-layer perceptron and the K-nearest neighbor classifiers with approximation (A4) and detailed coefficients (D4), which represent the frequency range of 0.53-3.06 and 3.06-6.12 Hz, respectively. The findings of this study demonstrated that the proposed feature extraction approach has the potential to classify the EEG signals recorded during a complex cognitive task by achieving a high accuracy rate.

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“…A variety of tasks related to the processing of novelty or conflict in relation to action performance have shown increased theta amplitudes over central regions, around the 300-400ms time-point after stimulus presentation (Cavanagh et al, 2012b;Cohen & Donner, 2013;Harper et al, 2014;Nigbur et al, 2011Nigbur et al, , 2012Ullsperger et al, 2014). Our results indicate that theta power compared to baseline action observation was smallest when further in time from action execution (i.e.…”

Section: Theta Band Activitysupporting

confidence: 50%

“…Other theories claim that mid-frontal theta activity reflects a generic process related to performance monitoring (Cavanagh et al, 2012a;Nigbur et al, 2011Nigbur et al, , 2012Ullsperger et al, 2014).…”

Section: Neural Oscillationsmentioning

confidence: 99%

“…A wide variety of tasks can induce a strong mid-frontal negativity, roughly around the 300ms timepoint after stimulus presentation, including the mismatch negativity (MMN) reflecting unexpected sensory information, the feedback related negativity (FRN) after feedback that indicates poor performance, and the control-related negativity occuring following response inhibition or response conflict (Cavanagh et al, 2012b;Nigbur et al, 2011Nigbur et al, , 2012Folstein & van Petten, 2008). Cavanagh and colleagues (2012b) reported that tasks commonly used to elicit MMN, FRN, or control-related negativity all show an elevated theta activity over medial prefrontal regions, claiming that neural activity in the theta frequency range plays a key component in the processing of novelty, conflict, punishment and error.…”

Section: Neural Oscillationsmentioning

confidence: 99%

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Neural processes for action observation

Halász¹

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Through actions we explore the world around us, we express ourselves, achieve goals and interact with others. We are thinking about actions, planning, executing, imitating, observing, and understanding them. In other words, our life is filled with motor cognition. Yet our knowledge of the brain processes underlying these tasks is limited.Based on extensive literature we know that action observation and production share common neural mechanisms and a common neural network. Throughout the studies in this thesis, I use this connection to explore neural processes related to motor cognition.In the first chapter, I examine current theories on action observation and identify key concepts investigated in the later experiments. I review a wide range of literature from the fields of neural disorders and healthy participants tested on various tasks, such as visual illusions, motor expertise, and conscious and unconscious visual processing. Focusing on the bidirectional information flow between motor and perceptual areas, I examine how well the common coding theory, the direct matching hypothesis, and predictive coding models fit the current experimental results. I argue that, while predictive coding theories are best to explain the wide variety of results related to motor cognition, there are still important questions unanswered in the literature. There is a relative lack of studies investigating motor cognition in close-tonatural settings, and attentional modulation is often ignored. Furthermore, more research is needed to explore the spatial and temporal dynamics of how observed and executed actions present on the neural level.In the first experiment, I investigate how the brain processes actions when they are not consciously attended. I recorded brain activity related to action observation under an attentionally demanding visual task. Data indicate that even when our attention is directed away from actions both the motor and perceptual systems -as part of the action observation network-show a systematic change depending on the novelty of action properties. The results of this experiment also suggest that action related information is prioritised even when attentional resources are limited. In the second experiment, I examined how attention on specific action representations, such as kinematics, goals and agency, influences brain response during the processing of actions. The results of this experiment suggest that, even though novelty-related 3 changes are very strong throughout in the action observation network, attention can specifically modulate neural activity to enhance the processing of task-specific information.Finally, in the third experiment, I investigated how a common system can deal with the parallel processing of action execution and observation. I aimed to give a comprehensive picture of neural activity related to motor cognition, and thus analysed event-related magnetic field activity and power changes in theta, alpha and beta frequency bands. Data indicated that neural processes are sensitive to ...

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Theta power as a marker for cognitive interference

Cited by 382 publications

References 68 publications

Common and differential electrophysiological mechanisms underlying semantic object memory retrieval probed by features presented in different stimulus types

Common and differential electrophysiological mechanisms underlying semantic object memory retrieval probed by features presented in different stimulus types

Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques

Neural processes for action observation

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