Publications
Evidence for the intrinsically nonlinear nature of receptive fields in vision. Scientific reports.
NLreceptiveFields.pdf (2.65 MB)
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2020. 
Visual Illusions Also Deceive Convolutional Neural Networks: Analysis and Implications. Vision Research.
visualIllusions.pdf (3.73 MB)
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2020. 
Visual information flow in Wilson-Cowan networks. Journal of Neurophysiology.
VisualInformation.pdf (3.12 MB)
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2020. 
In Praise of Artifice Reloaded: Caution With Natural Image Databases in Modeling Vision. *Accepted* in Frontiers in Neuroscience.
NatImagesDatabases.pdf (4.25 MB)
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2019. 
Derivatives and Inverse of Cascaded Linear+Nonlinear Neural Models. PLOS ONE.
paper.pdf (7.86 MB)
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2017. 
The Wilson-Cowan Model Describes Contrast Response and Subjective Distortion. Vision Sciences Society Annual Meeting.
VSS_2017_M.pdf (384.41 KB)
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2017. 