4,478 research outputs found

    Impact of a Right Ventricular Impedance Sensor on the Cardiovascular Responses to Exercise in Pacemaker Dependent Patients

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    Background. The evaluation of the heart rate (HR) response to exercise is important for the assessment of the rate response algorithm of sensor-controlled pacemakers. This study examined the effects of a right ventricular impedance sensor driven pacemaker on the cardiovascular responses to incremental exercise in pacemaker dependent patients. Methods. Twelve patients (70.5 ± 9.5 years; 5 Females: 7 Males) implanted with an Inos2+ closed loop stimulation (CLS) pacemaker were compared to 12 healthy age and sex matched controls (70.6 ± 4.8 years). All subjects performed the chronotropic assessment exercise protocol (CAEP). Variables of interest included HR, cardiac output (Q), oxygen uptake (Vo2) and blood pressure (BP). Data were analyzed at rest, throughout exercise and during recovery. Furthermore, patient chronotropic responses were compared to a reference chronotropic response slope for aerobic exercise. Results. There were no differences between groups for HR or Q. response throughout exercise. At peak exercise, V.o2 (mL.kg-1.min-1) was higher for the controls (p < 0.05). The patient chronotropic response slope was comparable to the CAEP reference slope from rest to both the anaerobic threshold (AT) and peak exercise. During recovery, no differences were observed between the groups for any parameters or for the HR decay slopes. Conclusions. Up to the anaerobic threshold, the right ventricular impedance sensor driven pacemaker delivered a pacing rate that contributed to an overall cardiovascular response similar to that observed in healthy age matched subjects

    The mechanisms of tinnitus: perspectives from human functional neuroimaging

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    In this review, we highlight the contribution of advances in human neuroimaging to the current understanding of central mechanisms underpinning tinnitus and explain how interpretations of neuroimaging data have been guided by animal models. The primary motivation for studying the neural substrates of tinnitus in humans has been to demonstrate objectively its representation in the central auditory system and to develop a better understanding of its diverse pathophysiology and of the functional interplay between sensory, cognitive and affective systems. The ultimate goal of neuroimaging is to identify subtypes of tinnitus in order to better inform treatment strategies. The three neural mechanisms considered in this review may provide a basis for TI classification. While human neuroimaging evidence strongly implicates the central auditory system and emotional centres in TI, evidence for the precise contribution from the three mechanisms is unclear because the data are somewhat inconsistent. We consider a number of methodological issues limiting the field of human neuroimaging and recommend approaches to overcome potential inconsistency in results arising from poorly matched participants, lack of appropriate controls and low statistical power

    What Electrophysiology Tells Us About Alzheimer’s Disease::A Window into the Synchronization and Connectivity of Brain Neurons

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    Electrophysiology provides a real-time readout of neural functions and network capability in different brain states, on temporal (fractions of milliseconds) and spatial (micro, meso, and macro) scales unmet by other methodologies. However, current international guidelines do not endorse the use of electroencephalographic (EEG)/magnetoencephalographic (MEG) biomarkers in clinical trials performed in patients with Alzheimer’s disease (AD), despite a surge in recent validated evidence. This Position Paper of the ISTAART Electrophysiology Professional Interest Area endorses consolidated and translational electrophysiological techniques applied to both experimental animal models of AD and patients, to probe the effects of AD neuropathology (i.e., brain amyloidosis, tauopathy, and neurodegeneration) on neurophysiological mechanisms underpinning neural excitation/inhibition and neurotransmission as well as brain network dynamics, synchronization, and functional connectivity reflecting thalamocortical and cortico-cortical residual capacity. Converging evidence shows relationships between abnormalities in EEG/MEG markers and cognitive deficits in groups of AD patients at different disease stages. The supporting evidence for the application of electrophysiology in AD clinical research as well as drug discovery pathways warrants an international initiative to include the use of EEG/MEG biomarkers in the main multicentric projects planned in AD patients, to produce conclusive findings challenging the present regulatory requirements and guidelines for AD studies

    Electrophysiological Signatures of Fear Conditioning: From Methodological Considerations to Catecholaminergic Mechanisms and Translational Perspectives

