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\"Examines the benefits of and the techniques for using neurofeedback to combat many childhood disorders, such as autism, ADHD, depression, and aggression\"--Provided by publisher.

Automated preprocessing methods are critically needed to process the large publicly-available EEG databases, but the optimal approach remains unknown because we lack data quality metrics to compare them. Here, we designed a simple yet robust EEG data quality metric assessing the percentage of significant channels between two experimental conditions within a 100 ms post-stimulus time range. Because of volume conduction in EEG, given no noise, most brain-evoked related potentials (ERP) should be visible on every single channel. Using three publicly available collections of EEG data, we showed that, with the exceptions of high-pass filtering and bad channel interpolation, automated data corrections had no effect on or significantly decreased the percentage of significant channels. Referencing and advanced baseline removal methods were significantly detrimental to performance. Rejecting bad data segments or trials could not compensate for the loss in statistical power. Automated Independent Component Analysis rejection of eyes and muscles failed to increase performance reliably. We compared optimized pipelines for preprocessing EEG data maximizing ERP significance using the leading open-source EEG software: EEGLAB, FieldTrip, MNE, and Brainstorm. Only one pipeline performed significantly better than high-pass filtering the data.

The brain activity of multiple subjects has been shown to synchronize during salient moments of natural stimuli, suggesting that correlation of neural responses indexes a brain state operationally termed ‘engagement’. While past electroencephalography (EEG) studies have considered both auditory and visual stimuli, the extent to which these results generalize to music—a temporally structured stimulus for which the brain has evolved specialized circuitry—is less understood. Here we investigated neural correlation during natural music listening by recording EEG responses from N=48 adult listeners as they heard real-world musical works, some of which were temporally disrupted through shuffling of short-term segments (measures), reversal, or randomization of phase spectra. We measured correlation between multiple neural responses (inter-subject correlation) and between neural responses and stimulus envelope fluctuations (stimulus-response correlation) in the time and frequency domains. Stimuli retaining basic musical features, such as rhythm and melody, elicited significantly higher behavioral ratings and neural correlation than did phase-scrambled controls. However, while unedited songs were self-reported as most pleasant, time-domain correlations were highest during measure-shuffled versions. Frequency-domain measures of correlation (coherence) peaked at frequencies related to the musical beat, although the magnitudes of these spectral peaks did not explain the observed temporal correlations. Our findings show that natural music evokes significant inter-subject and stimulus-response correlations, and suggest that the neural correlates of musical ‘engagement’ may be distinct from those of enjoyment. [Display omitted] •We recorded EEG from 48 adults as they heard intact and scrambled natural music.•Inter-subject and stimulus-response EEG correlation and coherence were computed.•Neural correlation was significant for all stimuli retaining musical features.•Time-domain correlation was highest for music shuffled in short time segments.•Coherence peaks implicated frequencies related to metrical pulse.

Transcranial alternating current stimulation (tACS) modulates endogenous neural oscillations in healthy human participants by the application of a low-amplitude electrical current with a periodic stimulation waveform. Yet, it is unclear if tACS can modulate and restore neural oscillations that are reduced in patients with psychiatric illnesses such as schizophrenia. Here, we asked if tACS modulates network oscillations in schizophrenia. We performed a randomized, double-blind, sham-controlled clinical trial to contrast tACS with transcranial direct current stimulation (tDCS) and sham stimulation in 22 schizophrenia patients with auditory hallucinations. We used high-density electroencephalography to investigate if a five-day, twice-daily 10Hz-tACS protocol enhances alpha oscillations and modulates network dynamics that are reduced in schizophrenia. We found that 10Hz-tACS enhanced alpha oscillations and modulated functional connectivity in the alpha frequency band. In addition, 10Hz-tACS enhanced the 40Hz auditory steady-state response (ASSR), which is reduced in patients with schizophrenia. Importantly, clinical improvement of auditory hallucinations correlated with enhancement of alpha oscillations and the 40Hz-ASSR. Together, our findings suggest that tACS has potential as a network-level approach to modulate reduced neural oscillations related to clinical symptoms in patients with schizophrenia.

