Music therapy with adult burn patients in the intensive care unit: short-term analysis of electrophysiological signals during music-assisted relaxation.

Burn patients often face elevated pain, anxiety, and depression levels. Music therapy adds to integrative care in burn patients, but research including electrophysiological measures is limited. This study reports electrophysiological signals analysis during Music-Assisted Relaxation (MAR) with burn patients in the Intensive Care Unit (ICU).

Effect of music therapy on short-term psychological and physiological outcomes in mechanically ventilated patients: A randomized clinical pilot study.

Background: Elevated anxiety levels are common in patients on mechanical ventilation (MV) and may challenge recovery. Research suggests music-based interventions may reduce anxiety during MV. However, studies investigating specific music therapy techniques, addressing psychological and physiological well-being in patients on MV, are scarce.

Evaluating the Electroencephalographic Signal Quality of an In-Ear Wearable Device.

Wearable in-ear electroencephalographic (EEG) devices hold significant promise for advancing brain monitoring technologies into everyday applications. However, despite the current availability of several in-ear EEG devices in the market, there remains a critical need for robust validation against established clinical-grade systems. In this study, we carried out a detailed examination of the signal performance of a mobile in-ear EEG device from Naox Technologies.

BOARD-FTD-PACC: a graphical user interface for the synaptic and cross-frequency analysis derived from neural signals.

In order to understand the link between brain functional states and behavioral/cognitive processes, the information carried in neural oscillations can be retrieved using different analytic techniques. Processing these different bio-signals is a complex, time-consuming, and often non-automatized process that requires customization, due to the type of signal acquired, acquisition method implemented, and the objectives of each individual research group. To this end, a new graphical user interface (GUI), named BOARD-FTD-PACC, was developed and designed to facilitate the visualization, quantification, and analysis of neurophysiological recordings.

Response of sleep slow oscillations to acoustic stimulation is evidenced by distinctive synchronization processes.

Closed-loop acoustic stimulation (CLAS) during sleep has shown to boost slow wave (SW) amplitude and spindle power. Moreover, sleep SW have been classified based on different processes of neuronal synchronization. Thus, different types of SW events may have distinct functional roles and be differentially affected by external stimuli.

Interictal epileptiform discharges show distinct spatiotemporal and morphological patterns across wake and sleep.

Presurgical evaluation of mesial temporal and neocortical focal pharmacoresistant epilepsy patients using intracranial EEG recordings has led to the generation of extensive data on interictal epileptiform discharges, located within or remotely from seizure onset zones. In this study, we used this data to investigate how interictal epileptiform discharges are modulated and how their spatial distribution changes during wake and sleep and analysed the relationship between these discharge events and seizure onset zones. Preoperative evaluation data from 11 adult patients with focal pharmacoresistant epilepsy were extracted from the Epilepsiae database.

Auditory closed-loop stimulation on sleep slow oscillations using in-ear EEG sensors.

Acoustic stimulation synchronized to slow oscillations in scalp electroencephalograms has been shown to enhance sleep features, which makes it promising in boosting cognitive functions as well as in the treatment of some sleep disturbances. Nevertheless, scalp electrode sensors are resource intensive and poorly tolerated by sleeping patients. The aim of this study was to investigate the potential usability of in-the-ear electroencephalography to implement auditory closed-loop stimulation during sleep.

Music therapy and music medicine interventions with adult burn patients: A systematic review and meta-analysis.

Background: Pain is one of the most common and most difficult symptoms to manage in adult burn patients in the Intensive Care Unit (ICU). Insufficient or unsuccessful pain management can negatively affect physiological, psychological, and social health in burn patients, both during and after hospitalization. Music therapy and music medicine interventions have been shown to positively affect pain and mental health in this population.

The Effect of Music Therapy on Perceived Pain, Mental Health, Vital Signs, and Medication Usage of Burn Patients Hospitalized in the Intensive Care Unit: A Randomized Controlled Feasibility Study Protocol.

Burn patients experience major physiological and psychological stressors during treatment and rehabilitation, including elevated levels of pain, anxiety, stress, or depression. Music interventions inclusive of music therapy (MT) have been shown to improve such symptoms, but rigorous clinical trials investigating specific music therapy methods in adult burn patients are scarce. This is a single center Randomized Controlled Trial (RCT) protocol with two parallel arms.

Acute Effects of Two Different Species of Amyloid- on Oscillatory Activity and Synaptic Plasticity in the Commissural CA3-CA1 Circuit of the Hippocampus.

Recent evidence indicates that soluble amyloid- (A) species induce imbalances in excitatory and inhibitory transmission, resulting in neural network functional impairment and cognitive deficits during early stages of Alzheimer's disease (AD). To evaluate the effects of two soluble A species (A and A ) on commissural CA3-to-CA1 (cCA3-to-CA1) synaptic transmission and plasticity, and CA1 oscillatory activity, we used acute intrahippocampal microinjections in adult anaesthetized male Wistar rats. Soluble A microinjection increased cCA3-to-CA1 synaptic variability without significant changes in synaptic efficiency.

Automatic seizure detection based on imaged-EEG signals through fully convolutional networks.

Seizure detection is a routine process in epilepsy units requiring manual intervention of well-trained specialists. This process could be extensive, inefficient and time-consuming, especially for long term recordings. We proposed an automatic method to detect epileptic seizures using an imaged-EEG representation of brain signals.