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    Fear conditioning describes a learning mechanism during which a specific stimulus gets associated with an aversive event (i.e., an unconditioned stimulus; US). Thereby, this initially neutral or arbitrary stimulus becomes a so-called “conditioned” stimulus (CS), which elicits a conditioned threat response. Fear extinction refers to the decrease in conditioned threat responses as soon as the CS is repeatedly presented in the absence of the US. While fear conditioning is an important learning model for understanding the etiology and maintenance of anxiety and fear-related disorders, extinction learning is considered to reflect the most important learning process of exposure therapy. Neurophysiological signatures of fear conditioning have been widely studied in rodents, leading to the development of groundbreaking neurobiological models, including brain regions such as the amygdala, insula, and prefrontal areas. These models aim to explain neural mechanisms of threat processing, with the ultimate goal to improve treatment strategies for pathological fear. Recording intracranial electrical activity of single units in animals offers the opportunity to uncover neural processes involved in threat processing with excellent spatial and temporal resolution. A large body of functional magnetic resonance imaging (fMRI) studies have helped to translate this knowledge about the anatomy of fear conditioning into the human realm. fMRI is an imaging technique with a high spatial resolution that is well suited to study slower brain processes. However, the temporal resolution of fMRI is relatively poor. By contrast, electroencephalography (EEG) is a neuroscientific method to capture fast and transient cortical processes. While EEG offers promising opportunities to unravel the speed of neural threat processing, it also provides the possibility to study oscillatory brain activity (e.g., prefrontal theta oscillations). The present thesis contains six research manuscripts, describing fear conditioning studies that mainly applied EEG methods in combination with other central (fMRI) and peripheral (skin conductance, heart rate, and fear-potentiated startle) measures. A special focus of this thesis lies in methodological considerations for EEG fear conditioning research. In addition, catecholaminergic mechanisms are studied, with the ultimate goal of opening up new translational perspectives. Taken together, the present thesis addresses several methodological challenges for neuroscientific (in particular, EEG) fear conditioning research (e.g., appropriate US types and experimental designs, signal-to-noise ratio, simultaneous EEG-fMRI). Furthermore, this thesis gives critical insight into catecholaminergic (noradrenaline and dopamine) mechanisms. A variety of neuroscientific methods (e.g., EEG, fMRI, peripheral physiology, pharmacological manipulation, genetic associations) have been combined, an approach that allowed us (a) to translate knowledge from animal studies to human research, and (b) to stimulate novel clinical directions

    Neuroeconomics: infeasible and underdetermined

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    Advocates of neuroeconomics claim to offer the prospect of creating a “unified behavioral theory” by drawing upon the techniques of neuroscience and psychology and combining them with economic theory. Ostensibly, through the “direct measurement” of our thoughts, economics and social science will be “revolutionized.” Such claims have been subject to critique from mainstream and non-mainstream economists alike. Many of these criticisms relate to measurability, relevance, and coherence. In this article, we seek to contribute to this critical examination by investigating the potential of underdetermination, such as the statement that testing involves the conjunction of auxiliary assumptions, and that consequently it may not be possible to isolate the effect of any given hypothesis. We argue that neuroeconomics is especially sensitive to issues of underdetermination. Institutional economists should be cautious of neuroeconomists’ zeal as they appear to over-interpret experimental findings and, therefore, neuroeconomics may provide a false prospectus seeking to reinforce the nostrums of homo economicus

    Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

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    Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention

    Validity of telemetric-derived measures of heart rate variability: a systematic review

