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163,578 results on '"Neurosciences"'

1. Indian Trial of Tranexamic Acid in Spontaneous Intracerebral Haemorrhage

Author

Indian Council of Medical Research, Sree Chitra Tirunal Institute for Medical Sciences & Technology, Post Graduate Institute of Medical Education and Research, Chandigarh, St. Stephen's Hospital, Delhi, All India Institute of Medical Sciences, New Delhi, Amrita Institute of Medical Sciences & Research Center, Kasturba Medical College Manipal, India, Institute of Neurosciences Kolkata, Bangur Institute of Neurosciences Kolkata, India, Guwahati Neurological Research Center, Guwahati, India, Baptist Christian Hospital, Tezpur, India, National Institute of Mental Health and Neuro Sciences, India, Jawaharlal Institute of Postgraduate Medical Education & Research, Christian Medical College, Vellore, India, CARE Hospitals Hyderabad, India, Lalitha Super Specialities Hospital Guntur, India, Dr. Ramesh Cardiac and Multispeciality Hospital Guntur, India, Government General Hospital Guntur, India, Fortis Escorts Hospital Jaipur, India, Institute of Medical Sciences of the Banaras Hindu University (BHU),India, Atal Institute of Medical Super Specilities, (AIMSS) Chamiana, Shimla, All India Institute of Medical Sciences, Bhubaneswar, KLEs Dr. Prabhakar Kore Hospital & Medical Research Centre Balgaum, India, Guru Gobind Singh Medical College & Hospital, PBM Hospital Bikaner, India, Shree Krishna Hospital Pramukhswami Medical College Anand, India, Apollo Excelcare Hospitals Guwahati, India, Manipal Hospital Bangalore, India, Artemis Hospital Gurgaon, India, Dr. Kamakshi Memorial Hospital Chennai, India, Bharati Vidyapeeth DTU Medical College Pune, India, Aster MIMS Hospital Calicut, India, Holy Spirit Hospital Mumbai, India, Sparsh Superspeciality Hospital Bangalore, India, All India Institute of Medical Sciences, Bilaspur, India, King George's Medical University, Lucknow, India, Assam Medical College, Dibrugarh, India, KG Hospital and Post Graduate Medical Institute Coimbatore, India, Tirunelveli Medical College, Tirunelveli, India, Santokba Durlabhji Memorial Hospital, Jaipur, India, Tezpur Medical College and Hospital, Assam, India, Baby Memorial Hospital Calicut, India, Institute of Human Behaviour and Allied Sciences Delhi, India, The Calcutta Medical Research Institute, Kolkata, India, Fortis Hospital Mulund Mumbai, India, Government Medical College Trivandrum, India, Ruby Hall Clinic, Pune, India, Manipal Hospital Goa, India, and Jeyaraj D Pandian, Principal and Professor, Department of Neurology

Published
2024

6. Cerebral Autoregulation in Pediatric ECMO (ECMOX 2) (ECMO-ECMOX2)

Author

Istituto Giannina Gaslini, Pediatric Intensive Care Unit, Trousseau University Hospital, France, Pediatric Intensive Care Unit, Necker University Hospital, France, and Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, UK

Published
2024

14. Cognitive Control in Parkinson's Disease (EEGControl)

Author

Université de Rennes, Laboratoire du Traitement du Signal et de l'Image (LTSI), Institut des Neurosciences Cliniques de Rennes (INCR), and Association des Parkinsoniens d'Ille-et-Vilaine (APIV)

Published
2023

17. Swiss SOS MoCA - DCI Study

Author

Universitätsklinik für Neurochirurgie, Inselspital Bern, Département des Neurosciences cliniques, Service de Neurochirurgie, Hôpitaux Universitaires de Genève, Primario Neurochirurgia, EOC Ospedale Regionale di Lugano - Civico e Italiano, Klinik für Neurochirurgie, Kantonsspital St. Gallen, Klinik für Neurochirurgie, Universitätsspital Zürich, Abteilung für Neuropsychologie, Universitätsklinik für Neurologie, Inselspital Bern, Primario Neurologia, EOC Ospedale Regionale di Lugano - Civico e Italiano, Abteilung für Neuropsychologie, Klinik für Neurologie, Kantonsspital St.Gallen, Abteilung für Neuropsychologie, Klinik für Neurologie, Universitätsspital Zürich, Département des Neurosciences cliniques, Service de Neurochirurgie, CHUV, Lausanne, Département des Neurosciences cliniques, Service de Neurologie, CHUV, Lausanne, and Département des Neurosciences cliniques, Service de Neurologie, Hôpitaux Universitaires de Genève

