Oscillatory brain responses to own names uttered by unfamiliar and familiar voices

AbstractAmong auditory stimuli, the own name is one of the most powerful and it is able to automatically capture attention and elicit a robust electrophysiological response. The subject’s own name (SON) is preferentially processed in the right hemisphere, mainly because of its self-relevance and emotional content, together with other personally relevant information such as the voice of a familiar person. Whether emotional and self-relevant information are able to attract attention and can be, in future, introduced in clinical studies remains unclear. In the present study we used EEG and asked participants to count a target name (active condition) or to just listen to the SON or other unfamiliar names uttered by a familiar or unfamiliar voice (passive condition). Data reveals that the target name elicits a strong alpha event related desynchronization with respect to non-target names and triggers in addition a left lateralized theta synchronization as well as delta synchronization.In the passive condition alpha desynchronization was observed for familiar voice and SON stimuli in the right hemisphere.Altogether we speculate that participants engage additional attentional resources when counting a target name or when listening to personally relevant stimuli which is indexed by alpha desynchronization whereas left lateralized theta synchronization may be related to verbal working memory load. After validating the present protocol in healthy volunteers it is suggested to move one step further and apply the protocol to patients with disorders of consciousness in which the degree of residual cognitive processing and self-awareness is still insufficiently understood

Better than sham? A double-blind placebo-controlled neurofeedback study in primary insomnia

Neurofeedback training builds upon the simple concept of instrumental conditioning, i.e. behaviour that is rewarded is more likely to reoccur, an effect Thorndike referred to as the ‘law of effect. In the case of neurofeedback, information about specific electroencephalographic activity is fed back to the participant who is rewarded whenever the desired electroencephalography pattern is generated. If some kind of hyperarousal needs to be addressed, the neurofeedback community considers sensorimotor rhythm neurofeedback as the gold standard. Earlier treatment approaches using sensorimotor-rhythm neurofeedback indicated that training to increase 1215 Hz sensorimotor rhythm over the sensorimotor cortex during wakefulness could reduce attention-deficit/hyperactivity disorder and epilepsy symptoms and even improve sleep quality by enhancing sleep spindle activity (lying in the same frequency range). In the present study we sought to critically test whether earlier findings on the positive effect of sensorimotor rhythm neurofeedback on sleep quality and memory could also be replicated in a double-blind placebo-controlled study on 25 patients with insomnia. Patients spent nine polysomnography nights and 12 sessions of neurofeedback and 12 sessions of placebo-feedback training (sham) in our laboratory. Crucially, we found both neurofeedback and placebo feedback to be equally effective as reflected in subjective measures of sleep complaints suggesting that the observed improvements were due to unspecific factors such as experiencing trust and receiving care and empathy from experimenters. In addition, these improvements were not reflected in objective electroencephalographic-derived measures of sleep quality. Furthermore, objective electroencephalographic measures that potentially reflected mechanisms underlying the efficacy of neurofeedback such as spectral electroencephalographic measures and sleep spindle parameters remained unchanged following 12 training sessions. A stratification into ‘true insomnia patients and ‘insomnia misperceivers (subjective, but no objective sleep problems) did not alter the results. Based on this comprehensive and well-controlled study, we conclude that for the treatment of primary insomnia, neurofeedback does not have a specific efficacy beyond unspecific placebo effects. Importantly, we do not find an advantage of neurofeedback over placebo feedback, therefore it cannot be recommended as an alternative to cognitive behavioural therapy for insomnia, the current (non-pharmacological) standard-of-care treatment. In addition, our study may foster a critical discussion that generally questions the effectiveness of neurofeedback, and emphasizes the importance of demonstrating neurofeedback efficacy in other study samples and disorders using truly placebo and double-blind controlled trials.(VLID)192045

Scientific Reports / Night and day variations of sleep in patients with disorders of consciousness

Brain injuries substantially change the entire landscape of oscillatory dynamics and render detection of typical sleep patterns difficult. Yet, sleep is characterized not only by specific EEG waveforms, but also by its circadian organization. In the present study we investigated whether brain dynamics of patients with disorders of consciousness systematically change between day and night. We recorded 24h EEG at the bedside of 18 patients diagnosed to be vigilant but unaware (Unresponsive Wakefulness Syndrome) and 17 patients revealing signs of fluctuating consciousness (Minimally Conscious State). The day-to-night changes in (i) spectral power, (ii) sleep-specific oscillatory patterns and (iii) signal complexity were analyzed and compared to 26 healthy control subjects. Surprisingly, the prevalence of sleep spindles and slow waves did not systematically vary between day and night in patients, whereas day-night changes in EEG power spectra and signal complexity were revealed in minimally conscious but not unaware patients.(VLID)192043

Clinical Neurophysiology / Sleep and circadian rhythms in severely braininjured patients A comment

FWF Y777-B24(VLID)268592

Sleep-specific processing of auditory stimuli is reflected by alpha and sigma oscillations

Recent research revealed a surprisingly large range of cognitive operations to be preserved during sleep in humans. The new challenge is therefore to understand functions and mechanisms of processes, which so far have been mainly investigated in awake subjects. The current study focuses on dynamic changes of brain oscillations and connectivity patterns in response to environmental stimulation during non-REM sleep. Our results indicate that aurally presented names were processed and neuronally differentiated across the wake-sleep spectrum. Simultaneously recorded EEG and MEG signals revealed two distinct clusters of oscillatory power increase in response to the stimuli: (1) vigilance state-independent θ synchronization occurring immediately after stimulus onset, followed by (2) sleep-specific α/σ synchronization peaking after stimulus offset. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep, and work toward a unified theory of brain rhythms and their functions during sleep. SIGNIFICANCE STATEMENT Previous research has revealed (residual) capacity of the sleeping human brain to interact with the environment. How sensory processing is realized by the neural assemblies in different stages of sleep is however unclear. To tackle this question, we examined simultaneously recorded MEG and EEG data. We discuss the possible role of θ, α, and σ oscillations during non-REM sleep. In contrast to versatile θ band response that reflected early stimulus processing step, succeeding α and σ band activity was sensitive to the saliency of the incoming information, and contingent on the sleep stage. Our findings suggest that the specific reorganization of mechanisms involved in later stages of sensory processing takes place upon falling asleep

On the development of sleep states in the first weeks of life.