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    Heart rate variability (HRV) is a widely accepted indirect measure of autonomic function with widespread application across many settings. Although traditionally measured from the 'gold standard' criterion electrocardiography (ECG), the development of wireless telemetric heart rate monitors (HRMs) extends the scope of the HRV measurement. However, the validity of telemetric-derived data against the criterion ECG data is unclear. Thus, the purpose of this study was twofold: (a) to systematically review the validity of telemetric HRM devices to detect inter-beat intervals and aberrant beats; and (b) to determine the accuracy of HRV parameters computed from HRM-derived inter-beat interval time series data against criterion ECG-derived data in healthy adults aged 19 to 62 yrs. A systematic review of research evidence was conducted. Four electronic databases were accessed to obtain relevant articles (PubMed, EMBASE, MEDLINE and SPORTDiscus. Articles published in English between 1996 and 2016 were eligible for inclusion. Outcome measures included temporal and power spectral indices (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996). The review confirmed that modern HRMs (Polar® V800™ and Polar® RS800CX™) accurately detected inter-beat interval time-series data. The HRV parameters computed from the HRM-derived time series data were interchangeable with the ECG-derived data. The accuracy of the automatic in-built manufacturer error detection and the HRV algorithms were not established. Notwithstanding acknowledged limitations (a single reviewer, language bias, and the restricted selection of HRV parameters), we conclude that the modern Polar® HRMs offer a valid useful alternative to the ECG for the acquisition of inter-beat interval time series data, and the HRV parameters computed from Polar® HRM-derived inter-beat interval time series data accurately reflect ECG-derived HRV metrics, when inter-beat interval data are processed and analyzed using identical protocols, validated algorithms and software, particularly under controlled and stable conditions

    Assessing neural network dynamics under normal and altered states of consciousness with MEG : methodological challenges and proposed solutions for atypical power spectra

