Do specific EEG frequencies indicate different processes during mental calculation?

Harmony, Thalı́a; Fernández, Thalı́a; Silva, Juan; Bosch, J.; Valdés, P.; Fernández-Bouzas, Antonio; Galán, Lı́dice; Aubert, Eduardo Henrik; Rodriguez, Daniel

doi:10.1016/s0304-3940(99)00244-x

Cited by 119 publications

(61 citation statements)

References 14 publications

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“…The complexity analysis supports this idea and is also in accordance with imaging evidence that suggests the participation of parietal areas in addition to the prefrontal areas in mental calculation [11]. The complexity variation in the occipita-parietal channels suggests the activation of visua-verbal regions while the frontal activation has been always been linked with working memory and attention [7]. The task here being serial subtraction, the processes can be comprehended as the sequential procedure of recognizing the numerals, forming a mental picture of the mental operations before the actual processing, storage of the current data in the working memory before going on to the next subtraction.…”

Section: Resultssupporting

confidence: 85%

Complexity Quantification of Dense Array Eeg Using Sample Entropy Analysis

Ramanand¹,

Nampoori²,

Sreenivasan³

2004

J. Integr. Neurosci.

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In this paper, a time series complexity analysis of dense array electroencephalogram signals is carried out using the recently introduced Sample Entropy (SampEn) measure. This statistic quantifies the regularity in signals recorded from systems that can vary from the purely deterministic to purely stochastic realm. The present analysis is conducted with an objective of gaining insight into complexity variations related to changing brain dynamics for EEG recorded from the three cases of passive,eyes closed condition, a mental arithmetic task and the same mental task carried out after a physical exertion task. It is observed that the statistic is a robust quantifier of complexity suited for short physiological signals such as the EEG and it points to the specific brain regions that exhibit lowered complexity during the mental task state as compared to a passive, relaxed state. In the case of mental tasks carried out before and after the performance of a physical exercise, the statistic can detect the variations brought in by the intermediate fatigue inducing exercise period. This enhances its utility in detecting subtle changes in the brain state that can find wider scope for applications in EEG based brain studies.

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Section: Resultssupporting

confidence: 85%

Complexity Quantification of Dense Array Eeg Using Sample Entropy Analysis

Ramanand¹,

Nampoori²,

Sreenivasan³

2004

J. Integr. Neurosci.

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“…Previously, the d band has been correlated with attention (Harmony, 1999) and h with memory (e.g., Klimesch, 1999). Therefore, the patterns of coherence changes common to word perception are assumed to be related to basic processes, such as attention, memory and semantics in terms of meaning construction.…”

Section: Word Processingmentioning

confidence: 99%

The contribution of EEG coherence to the investigation of language

2003

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The contribution of EEG coherence analysis to the investigation of cognition and, in particular, language processing is demonstrated with examples of recent EEG studies. The concept of EEG coherence analysis is explained, and its importance emphasized in the light of recent neurobiological findings on frequency-dependent synchrony as a code of information processing between nerve cell assemblies. Furthermore, EEG coherence studies on naturally spoken and written word and sentence processing are reviewed and experimental results are presented giving new insights into the occurrence of ''transient functional language centers'' within the brain.

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“…In previous works, mental arithmetic task recognition and training systems were mainly based on EEG power spectrum density (PSD) calculation [16]- [18]. For example, in [16], decrease at lower beta band within the left parietal cortex was associated to a sign of retrieval of arithmetic facts from long term memory.…”

mentioning

confidence: 99%

“…For example, in [16], decrease at lower beta band within the left parietal cortex was associated to a sign of retrieval of arithmetic facts from long term memory. In another work [17], significant changes in alpha band and beta band were reported when the subject was doing the mental arithmetic task.…”

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confidence: 99%

Real-Time Mental Arithmetic Task Recognition From EEG Signals

Wang

Sourina

2013

IEEE Trans. Neural Syst. Rehabil. Eng.

171

102

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Abstract-Electroencephalography (EEG)-based monitoring the state of the user's brain functioning and giving her/him the visual/audio/tactile feedback is called neurofeedback technique, and it could allow the user to train the corresponding brain functions. It could provide an alternative way of treatment for some psychological disorders such as attention deficit hyperactivity disorder (ADHD), where concentration function deficit exists, autism spectrum disorder (ASD), or dyscalculia where the difficulty in learning and comprehending the arithmetic exists. In this paper, a novel method for multifractal analysis of EEG signals named generalized Higuchi fractal dimension spectrum (GHFDS) was proposed and applied in mental arithmetic task recognition from EEG signals. Other features such as power spectrum density (PSD), autoregressive model (AR), and statistical features were analyzed as well. The usage of the proposed fractal dimension spectrum of EEG signal in combination with other features improved the mental arithmetic task recognition accuracy in both multi-channel and one-channel subject-dependent algorithms up to 97.87% and 84.15% correspondingly. Based on the channel ranking, four channels were chosen which gave the accuracy up to 97.11%. Reliable real-time neurofeedback system could be implemented based on the algorithms proposed in this paper.Index Terms-Brain state, electroencephalography (EEG), fractal dimension, mental arithmetic task, neurofeedback.

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Do specific EEG frequencies indicate different processes during mental calculation?

Cited by 119 publications

References 14 publications

Complexity Quantification of Dense Array Eeg Using Sample Entropy Analysis

Complexity Quantification of Dense Array Eeg Using Sample Entropy Analysis

The contribution of EEG coherence to the investigation of language

Real-Time Mental Arithmetic Task Recognition From EEG Signals

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