Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Manjari Narayan"'
Autor:
John Kruper, McKenzie P. Hagen, François Rheault, Isaac Crane, Asa Gilmore, Manjari Narayan, Keshav Motwani, Eardi Lila, Chris Rorden, Jason D. Yeatman, Ariel Rokem
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionThe Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP
Externí odkaz:
https://doaj.org/article/bea7ca29c08d4be1844112ef10b4244b
Autor:
Ethan Roy, Adam Richie-Halford, John Kruper, Manjari Narayan, David Bloom, Pierre Nedelec, Andreas M. Rauschecker, Leo P. Sugrue, Timothy T. Brown, Terry L. Jernigan, Bruce D. McCandliss, Ariel Rokem, Jason D. Yeatman
Publikováno v:
Developmental Cognitive Neuroscience, Vol 65, Iss , Pp 101341- (2024)
Cross-sectional studies have linked differences in white matter tissue properties to reading skills. However, past studies have reported a range of, sometimes conflicting, results. Some studies suggest that white matter properties act as individual-l
Externí odkaz:
https://doaj.org/article/9fc672d0ba5f430ea244001faa4bf9c9
Publikováno v:
Entropy, Vol 22, Iss 6, p 617 (2020)
Dynamic correlation is the correlation between two time series across time. Two approaches that currently exist in neuroscience literature for dynamic correlation estimation are the sliding window method and dynamic conditional correlation. In this p
Externí odkaz:
https://doaj.org/article/346471699d334773a835d83ea474b0b7
Autor:
Ethan Roy, Adam Richie-Halford, John Kruper, Manjari Narayan, David Bloom, Pierre Nedelec, Leo P. Sugrue, Andreas Rauschecker, Timothy T. Brown, Terry L. Jernigan, Bruce D. McCandliss, Ariel Rokem, Jason D. Yeatman
Cross-sectional studies have linked differences in white matter tissue properties to reading skills. However, past studies have reported a range of, sometimes conflicting, results. Some studies suggest that white matter properties act as individual-l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce8bc35e58e5302e14e5e8a2ad8c33df
https://doi.org/10.1101/2022.06.21.497048
https://doi.org/10.1101/2022.06.21.497048
Autor:
Kamron Sarhadi, Duna Abu-Amara, Russell T. Toll, Amit Etkin, Manjari Narayan, Kasra Sarhadi, Yu Zhang, Rachael Wright, Emmanuel Shpigel, Carena A. Cornelssen, Charles R. Marmar, Roland Hart, Carlo de los Angeles, Nicole Anicetti, Wei Wu, Parker Longwell, Sharon Naparstek, Bryan Gonzalez, Brian Patenaude, Silas Mann, Jennifer Newman
Publikováno v:
American Journal of Psychiatry. 177:233-243
The authors sought to identify brain regions whose frequency-specific, orthogonalized resting-state EEG power envelope connectivity differs between combat veterans with posttraumatic stress disorder (PTSD) and healthy combat-exposed veterans, and to
Autor:
Noriah Johnson, Russell T. Toll, Michelle L. Eisenberg, Amit Etkin, Mallissa Waats, Camarin E. Rolle, Manjari Narayan, Trevor Caudle, Marvin Yan, Dawlat El-Said, Wei Wu
Publikováno v:
Journal of neuroscience methods. 367
Electrophysiological resting state functional connectivity using high density electroencephalography (hdEEG) is gaining momentum. The increased resolution offered by hdEEG, usually either 128 or 256 channels, permits source localization of EEG signal
Publikováno v:
Entropy, Vol 22, Iss 617, p 617 (2020)
Entropy
Volume 22
Issue 6
Entropy
Volume 22
Issue 6
Dynamic correlation is the correlation between two time series across time. Two approaches that currently exist in neuroscience literature for dynamic correlation estimation are the sliding window method and dynamic conditional correlation. In this p
Publikováno v:
Brain Stimulation, Vol 11, Iss 3, Pp 536-544 (2018)
Background Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs), recorded using electroencephalography (TMS-EEG), offer a powerful tool for measuring causal interactions in the human brain. However, the test-retest reliability of TEPs, cr
Publikováno v:
Biological Psychiatry. 89:S250
Publikováno v:
Journal of Open Source Software. 6:3024
For high-dimensional supervised learning, it is often beneficial to use domain-specific knowledge to improve the performance of statistical learning models. When the problem contains covariates which form groups, researchers can include this grouping