20 research outputs found
Cortical–subcortical interactions in hypersomnia disorders: Mechanisms underlying cognitive and behavioral aspects of the sleep–wake cycle
Subcortical circuits mediating sleep–wake functions have been well characterized in animal models, and corroborated by more recent human studies. Disruptions in these circuits have been identified in hypersomnia disorders (HDs) such as narcolepsy and Kleine–Levin Syndrome, as well as in neurodegenerative disorders expressing excessive daytime sleepiness. However, the behavioral expression of sleep–wake functions is not a simple on-or-off state determined by subcortical circuits, but encompasses a complex range of behaviors determined by the interaction between cortical networks and subcortical circuits. While conceived as disorders of sleep, HDs are equally disorders of wake, representing a fundamental instability in neural state characterized by lapses of alertness during wake. These episodic lapses in alertness and wakefulness are also frequently seen in neurodegenerative disorders where electroencephalogram demonstrates abnormal function in cortical regions associated with cognitive fluctuations (CFs). Moreover, functional connectivity MRI shows instability of cortical networks in individuals with CFs. We propose that the inability to stabilize neural state due to disruptions in the sleep–wake control networks is common to the sleep and cognitive dysfunctions seen in hypersomnia and neurodegenerative disorders
Human sensory-evoked responses differ coincident with either "fusion-memory" or "flash-memory", as shown by stimulus repetition-rate effects
BACKGROUND: A new method has been used to obtain human sensory evoked-responses whose time-domain waveforms have been undetectable by previous methods. These newly discovered evoked-responses have durations that exceed the time between the stimuli in a continuous stream, thus causing an overlap which, up to now, has prevented their detection. We have named them "A-waves", and added a prefix to show the sensory system from which the responses were obtained (visA-waves, audA-waves, somA-waves). RESULTS: When A-waves were studied as a function of stimulus repetition-rate, it was found that there were systematic differences in waveshape at repetition-rates above and below the psychophysical region in which the sensation of individual stimuli fuse into a continuity. The fusion phenomena is sometimes measured by a "Critical Fusion Frequency", but for this research we can only identify a frequency-region [which we call the STZ (Sensation-Transition Zone)]. Thus, the A-waves above the STZ differed from those below the STZ, as did the sensations. Study of the psychophysical differences in auditory and visual stimuli, as shown in this paper, suggest that different stimulus features are detected, and remembered, at stimulation rates above and below STZ. CONCLUSION: The results motivate us to speculate that: 1) Stimulus repetition-rates above the STZ generate waveforms which underlie "fusion-memory" whereas rates below the STZ show neuronal processing in which "flash-memory" occurs. 2) These two memories differ in both duration and mechanism, though they may occur in the same cell groups. 3) The differences in neuronal processing may be related to "figure" and "ground" differentiation. We conclude that A-waves provide a novel measure of neural processes that can be detected on the human scalp, and speculate that they may extend clinical applications of evoked response recordings. If A-waves also occur in animals, it is likely that A-waves will provide new methods for comparison of activity of neuronal populations and single cells
Characterization of Scale-Free Properties of Human Electrocorticography in Awake and Slow Wave Sleep States
Like many complex dynamic systems, the brain exhibits scale-free dynamics that follow power-law scaling. Broadband power spectral density (PSD) of brain electrical activity exhibits state-dependent power-law scaling with a log frequency exponent that varies across frequency ranges. Widely divergent naturally occurring neural states, awake and slow wave sleep (SWS), were used to evaluate the nature of changes in scale-free indices of brain electrical activity. We demonstrate two analytic approaches to characterizing electrocorticographic (ECoG) data obtained during awake and SWS states. A data-driven approach was used, characterizing all available frequency ranges. Using an equal error state discriminator (EESD), a single frequency range did not best characterize state across data from all six subjects, though the ability to distinguish awake and SWS ECoG data in individual subjects was excellent. Multi-segment piecewise linear fits were used to characterize scale-free slopes across the entire frequency range (0.2–200 Hz). These scale-free slopes differed between awake and SWS states across subjects, particularly at frequencies below 10 Hz and showed little difference at frequencies above 70 Hz. A multivariate maximum likelihood analysis (MMLA) method using the multi-segment slope indices successfully categorized ECoG data in most subjects, though individual variation was seen. In exploring the differences between awake and SWS ECoG data, these analytic techniques show that no change in a single frequency range best characterizes differences between these two divergent biological states. With increasing computational tractability, the use of scale-free slope values to characterize ECoG and EEG data will have practical value in clinical and research studies
The Human Connectome Project: A retrospective
The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the “WU-Minn-Ox” HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The “HCP-style” neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium
New genetic loci link adipose and insulin biology to body fat distribution.
Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms
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Human sensory-evoked responses differ coincident with either "fusion-memory" or "flash-memory", as shown by stimulus repetition-rate effects.
