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The authors examined the time course of affective responding associated with different affective dimensions--anxious apprehension, anxious arousal, and anhedonic depression--using an emotion-modulated startle paradigm. Participants high on 1 of these 3 dimensions and nonsymptomatic control participants viewed a series of affective pictures with acoustic startle probes presented before, during, and after the stimuli. All groups exhibited startle potentiation during unpleasant pictures and in anticipation of both pleasant and unpleasant pictures. Compared with control participants, symptomatic participants exhibited sustained potentiation following the offset of unpleasant stimuli and a lack of blink attenuation during and following pleasant stimuli. Common and unique patterns of affective responses in the 3 types of mood symptoms are discussed.
Facial expression, EEG, and self-report of subjective emotional experience were recorded while subjects individually watched both pleasant and unpleasant films. Smiling in which the muscle that orbits the eye is active in addition to the muscle that pulls the lip corners up (the Duchenne smile) was compared with other smiling in which the muscle orbiting the eye was not active. As predicted, the Duchenne smile was related to enjoyment in terms of occurring more often during the pleasant than the unpleasant films, in measures of cerebral asymmetry, and in relation to subjective reports of positive emotions, and other smiling was not.
Muscle or electromyogenic (EMG) artifact poses a serious risk to inferential validity for any electroencephalography (EEG) investigation in the frequency-domain owing to its high amplitude, broad spectrum, and sensitivity to psychological processes of interest. Even weak EMG is detectable across the scalp in frequencies as low as the alpha band. Given these hazards, there is substantial interest in developing EMG correction tools. Unfortunately, most published techniques are subjected to only modest validation attempts, rendering their utility questionable. We review recent work by our laboratory quantitatively investigating the validity of two popular EMG correction techniques, one using the general linear model (GLM), the other using temporal independent component analysis (ICA). We show that intra-individual GLM-based methods represent a sensitive and specific tool for correcting on-going or induced, but not evoked (phase-locked) or source-localized, spectral changes. Preliminary work with ICA shows that it may not represent a panacea for EMG contamination, although further scrutiny is strongly warranted. We conclude by describing emerging methodological trends in this area that are likely to have substantial benefits for basic and applied EEG research.
Although there is much evidence demonstrating muscle tension changes during mental work, there are few data concerning muscle tension patterns during effortful attention to simple sensory stimuli. In the present study, sensory attention was evoked by a pitch discrimination task at three levels of difficulty, with a digit retention task administered for comparison. Twenty-four females each performed both tasks at all levels of difficulty, while the EKG, and the corrugator supercilii, frontalis, lip, jaw, chin, and forearm area EMG were recorded. As expected, heart rate decreased significantly with increasing difficulty of the pitch task. A pattern of facial EMG responses accompanied the pitch task, which included significant increases in corrugator and frontalis, and decreases in the jaw as a function of difficulty, and time within trials. The tension pattern observed during sensory intake is discussed in terms of its relation to emotional expressions and motor theories of attention.
The development of functional neuroimaging of emotion holds the promise to enhance our understanding of the biological bases of affect and improve our knowledge of psychiatric diseases. However, up to this point, researchers have been unable to objectively, continuously and unobtrusively measure the intensity and dynamics of affect concurrently with functional magnetic resonance imaging (fMRI). This has hindered the development and generalizability of our field. Facial electromyography (EMG) is an objective, reliable, valid, sensitive, and unobtrusive measure of emotion. Here, we report the successful development of a method for simultaneously acquiring fMRI and facial EMG. The ability to simultaneously acquire brain activity and facial physiology will allow affective neuroscientists to address theoretical, psychiatric, and individual difference questions in a more rigorous and generalizable way.
Muscle electrical activity, or "electromyogenic" (EMG) artifact, poses a serious threat to the validity of electroencephalography (EEG) investigations in the frequency domain. EMG is sensitive to a variety of psychological processes and can mask genuine effects or masquerade as legitimate neurogenic effects across the scalp in frequencies at least as low as the alpha band (8-13 Hz). Although several techniques for correcting myogenic activity have been described, most are subjected to only limited validation attempts. Attempts to gauge the impact of EMG correction on intracerebral source models (source "localization" analyses) are rarer still. Accordingly, we assessed the sensitivity and specificity of one prominent correction tool, independent component analysis (ICA), on the scalp and in the source-space using high-resolution EEG. Data were collected from 17 participants while neurogenic and myogenic activity was independently varied. Several protocols for classifying and discarding components classified as myogenic and non-myogenic artifact (e.g., ocular) were systematically assessed, leading to the exclusion of one-third to as much as three-quarters of the variance in the EEG. Some, but not all, of these protocols showed adequate performance on the scalp. Indeed, performance was superior to previously validated regression-based techniques. Nevertheless, ICA-based EMG correction exhibited low validity in the intracerebral source-space, likely owing to incomplete separation of neurogenic from myogenic sources. Taken with prior work, this indicates that EMG artifact can substantially distort estimates of intracerebral spectral activity. Neither regression- nor ICA-based EMG correction techniques provide complete safeguards against such distortions. In light of these results, several practical suggestions and recommendations are made for intelligently using ICA to minimize EMG and other common artifacts.
EEG and EEG source-estimation are susceptible to electromyographic artifacts (EMG) generated by the cranial muscles. EMG can mask genuine effects or masquerade as a legitimate effect-even in low frequencies, such as alpha (8-13 Hz). Although regression-based correction has been used previously, only cursory attempts at validation exist, and the utility for source-localized data is unknown. To address this, EEG was recorded from 17 participants while neurogenic and myogenic activity were factorially varied. We assessed the sensitivity and specificity of four regression-based techniques: between-subjects, between-subjects using difference-scores, within-subjects condition-wise, and within-subject epoch-wise on the scalp and in data modeled using the LORETA algorithm. Although within-subject epoch-wise showed superior performance on the scalp, no technique succeeded in the source-space. Aside from validating the novel epoch-wise methods on the scalp, we highlight methods requiring further development.