Oliver W. Layton

Affiliations: 
Cognitive & Neural Systems Boston University, Boston, MA, United States 
Area:
Vision, optic flow, figure-ground segregation
Website:
http://olayton.com
Google:
"Oliver Layton"
Mean distance: 14.79 (cluster 23)
 
SNBCP

Parents

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Flip Phillips research assistant 2007-2009 Skidmore College
N. Andrew Browning grad student 2010- Boston University
Ennio Mingolla grad student 2010- Boston University
Arash Yazdanbakhsh grad student 2010- Boston University
Brett Fajen post-doc 2014- RPI
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Publications

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Ali M, Decker E, Layton OW. (2023) Temporal stability of human heading perception. Journal of Vision. 23: 8
Layton OW, Parade MS, Fajen BR. (2023) The accuracy of object motion perception during locomotion. Frontiers in Psychology. 13: 1068454
Maus N, Layton OW. (2022) Estimating heading from optic flow: Comparing deep learning network and human performance. Neural Networks : the Official Journal of the International Neural Network Society. 154: 383-396
Layton OW, Fajen BR. (2022) Distributed encoding of curvilinear self-motion across spiral optic flow patterns. Scientific Reports. 12: 13393
Layton OW, Powell N, Steinmetz ST, et al. (2022) Estimating curvilinear self-motion from optic flow with a biologically inspired neural system. Bioinspiration & Biomimetics. 17
Steinmetz ST, Layton OW, Powell NV, et al. (2022) A Dynamic Efficient Sensory Encoding Approach to Adaptive Tuning in Neural Models of Optic Flow Processing. Frontiers in Computational Neuroscience. 16: 844289
Layton OW. (2021) ARTFLOW: A Fast, Biologically Inspired Neural Network that Learns Optic Flow Templates for Self-Motion Estimation. Sensors (Basel, Switzerland). 21
Yumurtaci S, Layton OW. (2021) Modeling Physiological Sources of Heading Bias from Optic Flow. Eneuro. 8
Steinmetz ST, Layton OW, Powell NV, et al. (2020) Affordance-based versus current-future accounts of choosing whether to pursue or abandon the chase of a moving target. Journal of Vision. 20: 8
Steinmetz S, Layton O, Powell N, et al. (2020) Self-regulating neural mechanisms for self-motion estimation from optic flow Journal of Vision. 20: 1212
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