Paul J. Laurienti

Affiliations: 
Wake Forest University, Winston-Salem, NC, United States 
Area:
aging, caffeine, multisensory
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"Paul Laurienti"
Mean distance: 14.34 (cluster 53)
 
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Publications

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Zukowski LA, Fino PC, Levin I, et al. (2024) Age and beta amyloid deposition impact gait speed, stride length, and gait smoothness while transitioning from an even to an uneven walking surface in older adults. Human Movement Science. 93: 103175
Kirse HA, Bahrami M, Lyday RG, et al. (2023) Differences in Brain Network Topology Based on Alcohol Use History in Adolescents. Brain Sciences. 13
Khodaei M, Laurienti PJ, Dagenbach D, et al. (2023) Brain working memory network indices as landmarks of intelligence. Neuroimage. Reports. 3
Tomlinson CE, Laurienti PJ, Lyday RG, et al. (2023) 3M_BANTOR: A regression framework for multitask and multisession brain network distance metrics. Network Neuroscience (Cambridge, Mass.). 7: 1-21
Laurienti PJ, Miller ME, Lyday RG, et al. (2023) Associations of physical function and body mass index with functional brain networks in community-dwelling older adults. Neurobiology of Aging. 127: 43-53
Thompson AC, Miller ME, Handing EP, et al. (2023) Corrigendum: Examining the intersection of cognitive and physical function measures: Results from the brain networks and mobility (B-NET) study. Frontiers in Aging Neuroscience. 15: 1166863
Thompson AC, Miller ME, Handing EP, et al. (2023) Examining the intersection of cognitive and physical function measures: Results from the brain networks and mobility (B-NET) study. Frontiers in Aging Neuroscience. 15: 1090641
Thompson AC, Chen H, Miller ME, et al. (2023) Association between contrast sensitivity and physical function in cognitively healthy older adults: the Brain Network and Mobility Function Study. The Journals of Gerontology. Series a, Biological Sciences and Medical Sciences
Bahrami M, Laurienti PJ, Shappell H, et al. (2022) Brain Network Analysis: A Review on Multivariate Analytical Methods. Brain Connectivity
Bahrami M, Laurienti PJ, Shappell HM, et al. (2022) A mixed-modeling framework for whole-brain dynamic network analysis. Network Neuroscience (Cambridge, Mass.). 6: 591-613
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