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    Cette dernière décennie a vu un certain nombre d'avancées significatives en mathématiques, en apprentissage computationnel et en traitement de signal, qui n'ont pas encore été pleinement exploitées en neurosciences. En particulier, l'évaluation de la connectivité dans les réseaux neuronaux peut grandement bénéficier de ces travaux. Nous proposons ici d'exploiter ces outils pour combler partiellement le fossé considérable qui existe encore entre la recherche connectomique à grande échelle (largement centrée sur des mesures indirectes de l'activité cérébrale comme l'Imagerie par résonance magnétique fonctionnelle (IRMf)) et les mesures physiologiques plus directes de l'activité cérébrale. Il est particulièrement important de combler ce fossé pour l'étude des propriétés physiologiques associées à divers états de conscience normaux et anormaux, notamment les troubles psychiatriques, le sommeil, l'anesthésie ou les états induits par les drogues. Les travaux récents sur l'induction d'états de conscience altérés par des agonistes non sélectifs de la sérotonine, tels que la psilocybine et le Diéthyllysergamide (LSD), en sont de bons exemples. Au cours des cinq dernières années, une résurgence rapide de la recherche sur la neurobiologie des tryptamines psychédéliques s'est produite, après une interruption d'un demi-siècle. Bien que ces substances présentent un grand potentiel pour éclairer des aspects jusqu'ici non interrogés du fonctionnement normal et anormal du cerveau, l'ampleur et le caractère inhabituel des changements qu'elles provoquent posent de sérieux défis aux chercheurs. La découverte de méthodes convaincantes et évolutives pour étudier ces données est d'une grande importance si nous voulons tirer parti de la fenêtre unique que ces substances atypiques offrent sur les aspects centraux de la conscience et des fonctions cérébrales anormales. Dans la présente thèse, nous résumons l'état actuel de la neuro-imagerie électrophysiologique en ce qui concerne l'étude des tryptamines psychédéliques, et nous démontrons un certain nombre de lacunes évidentes dans la recherche électrophysiologique actuelle sur les psychédéliques. Nous offrons également quelques modestes contributions méthodologiques au domaine. L'utilité de ces contributions est soutenue par quelques résultats empiriques intrigants, bien que préliminaires. Dans le premier chapitre, nous présentons l'histoire de la recherche neuroscientifique sur le LSD. Il a été rapporté que le LSD induit des déplacements de pics dans les spectres de puissance, en même temps que des diminutions de l'amplitude des pics. Le fait que ces effets soient liés entre eux et que la plupart des recherches menées jusqu'à présent n'aient pas cherché à les distinguer est uniformément négligé dans la littérature, ce qui, selon nous, peut conduire à de fausses interprétations. Le chapitre 2 examine certains des avantages plausibles ainsi que les obstacles sérieux à la recherche sur la connectivité du cerveau entier par magnétoencéphalographie (MEG), et propose plusieurs stratégies pour surmonter ces limites méthodologiques. Celles-ci comprennent des stratégies d'imagerie de source convaincantes, des développements nouveaux et récents dans la décomposition spectrale, des mesures de connectivité insensibles à la conduction volumique, et des implémentations évolutives de métriques de couplage interfréquence bien établies. Nous montrons que ces techniques peuvent être étendues à une grille corticale et sous-corticale de plus haute résolution que celle qui existe actuellement. Nous discutons également d'une mise en œuvre allégée de statistiques non paramétriques adaptées à ces données. Le troisième chapitre a pour but de démontrer l'efficacité de ces procédures, en montrant les résultats empiriques d'une étude de la connectivité du cerveau entier sous LSD par MEG. Le quatrième et dernier chapitre discute de ces résultats, ainsi que des précautions nécessaires et des orientations futures prometteuses pour ce type de recherche. Il propose des approches computationnelles supplémentaires qui pourraient étendre la portée de ces recherches et, plus généralement, de l'électrophysiologie du cerveau entier. Dans l'ensemble, le cadre méthodologique proposé dans ce travail surmonte les limitations endémiques précédentes, non seulement dans la recherche sur les psychédéliques, mais aussi dans la recherche électrophysiologique en général, et jette une lumière nouvelle sur sur les mécanismes centraux qui sous-tendent ces états de conscience anormaux, ainsi que sur les importantes précautions à prendre dans la recherche électrophysiologique.The past decade has seen a number of significant advances in mathematics, computational learning, and signal processing, which have yet to be deployed in neuroscience. In particular the assessment of connectivity in neural networks has much to gain from this work. Here we propose these tools be leveraged to partially bridge the considerable gap that still exists between large-scale connectomics research (largely centered around indirect measures of brain activity such as fMRI), and more direct, physiological measures of brain activity. Bridging this gap is especially important to the study of physiological properties associated with various normal and abnormal states of consciousness including Psychiatric conditions, sleep, anaesthesia or drug-induced states. Exemplary of such research, is recent work surrounding the induction of altered states of consciousness by non-selective serotonin agonists such as Psilocybin and LSD. During the past five years, a rapid resurgence of research into the neurobiology of Psychedelic tryptamines has transpired, following a half-century hiatus. While these substances hold great potential to illuminate hitherto uninterrogated aspects of normal and abnormal brain function, the scope and unusual character of the changes they illicit pose serious challenges to researchers. Uncovering cogent and scalable methods for investigating such data is a matter of great importance if we are to leverage the unique window such atypical substances provide into central aspects of consciousness and abnormal brain function. In the present thesis, we summarize the current state of electrophysiological neuroimaging as it pertains to the study of Psychedelic tryptamines, and demonstrate a number of clear shortcomings in current electrophysiological research on Psychedelics. We also offer some modest methodological contributions to the field. The utility of these contributions is supported by some intriguing, albeit preliminary, empirical findings. In the first chapter, we present the history of neuroscientific research on LSD. LSD has been reported to induce peak shifts in power spectra, alongside decreases in peak amplitude. The fact that these effects are inter-related and most research so far has not sought to disambiguate them is uniformly overlooked in the literature, which we believe may lead to false interpretations. Chapter Two discusses some of the plausible advantages as well as serious barriers to whole-brain connectivity research in MEG, proposing several strategies to overcome these methodological limitations. These include cogent source imaging strategies, novel and recent developments in spectral decomposition, connectivity measures insensitive to volume conduction, and scalable implementations of well-established cross-frequency coupling metrics. We show that these techniques can be extended to a higher resolution cortical and subcortical grid than previously shown. We also discuss a lightweight implementation of non-parametric statistics suitable to such data. Chapter Three serves to demonstrate the efficacy of these procedures, showing empirical results from a whole-brain study of connectivity under LSD in MEG. The fourth and final chapter discusses these results, as well as necessary precautions and promising future directions for this kind of research. It proposes additional computational approaches that might extend the scope of such research and whole-brain electrophysiology more generally. Taken together, the methodological framework proposed in this work overcomes previous limitations endemic not only in Psychedelics research, but electrophysiological research broadly, and sheds new light on central mechanisms underlying these abnormal states of consciousness, as well as important precautions in electrophysiological research

