Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Pradyumna Lanka"'
Autor:
Ali Rahimpour Jounghani, Pradyumna Lanka, Luca Pollonini, Shannon Proksch, Ramesh Balasubramaniam, Heather Bortfeld
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-20 (2023)
Abstract Procedures used to elicit both behavioral and neurophysiological data to address a particular cognitive question can impact the nature of the data collected. We used functional near-infrared spectroscopy (fNIRS) to assess performance of a mo
Externí odkaz:
https://doaj.org/article/d0139d0e93c24c529ed73ca7b476b320
Autor:
Pradyumna Lanka, D. Rangaprakash, Sai Sheshan Roy Gotoor, Michael N. Dretsch, Jeffrey S. Katz, Thomas S. Denney, Jr., Gopikrishna Deshpande
Publikováno v:
Data in Brief, Vol 29, Iss , Pp - (2020)
Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has been extensively used for diagnostic classification because it does not require task compliance and is easier to pool data from multiple imaging sites, thereby increasing the sample si
Externí odkaz:
https://doaj.org/article/1ac933edd2e0461da07f78c54a11f3d9
Autor:
Pradyumna Lanka, Gopikrishna Deshpande
Publikováno v:
Data in Brief, Vol 20, Iss , Pp 2072-2075 (2018)
Due to the confounding effects of head motion artifacts on resting-state functional connectivity (RSFC), there has been a growing interest in both acquisition and preprocessing strategies for removing motion-related artifacts from resting state funct
Externí odkaz:
https://doaj.org/article/aa2a72cf97954c078f3512187d7f9e37
Autor:
Pradyumna Lanka, Gopikrishna Deshpande
Publikováno v:
Brain and Behavior, Vol 9, Iss 8, Pp n/a-n/a (2019)
Abstract Background Head movement in the scanner causes spurious signal changes in the blood‐oxygen‐level‐dependent (BOLD) signal, confounding resting state functional connectivity (RSFC) estimates obtained from functional magnetic resonance im
Externí odkaz:
https://doaj.org/article/50ef472df87443f8858c4f43f11d48cc
Autor:
Michael N. Dretsch, D. Rangaprakash, Gopikrishna Deshpande, Thomas S. Denney, Jeffrey S. Katz, Pradyumna Lanka
Publikováno v:
Brain Imaging Behav
There are growing concerns about the generalizability of machine learning classifiers in neuroimaging. In order to evaluate this aspect across relatively large heterogeneous populations, we investigated four disorders: Autism spectrum disorder (N = 9
Publikováno v:
Neurophotonics. 9(3)
Autor:
Michael N. Dretsch, Gopikrishna Deshpande, Pradyumna Lanka, D. Rangaprakash, Jeffrey S. Katz, Sai Sheshan Roy Gotoor, Thomas S. Denney
Publikováno v:
Data in Brief
Data in Brief, Vol 29, Iss, Pp-(2020)
Data in Brief, Vol 29, Iss, Pp-(2020)
Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has been extensively used for diagnostic classification because it does not require task compliance and is easier to pool data from multiple imaging sites, thereby increasing the sample si
Autor:
Pradyumna Lanka, Peter F. Liddle, Lena Palaniyappan, Gopikrishna Deshpande, Susan T. Francis, D. Rangaprakash, Sarina J. Iwabuchi
Publikováno v:
Brain and Mind Institute Researchers' Publications
Objective Schizophrenia spectrum disorders (SSD) and psychotic bipolar disorder share a number of genetic and neurobiological features, despite a divergence in clinical course and outcome trajectories. We studied the diagnostic classification potenti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afad6f9329fc48ab77b1aad3cba64a1b
https://ir.lib.uwo.ca/brainpub/1052
https://ir.lib.uwo.ca/brainpub/1052
Autor:
Gopikrishna Deshpande, Pradyumna Lanka
Publikováno v:
Data in Brief
Data in Brief, Vol 20, Iss, Pp 2072-2075 (2018)
Data in Brief, Vol 20, Iss, Pp 2072-2075 (2018)
Due to the confounding effects of head motion artifacts on resting-state functional connectivity (RSFC), there has been a growing interest in both acquisition and preprocessing strategies for removing motion-related artifacts from resting state funct
Autor:
Changfeng Jin, Tianming Liu, Pradyumna Lanka, Hao Jia, Xiaoping Hu, D. Rangaprakash, Lingjiang Li, Gopikrishna Deshpande
Publikováno v:
Human Brain Mapping. 38:4479-4496
Using resting-state functional magnetic resonance imaging, we test the hypothesis that subjects with post-traumatic stress disorder (PTSD) are characterized by reduced temporal variability of brain connectivity compared to matched healthy controls. S