Published
2022

23. Effect of Bright Light on Mood and Sleep in Parkinson's Disease (LightPD)

Author

International Parkinson Foundation ('IPF'), Hoofddorp, The Netherlands, Parkinsonvereniging, Bunnik, the Netherlands, Netherlands Brain Foundation, Netherlands Institute for Neurosciences, Amsterdam, The Netherlands, GGZ inGeest, and O.A. van den Heuvel, Principal Investigator

Published
2022

44. The strain – Counter strain technique in the management of anterior interosseous nerve syndrome: A case report

Author

Manu Goyal, MSc (Applied Musculoskeletal Physiotherapy), Kanu Goyal, BPT, Kanimozhi Narkeesh, PhD, Asir J. Samuel, MPT (Neurosciences and Pediatric Neurology), Sorabh Sharma, MPT (Sports Physiotherapy), and Subhasish Chatterjee, MPT (Neurology)

Subjects
تقنية الإفراج الموضعية, الانزلاقات العصبية, متلازمة العصب المتوسط, الاعتلال العصبي الانحباسي, العلاج الطبيعي, الاعتلال العظمي, Medicine (General), R5-920
Abstract

متلازمة العصب بين العظمي الأمامي؛ هي الاعتلال العصبي للعصب المتوسط القريب على مستوى الساعد. يمكن أن تحدث نقاط الزناد في المقصورات الأمامية للساعد ضغطا للعصب بين العظمي الأمامي، وهذا بدوره يسبب ضعف العضلات. يعرض التقرير حالة سيدة عمرها ٣٧ عاما، اشتكت من شعور غير طبيعي عند مسك القلم أثناء الكتابة. وأظهر الفحص السريري (الملاحظة٬ والملامسة٬ وقوة القبضة) ضعفا في قوة القبضة٬ ونقاط الزناد النشطة في منتصف الجانب الأمامي من الساعد وإيجابية علامة الدائرة. بدأ علاجها بالتدليك بالتبريد٬ والتحريك العصبي٬ والتحفيز العصبي الكهربائي عبر الجلد٬ وتقنية الضغط الإجهادي المعاكس أربع مرات أسبوعيا لأسبوعين. وجدت المريضة تحسنا في قوة القبضة، تم قياسه بمقياس القبضة الهيدروليكي الأساسي٬ كما وجدت تحسنا في نقاط الزناد غير النشطة باللمس٬ وتحسن خط اليد. يكشف تقرير هذه الحالة فاعلية تقنية الضغط الإجهادي المعاكس في الاعتلال العصبي الانحباسي كإضافة هامة للعلاج التحفظي. كما أظهرت تقنية الضغط الإجهادي المعاكس تحسنا في قوة العضلات.

Published
2017
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46. Effect of Smartphone Distractions on Cognitive Performance in Adolescents: An Electroencephalography Approach

Author

Cognitive Neurosciences, Shoranur , Kerala, India., E. M Suhara, K P Indiradevi, Suresh A. Poovathinal, Ayyappan Anitha, and T. A Suhail

Subjects
Cellular and Molecular Neuroscience, medicine.diagnostic_test, medicine, Neurology (clinical), Effects of sleep deprivation on cognitive performance, Electroencephalography, Psychology, Cognitive psychology
Abstract