The unique social sense of puerperium: Increased empathy and Schadenfreude in parents of newborns.

Pregnancy and puerperium are typified by marked biobehavioral changes. These changes, which are traceable in both mothers and fathers, play an important role in parenthood and may modulate social cognition abilities. However, the latter effects remain notably unexplored in parents of newborns (PNs).

Entrainment and synchronization of brain oscillations to auditory stimulations.

Oscillations of neural excitability shape sensory, motor or cognitive processes. Furthermore, a large body of research demonstrates that intrinsic oscillations are entrained by external rhythms, allowing a simple and efficient way to enhance human brain functions. As an external stimulation source, repeating acoustic stimuli have been shown to provide a possible pacing signal for modulating the electrical activity recorded by the electroencephalogram (EEG).

Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances.

In recent years, new recording technologies have advanced such that oscillations of neuronal networks can be identified from simultaneous, multisite recordings at high temporal and spatial resolutions. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings also depends on the development of new mathematical methods capable of extracting meaningful information related to time, frequency and space. In this review, we aim to bridge this gap by focusing on the new analysis tools developed for the automated detection of high-frequency oscillations (HFOs, >40Hz) in local field potentials.

Altered Oscillatory Dynamics of CA1 Parvalbumin Basket Cells during Theta-Gamma Rhythmopathies of Temporal Lobe Epilepsy.

Recent reports in human demonstrate a role of theta-gamma coupling in memory for spatial episodes and a lack of coupling in people experiencing temporal lobe epilepsy, but the mechanisms are unknown. Using multisite silicon probe recordings of epileptic rats engaged in episodic-like object recognition tasks, we sought to evaluate the role of theta-gamma coupling in the absence of epileptiform activities. Our data reveal a specific association between theta-gamma (30-60 Hz) coupling at the proximal stratum radiatum of CA1 and spatial memory deficits.

Voluntary control of intracortical oscillations for reconfiguration of network activity.

Voluntary control of oscillatory activity represents a key target in the self-regulation of brain function. Using a real-time closed-loop paradigm and simultaneous macro- and micro-electrode recordings, we studied the effects of self-induced intracortical oscillatory activity (4-8 Hz) in seven neurosurgical patients. Subjects learned to robustly and specifically induce oscillations in the target frequency, confirmed by increased oscillatory event density.

Self-induced intracerebral gamma oscillations in the human cortex.

Gamma oscillations play a pivotal role in multiple cognitive functions. They enable coordinated activity and communication of local assemblies, while abnormalities in gamma oscillations exist in different neurological and psychiatric diseases. Thus, a specific rectification of gamma synchronization could potentially compensate the deficits in pathological conditions.

RIPPLELAB: A Comprehensive Application for the Detection, Analysis and Classification of High Frequency Oscillations in Electroencephalographic Signals.

High Frequency Oscillations (HFOs) in the brain have been associated with different physiological and pathological processes. In epilepsy, HFOs might reflect a mechanism of epileptic phenomena, serving as a biomarker of epileptogenesis and epileptogenicity. Despite the valuable information provided by HFOs, their correct identification is a challenging task.

Inhibiting cholesterol degradation induces neuronal sclerosis and epileptic activity in mouse hippocampus.

Elevations in neuronal cholesterol have been associated with several degenerative diseases. An enhanced excitability and synchronous firing in surviving neurons are among the sequels of neuronal death in these diseases and also in some epileptic syndromes. Here, we attempted to increase neuronal cholesterol levels, using a short hairpin RNA to suppress expression of the enzyme cytochrome P450 family 46, subfamily A, polypeptide 1 gene (CYP46A1).

Spike avalanches in vivo suggest a driven, slightly subcritical brain state.

In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking.

Epileptic seizure predictors based on computational intelligence techniques: a comparative study with 278 patients.

The ability of computational intelligence methods to predict epileptic seizures is evaluated in long-term EEG recordings of 278 patients suffering from pharmaco-resistant partial epilepsy, also known as refractory epilepsy. This extensive study in seizure prediction considers the 278 patients from the European Epilepsy Database, collected in three epilepsy centres: Hôpital Pitié-là-Salpêtrière, Paris, France; Universitätsklinikum Freiburg, Germany; Centro Hospitalar e Universitário de Coimbra, Portugal. For a considerable number of patients it was possible to find a patient specific predictor with an acceptable performance, as for example predictors that anticipate at least half of the seizures with a rate of false alarms of no more than 1 in 6 h (0.

Neuronal avalanches differ from wakefulness to deep sleep--evidence from intracranial depth recordings in humans.

Neuronal activity differs between wakefulness and sleep states. In contrast, an attractor state, called self-organized critical (SOC), was proposed to govern brain dynamics because it allows for optimal information coding. But is the human brain SOC for each vigilance state despite the variations in neuronal dynamics? We characterized neuronal avalanches--spatiotemporal waves of enhanced activity--from dense intracranial depth recordings in humans.

The EPILEPSIAE database: an extensive electroencephalography database of epilepsy patients.

From the very beginning the seizure prediction community faced problems concerning evaluation, standardization, and reproducibility of its studies. One of the main reasons for these shortcomings was the lack of access to high-quality long-term electroencephalography (EEG) data. In this article we present the EPILEPSIAE database, which was made publicly available in 2012.