Unsupervised Multitaper Spectral Method for Identifying REM Sleep in Intracranial EEG Recordings Lacking EOG/EMG Data.

A large number of human intracranial EEG (iEEG) recordings have been collected for clinical purposes, in institutions all over the world, but the vast majority of these are unaccompanied by EOG and EMG recordings which are required to separate Wake episodes from REM sleep using accepted methods. In order to make full use of this extremely valuable data, an accurate method of classifying sleep from iEEG recordings alone is required. Existing methods of sleep scoring using only iEEG recordings accurately classify all stages of sleep, with the exception that wake (W) and rapid-eye movement (REM) sleep are not well distinguished.

Physical and cognitive impairments in people suffering from long COVID: protocol for a longitudinal population-based cohort study.

Introduction: Approximately 33% of people who contracted COVID-19 still experience symptoms 12 weeks after infection onset. This persistence of symptoms is now considered a syndrome itself called 'long COVID'. Evidence regarding long COVID and its cognitive and physical impacts is growing, but the literature is currently lacking objectively measured data to guide towards adapted healthcare trajectories.

Lessons Learned from the Implementation of a Person-Centred Digital Health Platform in Cancer Care.

The SARS-CoV-2 (COVID-19) pandemic has accelerated the development and use of digital health platforms to support individuals with health-related challenges. This is even more frequent in the field of cancer care as the global burden of the disease continues to increase every year. However, optimal implementation of these platforms into the clinical setting requires careful planning and collaboration.

Multitaper estimates of phase-amplitude coupling.

Phase-amplitude coupling (PAC) is the association of the amplitude of a high-frequency oscillation with the phase of a low-frequency oscillation. In neuroscience, this relationship provides a mechanism by which neural activity might be coordinated between distant regions. The dangers and pitfalls of assessing PAC with commonly used statistical measures have been well-documented.

Visual detection of affordances for aperture negotiation in people with Parkinson disease.

Background: An essential requirement for the guidance of action in cluttered environments is that people can accurately perceive what actions are afforded by particular surroundings given the person's action capabilities. Research has shown that healthy young individuals turn their shoulders when walking through a doorway when the aperture is less than a certain percentage of their shoulder width and that they are able to detect this critical width with visual inspection. These findings imply that movements are constrained by perception of the environment in body-scaled unit.

Frontal beta-theta network during REM sleep.

We lack detailed knowledge about the spatio-temporal physiological signatures of REM sleep, especially in humans. By analyzing intracranial electrode data from humans, we demonstrate for the first time that there are prominent beta (15-35 Hz) and theta (4-8 Hz) oscillations in both the anterior cingulate cortex (ACC) and the DLPFC during REM sleep. We further show that these theta and beta activities in the ACC and the DLPFC, two relatively distant but reciprocally connected regions, are coherent.

Factors influencing the effectiveness of audit and feedback: nurses' perceptions.

Aim: To explore the perceptions of nurses in an acute care setting on factors influencing the effectiveness of audit and feedback.

Background: Audit and feedback is widely used and recommended in nursing to promote evidence-based practice and to improve care quality. Yet the literature has shown a limited to modest effect at most.

What Do Patients Want? A Needs Assessment of Vulvodynia Patients Attending a Vulvar Diseases Clinic.

Introduction: Vulvodynia is a chronic pain disorder that negatively impacts the quality of life of affected women.

Aim: The goal of this study was to identify unmet needs among localized provoked vulvodynia patients.

Methods: A qualitative needs assessment was performed in a subspecialized vulvar clinic in a single academic institution in Canada.

Age-Related Changes in 1/f Neural Electrophysiological Noise.

Aging is associated with performance decrements across multiple cognitive domains. The neural noise hypothesis, a dominant view of the basis of this decline, posits that aging is accompanied by an increase in spontaneous, noisy baseline neural activity. Here we analyze data from two different groups of human subjects: intracranial electrocorticography from 15 participants over a 38 year age range (15-53 years) and scalp EEG data from healthy younger (20-30 years) and older (60-70 years) adults to test the neural noise hypothesis from a 1/f noise perspective.

Slow Spatial Recruitment of Neocortex during Secondarily Generalized Seizures and Its Relation to Surgical Outcome.

Understanding the spatiotemporal dynamics of brain activity is crucial for inferring the underlying synaptic and nonsynaptic mechanisms of brain dysfunction. Focal seizures with secondary generalization are traditionally considered to begin in a limited spatial region and spread to connected areas, which can include both pathological and normal brain tissue. The mechanisms underlying this spread are important to our understanding of seizures and to improve therapies for surgical intervention.

Experiences of "Being Known" by the Healthcare Team of Young Adult Patients with Cancer.

Purpose/objectives: To explore how young adult patients with cancer experience "being known" by their healthcare team.

Research Approach: Qualitative, descriptive.

