Results 231 to 240 of about 126,855 (275)

Transforming Brain Health With Neurotechnology Convergence (Part II): Intelligent Neurointervention Systems for Neurological Disorders

Brain Health, EarlyView.
ABSTRACT Neurological disorders represent a critical domain within global health, necessitating advanced interventions to address complex pathologies such as tumors, functional disorders, and cerebrovascular diseases. Despite the proven benefits of early intervention, current treatment paradigms face significant challenges: (1) limited precision in ...
Qing Ye, Fei Peng, Chao Pan, Ping Zhang, Xuewei Xie, Zixiao Li, Yingxin Tang, Danyang Chen, Yuanwei Li, Jiawen Wu, Zao Han, Qing Dai, Quansheng Gu, Jizong Zhao, Zhouping Tang   +14 more
wiley   +1 more source

Housing Warmth/Coolness and Quietness Correlate With Whole‐Brain Fractional Anisotropy in Healthy Adults

Brain Health, EarlyView.
ABSTRACT Introduction Residential environments have been linked to brain structure, particularly in children, older adults, and clinical populations. However, little is known about how different dimensions of the housing environment relate to brain white matter microstructure in healthy adults, or whether specific environmental factors show stronger ...
Keisuke Kokubun, Kiyotaka Nemoto, Toshiharu Ikaga, Yoshinori Yamakawa   +3 more
wiley   +1 more source

Brain Health Deviation Index: A Comprehensive Brain Health Assessment Biomarker for Predicting Cognitive Decline and Polyvascular Stenosis

Brain Health, EarlyView.
ABSTRACT Assessing and quantifying brain health remains a pressing challenge, despite its importance for overall well‐being. Traditional methods that focus on isolated brain measures often fail to capture the multifaceted nature of brain health and may miss early signs of dysfunction.
Ziyang Liu, Shaodong Ding, Hao Liu, Jing Jing, Jian Cheng, Huaguang Zheng, Jiyang Jiang, Wei Wen, Zhe Zhang, Wanlin Zhu, Shiping Li, Yuesong Pan, Xueli Cai, Yijun Zhou, Chang Liu, Xia Meng, Yilong Wang, Hao Li, Yong Jiang, Haijun Niu, Nicole Kochan, Henry Brodaty, Tiemin Wei, Yubo Fan, Zixiao Li, Perminder S. Sachdev, Tao Liu, Yongjun Wang   +27 more
wiley   +1 more source

Advances in causal discovery methods for ecological time series

Biological Reviews, EarlyView.
ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki, Masato Yamamichi, Yutaka Osada, Masayuki Ushio, Kohei Nakajima, Hiroshi Masuya, Shohei Shimizu   +6 more
wiley   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

A guide to neuromodulation in drug‐resistant epilepsy

Epileptic Disorders, EarlyView.
Abstract Neuromodulation is approved for the treatment of drug‐resistant epilepsy. It has been increasingly utilized over the past two decades with the approval of deep brain stimulation (DBS) and responsive neurostimulation (RNS) in addition to vagus nerve stimulation (VNS)—particularly in patients who are not deemed to be good resective surgical ...
Prachi Parikh, Irena Dolezawa, Manu Hegde, Lukas Imbach, Brian N. Lundstrom, Francesca Pizzo, Vikram R. Rao, Jaysingh Singh, Derek Southwell, Satsuke Watanabe, Birgit Frauscher   +10 more
wiley   +1 more source

Can epilepsy be predicted after the first febrile seizure? Insights from machine learning of postictal EEG

Epileptic Disorders, EarlyView.
Abstract Objective Febrile seizures (FS) are the most common seizures in childhood, yet identifying children at risk of developing epilepsy after the first FS remains challenging. We aimed to evaluate the prognostic potential of machine learning (ML) algorithms applied to post‐febrile seizure electroencephalography (EEG) recordings.
Boran Şekeroğlu, Hüseyin Öztoprak, Özlem Yayıcı Köken, Hatice Demir, Mehpare Sarı Yanartaş, Deniz Yılmaz, Burçin Şanlıdağ, Ayşegül Neşe Çıtak Kurt   +7 more
wiley   +1 more source

Video‐based diagnostics supported by artificial intelligence as an opportunity to address the epilepsy diagnostic gap: A narrative review

Epilepsia, EarlyView.
Abstract Despite advancements in epilepsy care, a substantial diagnostic gap persists, particularly in resource‐limited settings. This narrative review explores the potential of video‐based diagnostics augmented by artificial intelligence (AI) to address this gap by enabling earlier and more accessible seizure detection and classification.
Gadi Miron, Robert Terziev, Maximilian Schöls, John McLaren, Tobias Loddenkemper, Jörg Wellmer, Sigrid Mues, Christian Meisel   +7 more
wiley   +1 more source

Mutation type‐specific transcriptomic signatures and readthrough therapy rescue in SMC1A‐related developmental and epileptic encephalopathy

Epilepsia, EarlyView.
Abstract Objective This study was undertaken to investigate the molecular consequences of pathogenic variants in the SMC1A gene—particularly those associated with developmental and epileptic encephalopathy (DEE85)—and to evaluate the therapeutic potential of ataluren in restoring SMC1A function and mitigating disease‐related transcriptomic and genomic ...
Maddalena Di Nardo, Francesca Sardina, Maria M. Pallotta, Iñigo Marcos‐Alcalde, Paulino Gómez‐Puertas, Cinzia Rinaldo, Ian D. Krantz, Antonio Musio   +7 more
wiley   +1 more source

27th Annual Computational Neuroscience Meeting (CNS*2018): Part Two. [PDF]

BMC Neurosci, 2018
europepmc   +1 more source