Oliver Hinds, Ph.D.

Boston University, Boston, MA, United States 
Computer Vision, Computational Neuroscience, Visual System
"Oliver Hinds"
Mean distance: 18.12 (cluster 17)


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Eric L. Schwartz grad student 2008 Boston University
 (The intrinsic geometric structure of human primary visual cortex.)
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Hinds O, Wighton P, Tisdall MD, et al. (2014) NEUROFEEDBACK USING FUNCTIONAL SPECTROSCOPY. International Journal of Imaging Systems and Technology. 24: 138-148
Hinds O, Thompson TW, Ghosh S, et al. (2013) Roles of default-mode network and supplementary motor area in human vigilance performance: evidence from real-time fMRI. Journal of Neurophysiology. 109: 1250-8
Yoo JJ, Hinds O, Ofen N, et al. (2012) When the brain is prepared to learn: enhancing human learning using real-time fMRI. Neuroimage. 59: 846-52
Hinds O, Ghosh S, Thompson TW, et al. (2011) Computing moment-to-moment BOLD activation for real-time neurofeedback. Neuroimage. 54: 361-8
Hinds O, Polimeni JR, Rajendran N, et al. (2009) Locating the functional and anatomical boundaries of human primary visual cortex. Neuroimage. 46: 915-22
Hinds O, Polimeni JR, Rajendran N, et al. (2008) The intrinsic shape of human and macaque primary visual cortex. Cerebral Cortex (New York, N.Y. : 1991). 18: 2586-95
Fischl B, Rajendran N, Busa E, et al. (2008) Cortical folding patterns and predicting cytoarchitecture. Cerebral Cortex (New York, N.Y. : 1991). 18: 1973-80
Hinds OP, Rajendran N, Polimeni JR, et al. (2008) Accurate prediction of V1 location from cortical folds in a surface coordinate system. Neuroimage. 39: 1585-99
Bose B, Fisher J, Fischl B, et al. (2007) Detecting cortical surface regions in structural MR data Proceedings of the Ieee International Conference On Computer Vision
Versace M, Bhatt R, Hinds O, et al. (2004) Predicting the exchange traded fund DIA with a combination of genetic algorithms and neural networks Expert Systems With Applications. 27: 417-425
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