No Detectable Electroencephalographic Activity After Clinical Declaration of Death Among Tibetan Buddhist Meditators in Apparent Tukdam, a Putative Postmortem Meditation State.

Recent EEG studies on the early postmortem interval that suggest the persistence of electrophysiological coherence and connectivity in the brain of animals and humans reinforce the need for further investigation of the relationship between the brain's activity and the dying process. Neuroscience is now in a position to empirically evaluate the extended process of dying and, more specifically, to investigate the possibility of brain activity following the cessation of cardiac and respiratory function. Under the direction of the Center for Healthy Minds at the University of Wisconsin-Madison, research was conducted in India on a postmortem meditative state cultivated by some Tibetan Buddhist practitioners in which decomposition is putatively delayed. For all healthy baseline (HB) and postmortem (PM) subjects presented here, we collected resting state electroencephalographic data, mismatch negativity (MMN), and auditory brainstem response (ABR). In this study, we present HB data to demonstrate the feasibility of a sparse electrode EEG configuration to capture well-defined ERP waveforms from living subjects under very challenging field conditions. While living subjects displayed well-defined MMN and ABR responses, no recognizable EEG waveforms were discernable in any of the tukdam cases.

Reduced stress and inflammatory responsiveness in experienced meditators compared to a matched healthy control group.

Psychological stress is a major contributor to symptom exacerbation across many chronic inflammatory conditions and can acutely provoke increases in inflammation in healthy individuals. With the rise in rates of inflammation-related medical conditions, evidence for behavioral approaches that reduce stress reactivity is of value. Here, we compare 31 experienced meditators, with an average of approximately 9000 lifetime hours of meditation practice (M age=51years) to an age- and sex-matched control group (n=37; M age=48years) on measures of stress- and inflammatory responsivity, and measures of psychological health. The Trier Social Stress Test (TSST) was used to induce psychological stress and a neurogenic inflammatory response was produced using topical application of capsaicin cream to forearm skin. Size of the capsaicin-induced flare response and increase in salivary cortisol and alpha amylase were used to quantify the magnitude of inflammatory and stress responses, respectively. Results show that experienced meditators have lower TSST-evoked cortisol (62.62±2.52 vs. 70.38±2.33; p<.05) and perceived stress (4.18±.41 vs. 5.56±.30; p<.01), as well as a smaller neurogenic inflammatory response (81.55±4.6 vs. 96.76±4.26; p<.05), compared to the control group. Moreover, experienced meditators reported higher levels of psychological factors associated with wellbeing and resilience. These results suggest that the long-term practice of meditation may reduce stress reactivity and could be of therapeutic benefit in chronic inflammatory conditions characterized by neurogenic inflammation.

Effects of meditation practice on spontaneous eyeblink rate.

A rapidly growing body of research suggests that meditation can change brain and cognitive functioning. Yet little is known about the neurochemical mechanisms underlying meditation-related changes in cognition. Here, we investigated the effects of meditation on spontaneous eyeblink rates (sEBR), a noninvasive peripheral correlate of striatal dopamine activity. Previous studies have shown a relationship between sEBR and cognitive functions such as mind wandering, cognitive flexibility, and attention-functions that are also affected by meditation. We therefore expected that long-term meditation practice would alter eyeblink activity. To test this, we recorded baseline sEBR and intereyeblink intervals (IEBI) in long-term meditators (LTM) and meditation-naive participants (MNP). We found that LTM not only blinked less frequently, but also showed a different eyeblink pattern than MNP. This pattern had good to high degree of consistency over three time points. Moreover, we examined the effects of an 8-week course of mindfulness-based stress reduction on sEBR and IEBI, compared to an active control group and a waitlist control group. No effect of short-term meditation practice was found. Finally, we investigated whether different types of meditation differentially alter eyeblink activity by measuring sEBR and IEBI after a full day of two kinds of meditation practices in the LTM. No effect of meditation type was found. Taken together, these findings may suggest either that individual difference in dopaminergic neurotransmission is a self-selection factor for meditation practice, or that long-term, but not short-term meditation practice induces stable changes in baseline striatal dopaminergic functioning.

LARS NETWORK FILTRATION IN THE STUDY OF EEG BRAIN CONNECTIVITY.

In a brain network, weak and non-significant edge weights between nodes signal spurious connections and are often discarded by thresholding the weights. Traditional practice of thresholding edge weights at an arbitrary value can be problematic. Network filtration provides an alternative by summarizing the changes in the network topology with respect to a broad range of thresholds. A well established network filtration approach depends on the graphical-LASSO (least absolute shrinkage and selection operator) model, where a sequence of binary networks are obtained based on non-zero sparse inverse covariance (IC) estimates of partial correlations at a range of sparsity parameters. The limitation of the graphical-LASSO network model is that it relies on the structural information rather than actual entries of the sparse IC matrices and therefore can only yield approximate dynamic topological changes in the network. In the current study, we propose a new network filtration approach based on least angle regression (LARS) that gives exact filtration values at which the filtration changes and apply it to study brain connectivity in response to emotional stimuli across different age groups via electroencephalographic (EEG) data.

Prolonged marital stress is associated with short-lived responses to positive stimuli.

Marital stress is associated with a higher incidence of psychiatric disorders, in particular major depression. One pathway through which marital stress may impact emotional health is by compromising emotion-responding processes. We examined a longitudinal sample of adults (N = 116; 59 males; 39-84 years) to verify how marital stress predicts reactivity to, and recovery from, emotional provocation. Individuals watched positive, neutral, and negative pictures while an objective measure of affective state, corrugator supercilii muscle activity, was recorded continuously. Our results indicate that marital stress is associated with short-lived responses to positive pictures, indexed by a less persistent decrease in corrugator activity after picture offset. Extending beyond the prior focus on negative emotional processes, these results suggest that social stress may impact health by influencing the time course of responding to positive events.

Temporal dynamics of emotional responding: amygdala recovery predicts emotional traits.

An individual's affective style is influenced by many things, including the manner in which an individual responds to an emotional challenge. Emotional response is composed of a number of factors, two of which are the initial reactivity to an emotional stimulus and the subsequent recovery once the stimulus terminates or ceases to be relevant. However, most neuroimaging studies examining emotional processing in humans focus on the magnitude of initial reactivity to a stimulus rather than the prolonged response. In this study, we use functional magnetic resonance imaging to study the time course of amygdala activity in healthy adults in response to presentation of negative images. We split the amygdala time course into an initial reactivity period and a recovery period beginning after the offset of the stimulus. We find that initial reactivity in the amygdala does not predict trait measures of affective style. Conversely, amygdala recovery shows predictive power such that slower amygdala recovery from negative images predicts greater trait neuroticism, in addition to lower levels of likability of a set of social stimuli (neutral faces). These data underscore the importance of taking into account temporal dynamics when studying affective processing using neuroimaging.

Validation of ICA-based myogenic artifact correction for scalp and source-localized EEG.

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.