Environmental psychologists have established multiple psychological benefits of interaction with natural, compared to urban, environments on emotion, cognition, and attention. Yet, given the increasing urbanisation worldwide, it is equally important to understand how differences within different urban environments influence human psychological experience. We developed a laboratory experiment to examine the psychophysiological effects of the physical (outdoor or indoor) and social (crowded versus uncrowded) environment in healthy young adults, and to validate the use of mobile electroencephalography (EEG) and electrodermal activity (EDA) measurements during active walking. Participants (N = 42) were randomly assigned into a walking or a standing group, and watched six 1-min walk-through videos of green, urban indoor and urban outdoor environments, depicting high or low levels of social density. Self-reported emotional states show that green spaces is perceived as more calm and positive, and reduce attentional demands. Further, the outdoor urban space is perceived more positively than the indoor environment. These findings are consistent with earlier studies on the psychological benefits of nature and confirm the effectiveness of our paradigm and stimuli. In addition, we hypothesised that even short-term exposure to crowded scenes would have negative psychological effects. We found that crowded scenes evoked higher self-reported arousal, more negative self-reported valence, and recruited more cognitive and attentional resources. However, in walking participants, they evoked higher frontal alpha asymmetry, suggesting more positive affective responses. Furthermore, we found that using recent signal-processing methods, the EEG data produced a comparable signal-to-noise ratio between walking and standing, and that despite differences between walking and standing, skin-conductance also captured effectively psychophysiological responses to stimuli. These results suggest that emotional responses to visually presented stimuli can be measured effectively using mobile EEG and EDA in ambulatory settings, and that there is complex interaction between active walking, the social density of urban spaces, and direct and indirect affective responses to such environments.

Both invasive and non-invasive electroencephalographic (EEG) recordings from the human brain have an increasingly important role in neuroscience research and are candidate modalities for medical brain–machine interfacing. It is often assumed that the major artifacts that compromise non-invasive EEG, such as caused by blinks and eye movement, are absent in invasive EEG recordings. Quantitative investigations on the signal quality of simultaneously recorded invasive and non-invasive EEG in terms of artifact contamination are, however, lacking. Here we compared blink related artifacts in non-invasive and invasive EEG, simultaneously recorded from prefrontal and motor cortical regions using an approach suitable for detection of small artifact contamination. As expected, we find blinks to cause pronounced artifacts in non-invasive EEG both above prefrontal and motor cortical regions. Unexpectedly, significant blink related artifacts were also found in the invasive recordings, in particular in the prefrontal region. Computing a ratio of artifact amplitude to the amplitude of ongoing brain activity, we find that the signal quality of invasive EEG is 20 to above 100 times better than that of simultaneously obtained non-invasive EEG. Thus, while our findings indicate that ocular artifacts do exist in invasive recordings, they also highlight the much better signal quality of invasive compared to non-invasive EEG data. Our findings suggest that blinks should be taken into account in the experimental design of ECoG studies, particularly when event related potentials in fronto-anterior brain regions are analyzed. Moreover, our results encourage the application of techniques for reducing ocular artifacts to further optimize the signal quality of invasive EEG.

•We propose a method to handle data corruption in EEG recorded with very few channels.•An attention-based neural network reweighs EEG channels according to task relevance.•We validate the method on clinical EEG and at-home mobile EEG with strong corruption.•Our method outperforms other denoising strategies under strong channel corruption. Building machine learning models using EEG recorded outside of the laboratory setting requires methods robust to noisy data and randomly missing channels. This need is particularly great when working with sparse EEG montages (1–6 channels), often encountered in consumer-grade or mobile EEG devices. Neither classical machine learning models nor deep neural networks trained end-to-end on EEG are typically designed or tested for robustness to corruption, and especially to randomly missing channels. While some studies have proposed strategies for using data with missing channels, these approaches are not practical when sparse montages are used and computing power is limited (e.g., wearables, cell phones). To tackle this problem, we propose dynamic spatial filtering (DSF), a multi-head attention module that can be plugged in before the first layer of a neural network to handle missing EEG channels by learning to focus on good channels and to ignore bad ones. We tested DSF on public EEG data encompassing ∼4000 recordings with simulated channel corruption and on a private dataset of ∼100 at-home recordings of mobile EEG with natural corruption. Our proposed approach achieves the same performance as baseline models when no noise is applied, but outperforms baselines by as much as 29.4% accuracy when significant channel corruption is present. Moreover, DSF outputs are interpretable, making it possible to monitor the effective channel importance in real-time. This approach has the potential to enable the analysis of EEG in challenging settings where channel corruption hampers the reading of brain signals.

