Zobrazeno 1 - 10
of 172
pro vyhledávání: '"Steven M Stufflebeam"'
Autor:
Subrat Bastola, Saeed Jahromi, Rupesh Chikara, Steven M. Stufflebeam, Mark P. Ottensmeyer, Gianluca De Novi, Christos Papadelis, George Alexandrakis
Publikováno v:
Bioengineering, Vol 11, Iss 9, p 897 (2024)
Dipole localization, a fundamental challenge in electromagnetic source imaging, inherently constitutes an optimization problem aimed at solving the inverse problem of electric current source estimation within the human brain. The accuracy of dipole l
Externí odkaz:
https://doaj.org/article/4362d7e45df54291b26b1da4f4353bf7
Autor:
Eleonora Tamilia, Matilde Dirodi, Michel Alhilani, P. Ellen Grant, Joseph R. Madsen, Steven M. Stufflebeam, Phillip L. Pearl, Christos Papadelis
Publikováno v:
Annals of Clinical and Translational Neurology, Vol 7, Iss 3, Pp 329-342 (2020)
Abstract Objective To assess the ability of high‐density Electroencephalography (HD‐EEG) and magnetoencephalography (MEG) to localize interictal ripples, distinguish between ripples co‐occurring with spikes (ripples‐on‐spike) and independen
Externí odkaz:
https://doaj.org/article/d13301cf59484e90bc86191702a0b1e9
Autor:
Fahimeh Mamashli, Sheraz Khan, Matti Hämäläinen, Mainak Jas, Tommi Raij, Steven M. Stufflebeam, Aapo Nummenmaa, Jyrki Ahveninen
Publikováno v:
Cell Reports, Vol 36, Iss 8, Pp 109566- (2021)
Summary: Neuronal oscillations are suggested to play an important role in auditory working memory (WM), but their contribution to content-specific representations has remained unclear. Here, we measure magnetoencephalography during a retro-cueing tas
Externí odkaz:
https://doaj.org/article/e0cb8f5dba6c49b89dc2e75357e5a74e
Autor:
Tonya M. Gilbert, Nicole R. Zürcher, Mary C. Catanese, Chieh-En J. Tseng, Maria A. Di Biase, Amanda E. Lyall, Baileigh G. Hightower, Anjali J. Parmar, Anisha Bhanot, Christine J. Wu, Matthew L. Hibert, Minhae Kim, Umar Mahmood, Steven M. Stufflebeam, Frederick A. Schroeder, Changning Wang, Joshua L. Roffman, Daphne J. Holt, Douglas N. Greve, Ofer Pasternak, Marek Kubicki, Hsiao-Ying Wey, Jacob M. Hooker
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-9 (2019)
Gene transcription is known to vary with age and sex, although the underlying mechanisms are unresolved. Here, the authors show that epigenetic enzymes known as HDACs, which regulate gene transcription, are increasingly expressed with age in the livi
Externí odkaz:
https://doaj.org/article/fd891fe0074148ad83476fb18c8b1d21
Autor:
Christos Papadelis, Michel Alhilani, Georgios Ntolkeras, Steven M. Stufflebeam, Jeffrey Bolton, Sanjay P. Prabhu, P. Ellen Grant, Eleonora Tamilia, Joseph R. Madsen, Phillip L. Pearl
Publikováno v:
Clinical Neurophysiology. 141:126-138
To assess the utility of interictal magnetic and electric source imaging (MSI and ESI) using dipole clustering in magnetic resonance imaging (MRI)-negative patients with drug resistant epilepsy (DRE).We localized spikes in low-density (LD-EEG) and hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::205c3f98a0e80ab009055d2bed507d4e
https://doi.org/10.1016/j.clinph.2021.01.036
https://doi.org/10.1016/j.clinph.2021.01.036
Autor:
Taha Gholipour, Xiaozhen You, Steven M. Stufflebeam, Murray Loew, Mohamad Z. Koubeissi, Victoria L. Morgan, William D. Gaillard
Publikováno v:
Epilepsia
OBJECTIVE: This study was undertaken to identify shared functional network characteristics among focal epilepsies of different etiologies, to distinguish epilepsy patients from controls, and to lateralize seizure focus using functional connectivity (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::69d1b316750b0e7638ac2143ee75d9c3
https://doi.org/10.1111/epi.17160
https://doi.org/10.1111/epi.17160
Autor:
Kourosh Jafari-Khouzani, Kyrre E. Emblem, Jayashree Kalpathy-Cramer, Atle Bjørnerud, Mark G. Vangel, Elizabeth R. Gerstner, Kathleen M. Schmainda, Kamran Paynabar, Ona Wu, Patrick Y. Wen, Tracy Batchelor, Bruce Rosen, Steven M. Stufflebeam
Publikováno v:
Translational Oncology, Vol 8, Iss 3, Pp 137-146 (2015)
OBJECTIVES: This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods. METHODS: Thirty-two patients with newly diagnosed glioblastoma
Externí odkaz:
https://doaj.org/article/c17686cecc5e47cf927e953b89f9c58a
Autor:
Daniel J. Zhou, Valentina Gumenyuk, Olga Taraschenko, Bartosz T. Grobelny, Steven M. Stufflebeam, Noam Peled
Magnetoencephalography (MEG) is clinically used to help localize interictal spikes in discrete brain areas through the equivalent current dipole (ECD) method for patients with refractory epilepsy. The propagation of interictal spikes in adjacent regi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::883c049ee167c9bba18660855ac7992b
https://doi.org/10.1101/2022.12.07.22282951
https://doi.org/10.1101/2022.12.07.22282951
Autor:
Qiang Xu, Fang Yang, Zheng Hu, Yan He, Qirui Zhang, Yin Xu, Zhiqiang Zhang, Guangming Lu, Junhao Xiao, Yifei Weng, Steven M. Stufflebeam
Publikováno v:
Brain Imaging and Behavior. 16:424-434
To investigate the influence of epileptogenic cortex (Rolandic areas) with executive functions in Rolandic epilepsy using structural covariance analysis of structural magnetic resonance imaging (MRI). Structural MRI data of drug-naive patients with R
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d215dcc2362d6598efba808ffe62a404
https://doi.org/10.1007/s11682-021-00517-5
https://doi.org/10.1007/s11682-021-00517-5
Delayed brain development of Rolandic epilepsy profiled by deep learning–based neuroanatomic imaging
Autor:
Fang Yang, Hesheng Liu, Zheng Hu, Wei Xing, Xiuli Li, Steven M. Stufflebeam, Valentina Gumenyuk, Zhiqiang Zhang, Qiang Xu, Yan He, Guangming Lu, Ying Lin, Taiping Qu, Qirui Zhang
Publikováno v:
European Radiology. 31:9628-9637
Although Rolandic epilepsy (RE) has been regarded as a brain developmental disorder, neuroimaging studies have not yet ascertained whether RE has brain developmental delay. This study employed deep learning–based neuroanatomic biomarker to measure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a86ebd671c1f46ca3874a9d674aa795c
https://doi.org/10.1007/s00330-021-08048-9
https://doi.org/10.1007/s00330-021-08048-9