Topographic mapping of electroencephalography coherence in hypnagogic state

Dynamic network interactions among distinct brain rhythms as a hallmark of physiologic state and function

Brain rhythms are associated with a range of physiologic states, and thus, studies have traditionally focused on neuronal origin, temporal dynamics and fundamental role of individual brain rhythms, and more recently on specific pair-wise interactions. Here, we aim to understand integrated physiologic function as an emergent phenomenon of dynamic network interactions among brain rhythms. We hypothesize that brain rhythms continuously coordinate their activations to facilitate physiologic states and functions. We analyze healthy subjects during sleep, and we demonstrate the presence of stable interaction patterns among brain rhythms. Probing transient modulations in brain wave activation, we discover three classes of interaction patterns that form an ensemble representative for each sleep stage, indicating an association of each state with a specific network of brain-rhythm communications. The observations are universal across subjects and identify networks of brain-rhythm interactions as a hallmark of physiologic state and function, providing new insights on neurophysiological regulation with broad clinical implications.

Transient Topographical Dynamics of the Electroencephalogram Predict Brain Connectivity and Behavioural Responsiveness During Drowsiness

As we fall sleep, our brain traverses a series of gradual changes at physiological, behavioural and cognitive levels, which are not yet fully understood. The loss of responsiveness is a critical event in the transition from wakefulness to sleep. Here we seek to understand the electrophysiological signatures that reflect the loss of capacity to respond to external stimuli during drowsiness using two complementary methods: spectral connectivity and EEG microstates. Furthermore, we integrate these two methods for the first time by investigating the connectivity patterns captured during individual microstate lifetimes. While participants performed an auditory semantic classification task, we allowed them to become drowsy and unresponsive. As they stopped responding to the stimuli, we report the breakdown of alpha networks and the emergence of theta connectivity. Further, we show that the temporal dynamics of all canonical EEG microstates slow down during unresponsiveness. We identify a specific microstate (D) whose occurrence and duration are prominently increased during this period. Employing machine learning, we show that the temporal properties of microstate D, particularly its prolonged duration, predicts the response likelihood to individual stimuli. Finally, we find a novel relationship between microstates and brain networks as we show that microstate D uniquely indexes significantly stronger theta connectivity during unresponsiveness. Our findings demonstrate that the transition to unconsciousness is not linear, but rather consists of an interplay between transient brain networks reflecting different degrees of sleep depth.

Microdream neurophenomenology

Nightly transitions into sleep are usually uneventful and transpire in the blink of an eye. But in the laboratory these transitions afford a unique view of how experience is transformed from the perceptually grounded consciousness of wakefulness to the hallucinatory simulations of dreaming. The present review considers imagery in the sleep-onset transition-"microdreams" in particular-as an alternative object of study to dreaming as traditionally studied in the sleep lab. A focus on microdream phenomenology has thus far proven fruitful in preliminary efforts to (i) develop a classification for dreaming's core phenomenology (the "oneiragogic spectrum"), (ii) establish a structure for assessing dreaming's multiple memory inputs ("multi-temporal memory sources"), (iii) further Silberer's project for classifying sleep-onset images in relation to waking cognition by revealing two new imagery types ("autosensory imagery," "exosensory imagery"), and (iv) embed a potential understanding of microdreaming processes in a larger explanatory framework ("multisensory integration approach"). Such efforts may help resolve outstanding questions about dream neurophysiology and dreaming's role in memory consolidation during sleep but may also advance discovery in the neuroscience of consciousness more broadly.

Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency

Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance for predicting sleep-onset latency using multi-level mixed models. Multiple EEG recordings were obtained from healthy male participants (N = 13) during a series of 5 min eyes-closed resting-state trials (in total, n = 223) followed by a period-varying in length up to 30 min-that either allowed subjects to transition into sleep ("sleep trials," n sleep = 144) or was ended while they were still awake ("wake trials," n wake = 79). After both eyes-closed rest, sleep and wake trials, subjective experience was assessed using the Amsterdam Resting-State Questionnaire (ARSQ). Our data revealed multiple associations between eyes-closed rest alpha and theta oscillations and ARSQ-dimensions Discontinuity of Mind, Self, Theory of Mind, Planning, and Sleepiness. The sleep trials showed that the transition toward the first sleep stage exclusively affected subjective experiences related to Theory of Mind, Planning, and Sleepiness. Importantly, sleep-onset latency was negatively associated both with eyes-closed rest ratings on the ARSQ dimension of Sleepiness and with the long-range temporal correlations of parietal theta oscillations derived by detrended fluctuation analysis (DFA). These results could be relevant to the development of personalized tools that help evaluate the success of falling asleep based on measures of resting-state cognition and EEG biomarkers.