Rationale During the last years, considerable progress has been made toward understanding the neuronal basis of consciousness by using sophisticated behavioral tasks, brain-imaging techniques, and various psychoactive drugs. Nevertheless, the neuronal mechanisms underlying some of the most intriguing states of consciousness, including spiritual experiences, remain unknown. Objectives To elucidate state of consciousness-related neuronal mechanisms, human subjects were given psilocybin, a naturally occurring serotonergic agonist and hallucinogen that has been used for centuries to induce spiritual experiences in religious and medical rituals. Methods In this double-blind, placebo-controlled study, 50 healthy human volunteers received a moderate dose of psilocybin, while high-density electroencephalogram (EEG) recordings were taken during eyes-open and eyes-closed resting states. The current source density and the lagged phase synchronization of neuronal oscillations across distributed brain regions were computed and correlated with psilocybin-induced altered states of consciousness. Results Psilocybin decreased the current source density of neuronal oscillations at 1.5–20 Hz within a neural network comprising the anterior and posterior cingulate cortices and the parahippocampal regions. Most intriguingly, the intensity levels of psilocybin-induced spiritual experience and insightfulness correlated with the lagged phase synchronization of delta oscillations (1.5–4 Hz) between the retrosplenial cortex, the parahippocampus, and the lateral orbitofrontal area. Conclusions These results provide systematic evidence for the direct association of a specific spatiotemporal neuronal mechanism with spiritual experiences and enhanced insight into life and existence. The identified mechanism may constitute a pathway for modulating mental health, as spiritual experiences can promote sustained well-being and psychological resilience.

Exercise can improve sleep by reducing sleep latency and increasing slow-wave sleep (SWS). Some studies, however, report adverse effects of exercise on sleep architecture, possibly due to a wide variety of experimental conditions used. We examined the effect of exercise on quality of sleep using standardized exercise parameters and novel analytical methods. In a cross-over intervention study we examined the effect of 60 min of vigorous exercise at 60% V ˙ O 2 max on the metabolic state, assessed by core body temperature and indirect calorimetry, and on sleep quality during subsequent sleep, assessed by self-reported quality of sleep and polysomnography. In a novel approach, envelope analysis was performed to assess SWS stability. Exercise increased energy expenditure throughout the following sleep phase. The subjective assessment of sleep quality was not improved by exercise. Polysomnography revealed a shorter rapid eye movement latency and reduced time spent in SWS. Detailed analysis of the sleep electro-encephalogram showed significantly increased delta power in SWS (N3) together with increased SWS stability in early sleep phases, based on delta wave envelope analysis. Although vigorous exercise does not lead to a subjective improvement in sleep quality, sleep function is improved on the basis of its effect on objective EEG parameters.

Patients diagnosed as vegetative have periods of wakefulness, but seem to be unaware of themselves or their environment. Although functional MRI (fMRI) studies have shown that some of these patients are consciously aware, issues of expense and accessibility preclude the use of fMRI assessment in most of these individuals. We aimed to assess bedside detection of awareness with an electroencephalography (EEG) technique in patients in the vegetative state. This study was undertaken at two European centres. We recruited patients with traumatic brain injury and non-traumatic brain injury who met the Coma Recovery Scale-Revised definition of vegetative state. We developed a novel EEG task involving motor imagery to detect command-following—a universally accepted clinical indicator of awareness—in the absence of overt behaviour. Patients completed the task in which they were required to imagine movements of their right-hand and toes to command. We analysed the command-specific EEG responses of each patient for robust evidence of appropriate, consistent, and statistically reliable markers of motor imagery, similar to those noted in healthy, conscious controls. We assessed 16 patients diagnosed in the vegetative state, and 12 healthy controls. Three (19%) of 16 patients could repeatedly and reliably generate appropriate EEG responses to two distinct commands, despite being behaviourally entirely unresponsive (classification accuracy 61–78%). We noted no significant relation between patients' clinical histories (age, time since injury, cause, and behavioural score) and their ability to follow commands. When separated according to cause, two (20%) of the five traumatic and one (9%) of the 11 non-traumatic patients were able to successfully complete this task. Despite rigorous clinical assessment, many patients in the vegetative state are misdiagnosed. The EEG method that we developed is cheap, portable, widely available, and objective. It could allow the widespread use of this bedside technique for the rediagnosis of patients who behaviourally seem to be entirely vegetative, but who might have residual cognitive function and conscious awareness. Medical Research Council, James S McDonnell Foundation, Canada Excellence Research Chairs Program, European Commission, Fonds de la Recherche Scientifique, Mind Science Foundation, Belgian French-Speaking Community Concerted Research Action, University Hospital of Liège, University of Liège.