    The effect of the interval-between-sessions on prefrontal transcranial direct current stimulation (tDCS) on cognitive outcomes: a systematic review and meta-analysis

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    Recently, there has been wide interest in the effects of transcranial direct current stimulation (tDCS) of the dorsolateral prefrontal cortex (DLPFC) on cognitive functioning. However, many methodological questions remain unanswered. One of them is whether the time interval between active and sham-controlled stimulation sessions, i.e. the interval between sessions (IBS), influences DLPFC tDCS effects on cognitive functioning. Therefore, a systematic review and meta-analysis was performed of experimental studies published in PubMed, Science Direct, and other databases from the first data available to February 2016. Single session sham-controlled within-subject studies reporting the effects of tDCS of the DLPFC on cognitive functioning in healthy controls and neuropsychiatric patients were included. Cognitive tasks were categorized in tasks assessing memory, attention, and executive functioning. Evaluation of 188 trials showed that anodal vs. sham tDCS significantly decreased response times and increased accuracy, and specifically for the executive functioning tasks, in a sample of healthy participants and neuropsychiatric patients (although a slightly different pattern of improvement was found in analyses for both samples separately). The effects of cathodal vs. sham tDCS (45 trials), on the other hand, were not significant. IBS ranged from less than 1 h to up to 1 week (i.e. cathodal tDCS) or 2 weeks (i.e. anodal tDCS). This IBS length had no influence on the estimated effect size when performing a meta-regression of IBS on reaction time and accuracy outcomes in all three cognitive categories, both for anodal and cathodal stimulation. Practical recommendations and limitations of the study are further discussed

    Quality of Life and Mental Health Outcomes in Implanted Cardioverter Defibrillator Treatment: Potential Effects of Informational Media History and Treatment Knowledge

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    Social workers in all care venues are increasingly responsible for clinical and case management services for people being treated with sophisticated medical interventions. Unfortunately, opportunities to aid in the promotion of quality of life (QOL), mental health, and informed consent are often not understood by social workers, other care providers, or patients. These missed opportunities may lead to attenuated effectiveness of medical interventions and negative impact on patients\u27 QOL. One such technological treatment is the implantable cardioverter defibrillator (ICD), a lifesaving therapy which carries risk to patients\u27 QOL. Moreover, patients frequently do not accurately understand the benefits, limitations, and possible risks associated with ICD therapy. A small body of literature exists addressing experimental and demographic groups at risk of QOL decrements among the ICD patient population, including those who have been shocked more than five times, older adults, female patients, and those who have experienced a life threatening cardiac event. A much more limited body of literature addresses the quality of some forms of patient educational activities and materials. No research to date has attempted to characterize potential relationships between patient information acquisition, treatment knowledge, and QOL/mental health outcomes in this patient group. Using a cross-sectional survey of ICD patients being treated at the University of Colorado Hospital (UCH), this dissertation project uses a social-ecological approach to describe the media through which ICD patients learn about device therapy, how well they understand their treatment, QOL and mental health outcomes, and any relationships between these constructs. The project was conducted in iterative phases, including the creation of two new measures assessing patient informational media history and ICD treatment knowledge, a pilot survey of 100 randomly selected patients to assess the quality of the new measures, and a larger survey of the remaining 655 potential ICD patient participants. A total of 205 ICD patients responded to the survey, with a mean age of 60.7 years (sd=14.53), 34.1% of whom identified as female, 10.2% of whom are African American, and 37.5% of whom live in a household with an annual income of less than $40,000. Findings from survey responses revealed both the viability of the new informational media history and ICD treatment knowledge measures, as well as broad use of a number of specific forms of media to learn about treatment. Older adult patients illustrated significantly lower treatment knowledge and use of fewer forms of informational media than their younger counterparts. Multiple regression analyses revealed significant relationships between patient history of having been shocked, health related depression, and QOL, but failed to replicate earlier findings linking these problems to demographic indicators. Each of these findings highlight opportunities for improved social work research and practice with ICD patients, including the need for improved patient education processes for older adults with these devices, and the importance of mental health status, particularly depression, to patient QOL
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