Spatiotemporal variations of alpha and sigma band EEG in the waking-sleeping transition period

The aim of this study is to evaluate the spatiotemporal variation of alpha and sigma band EEGs during the waking-sleeping transition or hypnagogic period. Power and coherence from 7 EEG channels (Fp1, F7, Fz, C3, Pz, T5, O1) were studied using EEG records of the period of 5 min. before the onset of Stage 1 to 24 min. after the onset of Stage 1. The EEG spectra were computed for 4 frequency bands (alpha 1: 8.0-9.0 Hz, alpha 2: 9.5-11.0 Hz, alpha 3: 11.5-12.5 Hz, and sigma: 13.0-15.0 Hz). The power of alpha 1 and 2 bands initially started to decrease before the onset of Stage 1. Principal component analysis of the coherence yielded Generalized and Localized Components in each band. The Generalized Component was widespread across scalp areas, while the Localized Component was a restricted local area. The Generalized Components of alpha 1 and 2 bands reached stable levels of NREM sleep about 1 min. after the onset of Stage 1. The component of sigma band reached a stable level of NREM sleep about 0.6 min. before the onset of Stage 2, while the component of alpha 3 band reached a stable level of NREM sleep about 3.4 min. after the onset of Stage 2. These results suggest that the alpha-sigma band EEG structures during the waking-sleeping transition period may not be uniform across EEG bands and that the hypnagogic EEG changes may start before the onset of Stage 1 and continue for several minutes after the onset of Stage 2.

Source distribution of neuromagnetic slow waves and MEG-delta activity in schizophrenic patients

BACKGROUND

Schizophrenic patients exhibit more activity in the electroencephalographic delta and theta frequency range than do control subjects. Using magnetic source imaging (MSI) our study aimed to explore this phenomenon in the magnetoencephalogram (MEG), the distribution of its sources, and associations between symptom profiles and sources of low-frequency activity in the brain.

METHODS

Whole-head MEG recordings were obtained from 28 schizophrenic patients and 20 healthy control subjects during a resting condition. The generators of the focal magnetic slow waves were located employing a single moving dipole model. Distributed or multiple delta and theta sources were captured by the minimum norm estimate.

RESULTS

Both localization procedures showed slow wave activity to be enhanced in schizophrenic patients compared with control subjects. Focal slow wave activity differed most between groups in frontotemporal and in posterior regions. Slow wave activity was associated with symptom characteristics in that positive symptoms varied with frontal delta and theta activity.

CONCLUSIONS

Results indicate that activity in low-frequency bands in schizophrenic patients exceeds the activity of control subjects in distinct areas, and that this focal clustering of neuromagnetic slow waves may be related to psychopathologic characteristics.

Estimation of generator sources of human sleep spindles by dipole tracing method

Equivalent dipole sources of two types of human sleep spindles (14 and 12 Hz) were investigated on five normal subjects. The present study showed that a sleep spindle can be represented by a single equivalent dipole. For both 14 and 12 Hz sleep spindles, the equivalent dipole sources were estimated near the thalamus. The orientation of the equivalent dipole of a 14 Hz sleep spindle was in the centro-parietal direction, while that of a 12 Hz sleep spindle was in the frontal direction. These results suggest that both types of sleep spindle activities are generated in the thalamus, and cortical de-arousal plays a modificatory role on their different topographical distributions.

Disturbed memory and amnesia related to intensive care

Patients, when admitted to an intensive care unit (ICU), have one thing in common: their illness is life-threatening. Patients may remain on ICU in a critical condition, needing support with their breathing, circulation, and/or kidneys for varying lengths of time, from days to weeks. During that time the patients will receive sedative and analgesic drugs to ensure compliance with artificial ventilation. Patients recovering from critical illness frequently have little or no recall of their period in ICU, or remember nightmare, hallucinations, or paranoid delusions. The nature, extent and reason for these difficulties, have been under-reported and consequently our purpose was to conduct a review of memory problems experienced by ICU patients. A systematic literature review of computer databases (Medline, PsycLit, and CINAHL) identified 25 relevant papers. In addition, other relevant articles were obtained, citation lists and associated articles retrieved. Due to lack of research on processes underlying memory problems in ICU patients all articles that introduced an insight into possible mechanisms were included in the review. There seem to be two possible processes contributing to memory problems in ICU patients. First the illness and treatment may have a general dampening effect on memory. Delirium and sleep disturbance are both common in ICU patients. Delirium can result in a profound amnesia for the period of confusion. Sleep deprivation exacerbates the confusional state. Slow wave sleep is important for the consolidation of episodic memories. Treatment administered to patients in ICU can have effects on memory. Opiates, benzodiazepines, sedative drugs such as propofol, adrenaline, and corticosteroids can all influence memory. In addition, the withdrawal of drugs, such as benzodiazepines, can cause profound withdrawal reactions, which may contribute to delirium. Second, we hypothesise that there is a process that affects memory negatively for external events but enhances memory for internal events. The physical constraints and social isolation experienced by ICU patients and the life-threatening nature of the illness may increase the experience of hypnagogic hallucinations. Attentional shift during hypnagogic images from external stimuli to internally generated images would explain why ICU patients have such poor recall of external ICU events, but can clearly remember hallucinations and nightmares. Patients describe these memories as being very vivid and this is explored in terms of flashbulb memory formation. The absence of memories for real events on ICU can result in ICU patients remembering paranoid delusions of staff trying to kill them, with little information to reject these vivid memories as unreal. This has implications for patients' future psychological health.