Sleep is characterized by nonrapid eye movement sleep, originating from widespread neuronal synchrony, and rapid eye movement sleep, with neuronal desynchronization akin to waking behavior. While these were thought to be global brain states, recent research suggests otherwise. Using time-frequency analysis of mesoscopic voltage-sensitive dye recordings of mice in a urethane-anesthetized model of sleep, we find transient neural desynchronization occurring heterogeneously across the cortex within a background of synchronized neural activity, in a manner reminiscent of a critical spreading process and indicative of an "edge-of-synchronization" phase transition.
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http://dx.doi.org/10.1103/PhysRevLett.132.218403 | DOI Listing |
J Integr Neurosci
January 2025
Department of Hepatology, Federal University of Health Sciences of Porto Alegre (UFCSPA), 90050-170 Porto Alegre, Rio Grande do Sul (RS), Brazil.
Mitochondria are organelles of eukaryotic cells delimited by two membranes and cristae that consume oxygen to produce adenosine triphosphate (ATP), and are involved in the synthesis of vital metabolites, calcium homeostasis, and cell death mechanisms. Strikingly, normal mitochondria function as an integration center between multiple conditions that determine neural cell homeostasis, whereas lesions that lead to mitochondrial dysfunction can desynchronize cellular functions, thus contributing to the pathophysiology of traumatic brain injury (TBI). In addition, TBI leads to impaired coupling of the mitochondrial electron transport system with oxidative phosphorylation that provides most of the energy needed to maintain vital functions, ionic homeostasis, and membrane potentials.
View Article and Find Full Text PDFTransl Stroke Res
January 2025
Department of Rehabilitation Sciences, KU Leuven, B-3001, Leuven, Belgium.
Electroencephalogram (EEG) during pinprick stimulation has the potential to unveil neural mechanisms underlying sensorimotor impairments post-stroke. A proof-of-concept study explored event-related peak pinprick amplitude and oscillatory responses in healthy controls and in people with acute and subuacute motor and sensorimotor stroke, their relationship, and to what extent EEG somatosensory responses can predict sensorimotor impairment. In this study, 26 individuals participated, 10 people with an acute and early subacute sensorimotor stroke, 6 people with an acute and early subacute motor stroke, and 10 age-matched controls.
View Article and Find Full Text PDFFront Neural Circuits
January 2025
Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Kanagawa, Japan.
Introduction: Motor-imagery-based Brain-Machine Interface (MI-BMI) has been established as an effective treatment for post-stroke hemiplegia. However, the need for long-term intervention can represent a significant burden on patients. Here, we demonstrate that motor imagery (MI) instructions for BMI training, when supplemented with somatosensory stimulation in addition to conventional verbal instructions, can help enhance MI capabilities of healthy participants.
View Article and Find Full Text PDFHum Brain Mapp
February 2025
Université libre de Bruxelles (ULB), UNI - ULB Neuroscience Institute, Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN2T), Brussels, Belgium.
Language control processes allow for the flexible manipulation and access to context-appropriate verbal representations. Functional magnetic resonance imaging (fMRI) studies have localized the brain regions involved in language control processes usually by comparing high vs. low lexical-semantic control conditions during verbal tasks.
View Article and Find Full Text PDFJ 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).
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