Human newborns spend up to 18 hours sleeping. The organization of their sleep differs immensely from adult sleep, and its quick maturation and fundamental changes correspond to the rapid cortical development at this age. Manual sleep classification is specifically challenging in this population given major body movements and frequent shifts between vigilance states; in addition various staging criteria co-exist. In the present study we utilized a machine learning approach and investigated how EEG complexity and sleep stages evolve during the very first weeks of life. We analyzed 42 full-term infants which were recorded twice (at week two and five after birth) with full polysomnography. For sleep classification EEG signal complexity was estimated using multi-scale permutation entropy and fed into a machine learning classifier. Interestingly the baby's brain signal complexity (and spectral power) revealed developmental changes in sleep in the first 5 weeks of life, and were restricted to NREM ("quiet") and REM ("active sleep") states with little to no changes in state wake. Data demonstrate that our classifier performs well over chance (i.e., >33% for 3-class classification) and reaches almost human scoring accuracy (60% at week-2, 73% at week-5). Altogether, these results demonstrate that characteristics of newborn sleep develop rapidly in the first weeks of life and can be efficiently identified by means of machine learning techniques

NeuroImage / Standing sentinel during human sleep : continued evaluation of environmental stimuli in the absence of consciousnes

While it is a well-established finding that subjects' own names (SON) and familiar voices are salient during wakefulness, we here investigated processing of environmental stimuli during sleep including deep N3 and REM sleep. Besides the effects of sleep depth we investigated how sleep-specific EEG patterns (i.e. sleep spindles and slow oscillations [SOs]) relate to stimulus processing. Using 256-channel EEG we studied processing of auditory stimuli by means of event-related oscillatory responses (de-/synchronisation, ERD/ERS) and potentials (ERPs) in N=17 healthy sleepers. We varied stimulus salience by manipulating subjective (SON vs. unfamiliar name) and paralinguistic emotional relevance (familiar vs. unfamiliar voice, FV/UFV). Results reveal that evaluation of voice familiarity continues during all NREM sleep stages and even REM sleep suggesting a ‘sentinel processing mode of the human brain in the absence of wake-like consciousness. Especially UFV stimuli elicit larger responses in a 115Hz range suggesting they continue being salient. Beyond this, we find that sleep spindles and the negative slope of SOs attenuate information processing. However, unlike previously suggested they do not uniformly inhibit information processing, but inhibition seems to be scaled to stimulus salience.(VLID)266793

Sleep Spindles & Cortical Up States / Individual baseline memory performance and its significance for sleep-dependent memory consolidation

Today, there is little doubt concerning the significance of sleep for memory consolidation. Some studies have suggested, however, that overnight memory consolidation as well as their underpinning neural mechanisms might be modulated by general cognitive abilities. In this paper, we used a more specific trait measure of declarative word-pair encoding efficiency, namely “baseline memory performance (BMP).” We explored its relation to consolidation and stabilization of declarative memories overnight as well as its relationship to sleep mechanisms. We included healthy subjects and insomnia patients from two studies with slightly differing demands on declarative memory. In the first study, an insomnia sample (N=21) performed a declarative word-pair association task with pre- and post-sleep retrieval sessions and recorded 8 hr of nocturnal sleep following learning. In the second study, insomnia (N=24) as well as sex-and-age-matched control (N=29) subjects underwent a similar task but with an additional interference and time delay manipulation. Based on their encoding efficiency in the evening, all three study samples were split into good (BMP+) and moderate (BMP) learners. Although not each subsample reached statistical significance, we observed across all three samples a pattern of only BMP forgetting overnight and BMP+ showing enhanced activity and density of sleep spindles. Our findings suggest that independent of the exact study design and subjective sleep complaint exclusively participants with high BMP seem to be able to eliminate forgetting over sleep which may be related to stronger “offline” replay.(VLID)192048

The Voice of Anger: Oscillatory EEG Responses to Emotional Prosody

<div><p>Emotionally relevant stimuli and in particular anger are, due to their evolutionary relevance, often processed automatically and able to modulate attention independent of conscious access. Here, we tested whether attention allocation is enhanced when auditory stimuli are uttered by an angry voice. We recorded EEG and presented healthy individuals with a passive condition where unfamiliar names as well as the subject’s own name were spoken both with an angry and neutral prosody. The active condition instead, required participants to actively count one of the presented (angry) names. Results revealed that in the passive condition the angry prosody only elicited slightly stronger delta synchronization as compared to a neutral voice. In the active condition the attended (angry) target was related to enhanced delta/theta synchronization as well as alpha desynchronization suggesting enhanced allocation of attention and utilization of working memory resources. Altogether, the current results are in line with previous findings and highlight that attention orientation can be systematically related to specific oscillatory brain responses. Potential applications include assessment of non-communicative clinical groups such as post-comatose patients.</p></div