BackgroundA new method has been used to obtain human sensory evoked-responses whose time-domain waveforms have been undetectable by previous methods. These newly discovered evoked-responses have durations that exceed the time between the stimuli in a continuous stream, thus causing an overlap which, up to now, has prevented their detection. We have named them "A-waves", and added a prefix to show the sensory system from which the responses were obtained (visA-waves, audA-waves, somA-waves).ResultsWhen A-waves were studied as a function of stimulus repetition-rate, it was found that there were systematic differences in waveshape at repetition-rates above and below the psychophysical region in which the sensation of individual stimuli fuse into a continuity. The fusion phenomena is sometimes measured by a "Critical Fusion Frequency", but for this research we can only identify a frequency-region [which we call the STZ (Sensation-Transition Zone)]. Thus, the A-waves above the STZ differed from those below the STZ, as did the sensations. Study of the psychophysical differences in auditory and visual stimuli, as shown in this paper, suggest that different stimulus features are detected, and remembered, at stimulation rates above and below STZ.ConclusionThe results motivate us to speculate that: 1) Stimulus repetition-rates above the STZ generate waveforms which underlie "fusion-memory" whereas rates below the STZ show neuronal processing in which "flash-memory" occurs. 2) These two memories differ in both duration and mechanism, though they may occur in the same cell groups. 3) The differences in neuronal processing may be related to "figure" and "ground" differentiation. We conclude that A-waves provide a novel measure of neural processes that can be detected on the human scalp, and speculate that they may extend clinical applications of evoked response recordings. If A-waves also occur in animals, it is likely that A-waves will provide new methods for comparison of activity of neuronal populations and single cells
Allodynia and Descending Pain Modulation in Migraine: A Resting State Functional Connectivity Analysis
Effect of armodafinil on cortical activity and working memory in patients with residual excessive sleepiness associated with CPAP-Treated OSA: a multicenter fMRI study.
Study objectiveTo assess the effect of armodafinil on task-related prefrontal cortex activation using functional magnetic resonance imaging (fMRI) in patients with obstructive sleep apnea (OSA) and excessive sleepiness despite continuous positive airway pressure (CPAP) therapy.MethodsThis 2-week, multicenter, prospective, randomized, double-blind, placebo-controlled, parallel-group study was conducted at five neuroimaging sites and four collaborating clinical study centers in the United States. Patients were 40 right-handed or ambidextrous men and women aged between 18 and 60 years, with OSA and persistent sleepiness, as determined by multiple sleep latency and Epworth Sleepiness Scale scores, despite effective, stable use of CPAP. Treatment was randomized (1:1) to once-daily armodafinil 200 mg or placebo. The primary efficacy outcome was a change from baseline at week 2 in the volume of activation meeting the predefined threshold in the dorsolateral prefrontal cortex during a 2-back working memory task. The key secondary measure was the change in task response latency.ResultsNo significant differences were observed between treatment groups in the primary or key secondary outcomes. Armodafinil was generally well tolerated. The most common adverse events (occurring in more than one patient [5%]) were headache (19%), nasopharyngitis (14%), and diarrhea (10%).ConclusionsArmodafinil did not improve fMRI-measured functional brain activation in CPAP-treated patients with OSA and excessive sleepiness.Study registrationDouble-Blind, Placebo-Controlled, Functional Neuroimaging Study of Armodafinil (200 mg/Day) on Prefrontal Cortical Activation in Patients With Residual Excessive Sleepiness Associated With Obstructive Sleep Apnea/Hypopnea
Effect of Armodafinil on Cortical Activity and Working Memory in Patients with Residual Excessive Sleepiness Associated with CPAP-Treated OSA: A Multicenter fMRI Study
STUDY OBJECTIVE: To assess the effect of armodafinil on task-related prefrontal cortex activation using functional magnetic resonance imaging (fMRI) in patients with obstructive sleep apnea (OSA) and excessive sleepiness despite continuous positive airway pressure (CPAP) therapy. METHODS: This 2-week, multicenter, prospective, randomized, double-blind, placebo-controlled, parallel-group study was conducted at five neuroimaging sites and four collaborating clinical study centers in the United States. Patients were 40 right-handed or ambidextrous men and women aged between 18 and 60 years, with OSA and persistent sleepiness, as determined by multiple sleep latency and Epworth Sleepiness Scale scores, despite effective, stable use of CPAP. Treatment was randomized (1:1) to once-daily armodafinil 200 mg or placebo. The primary efficacy outcome was a change from baseline at week 2 in the volume of activation meeting the predefined threshold in the dorsolateral prefrontal cortex during a 2-back working memory task. The key secondary measure was the change in task response latency. RESULTS: No significant differences were observed between treatment groups in the primary or key secondary outcomes. Armodafinil was generally well tolerated. The most common adverse events (occurring in more than one patient [5%]) were headache (19%), nasopharyngitis (14%), and diarrhea (10%). CONCLUSIONS: Armodafinil did not improve fMRI-measured functional brain activation in CPAP-treated patients with OSA and excessive sleepiness. STUDY REGISTRATION: Double-Blind, Placebo-Controlled, Functional Neuroimaging Study of Armodafinil (200 mg/Day) on Prefrontal Cortical Activation in Patients With Residual Excessive Sleepiness Associated With Obstructive Sleep Apnea/Hypopnea. ClinicalTrials.gov Identifier: NCT00711516. http://www.clinicaltrials.gov/ct2/show/study/NCT00711516 CITATION: Greve DN; Duntley SP; Larson-Prior L; Krystal AD; Diaz MT; Drummond SP; Thein SG; Kushida CA; Yang R; Thomas RJ. Effect of armodafinil on cortical activity and working memory in patients with residual excessive sleepiness associated with CPAP-treated OSA: a multicenter fMRI study. J Clin Sleep Med 2014;10(2):143-153