Setting: A university-affiliated hospital in Montreal, Quebec.

A time-series model of phase amplitude cross frequency coupling and comparison of spectral characteristics with neural data.

Stochastic processes that exhibit cross-frequency coupling (CFC) are introduced. The ability of these processes to model observed CFC in neural recordings is investigated by comparison with published spectra. One of the proposed models, based on multiplying a pulsatile function of a low-frequency oscillation (θ) with an unobserved and high-frequency component, yields a process with a spectrum that is consistent with observation.

Fast maximum likelihood estimation using continuous-time neural point process models.

A recent report estimates that the number of simultaneously recorded neurons is growing exponentially. A commonly employed statistical paradigm using discrete-time point process models of neural activity involves the computation of a maximum-likelihood estimate. The time to computate this estimate, per neuron, is proportional to the number of bins in a finely spaced discretization of time.

Rate-adjusted spike-LFP coherence comparisons from spike-train statistics.

Coherence is a fundamental tool in the analysis of neuronal data and for studying multiscale interactions of single and multiunit spikes with local field potentials. However, when the coherence is used to estimate rhythmic synchrony between spiking and any other time series, the magnitude of the coherence is dependent upon the spike rate. This property is not a statistical bias, but a feature of the coherence function.

A statistically robust EEG re-referencing procedure to mitigate reference effect.

Background: The electroencephalogram (EEG) remains the primary tool for diagnosis of abnormal brain activity in clinical neurology and for in vivo recordings of human neurophysiology in neuroscience research. In EEG data acquisition, voltage is measured at positions on the scalp with respect to a reference electrode. When this reference electrode responds to electrical activity or artifact all electrodes are affected.

Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses.

The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas.

An active method for tracking connectivity in temporally changing brain networks.

The inference of connectivity in brain networks has typically been performed using passive measurements of ongoing activity across recording sites. Passive measures of connectivity are harder to interpret, however, in terms of causality - how evoked activity in one region might induce activity in another. To obviate this issue, recent work has proposed the use of active stimulation in conjunction with network estimation.

Some sampling properties of common phase estimators.

The instantaneous phase of neural rhythms is important to many neuroscience-related studies. In this letter, we show that the statistical sampling properties of three instantaneous phase estimators commonly employed to analyze neuroscience data share common features, allowing an analytical investigation into their behavior. These three phase estimators-the Hilbert, complex Morlet, and discrete Fourier transform-are each shown to maximize the likelihood of the data, assuming the observation of different neural signals.

Human seizures self-terminate across spatial scales via a critical transition.

Why seizures spontaneously terminate remains an unanswered fundamental question of epileptology. Here we present evidence that seizures self-terminate via a discontinuous critical transition or bifurcation. We show that human brain electrical activity at various spatial scales exhibits common dynamical signatures of an impending critical transition--slowing, increased correlation, and flickering--in the approach to seizure termination.

A procedure for testing across-condition rhythmic spike-field association change.

Many experiments in neuroscience have compared the strength of association between neural spike trains and rhythms present in local field potential (LFP) recordings. The measure employed in these comparisons, "spike-field coherence", is a frequency dependent measure of linear association, and is shown to depend on overall neural activity (Lepage et al., 2011).

Inferring evoked brain connectivity through adaptive perturbation.

Inference of functional networks-representing the statistical associations between time series recorded from multiple sensors-has found important applications in neuroscience. However, networksexhibiting time-locked activity between physically independent elements can bias functional connectivity estimates employing passive measurements. Here, a perturbative and adaptive method of inferring network connectivity based on measurement and stimulation-so called "evoked network connectivity" is introduced.

The statistical analysis of partially confounded covariates important to neural spiking.

A method is presented capable of disambiguating the relative influence of statistical covariates upon neural spiking activity. The method, an extension of the generalized linear model (GLM) methodology introduced in Truccolo et al. (2005) to analyze neural spiking data, exploits projection operations motivated by a geometry present in the Fisher information of the GLM maximum likelihood parameter estimator.

Emergence of persistent networks in long-term intracranial EEG recordings.

Over the past two decades, the increased ability to analyze network relationships among neural structures has provided novel insights into brain function. Most network approaches, however, focus on static representations of the brain's physical or statistical connectivity. Few studies have examined how brain functional networks evolve spontaneously over long epochs of continuous time.

Hippocampal "time cells" bridge the gap in memory for discontiguous events.

The hippocampus is critical to remembering the flow of events in distinct experiences and, in doing so, bridges temporal gaps between discontiguous events. Here, we report a robust hippocampal representation of sequence memories, highlighted by "time cells" that encode successive moments during an empty temporal gap between the key events, while also encoding location and ongoing behavior. Furthermore, just as most place cells "remap" when a salient spatial cue is altered, most time cells form qualitatively different representations ("retime") when the main temporal parameter is altered.