@Article{Burge2015,
  author    = {Burge, Johannes and Geisler, Wilson S.},
  journal   = {Nat Commun},
  title     = {Optimal speed estimation in natural image movies predicts human performance},
  year      = {2015},
  pages     = {--},
  volume    = {6},
  abstract  = {Accurate perception of motion depends critically on accurate estimation
	of retinal motion speed. Here we first analyse natural image movies
	to determine the optimal space-time receptive fields (RFs) for encoding
	local motion speed in a particular direction, given the constraints
	of the early visual system. Next, from the RF responses to natural
	stimuli, we determine the neural computations that are optimal for
	combining and decoding the responses into estimates of speed. The
	computations show how selective, invariant speed-tuned units might
	be constructed by the nervous system. Then, in a psychophysical experiment
	using matched stimuli, we show that human performance is nearly optimal.
	Indeed, a single efficiency parameter accurately predicts the detailed
	shapes of a large set of human psychometric functions. We conclude
	that many properties of speed-selective neurons and human speed discrimination
	performance are predicted by the optimal computations, and that natural
	stimulus variation affects optimal and human observers almost identically.},
  comment   = {Supplementary information available for this article at http://www.nature.com/ncomms/2015/150804/ncomms8900/suppinfo/ncomms8900_S1.html},
  publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
  timestamp = {2015.08.05},
}

{"_id":"cTCXbetRbiLFZKmsB","bibbaseid":"burge-geisler-optimalspeedestimationinnaturalimagemoviespredictshumanperformance-2015","author_short":["Burge, J.","Geisler, W. S."],"bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Burge"],"firstnames":["Johannes"],"suffixes":[]},{"propositions":[],"lastnames":["Geisler"],"firstnames":["Wilson","S."],"suffixes":[]}],"journal":"Nat Commun","title":"Optimal speed estimation in natural image movies predicts human performance","year":"2015","pages":"–","volume":"6","abstract":"Accurate perception of motion depends critically on accurate estimation of retinal motion speed. Here we first analyse natural image movies to determine the optimal space-time receptive fields (RFs) for encoding local motion speed in a particular direction, given the constraints of the early visual system. Next, from the RF responses to natural stimuli, we determine the neural computations that are optimal for combining and decoding the responses into estimates of speed. The computations show how selective, invariant speed-tuned units might be constructed by the nervous system. Then, in a psychophysical experiment using matched stimuli, we show that human performance is nearly optimal. Indeed, a single efficiency parameter accurately predicts the detailed shapes of a large set of human psychometric functions. We conclude that many properties of speed-selective neurons and human speed discrimination performance are predicted by the optimal computations, and that natural stimulus variation affects optimal and human observers almost identically.","comment":"Supplementary information available for this article at http://www.nature.com/ncomms/2015/150804/ncomms8900/suppinfo/ncomms8900_S1.html","publisher":"Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.","timestamp":"2015.08.05","bibtex":"@Article{Burge2015,\n author = {Burge, Johannes and Geisler, Wilson S.},\n journal = {Nat Commun},\n title = {Optimal speed estimation in natural image movies predicts human performance},\n year = {2015},\n pages = {--},\n volume = {6},\n abstract = {Accurate perception of motion depends critically on accurate estimation\n\tof retinal motion speed. Here we first analyse natural image movies\n\tto determine the optimal space-time receptive fields (RFs) for encoding\n\tlocal motion speed in a particular direction, given the constraints\n\tof the early visual system. Next, from the RF responses to natural\n\tstimuli, we determine the neural computations that are optimal for\n\tcombining and decoding the responses into estimates of speed. The\n\tcomputations show how selective, invariant speed-tuned units might\n\tbe constructed by the nervous system. Then, in a psychophysical experiment\n\tusing matched stimuli, we show that human performance is nearly optimal.\n\tIndeed, a single efficiency parameter accurately predicts the detailed\n\tshapes of a large set of human psychometric functions. We conclude\n\tthat many properties of speed-selective neurons and human speed discrimination\n\tperformance are predicted by the optimal computations, and that natural\n\tstimulus variation affects optimal and human observers almost identically.},\n comment = {Supplementary information available for this article at http://www.nature.com/ncomms/2015/150804/ncomms8900/suppinfo/ncomms8900_S1.html},\n publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},\n timestamp = {2015.08.05},\n}\n\n","author_short":["Burge, J.","Geisler, W. S."],"key":"Burge2015","id":"Burge2015","bibbaseid":"burge-geisler-optimalspeedestimationinnaturalimagemoviespredictshumanperformance-2015","role":"author","urls":{},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://endress.org/publications/ansgar.bib","dataSources":["xPGxHAeh3vZpx4yyE","TXa55dQbNoWnaGmMq"],"keywords":[],"search_terms":["optimal","speed","estimation","natural","image","movies","predicts","human","performance","burge","geisler"],"title":"Optimal speed estimation in natural image movies predicts human performance","year":2015}