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Spontaneous oxycodone withdrawal disrupts sleep, diurnal, and electrophysiological dynamics in rats.
PLoS One
January 2025
Dept. of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, Massachusetts, United States of America.
Opioid dependence is defined by an aversive withdrawal syndrome upon drug cessation that can motivate continued drug-taking, development of opioid use disorder, and precipitate relapse. An understudied but common opioid withdrawal symptom is disrupted sleep, reported as both insomnia and daytime sleepiness. Despite the prevalence and severity of sleep disturbances during opioid withdrawal, there is a gap in our understanding of their interactions.
View Article and Find Full Text PDFHealthy aging changes in conventional frequency bands of neuroelectric brain activity reconstructed from resting-state MEG.
Geroscience
January 2025
Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, 125047, Russia.
Age-related dependencies of electric and spectral powers in conventional frequency bands were studied by the newly proposed method of detailed spectral analysis. The magnetic encephalograms (MEG) and magnetic resonance images (MRI) of the head were obtained from the open archive Cam-CAN. The spatial distributions of elementary spectral components (MEG-based functional tomograms) were reconstructed from MEG for 501 subjects (248 males and 253 females, ages 18-88 years, mean age 54.
View Article and Find Full Text PDFEdge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis.
PLoS One
January 2025
Computer Engineering, CCSIT, King Faisal University, Al Hufuf, Kingdom of Saudi Arabia.
The health of poultry flock is crucial in sustainable farming. Recent advances in machine learning and speech analysis have opened up opportunities for real-time monitoring of the behavior and health of flock. However, there has been little research on using Tiny Machine Learning (Tiny ML) for continuous vocalization monitoring in poultry.
View Article and Find Full Text PDFPersonalized μ-transcranial alternating current stimulation improves online brain-computer interface control.
J Neural Eng
January 2025
ECE & Neurology, University of Texas at Austin, 301 E. Dean Keeton St. C2100, Austin, Texas, 78712-1139, UNITED STATES.
Objective: A motor imagery (MI)-based brain-computer interface (BCI) enables users to engage with external environments by capturing and decoding electroencephalography (EEG) signals associated with the imagined movement of specific limbs. Despite significant advancements in BCI technologies over the past 40 years, a notable challenge remains: many users lack BCI proficiency, unable to produce sufficiently distinct and reliable MI brain patterns, hence leading to low classification rates in their BCIs. The objective of this study is to enhance the online performance of MI-BCIs in a personalized, biomarker-driven approach using transcranial alternating current stimulation (tACS).
View Article and Find Full Text PDFLow-Frequency Resistance Noise in Near-Magic-Angle Twisted Bilayer Graphene.
ACS Nano
January 2025
Department of Physics, Indian Institute of Science, Bangalore 560012, India.
The low-frequency resistance fluctuations, or noise, in electrical resistance not only set a performance benchmark in devices but also form a sensitive tool to probe nontrivial electronic phases and band structures in solids. Here, we report the measurement of such noise in the electrical resistance in twisted bilayer graphene (tBLG), where the layers are misoriented close to the magic angle (θ ∼ 1°). At high temperatures ( ≳ 60-70 K), the power spectral density (PSD) of the fluctuation inside the low-energy moiré bands is predominantly ∝1/, where is the frequency, being generally lowest close to the magic angle, and can be well-explained within the conventional McWhorter model of the '1/ noise' with trap-assisted density-mobility fluctuations.
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