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Mashup Score: 0
Rett syndrome (RTT) is a severe X-linked dominant neurodevelopmental disorder predominantly affecting females and over 90% of these patients mutations linked to the methyl-CpG-binding protein 2 (MeCP2) gene. Although the syndrome is well noted for the classic repetitive hand motion with decline in speech, patients may have a wide range of cognitive and motor impairments. Typical comorbidities in RTT are characterized by poor growth, seizures, disrupted sleep, hyperventilation, breath holding spells, feeding difficulties, scoliosis, and behavioral issues. This paper aims to provide a brief overview of RTT, focusing on the clinical features of sleep and epilepsy, effects on childhood development, and available emerging treatment options. Sleep disturbances, epilepsy, and developmental regression can have profound effects on the quality of life in affected individuals. Current management strategies focus on a multidisciplinary approach to address symptoms and enhance overall wellbeing of
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Mashup Score: 1The role of the reticulospinal tract in spasticity and rigidity - 4 hour(s) ago
The reticulospinal tract (RST) is a major descending pathway which is mostly known to be involved in the control of posture and locomotion in human. However, this vision that RST is exclusively involved in the control of posture and locomotion would largely neglect the role of RST on the balancing effect it has on the spinal motoneurons through its inhibitory and excitatory outputs. In fact, RST has two major tracts (a dorsal and a medial tract), which post inhibitory and excitatory effect on spinal reflexes. This pathway shows substantial neuroplastic changes after insults to the central nervous system (such as stroke, multiple sclerosis and Parkinson). In recent years, the role of RST in hyperreflexia and spasticity has been subject to great attention. Our knowledge about the role of RST in spinal reflexes, has therefore been significantly revisited. In this Research Topic we aim to gather manuscripts which show new horizons and findings on the role of RST in CNS pathologies.The role
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Mashup Score: 7Metabolic Dysregulation in Neurodegenerative Diseases - 4 day(s) ago
Several lines of evidence link metabolic dysregulation to late-life neurodegenerative diseases. The altered glucose metabolism observed in both Alzheimer’s disease (AD) and Parkinson’s disease (PD), as well as their connection to type 2 diabetes, is an area of significant interest. Notably, there is an overlap in risk factors for obesity, diabetes, and neurodegenerative diseases (particularly AD and PD) such as a lack of physical activity and excessive calorie consumption. Furthermore, variants in insulin signaling pathway genes have been associated with an increased risk of PD. In AD brains, there is a decrease in the glucose transporters GLUT1 (insulin-insensitive) and GLUT3 (insulin-sensitive) and GLUT4(insulin-sensitive). Additionally, insulin deficiency promotes tau phosphorylation and the development of neurofibrillary pathology. All together supports the role of disrupted insulin signaling in neurodegenerative disease progression.This Research Topic aims to explore the critical
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A research topic, led by Carlos Guillén, Maria Jimenez Gonzalez, and Andrea Torrao via Frontiers in Cellular Neuroscience, will explore groundbreaking research on Metabolic Dysregulation in Neurodegenerative Diseases. Deadline 24 March 2024. Read more➡️https://t.co/3MO9Lh9HX7 https://t.co/DR3Wfr2aVH
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Mashup Score: 2Bringing together multimodal and multilevel approaches to study the emergence of social bonds between children and improve social AI - 4 day(s) ago
This protocol paper outlines an innovative multimodal and multilevel approach to studying the emergence and evolution of how children build social bonds with their peers, and its potential application to improving social artificial intelligence (AI). We detail a unique hyperscanning experimental framework utilizing functional near-infrared spectroscopy (fNIRS) to observe inter-brain synchrony in child dyads during collaborative tasks and social interactions. Our proposed longitudinal study spans middle childhood, aiming to capture the dynamic development of social connections and cognitive engagement in naturalistic settings. To do so we bring together four kinds of data: the multimodal conversational behaviors that dyads of children engage in, evidence of their state of interpersonal rapport, collaborative performance on educational tasks, and inter-brain synchrony. Preliminary pilot data provide foundational support for our approach, indicating promising directions for identifying ne
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Mashup Score: 6
The emerging integration of Brain-Computer Interfaces (BCIs) in human-robot collaboration holds promise for dynamic adaptive interaction. The use of electroencephalogram (EEG)-measured error-related potentials (ErrPs) for online error detection in assistive devices offers a practical method for improving the reliability of such devices. However, continuous online error detection faces challenges such as developing efficient and lightweight classification techniques for quick predictions, reducing false alarms from artifacts, and dealing with the non-stationarity of EEG signals. Further research is essential to address the complexities of continuous classification in online sessions. With this study, we demonstrated a comprehensive approach for continuous online EEG-based machine error detection, which emerged as the winner of a competition at the 32nd International Joint Conference on Artificial Intelligence. The competition consisted of two stages: an offline stage for model developme