Introduction: The dependence on smartphones has become widespread among all age groups in every realm of daily life. There has been increased concern about the adverse effects of problematic smartphone use and media multitasking among adolescents. Recent studies used various performance measures like questionnaire surveys to examine the association between smartphone addiction and learning performance, and such studies have yielded mixed findings. The current study investigates the effects of media multitasking on cognitive performance using Electroencephalography (EEG) features and a self-report questionnaire survey. Methods: The patterns of smartphone use among adolescents in South India were investigated in this study, using a questionnaire survey. Further, the impact of smartphone usage on cognitive task performance was examined using EEG features. For this, EEGs of twenty-two healthy subjects were recorded during learning tasks before and after using a social networking site on smartphones. Subsequently, various EEG features were extracted, including ratios of wavelet decomposed EEG bands, attention index, and Sample entropy. Finally, these cognitive performance indices were evaluated and compared with a control group. Results: A total of 600 healthy individuals (341 males, 259 females) participated in the survey among whom, 310 (50.91%) belonged to the high-user group. Performance degradation (p=0.005), sleep problems (p=0.040) and mental stress (p=0.049) were more prevalent among the high-user group. A significant decline in EEG-based cognitive performance indices was also observed in the phone-use group compared to the control group. Conclusion: The findings of this study highlight the importance of controlling phone use when engaged in cognitive tasks. The study also offers an insight to develop neurofeedback techniques that enhance cognitive skills.

Published
2021

48. Machine Learning based Classification of Meditators using Functional Connectivity over Resting State Networks

Author

affiliated to Vtu, Belagavi, Karnataka, India., Neurosciences, Bangalore, Karnataka, India., Dr.P.A. Vijaya, Bindu M. Kutty, Ashwini S Savanth, and Ajay Kumar Nair

Subjects
Resting state fMRI, business.industry, Functional connectivity, General Engineering, Artificial intelligence, Machine learning, computer.software_genre, Psychology, business, computer
Abstract

Meditation has several health benefits and is also used as a complementary treatment for various ailments. Neuroimaging studies have shed light on the effects of meditation, especially on the brain. Functional Magnetic Resonance Imaging, a powerful non-invasive imaging technique is used in this study to determine the functional connectivity in meditator’s brain. In this study, long-term effects of Rajayoga Meditation practice were considered where the difference in functional connectivity between two groups of subjects one with long duration and the other with short duration of Rajayogameditation practice was found. Two groups of subjects with long-term and short-term practice of Rajayoga meditation were recruited. Task-based fMRI was acquired as the subject performed a Neurocognitive task. Functional connectivity among the regions of Resting-State Networks was performed and four functional connectivity metrics were derived. Machine learning algorithms were used to classify these two groups based on functional connectivity metrics used as features. It was found that the…… classifier could differentiate the two groups with …. Accuracy.

Published
2021

49. Electroencephalography based detection of cognitive state during learning tasks: An extensive approach

Author

Cognitive Neurosciences, Shoranur , Kerala, India., Theparambil Asharaf Suhail, Ekkarakkudy Makkar Suhara, Poovathinal Azhakan Suresh, Kottanayil Pally Indiradevi, and Ayyappan Anitha

Subjects
medicine.diagnostic_test, Computer science, medicine, Experimental and Cognitive Psychology, Cognition, State (computer science), Electroencephalography, Cognitive psychology
Abstract

Detecting cognitive states during learning tasks is an essential component in neurocognitive experiments for assessing and enhancing the cognitive performance of individuals. Studies have demonstrated that mental state recognition systems utilizing brain signals are proficient in the automated monitoring of learners’ cognitive states. The current study focuses on developing an efficient individualized and cross-subject cognitive state assessment model based on Electroencephalography (EEG) patterns during learning tasks. For this study, EEGs of 20 healthy subjects were recorded during a resting state followed by a learning task and examined EEG activations patterns in a wide perspective of feature types and rhythms. The extracted features included time-domain features such as Hjorth parameters, Wavelet-based features, and Spectral entropy. Three classifiers, Support Vector Machine, k-Nearest Neighbor, and Linear Discriminant Analysis were employed to recognize the mental state. A new EEG-based attention index using band ratios is proposed and is demonstrated as an effective predictor for recognizing attentive reading. The proposed model can yield recognition performance with an accuracy of 92.9% in the subject-dependent approach and 77.2% in the subject-independent approach with the Support Vector Machine Classifier. The findings are useful for the design and development of neurofeedback systems that monitor and enhance the cognitive performance in healthy individuals, as well as in individuals with cognitive deficits.

Published
2021

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