S R Lehky

Summary

Affiliation: The Salk Institute
Country: USA

Publications

  1. pmc Population coding of visual space: modeling
    Sidney R Lehky
    Computational Neuroscience Laboratory, Salk Institute for Biological Studies La Jolla, CA, USA
    Front Comput Neurosci 4:155. 2011
  2. pmc Unmixing binocular signals
    Sidney R Lehky
    Computational Neuroscience Laboratory, The Salk Institute La Jolla, CA, USA
    Front Hum Neurosci 5:78. 2011
  3. doi request reprint Population coding and the labeling problem: extrinsic versus intrinsic representations
    Sidney R Lehky
    Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, USA
    Neural Comput 25:2235-64. 2013
  4. ncbi request reprint Fine discrimination of faces can be performed rapidly
    S R Lehky
    RIKEN Brain Science Institute, Wako, Japan
    J Cogn Neurosci 12:848-55. 2000
  5. pmc Selectivity and sparseness in the responses of striate complex cells
    Sidney R Lehky
    Cognitive Brain Mapping Laboratory, RIKEN Brain Science Institute, Hirosawa 2 1, Wako Shi, Saitama 351 0198, Japan
    Vision Res 45:57-73. 2005
  6. ncbi request reprint Enhancement of object representations in primate perirhinal cortex during a visual working-memory task
    Sidney R Lehky
    Computational Neuroscience Lab, The Salk Institute, 10010 N Torrey Pines Road, La Jolla, CA 92037, USA
    J Neurophysiol 97:1298-310. 2007
  7. doi request reprint Decoding Poisson spike trains by Gaussian filtering
    Sidney R Lehky
    Computational Neuroscience Laboratory, Salk Institute, La Jolla, CA 92037, USA
    Neural Comput 22:1245-71. 2010

Detail Information

Publications7

  1. pmc Population coding of visual space: modeling
    Sidney R Lehky
    Computational Neuroscience Laboratory, Salk Institute for Biological Studies La Jolla, CA, USA
    Front Comput Neurosci 4:155. 2011
    ..In fact, at a population level, the modeling suggests that higher ventral stream areas with highly restricted RF dispersion would be unable to achieve positionally-invariant representations beyond this narrow region around fixation...
  2. pmc Unmixing binocular signals
    Sidney R Lehky
    Computational Neuroscience Laboratory, The Salk Institute La Jolla, CA, USA
    Front Hum Neurosci 5:78. 2011
    ..This is a clear example how non-linear algorithms can lead to highly non-intuitive behavior in neural information processing...
  3. doi request reprint Population coding and the labeling problem: extrinsic versus intrinsic representations
    Sidney R Lehky
    Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, USA
    Neural Comput 25:2235-64. 2013
    ..We show that intrinsic coding has representational advantages, including invariance, categorization, and discrimination, and in certain situations it may also recover absolute stimulus values. ..
  4. ncbi request reprint Fine discrimination of faces can be performed rapidly
    S R Lehky
    RIKEN Brain Science Institute, Wako, Japan
    J Cogn Neurosci 12:848-55. 2000
    ....
  5. pmc Selectivity and sparseness in the responses of striate complex cells
    Sidney R Lehky
    Cognitive Brain Mapping Laboratory, RIKEN Brain Science Institute, Hirosawa 2 1, Wako Shi, Saitama 351 0198, Japan
    Vision Res 45:57-73. 2005
    ..We raise the possibility that high sparseness is the result of distortions in the shape of response distributions caused by non-linear, information-losing transforms, unrelated to information theoretic issues of efficient coding...
  6. ncbi request reprint Enhancement of object representations in primate perirhinal cortex during a visual working-memory task
    Sidney R Lehky
    Computational Neuroscience Lab, The Salk Institute, 10010 N Torrey Pines Road, La Jolla, CA 92037, USA
    J Neurophysiol 97:1298-310. 2007
    ..The onset of the enhanced signal in PRh during the object-memory task occurred with a latency of 80 ms after the onset of the stimulus response, suggesting that it was the result of top-down feedback...
  7. doi request reprint Decoding Poisson spike trains by Gaussian filtering
    Sidney R Lehky
    Computational Neuroscience Laboratory, Salk Institute, La Jolla, CA 92037, USA
    Neural Comput 22:1245-71. 2010
    ..Besides applications for data analysis, optimal recovery of an analog signal waveform lambda(t) from spike trains may also be useful in understanding neural signal processing in vivo...