Thinking activates EMG in scalp electrical recordings

Abstract-This study aims to characterize the EEG correlates of exploratory behavior. Decision making in an uncertain environment raises a conflict between two opposing needs: gathering information about the environment and exploiting this knowledge in order to optimize the decision. Exploratory behavior has already been studied using fMRI. Based on a usual paradigm in reinforcement learning, this study has shown bilateral activation in the frontal and parietal cortex. To our knowledge, no previous study has been done on it using EEG.The study of the exploratory behavior using EEG signals raises two difficulties. First, the labels of trial as exploitation or exploration cannot be directly derived from the subject action. In order to access this information, a model of how the subject makes his decision must be built. The exploration related information can be then derived from it. Second, because of the complexity of the task, its EEG correlates are not necessarily time locked with the action. So the EEG processing methods used should be designed in order to handle signals that shift in time across trials.Using the same experimental protocol as the fMRI study, results show that the bilateral frontal and parietal areas are also the most discriminant. This strongly suggests that the EEG signal also conveys information about the exploratory behavior.

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“…It has been argued that EEG signals above 20 Hz are highly affected by EMG artifacts [18], [19]. However, distant EMG activity (i.e.…”

Section: Discussionmentioning

confidence: 99%

Characterizing the EEG Correlates of Exploratory Behavior

Bourdaud

Chavarriaga

Galán

et al. 2008

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…Muscle or electromyogenic (EMG) artifact poses a serious risk to the inferential validity of any EEG investigation in the frequency-domain owing to its high amplitude, Moreover, cognitive task performance often activates EMG in scalp electrical recordings making it difficult to differentiate EEG from EMG signals in the theta, beta and gamma ranges (Whitham, et al, 2008). Generally, EMG has a broad frequency distribution from 0 to >200 Hz and spectra that often have peaks in the beta frequency range that resemble EEG beta peaks.…”

Section: Electromyogenic Influencesmentioning

confidence: 99%

Interpreting EEG alpha activity

Bazanova

Вернон

2014

Neuroscience & Biobehavioral Reviews

415

290

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Exploring EEG alpha oscillations has generated considerable interest, in particular with regards to the role they play in cognitive, psychomotor, psycho-emotional and physiological aspects of human life. However, there is no clearly agreed upon definition of what constitutes 'alpha activity' or which of the many indices should be used to characterize it.To address these issues this review attempts to delineate EEG alpha-activity, its physical, molecular and morphological nature, and examine the following indices: (1) the individual alpha peak frequency; (2) activation magnitude, as measured by alpha amplitude suppression across the individual alpha bandwidth in response to eyes opening, and (3) alpha "auto-rhythmicity" indices: which include intra-spindle amplitude variability, spindle length and steepness.Throughout, the article offers a number of suggestions regarding the mechanism(s) of alpha activity related to inter and intra-individual variability. In addition, it provides some insights into the various psychophysiological indices of alpha activity and highlights their role in optimal functioning and behavior.Key words: individual alpha peak frequency, individual alpha bandwidth, alpha amplitude suppression, spindle-form segments length, intra-spindle amplitude variability Highlights 1. Alpha indices are amplitude, peak frequency, band width and spindle structure 2. Alpha peak frequency could be an endophenotypic marker 3. Alpha band width and amplitude suppression reflect activation 4. The spindle-form, segment length and amplitude reflect a neuronal ensemble property 5. Alpha activity is manifested depending on the individual alpha peak frequency 2

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“…Transcranial magnetic stimulation-evoked EEG responses may be contaminated by muscular activity, indirect cranial reflexes and somatosensory evoked potentials, [112][113][114] producing artifacts in the recordings.…”

Section: Limitationsmentioning

confidence: 99%