Sidney R. Lehky

Affiliations: 
Salk Institute for Biological Studies, La Jolla, CA, United States 
Area:
Vision
Google:
"Sidney Lehky"
Bio:

1985 Ph. D. Biophysics and Theoretical Biology, U. of Chicago

Mean distance: 11.6 (cluster 17)
 
SNBCP

Parents

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Daniel L. Alkon research assistant 1975-1976 NIH
Hugh R. Wilson grad student
Terrence J. Sejnowski post-doc Salk Institute
Robert Desimone post-doc 1988-1991 NIMH
John HR Maunsell post-doc 1991-1994 University of Rochester Medical Center
Keiji Tanaka research scientist 1994-1999 RIKEN BSI
Leslie Ungerleider research scientist 2000-2001 NIMH
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Publications

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Lehky SR, Tanaka K, Sereno AB. (2021) Pseudosparse neural coding in the visual system of primates. Communications Biology. 4: 50
Lehky SR, Phan AH, Cichocki A, et al. (2019) Face Representations via Tensorfaces of Various Complexities. Neural Computation. 1-49
Lehky SR, Sereno AB. (2019) Extrinsic and intrinsic representations. The Behavioral and Brain Sciences. 42: e235
Sereno AB, Lehky SR, Sereno ME. (2019) Representation of shape, space, and attention in monkey cortex. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
Sereno AB, Lehky SR. (2018) Attention Effects on Neural Population Representations for Shape and Location Are Stronger in the Ventral than Dorsal Stream. Eneuro. 5
Ghodrati M, Khaligh-Razavi SM, Lehky SR. (2017) Towards building a more complex view of the lateral geniculate nucleus: recent advances in understanding its role. Progress in Neurobiology
Sereno A, Lehky S. (2017) Attention to shape enhances shape discrimination in AIT neural population coding but attention to space does not modulate location discrimination in LIP of macaque monkeys. Journal of Vision. 17: 389
Lehky S, Phan AH, Cichocki A, et al. (2017) Coding of faces by tensor components Journal of Vision. 17: 243
Lehky SR, Tanaka K. (2016) Neural representation for object recognition in inferotemporal cortex. Current Opinion in Neurobiology. 37: 23-35
Lehky S, Sereno M, Sereno A. (2016) Characteristics of eye-position gain field populations in AIT and LIP determined through genetic algorithm modeling of monkey data Journal of Vision. 16: 103
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