Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Link Tejavibulya"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract Predictive modeling is a central technique in neuroimaging to identify brain-behavior relationships and test their generalizability to unseen data. However, data leakage undermines the validity of predictive models by breaching the separatio
Externí odkaz:
https://doaj.org/article/dd2bea4ec50b4543bdd42bc468cb5294
Publikováno v:
NeuroImage, Vol 264, Iss , Pp 119742- (2022)
The human connectome is modular with distinct brain regions clustering together to form large-scale communities, or networks. This concept has recently been leveraged in novel inferencing procedures by averaging the edge-level statistics within netwo
Externí odkaz:
https://doaj.org/article/df0d0f7df3034d1f811c6d825e0c4017
Autor:
Begüm Aydin, Michael Sierk, Mireia Moreno-Estelles, Link Tejavibulya, Nikathan Kumar, Nuria Flames, Shaun Mahony, Esteban O. Mazzoni
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Neuronal programming by forced expression of transcription factors (TFs) holds promise for clinical applications of regenerative medicine. However, the mechanisms by which TFs coordinate their activities on the genome and control distinct neuronal fa
Externí odkaz:
https://doaj.org/article/7f1cb8a0d28b411c88f0b01e3a7958e8
Autor:
Link Tejavibulya, Hannah Peterson, Abigail Greene, Siyuan Gao, Max Rolison, Stephanie Noble, Dustin Scheinost
Publikováno v:
NeuroImage, Vol 252, Iss , Pp 119040- (2022)
Handedness influences differences in lateralization of language areas as well as dominance of motor and somatosensory cortices. However, differences in whole-brain functional connectivity (i.e., functional connectomes) due to handedness have been rel
Externí odkaz:
https://doaj.org/article/3f84e0978b9b4df5a33e0dd192517295
Autor:
Corey Horien, Kangjoo Lee, Margaret L. Westwater, Stephanie Noble, Link Tejavibulya, Teimur Kayani, R. Todd Constable, Dustin Scheinost
Publikováno v:
STAR Protocols, Vol 3, Iss 1, Pp 101077- (2022)
Summary: Large, publicly available neuroimaging datasets are becoming increasingly common, but their use presents challenges because of insufficient knowledge of the tool options for data processing and proper data organization. Here, we describe a p
Externí odkaz:
https://doaj.org/article/43161637d27e4eccb909aadbd0452889
Autor:
Dustin Scheinost, Angeliki Pollatou, Alexander J. Dufford, Rongtao Jiang, Michael C. Farruggia, Matthew Rosenblatt, Hannah Peterson, Raimundo X. Rodriguez, Javid Dadashkarimi, Qinghao Liang, Wei Dai, Maya L. Foster, Chris C. Camp, Link Tejavibulya, Brendan D. Adkinson, Huili Sun, Jean Ye, Qi Cheng, Marisa N. Spann, Max Rolison, Stephanie Noble, Margaret L. Westwater
Publikováno v:
Biological Psychiatry. 93:893-904
Autor:
Corey Horien, Dorothea L. Floris, Abigail S. Greene, Stephanie Noble, Max Rolison, Link Tejavibulya, David O’Connor, James C. McPartland, Dustin Scheinost, Katarzyna Chawarska, Evelyn M.R. Lake, R. Todd Constable
Publikováno v:
Biological Psychiatry. 92:626-642
Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging-based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of funct
Autor:
Kristina M. Rapuano, Link Tejavibulya, Eda Naz Dinc, Anfei Li, Haley Davis, Rachel Korn, Rudolph L. Leibel, B. Timothy Walsh, Lisa Ranzenhofer, Michael Rosenbaum, B. J. Casey, Laurel Mayer
Publikováno v:
Brain Imaging and Behavior.
Pediatric obesity is a major public health concern. Genetic susceptibility and increased availability of energy-dense food are known risk factors for obesity. However, the extent to which these factors jointly bias behavior and neural circuitry towar
Autor:
Link Tejavibulya, Max Rolison, Siyuan Gao, Qinghao Liang, Hannah Peterson, Javid Dadashkarimi, Michael C. Farruggia, C. Alice Hahn, Stephanie Noble, Sarah D. Lichenstein, Angeliki Pollatou, Alexander J. Dufford, Dustin Scheinost
Publikováno v:
Molecular Psychiatry. 27:3129-3137
Predictive modeling using neuroimaging data has the potential to improve our understanding of the neurobiology underlying psychiatric disorders and putatively information interventions. Accordingly, there is a plethora of literature reviewing publish
Autor:
Javid Dadashkarimi, Amin Karbasi, Qinghao Liang, Matthew Rosenblatt, Stephanie Noble, Maya Foster, Raimundo Rodriguez, Brendan Adkinson, Jean Ye, Huili Sun, Chris Camp, Michael Farruggia, Link Tejavibulya, Wei Dai, Rongtao Jiang, Angeliki Pollatou, Dustin Scheinost
Open-source, publicly available neuroimaging datasets—whether from large-scale data collection efforts or pooled from multiple smaller studies—offer unprecedented sample sizes and promote generalization efforts. Releasing data can democratize sci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f312da0e9eac5ca9a64e30cd80790a6a
https://doi.org/10.1101/2022.07.19.500642
https://doi.org/10.1101/2022.07.19.500642