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Mashup Score: 6Frontiers ⎮ Participate in "Machine Learning Algorithms for Brain Imaging: New Frontiers in Neurodiagnostics and Treatment" - 7 day(s) ago
Participate in the open-access Research topic entitled “Machine Learning Algorithms for Brain Imaging: New Frontiers in Neurodiagnostics and Treatment”
Source: www.frontiersin.orgCategories: General Medicine News, NeurologyTweet
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Mashup Score: 14Novel Approaches to Targeting the Vasculature and Metabolome to Prevent Brain Aging and Related Diseases - 11 day(s) ago
The human brain is highly metabolically active and expends about 20% of the body’s energy just for normal functioning. Neuronal activation locally leads to a transient increase in cerebral blood flow – a process called neurovascular coupling, thus ensuring that bioenergetic substrates are efficiently delivered to that region of the brain. Neurovascular coupling is brought about by the coordinated action of neurons, astrocytes and other glial cells, and endothelial cells and smooth muscle cells forming the blood vessels, collectively termed as the neurovascular unit. The neurovascular unit also functions to keep the blood brain barrier (BBB) intact. Normal neurovascular and neurometabolic coupling as well as BBB function are essential to maintain brain homeostasis and for proper cognitive function. As the brain ages, there is significant impairment of neurovascular coupling and the integrity of the BBB which leads to insufficient blood flow to the brain, reduced delivery of oxygen and b
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A research topic, via Frontiers in Cellular Neuroscience will explore groundbreaking research on Novel Approaches Targeting the Vasculature and Metabolome to Prevent Brain Aging and Related Diseases. Closing date 14 May 2024. Make your contribution ➡️ https://t.co/72A5DgCXn7 https://t.co/QmTLggq0mK
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Mashup Score: 2Application of Chatbot Natural Language Processing Models to Psychotherapy and Behavioral Mood Health - 11 day(s) ago
The prevalence of mental health issues is rapidly increasing worldwide, whereas the gap between the need for treatment and the capacity to deliver it, is constantly increasing even in high-income countries. Though the COVID-19 pandemic had detrimental mental health consequences, including decreased cognition, decreased focus, performance problems, and changes in mood and behavior, it also offered new and advanced digital health applications within the fields of psychiatry and psychotherapy. These tools offer a promising new avenue for approaching mental health issues via a complementary to traditional care channel, that offers scalable interventions even in cases of lack of physical contact between the patient and the carer.The tremendous increase in Artificial Intelligence (AI) applications allows the early identification of mood disorders and digital psychological interventions. Natural Language Processing (NLP) techniques enable computers to understand unstructured text from social
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🚀Submissions Open! @chfrantz E. Peristeri S. Ananiadou & K. Denecke are exploring the impact of #NLP in #digitalpsychiatry & #psychotherapy 👉https://t.co/lHVnS4tQXw Share insights on AI-driven solutions' effectiveness in #DigitalHealth #NLPResearch early identification of… https://t.co/9TDakB09ev https://t.co/If1EQywXde
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Mashup Score: 3Neuroenergetics in Health and Disease - 12 day(s) ago
Bioenergetics play a crucial role in maintaining healthy neuronal functions. Understanding the intricate mechanisms underlying the bioenergetic requirements of neurons is vital for unraveling the energy dysfunctions associated with aging, neurodegenerative disorders, and traumatic brain injury.Through an interdisciplinary approach combining neuroscience, molecular biology, and biochemistry, this Research Topic aims to identify and characterize the specific metabolic pathways, cellular processes, and energy utilization patterns that support healthy neuronal function. By uncovering the unique bioenergetic demands of neurons, we can gain valuable insights into the vulnerabilities of these energy-intensive cells.In this way, the Research Topic seeks to investigate the consequences of energy dysfunction in aging, neurodegenerative conditions such as Alzheimer’s, Parkinson’s, and Huntington’s diseases, as well as traumatic brain injury. By scrutinizing the alterations in neuroenergetic profi
Source: www.frontiersin.orgCategories: General Medicine News, NeurologyTweet
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Mashup Score: 03D inversion recovery ultrashort echo time MRI can detect demyelination in cuprizone-treated mice - 12 day(s) ago
PurposeTo test the ability of inversion-recovery ultrashort echo time (IR-UTE) MRI to directly detect demyelination in mice using a standard cuprizone mouse model.MethodsNon-aqueous myelin protons have ultrashort T2s and are “invisible” with conventional MRI sequences but can be detected with UTE sequences. The IR-UTE sequence uses an adiabatic inversion-recovery preparation to suppress the long T2 water signal so that the remaining signal is from the ultrashort T2 myelin component. In this study, eight 8-week-old C57BL/6 mice were fed cuprizone (n = 4) or control chow (n = 4) for 5 weeks and then imaged by 3D IR-UTE MRI. The differences in IR-UTE signal were compared in the major white matter tracts in the brain and correlated with the Luxol Fast Blue histochemical marker of myelin.ResultsIR-UTE signal decreased in cuprizone-treated mice in white matter known to be sensitive to demyelination in this model, such as the corpus callosum, but not in white matter known to be resistant to d
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New Research: New Research: Rett syndrome: a review of clinical manifestations and therapeutic approaches https://t.co/MOTCtDXfDH #SleepResearch